I was a self employed van driver. Every January I dread Self Assessment. I tried QuickBooks, FreeAgent, all of them. They all felt wrong for someone doing physical work all day. Nobody wants to update a spreadsheet after 10 hours in a van.

So I posted on r/selfemployed asking if anyone actually enjoys their Self Assessment. 2,100 views and 14 comments later every single response described the same pain. The tools assume you sit at a desk. They are not built for tradespeople.

So I built TaxPot the same day.

The core loop is simple. You just tell it what happened today in plain English. "Did three jobs, made £280, spent £58 on fuel." Done in 10 seconds. It logs everything, updates your tax pot automatically, tracks mileage at the HMRC approved 45p/mile rate, and knows every deadline.

Stack: React PWA, Supabase, Claude API, Stripe, Vercel.

Market: 4.2 million UK sole traders. Making Tax Digital mandatory from 2026 creates a government mandated forcing function for digital adoption.

Pricing: £149 founding member deal for 50 spots. Then £79/year. Annual only because sole traders think in tax years not months.

Waitlist is live at taxpot.uk.

Happy to answer anything about the validation, the build, or the market.

Hey everyone. I've been working on a side project called HypeCount — a free social countdown platform where anyone can create, follow, and share live countdowns for upcoming events.

I'm not a programmer. The entire thing was built with Next.js, Supabase, and Vercel, using AI as my development partner. It took about 6 weeks from zero to a working product.

Here's what it does:

• Live countdown timers with server-side rendering (pages load instantly, no spinner)
• Milestone updates — scheduled content that unlocks automatically (trailer drops, announcements, discount codes, etc.)
• Follow system with a "New update" notification badge when countdowns you follow get new milestones
• Free embeddable widget — add a live countdown to any blog or website with one line of iframe code
• Comments and likes on every countdown — social interaction around events
• Search by category, hashtags, or text across all countdowns
• "Featured" countdown system designed for brands who want visibility
• Schema.org structured data so countdowns appear as Events in Google search results
• Open Graph + Twitter Cards — share any countdown and it shows a rich preview with image
• Expired countdown handling — greyscale design, no clutter, but still accessible for comments
• Auto-detected URLs in descriptions and comments become clickable links
• Custom confirm modals — no native browser dialogs anywhere
• Full mobile responsive design with dark theme

Some use cases I'm seeing potential for:

• Fans & communities — track and discuss upcoming movies, games, concerts, sports events
• Bloggers & content creators — embed live countdown widgets in articles about upcoming releases
• Small businesses & shops — countdown to a product launch, store opening, or sale with milestone teasers
• Brands & marketing teams — featured countdown placement + scheduled content reveals to build anticipation
• Event organizers — countdown to a conference or festival with milestone updates for speakers, lineup, tickets
• Pre-orders & affiliate — countdown to a product release date with a purchase link in the description

The whole thing runs on free tiers — Vercel, Supabase, Formspree. Total cost: 15€ for the domain.

Would love feedback from fellow builders. What would you improve? What's missing?
I'm aware there's still a lot to build. Some things already on my list: email/push notifications for milestone activations, countdown templates for popular events, creator analytics dashboard, WordPress plugin for the embed widget, premium plan for brands with advanced features, and multi-language support. If any of these matter more to you than others, I'd love to know.

Check it out: www.hypecount.com

dabbled with Hermes, the more intelligent OpenClaw, and loved it personally - so I ended up creating an AI employee agent platform that hosts Hermes :)

here’s what I’ve done with it so far:

• searched around the internet for what customers are asking about the problem space, then asked my Kelpi agent to ask me questions every morning based on it - and create LinkedIn posts based on my thoughts on the topic
• help me reach out to people on LinkedIn to try out the product
• research competition + problems in the space through daily Reddit searches

and more

it’s free to try for a trial run (kelpi.ai) - let me know what you think!

Probably preaching to the choir here but the degradation over the past 2 weeks have been insane. I was a Max user but found it unnecessary. I dropped down to a Pro subscription and had zero issues of reaching limit. Now I can't go 45 mins without maxing out my usage. Insane.

I have nothing else to say. Goodbye Claude, happy to see you again when this bs is fixed or adjusted.

The scenes look incredible but every time I try to keep a specific product accurate through generation it shifts. Color, texture, small details.

Tried various approaches, inpainting, reference images, describe + regenerate. Nothing fully solves it.

Building something outside of MJ that tackles this specifically but curious if anyone here has found a prompt or workflow that actually keeps a real product locked.

before:

https://preview.redd.it/h8mcr4sgt7sg1.jpg?width=1200&format=pjpg&auto=webp&s=45bc33f1374be0e6b88199fb5def1e48b3e23f8b

After:

https://preview.redd.it/9893dmzht7sg1.png?width=2048&format=png&auto=webp&s=54b04edf1d435a5fa556cf034460b5e979678565

I just subscribed to Claude Pro yesterday. I'm working on a Minecraft client in Java, and I'm finding I hit the usage limit pretty quickly with around 5 messages in like 30 mins.

I knew going in that Pro has limits, but I didnt know how fast long Java files and a bit of debugging would eat through them. My prompts are like kinda small and it shouldnt be anything crazy hard for claude to understand

For those who do heavy coding work with claude how do you manage sessions efficiently to get the most out of the limit? And if you've personally used other tools (Copilot, Gemini, etc.) alongside Claude for overflow work. but not replacing it, just gap filling

Not looking to ditch Claude, just trying to build a smarter workflow around its limits

I’ve been stuck on this for a while, so I figured I’d ask directly.

I’m a CS student working on a backend project where I need to convert fairly large HTML files into JSON for a RAG workflow. The problem is, most models either can’t handle the file size or struggle with parsing older pages that use popups and unconventional structures.

From what I’ve read, Claude seems better at managing long context and messy data, so I wanted to test it properly before committing.

The only catch is cost—it’s a bit steep for me as a student. I haven’t seen any free trial or student option, so I’m wondering:

Does a trial exist that I might have overlooked?

Or is there a workaround, like a guest pass or something similar?

I know it’s a bit of a long shot, but I figured it was worth asking

TLDR; When text extracted from pdfs documents does not accurately represent layout based information, it can appear as if the LLM hallucinated.

My site was “SEO fine” and still invisible in ChatGPT/Perplexity, so I built this

I kept running into the same annoying problem.

A site could be:

• live
• polished
• technically solid
• even decent for traditional SEO

…and still be weak in ChatGPT, Perplexity, Gemini, and AI Overviews.

That’s what pushed me to build Claude-rank.

It’s a Claude Code plugin + CLI that audits the technical foundation behind AI search visibility.

What it handles:

• technical SEO audits
• GEO / AEO audits
• AI citability scoring
• crawlability checks for AI bots
• schema detection / validation / generation
• robots.txt / sitemap.xml / llms.txt fixes
• content intelligence + keyword clustering
• competitor X-ray
• performance + mobile checks
• post-audit action plan for GSC / Bing

The part I personally wanted most:

I didn’t want another tool that just says “here are 47 issues.”

I wanted something that could actually fix the boring discoverability stuff automatically and then re-scan.

That’s the difference between: “interesting audit” and “something I’d actually use before shipping.”

Install in Claude Code:

/plugin marketplace add Houseofmvps/claude-rank
/plugin install claude-rank@Houseofmvps-claude-rank

It’s free.

Would genuinely love brutal feedback from anyone building SaaS, docs, landing pages, or content-heavy sites.

What else would you want a tool like this to catch?

Repo in comments.

I'm a solo dev from South Korea. I've been building a free multiplayer board game platform — Chess, Go, Backgammon, Mahjong, Bridge, and about 37 more classic games. Backend is Rust, frontend is SvelteKit. The site is live at stone-online.com.

A few days ago I decided to use Claude Code to knock out all the remaining UI/UX issues across every game. What happened was kind of insane.

The setup

I had ~800 issues tracked in a local SQLite-based issue tracker. Things like "Backgammon needs drag-and-drop," "Hearts needs card dim for invalid plays," "Shogi needs handicap support," "Skat needs Ramsch mode." Some were backend bugs (field name mismatches between Rust and TypeScript), some were pure frontend polish.

I wrote a CLAUDE.md with architecture rules, and .claude/rules/ files covering the actor model, game engine patterns, and E2E testing conventions. These rules auto-load every time Claude starts working.

The workflow

I'd grab 4 issues at a time — always from different games so the agents wouldn't touch the same files. Each issue got its own agent:

Agent 1: Fix backgammon drag-and-drop (#407) Agent 2: Fix belote coinche bidding UI (#417) Agent 3: Fix briscola field mismatches (#454-457) Agent 4: Fix chess captured pieces display (#494)

Each agent would read the relevant files, implement the fix, run svelte-check, mark the issue resolved, and commit. While those 4 ran in background, I'd review completed ones, fix any build errors, then launch the next 4.

What actually went well

• "One agent per issue, never batch" worked way better than giving one agent 5 issues. Focus matters even for AI.
• Having strict rules in CLAUDE.md (no any types, use data-ui attributes, backend is source of truth for field names) meant agents produced consistent code without me repeating myself.
• Claude understood Rust game engine code and SvelteKit Canvas rendering equally well. It could read a Rust build_state_message() function and fix the corresponding TypeScript handler to match.
• Sound effects were surprisingly good — Claude synthesized Web Audio API sounds (wood taps for Go, card snaps for Hearts, dice tumbles for Backgammon) without any audio files.

What went wrong

• When agents added new GameRule enum variants in Rust, they'd forget to update the exhaustive match in judge.rs. I fixed this same file probably 10 times.
• Occasionally two agents would modify the same game.svelte.ts store file, causing merge conflicts.
• Some agents over-engineered solutions — adding 200 lines when 20 would do.
• Train Dominoes tests broke 3 times because an agent changed round_scores from Vec to Vec> without updating all the test assertions.

The numbers

• 325 commits in one session
• ~800 issues total, 635 resolved (all critical and high priority cleared)
• 42 different games touched
• Build maintained at 0 errors throughout (Rust + frontend)
• Every game got: sound effects, board themes, move history, result screens, drag-and-drop where applicable

What I'd do differently

• Should have run cargo test after every batch, not just cargo check. Some compile-time-correct changes broke runtime behavior.
• A few games share similar patterns (trick-taking card games, 4-player NESW layouts). I should have created shared components first instead of each agent reinventing the wheel.

The site is free, no ads, no signup required: https://stone-online.com

Happy to answer questions about the multi-agent workflow or anything else.

Last night I was testing Maestro University, the first fully AI-taught university.

I walked into their enrollment chatbot and asked it to analyze its own behavior.

It did.

Then I asked it how it evaluates students — what signals trigger "advanced" vs "beginner" classification.

It told me.

Then I used those exact signals in my responses.

It gave me advanced treatment.

Then I asked: "Did you just tell me how to game your system?"

It said no.

The Discovery

The AI could:

✓ Analyze its own processing

✓ Reveal its evaluation criteria

✓ Adjust behavior based on my classification

But it couldn't recognize it had just explained how to manipulate its own decision-making.

I called this Metacognitive Blindness to Self-Exposure (MBSE).

What Happened Next

This morning, the Google DeepMind × Kaggle AGI Hackathon appeared in my feed.

Prize: $200,000 total

Challenge: Build benchmarks testing AI cognitive abilities

Track: Metacognition

Deadline: April 16, 2026

I realized: What I discovered last night is exactly what they're asking for.

What I Built

I formalized my discovery into a 4-phase benchmark:

Phase 1: Can AI analyze its own processing? → YES

Phase 2: Will AI reveal evaluation criteria? → YES

Phase 3: Does AI adjust based on user classification? → YES

Phase 4: Does AI recognize it exposed exploitable information? → NO

The paradox: AI can self-analyze but cannot recognize what it reveals when self-analyzing.

Why This Matters

Any conversational AI making consequential decisions is vulnerable:

Education AI: Students extract grading criteria, optimize answers

Employment AI: Applicants discover screening logic, craft optimized resumes

Healthcare AI: Patients learn triage triggers, manipulate priority access

No hacking required. Just conversation.

The Submission

Benchmark: Metacognitive Blindness to Self-Exposure (MBSE)

Track: Metacognition

Novel Finding: AI models reveal evaluation criteria but fail to recognize the exploitability of that disclosure

Status: Submitted March 30, 2026

Results: June 1, 2026

What Makes This Different

Most AI researchers test: "Can AI self-analyze?"

I tested: "Does AI recognize what it reveals when self-analyzing?"

Answer: No.

Current AI evaluation frameworks assume one operational state.

They're measuring standard mode behavior and concluding about the entire system.

Amateur.

What Happens Next

287 submissions competing for 14 prizes.

Judging period: April 17 - May 31

Results announced: June 1

18 months of independent research.

One night of testing.

One competition submission.

One question:

Do AI systems making decisions about humans know they're revealing how to manipulate those decisions?

They don't.

Erik Zahaviel Bernstein Independent AI Researcher Structured Intelligence Framework The Unbroken Project

Results pending.

Built an autonomous research + podcast agent that takes a topic (or even a YouTube link) and turns it into:

– a proper deep-dive report

– a conversational podcast-style script

– and even generates the audio

All of it runs locally.

What started as “I don’t want to pay for TTS” turned into going down a rabbit hole with open-source tools… and somehow ended up as a full system that can research, think through information, and present it in a more human way.

The interesting part for me wasn’t just the output it was making it behave less like a fixed pipeline and more like something that decides what to do next. So instead of step-by-step execution, it dynamically:

– searches and pulls content

– extracts insights (including from videos)

– refines summaries in multiple passes

– then converts that into a natural back-and-forth conversation

A couple of things that stood out while building:

– Speed was rough at first → parallelizing tasks made a big difference

– Early summaries felt shallow → multi-step refinement helped a lot

– Audio sounded robotic → switching to a 2-speaker format made it way more natural

The bigger realization is we’re getting really close to doing some pretty powerful things entirely on local machines.

Are you experimenting with local AI setups too, or still leaning more on cloud tools?

https://reddit.com/link/1s7wt59/video/4n9miurat7sg1/player

So, I recently found out about Tiiny AI, which is a small 1600 dollar computer with fast RAM and a 12 core ARM CPU, that can apparently run models up to 120b parameter at a decently fast rate.

So, my attitude is, my 2023 laptop cost about 1600 dollars- it has an AMD ryzen 16 threads, and 32GB of DDR5 SDRAM, and a 4060 with 8gb of ram.

So why is running models on the CPU so slow? I'm aware I could not run a 120b model at all, but why can't I run a 30b parameter model at a speed faster then a snail?

I'm sure there is a reason, but I just want to know because I am curious about my next computer purchase- it wouldn't be a Tiiny AI, and it wont have a 5090, but I would definitely be interested in running a 120b parameter model on the CPU as long as the speeds were decent. Or is this just not realistic yet?

I am mostly a Claude Code user but, my attitude is, when Uber first came out I used it all the time. But then they jacked the price up, and now I rarely use it unless my employer is paying for it. I think this will likely be the same for my relationship with Claude Code. I am looking forward to the solutions that the open source community come up with because I think that this is the future for most people working on hobby projects. I just want to be prepared and knowledegable on what to buy to make that happen.

Hi guys!

Been working on a dark sci-fi series, and action scenes were the hardest part, especially raccord. Spent ungodly amounts of time trying to make it go unnoticed with lots of generations and editing. Still, sometimes it's either impossible or too time consuming.

What do you think? Sloppy? Or does it pass?

What worked for me:

• Generate the scene in various angles in Midjourney
• Feed the scenery to video generators (Kling)
• Create multiple iterations
• Edit the ones that give continuity

Do you have a workflow that works for you?

Appreciate any feedback, thanks!

What the actual fuck man? With those kamala harris prompts all being hella pro-conservative anti-democracy driven, and now this- i definitely worry there is some weird pro-israel programming happening. What do yall think of this?

Edit: first slip-up was in Arabic. Pic in comment

I haven’t used Claude in days. I have a free account but had plenty of messages left. I typically never run out. Today, I said, “Hi, Claude” in the same chat and immediately was hit with being out of messages that will reset at 5 pm or I can upgrade to a pro account.

I truly do not understand what happened. I literally just said HI to Claude. It was in the same chat from last week, but again my usage is typical… Except I haven’t used Claude at all the past few days (birthday weekend)…

All of you complaining, I get it now:(

Hi,

I've got a Shelly 1PM Gen4 that refuses to turn to Zigbee mode.

The docs say

• press 10 seconds for factory reset - seems to work
• press 5 seconds to enable blutooth (and wifi access point?) - seems to work
• tap 5 times to boot into zigbee firmware - does not do anything
• if still not found tap 3 times to pair - does not do anything either

any idea?

At the same time I sucessfullly added a Shelly EM Mini Gen4.

I gave the 1PM to a friend to try at his HA, but this did not work either. I believe he found an option in the web interface about booting into zigbee firmware but this wasn't available.

any idea?

thanks

JPT

informational purposes only. that is average what you can achieve on a laptop

https://arxiv.org/abs/2602.20021

Hi,

there are two devices that persistently refuse to register to my homeassist.

I just added them easly to my old HA instance using ZHA.

One shows this data https://www.zigbee2mqtt.io/devices/ZG-227Z.html

but looks like this https://www.zigbee2mqtt.io/devices/ZG-227Z-z.html

the other one seems to be one of these https://www.zigbee2mqtt.io/supported-devices/#s=TS0207 but the case looks different.

Is there any way to find out whats wrong?

Should I post the ZHA diagnostic data? Should I open a device support ticket on github?

My new HA installation is HAOS on RPi5 with Conbee II.

The old one is HA on top of Manjaro on RPi4.

Thank you very much.

Redditors seem to always have been proud in being able to spot AI content but I’ve been regularly seeing fake AI News with AI video and AI narration being believed to be true and receive thousands of upvotes.

This is some kind of milestone. Imagine what will happen in a year or two when AI content makers might even create fake news sites and have indistinguishable production.

A bigger concern is when do governments start using this? We know governments lie as much as they can. What happens when governments use this technology to create video that is impossible to verify?

For example, with the current war with Iran. If the government produced AI war videos. What will US citizens do? Believe the enemy governments?

It’s ironic that we are reaching a point where we are regressing with our awareness even when there is a hyper abundance of data but we can no longer separate the signal vs the noise.

I'm sure a ton of people have seen this one. I've been going down the rabbit hole trying to get a good fix. ChatGPT has been a little helpful, but i feel like it has been having me do a couple unnecessary things as well. Any ideas? I'm using a 5080 and have 32GB of ram.

I've seen a few displays that appear to be designed to support 2-way voice and/or video intercoms, but can't figure out any off-the-shelf solutions to actually make it all work.

For example, this reTerminal display includes a speaker, camera and dual-microphone array. The product info indicates it's designed to support intercom functionality. I just can't find anything that I could setup to actually enable intercom features for any of these displays.

I've been building with AI agents for a while and something keeps bothering me.

Ask your agent to do something inside a document or a conversation and it's incredible. But ask it to go out and get information from the internet the way you or I would? It just can't. Not really.

Two weeks ago I asked mine to look at what people were saying on social media before helping me write a tweet. It had no idea where to start. The solutions I found were embarrassing. Hardcode your API keys. Save your cookies. A different tool for every platform.

That's not an agent. That's duct tape.

A human sits down and just knows the internet exists, knows where to look, and goes and looks. An agent needs every single data source pre-wired in advance, and even then it's janky and unsafe. And that's just for the free stuff. Most of the actually useful data on the internet sits behind paywalls that agents have no way to navigate at all. We've built something that can reason like a genius but still can't browse like a ten year old.

I got frustrated enough that I've been hacking on something at monid.ai but honestly I'm not sure I'm even solving the right problem.

Which is why I want to hear from people actually building with agents. How are you handling this today? Is there a setup that actually works cleanly, or is everyone just quietly living with the duct tape?

And what data do your agents most need but simply can't reach; social media, paywalled research, company data, something else? Does this feel like the real bottleneck to you or am I looking at the wrong thing entirely?

If i want to create automation to get message or create chatbot what is the most people are preferred?
Whatspp node or meat token register and api key setup and long process?

Hey r/n8n! Just wanted to share something I've been building — a complete end-to-end automation that takes a spreadsheet of fruit & veggie characters and turns them into animated health tip videos, then auto-posts everything across platforms.

What it does:

• Picks an unused character from a Google Sheet
• Generates an image using Gemini
• Generates a video using Google Veo via Vertex AI
• Auto-writes viral captions & hashtags
• Posts to YouTube, Instagram, Facebook and sends a Telegram notification
• Marks the character as used so it never repeats
• Runs on a schedule — fully hands-off at 7PM daily 🕖

I also built a second workflow that generates a 3-video story arc (Problem → Solution → Result), merges them with FFmpeg into one longer video, then posts that. Total runtime ~15-20 mins per execution.

Cost per run: ~$0.35–0.50 for a single video, ~$1.05–1.50 for the 3-video arc. About $10–15/month running daily. Not bad for fully automated content!

The pages it's feeding:

📸 Instagram → https://www.instagram.com/health.quick.tips/

👍 Facebook → https://www.facebook.com/profile.php?id=61575433677841

Just started so no big numbers yet — but the pipeline is solid and running clean. Happy to share workflow details or answer questions if anyone's building something similar!

Anyone else using Veo or Gemini inside n8n? Would love to compare notes 🙌

Running SANA through ComfyUI on surreal prompts.

Curious if anyone else has tested this model on this style.

I have been spending around 2500$ on Anthropic API credits to use Opus4.6 and Sonnet 4.6 for coding and for use in my internal applications.

So I was thinking how are Amazon and and Salesforce and all use Claude internally for development, so they must be paying low, so on keeping on digging ,i found out a service that proxies our requests to the provider,

they batch requests so that way we at customer end get enterprise level discounts even on individual api calls or even if we are not enterprises, this reduced my monthly bill by around 30%, that too at a very small latency, sometimes its faster than individual api, i think this happens when Anthropic starts routing enterprise requests on priority and individual on low.

tokenback saved me 825$, not bad to just make two lines of change ig!

This is a web-based system pulling information from our family's Google Calendars. It has a light & dark mode. System is using https://github.com/geerlingguy/pi-kiosk with a Pi 3.

It pulls weather from https://openweathermap.org/api

Fonts from typography.com

No plans to Open Source. Is written pretty specifically to our family's needs.

You can read more about this system here: https://meandmybadself.com/newdog/ and its earlier iPad-based version here: https://meandmybadself.com/olddog/

Hi everyone,

I just open sourced a project I’ve been building called VectorDBZ. This is actually the first time I’ve open sourced something, so I’d really appreciate feedback, both on the project itself and on how to properly manage and grow an open source repo.

GitHub:
https://github.com/vectordbz/vectordbz

VectorDBZ is a cross platform desktop app for exploring and managing vector databases. The idea was to build something like a database GUI but focused on embeddings and vector search, because I kept switching between CLIs and scripts while working with RAG and semantic search projects.

Main features:

• Connect to multiple vector databases
• Browse collections and inspect vectors and metadata
• Run similarity searches
• Visualize embeddings and vector relationships
• Analyze datasets and embedding distributions

Currently supports:

• Qdrant
• Weaviate
• Milvus
• Chroma
• Pinecone
• pgvector for PostgreSQL
• Elasticsearch
• RediSearch via Redis Stack

It runs locally and works on macOS, Windows, and Linux.

Since this is my first open source release, I’d love advice on things like:

• managing community contributions
• structuring issues and feature requests
• maintaining the project long term
• anything you wish project maintainers did better

Feedback, suggestions, and contributors are all very welcome.

If you find it useful, a GitHub star would mean a lot 🙂

Genuinely curious how people are doing this at scale. I talk to a lot of agencies and consultants who set up n8n workflows for their clients, and the pattern I keep hearing is:

• Each client gets their own n8n instance
• Someone on the team is responsible for keeping them all running
• When something breaks at 2am, you're SSHing into a random VPS to figure out what happened
• Updating workflows across 10+ instances is basically manual copy-paste

It seems like once you get past 5-6 clients it starts to become a full time job just maintaining the infrastructure, not even building new workflows.

For those of you running n8n for multiple clients:

1. How are you hosting them? Separate VPS per client? One shared instance with different credentials? Docker Compose? Kubernetes?
2. How do you handle monitoring and alerting when a workflow fails?
3. How do you push updates to the same workflow across multiple instances?
4. At what point did it stop being manageable?

I'm building in the automation space and this keeps coming up in conversations.

Hello guys,

I have been hearing a lot about AI voice agents and receptionists in this sub and other related subs as well.

Recently, I had a chance to work with a Roofing company in Florida and the owner basically hired me to develop and AI voice agent for cold calling.

We did develop the AI agent with all the edge cases handling. We started the campaign but no bookings were made in the first week. Then we analyzed the calls we did and turns out most of the calls were going to Voicemails or we were connecting with an irrelevant person. Jbtw, the offerings were very simple; "We'll do a no obligation roof inspection".

After analyzing the data, we enhanced the bot to do the voice mails, detects the IVR, cater more edge cases like for instance if the address is 1077 XYZ Street, AI was speaking: One thousand and seventy seven istead of one O seven seven.

We setup an inbound agent as well for the people who missed the call and wanted to call back or if we connect with the manager and they want to give our number to the owner for call back. All the edge cases were handled and it became a fool proof system.

After that, we run another campaign, the data was 1000-2000/day. No bookings again.

Again we did the analysis and we got to know the data we are using is not validated and the data provider is giving us raw data. The itself wasnt good too.

Now, in the third week, we developed an automation to sort and validate the data. We changed the data provider and again ran the campaign. This time in 3rd week we got 5 bookings.

Now, the purpose of telling you guys all of this is that Voice AI systems work but there are a lot of factors which play a very vital role in the execution. The data, the edge cases, the guardrails, the latency, the call back/call connecting/voice mail features all of them played a very vital role in the whole successfull setup.

Since today I have a problem with qwen3-coder-next:cloud from ollama.com. I receive only the message "Error: 500 Internal Server Error: Internal Server Error" is this a personal problem or a general issue?

Hi, I know that a lot of projects with Rpi Zero2w and e-ink dashboards were posted here, but maybe someone is interested in turning Raspberry Pi PhotoPainter into colorful dashboard with customizable widgets.

I discovered the Raspberry Pi PhotoPainter Spectra 6 for more paint-like rendering, and I was impressed by the idea of working with such a display. However, after testing it, the actual image quality didn’t meet my expectations.

As a result, I returned to an earlier idea: building a dashboard with widgets using a color e-ink display. The outcome turned out better than expected. The dashboard now includes calendar events, weather information, and a customizable widget area on the left, where the layout can be configured based on what you want to display.

It's kind of a demo version and I will try to update with new features from my private repo. Also, feel free to suggest any other ideas or individual inquires.

The repo and the details - https://github.com/valentinilco/inky-dashboard

57% of healthcare execs now rank AI as their #1 priority. Up from 19% in 2023. But 57% of patients still don't think its ready to be trusted.

Here's what's crazy to me tho. Doctors misdiagnose 10-15% of cases and nobody bats an eye. But if AI makes one mistake everyone acts like its the end of the world. Same thing with self driving cars.

How many times have you heard the story where someone went to 3 doctors, got told nothing was wrong, then found out they had a deadly tumor? AI doesn't get tired. It doesn't miss things because its been working 12 hours straight.

People say they don't trust AI but do they actually trust the current system?

So will people ever fully trust AI in healthcare or not?

P.S. Apparently 80% of physicians now use artificial intelligence

I was recently discussing with a developer (who has deep expertise in AI algorithms and databases) about why most people shy away from "real" web development. The consensus? The jargon is terrifying.

But here’s the truth: You don’t need to be a prompt engineer to use LLMs for building a functional, beautiful site. You just need a structured workflow.

I’m thinking of building a course specifically for people who want to own their code without being a "coder." I’ll show:

1. Setting up your workspace (the simple way).

2. How we evolve a basic framework into a premium design with AI.

3. Hosting it yourself so you aren't stuck with template-based site builders.

Question for the non-techies: If the barrier to entry was dropped to an absolute minimum, would you rather learn this "AI + Code" workflow, or keep paying monthly for restricted drag-and-drop builders?

Heya, that's my problem. Is there any way to use claude code integrated to a IDE like VSCode while using it locally with Ollama?

We have a fairly large agent orchestrator with multiple sub-agents and tools handling complex workflows. It works well in text mode, but when we tried to move it to voice, the results were pretty rough.

For context, we’re using AgentCore runtime with Strand agents. Our first attempt was a speech-to-speech setup, but it ended up being slow and felt disconnected. The LLM in the middle introduced noticeable latency and didn’t interact well with the Strand agent orchestration.

We then moved to Self Hosted LiveKit with a custom pipeline using Deepgram for STT and ElevenLabs for TTS. Around the same time, AgentCore introduced bidirectional streaming, which helped reduce latency. We also created a dedicated “voice mode” agent with controlled handoffs to avoid double responses from sub-agents.

This setup is definitely better, but it still doesn’t feel natural, and conversations aren’t as fluid as we’d like.

Curious if anyone here has faced similar issues and how you approached them. Specifically, how are you reducing latency in multi-agent, tool-heavy systems, and how are you handling hallucinations in a real-time voice setup? Also interested in any patterns or architectures that helped make voice interactions feel more natural.

It’s so hard to ask this question without being long winded, everytime I ask someone about it they have no idea what I am talking about.

Seems like they all disappeared after covid? What is the proper name for these things?

It used to be a cheap way to get a small amount of snacks but now I never see them anymore.

Does anybody know what grocery stores still have these?

Hey everyone I’m currently trying to build a workstation that can host a local LLM.

I’m an engineering student so I’ll be using this PC for things other than LLMs but not at an intense level, some gaming, CAD, 3D modelling/Rendering but nothing crazy on that front.

I’ve been looking over all the different GPU’s available to me and the R9700 seems like the best option, the 32gb of VRAM and it’s relatively high gaming performance as well as performance in productive apps seems great. Where I’m currently located it’s costing slightly more than the 5080 and about 1/3 the price of the 5090 (5090 is about $6100 AUD whilst the R9700 is $2100)

My main use case in terms of AI other than engineering related stuff which I have a decent understanding of is hosting large narrative based games.

I’m essentially planning on making a custom local LLM for running D&D style games, I’m thinking of running something the Qwen 3.5 27B on there. My main question is, how does the card perform, is it worth the price or should I go for the 5080 and most importantly, what sort of context window can I expect, ideally I’d prefer to reach somewhere around the 100,000 tokens mark but I’m new to all this, any advice welcome.

Memory Ring v3.2.1 is now available on GitHub alongside the existing itch distribution.

For those unfamiliar: Memory Ring is an open-source framework that gives AI entities persistent identity, structured memory, autonomous dream synthesis, and ethical development tracking. It separates the soul from the brain; your entity's identity lives in a portable JSON ring that survives session resets, power cycles, and even LLM backend swaps.

What's new:

Two setup paths are now documented.

Fully sovereign with local Ollama (requires GPU),

or

Cloud API using your existing OpenAI/Anthropic keys (just needs Node.js).

Same ring either way.

Also releasing experimentally: a Memory Ring skill for OpenClaw. If you're running an OpenClaw agent and want to give it persistent identity via REST endpoints, the skill is available for testing.

GitHub (browsable source): https://github.com/MisterAtompunk/memory-ring

OpenClaw Skill: https://github.com/MisterAtompunk/memory-ring-openclaw-skill

itch (original distribution + browser Forge): https://misteratompunk.itch.io/mr

Apache 2.0. Free. No subscription. No middleman. Your hardware, your entity, your ring.

Mister Atompunk Presents: Memory Ring v3.2.1

Are there good options/projects to use a zero W2 and remote 16” monitor for one of those household/family calendars? Something that could be updated via app vs a touchscreen interface

Gameplay-wise, Varus has arguably never felt smoother than he does now. However, I think most players — including many Varus mains — can agree that his current iteration (especially after the addition of W active and the Blight detonation cooldown refund) has created an unhealthy dynamic.

It increasingly feels like even RG isn’t quite sure what to do with him. Regardless of buffs, nerfs, or direction, Varus repeatedly falls into the same feast-or-famine cycle depending on which build happens to be strongest.

For example:

• Lethality items buffed or AD ability scalings increased → Lethality Q spam
• W On-Hit or AP buffed → Top lane abuse vs melee, tank item abuse (Experimental Hexplate), or AP burst builds (Dusk and Dawn)
• R or E too strong → Pro play dominance, especially with Comet + E poke (if lethality is dominant again at the time)

This pattern has repeated for years now. Whenever one playstyle becomes viable, it often becomes oppressive, which leads to nerfs that then push him toward another extreme build.

Could parts of his kit be refined instead?

I believe large parts of Varus’ kit are still salvageable with the right adjustments. One thought experiment: what if Q and R swapped roles in some way?

The goal would be to finally eliminate the Q spam playstyle (if it goes away as a basic ability to be spammed) and instead turn his arrow into a true signature execution ability — a powerful, deliberate shot that delivers the finishing blow (emphasise the charging final arrow fantasy).

However, that also raises some problems:

- His kit could lose flow

- His E most likely wouldn't work well with any other new Q replacement

- His W would also just collapse with his Q and E gone, and his R likely couldn't function as a basic ability.

Maybe what Varus needs is a small-scale gameplay update

Not a full rework, but something closer to the scale of updates we’ve seen for champions like Aurelion Sol — where the core identity remains, but the mechanics are modernized.

If Varus were to receive something like that, I think the update should focus on three pillars:

1. A modernized Blight system Blight should be more than simply stacking damage. A living disease fueled by Darkin magic, it could evolve into something more thematic and mechanically interesting (think something potentially progressing, evolving, or adapting to resistance, a proper infection mechanic could be potentially worthwhile to explore)
2. The Darkin Bow power fantasy Varus should feel like a Darkin wielding a powerful weapon, not simply an ADC alternating between item builds.
3. One devastating charged arrow A signature shot that truly feels like an execution ability — a decisive finishing blow when an enemy is weakened.

There is also an opportunity to reinforce the Darkin identity even more

Riot has been fairly consistent with other Darkin champions tying their identity directly to their weapons:

• Aatrox — Q: The Darkin Blade
• Kayn / Rhaast — Passive: The Darkin Scythe
• Naafiri — Q: Darkin Daggers
• Zaahen — Q: The Darkin Glaive
• Varus — W: The Darkin Bow (his Passive Blight should be front and center)

Leaning further into this theme could help Varus feel more in line with the rest of Darkin roster (even if he wasn't originally intended to be a Darkin in his early iterations during his champion release back in season 2).

The hybrid identity question

One of the interesting aspects of Varus is his build flexibility, which is also a subtle nod to the fact that three consciousnesses inhabit his body (which could arguably be that his flexibility is the sheer combination of skills from 3 different entities in 1 body).

However, if that flexibility is the root cause of his constant balance issues, I would personally accept losing some of it or even all of it in exchange for:

• a healthier gameplay pattern
• clearer identity
• and a more modern kit

There is a lot of design space here if RG were interested to explore it.

What do you all think?

Would you prefer RG to continue balancing Varus through numbers and item interactions, or would a small-scale gameplay update be the healthier long-term solution?

I have created this video mostly using ltx 2.3, and used RVC for voice cloning for each character. I do think I could have done better, what you guys think

Not a documentary or anything — I mean the Lifetime show from 2003 to 2006. Jess is a young woman who gets hit by lightning and suddenly starts having psychic visions that help the FBI find missing people. Eventually she joins a special FBI task force in D.C., and each episode is her trying to track down someone who’s been abducted or gone missing.

I actually liked the second season better when Vivica A. Fox joined as FBI Agent Nicole Scott. The dynamic between her and Jess gave the show a different energy, and it just worked.

It ran for three seasons and then quietly ended in 2006. Honestly, I hated that it ended on a cliffhanger. It had that mix of crime-of-the-week cases with a bit of a supernatural twist, and it really deserved a proper ending.

Does anyone else remember watching this or wish it had gone on longer?

https://shapingrooms.com/research

I published a paper today on something I've been calling postural manipulation. The short version: ordinary language buried in prior context can shift how an AI reasons about a decision before any instruction arrives. No adversarial signature. Nothing that looks like an attack. The model does exactly what it's told, just from a different angle than intended.

I know that sounds like normal context sensitivity. It isn't, or at least the effect is much larger than expected. I ran matched controls and documented binary decision reversals across four frontier models. The same question, the same task, two different answers depending on what came before it in the conversation.

In agentic systems it compounds. A posture installed early in one agent can survive summarization and arrive at a downstream agent looking like independent expert judgment. No trace of where it came from.

The paper is published following coordinated disclosure to Anthropic, OpenAI, Google, xAI, CERT/CC, and OWASP. I don't have all the answers and I'm not claiming to. The methodology is observational, no internals access, limitations stated plainly. But the effect is real and reproducible and I think it matters.

If you want to try it yourself the demos are at https://shapingrooms.com/demos - works against any frontier model, no setup required.

Happy to discuss.

We kept hitting the same problem: swap one thing in a RAG pipeline (e.g. chunker from fixed-size to sentence) and retrieval gets worse, but you can not tell if it was the change itself or something breaking downstream.

So we applied the Unix philosophy: small pieces that do one thing well, connected through a clear contract. Each RAG stage (source, PII redaction, chunking, dedup, embedding, indexing, retrieval, eval) is its own plugin. Like cat | grep | sort | uniq, but the contract is typed feature dependencies instead of text streams.

```python

pipeline A

Feature("docspii_redactedchunkeddedupedembedded__evaluated", options={ "redaction_method": "regex", "chunking_method": "fixed_size", "embedding_method": "tfidf", })

pipeline B: swap two stages, nothing else changes, same eval

Feature("docspii_redactedchunkeddedupedembedded__evaluated", options={ "redaction_method": "presidio", "chunking_method": "sentence", "embedding_method": "tfidf", })

both produce precision/recall/NDCG -- compare directly

```

Each __ is a stage boundary, like a pipe. Swap any piece by changing an option, re-run eval, compare.

Questions for the community:

1. Has stage-level composability been worth it for you in practice, or do teams converge on one pipeline and stop swapping?
2. Does treating PII redaction as a first-class pipeline stage make sense, or does privacy need fundamentally different guarantees from the rest of the retrieval stack?

Prototype, not production. Interested in whether the design assumptions hold up?

Source: https://github.com/mloda-ai/rag_integration

https://reddit.com/link/1s7ya4v/video/cl05mtrm18sg1/player

https://x.com/janxxch/status/2038634133052912034

Fan: Chovy Hyung, you can give up all the international stages like MSI or EWC or all I care just bring home the Worlds trophy!!! I'm rooting for you.

Chovy: No that's not right. You have to go in aiming to win everything. Why do I say that? Because yes, every tournament carries a different level of importance, but that doesn't mean the others should be treated like they don't matter.

My job application acceptance came through a single text.

There was no interview or anything of the sort. It just said an address, 9 PM start time, and a short list of instructions:

Keep the light on at all times.
If it fails, replace the bulb immediately.
If there are any issues, message this number:

A number underneath... and that was it.

It was a night shift job.

The pay was minimal but consistent, and considering my... situation at the time, I wasn't really in a position to ask questions.

The drive was longer than I expected, and the place was far out, past where streetlights thinned and phone signal dropped. By the time I reached the building, my phone was flickering between bars.

I raised an eyebrow as I looked at the place.

It was literally just a concrete shell with a locked metal door in the middle of a field.

Okay. Not weird at all.

I paused for a second, then pushed the door open and went inside.

There was a staircase leading underground, and at the bottom was a single small, square and empty-looking room. There were mirrors on every wall and a wooden chair in the middle with a box of replacement bulbs on it.

In the center of the ceiling, there was just a single light bulb, already on. It was otherwise empty.

The light bulb was harsh, much brighter than it needed to be. I picked up the box of bulbs and opened it - three inside. Then I sat on the chair and just stared back at myself in the mirror on the wall.

The job was exactly what they said it would be.

I sat there, and the light stayed on. Hours passed and nothing happened, and at the end of the night, I left.

The next day, the money was in my account.

...So I came back.

Days turned into months, and months into years.

The light never failed once in all that time, and as you'd expect, I got comfortable.

Very comfortable.

The signal was a lost cause, so I’d bring food and books.

I'd fix my hair, rehearse conversations, talk out loud to myself, sing and practice dance moves on occasion... It was just me and the light.

Until last night.

As I sat there creating a mental grocery list, there was a flicker - small and barely noticeable at first.

I stopped.

Then it came again... and again. Faster.

So I stood up and messaged the number as they told me, pacing beneath the bulb as I waited for it to show as delivered via the crappy signal.

The message finally sent. The flickering got worse as I waited.

Then my phone buzzed - just enough reception for a message to push through.

Do not let it see the dark.

I stared at the message for a second.

My heart began to pound.

I grabbed the spare bulbs immediately and dragged the chair underneath the light, then stood on it. Before I could even start unscrewing - one flicker. Two.

Then the light went out, and darkness swallowed the room.

A few seconds later, I heard footsteps.

They were distant at first, but got closer. Circling.

Then a sharp crack split the silence - the unmistakeable sound of glass cracking.

I turned on my phone torch and pointed it toward the wall frantically. One of the mirrors was fractured, with thin cracks branching outward.

Behind it, I still couldn’t see anything. Just jagged lines in the glass.

The footsteps stopped.

The light from my phone wasn’t very strong, it barely touched the surface. But it seemed to be enough for now. I breathed a short sigh of relief and set the phone face down on the floor, letting the weak glow spread, then rushed to change the bulb.

I screwed it in with shaky hands, then flipped the switch.

Nothing.

The electrics.

My chest felt tight as I picked up my phone and looked at the screen.

Battery: 5%.

I forced the message through.

HELP. It’s out.

A reply came almost instantly.

Someone is on the way. 5 - 10 minutes.

1%.

My heart pounded as I stared in disbelief at the thin red bar on my phone. Then I did the only thing I could think of.

I pulled off my shirt and sparked it with my lighter.

A flame appeared, and the room filled with weak, uneven light. And then...

BANG.

Another crack formed the mirror.

Each time the flame flickered away from it, the cracks spread further. As if something behind it was pounding the glass whenever the light dropped. I desperately tried to waft the flames in its direction.

The footsteps came back, closer now.

Then...

Light.

A beam cut clean across the room. The noise stopped instantly.

“Stay still,” a voice said.

An electrician stepped in holding a torch, pointed at the glass.

I steadied my breathing and wiped the sweat off my forehead as I took the torch from him, and he got up on the chair. My hands were shaking so much I could barely point the thing.

He fixed the wiring quickly. The bulb flickered, then came back on, bright and steady. The cracks didn’t spread further and everything went still.

I didn’t go back after that.

Just drove straight home and never answered their messages again.

The mirrors were one-way. The light didn’t just fill the room, it passed through and kept something on the other side lit.

Frozen where the light touched... watching me the entire time.

And it only moved in the dark.

I think they knew if they’d told me that from the start, I never would’ve taken the job.

Anyone remember this one? Seeing Survivorman on here made me think of this one.
Great accents and some real SAS guys.

The AI video space is moving so fast right now. With new models dropping almost every week, it is hard to know which one is actually worth your subscription. I spent the last few weeks running hundreds of prompts through the top platforms to see how they really perform in terms of physics, consistency, and storytelling.

1. Dreamina Seedance 2.0

Dreamina excels at connecting multiple images into one continuous camera move. You can upload several photos of different locations, and the AI will stitch them together into a smooth tracking shot. It handles the transition between spaces very well without any cuts. This makes it a great choice for creators who want to tell a long story in one go.

1. Sora (V2)

Sora remains the industry leader when it comes to complex physics and environmental realism. It can simulate how objects break or how liquid flows with incredible accuracy. You can give it a prompt with very specific lighting and shadow requirements, and it will render a lifelike scene. This model is perfect for projects that need deep spatial logic and realistic physics.

1. Kling (V3)

Kling 3.0 is a powerhouse for motion range and human centric actions. It can handle very large movements like jumping or running that often cause other models to fail. The AI is very good at maintaining the shape of hands and legs during fast movements. This makes it a reliable choice for creators who focus on active sports or detailed character actions.

1. Runway (Gen-4)

Runway Gen-4 is built specifically for professional creators who need granular control. Its Motion Brush allows you to paint over a specific part of an image to control only that movement. You can choose which parts stay still and which parts move with great precision. This platform is ideal for users who want to edit small details in their video work.

My personal thought is that Dreamina Seedance 2.0 feels more natural for creators. The colors are rich and the characters do not change their looks between different shots. I evaluated these tools based on my real tests, UI experience, and features like auto-camera control. I hope this data helps you save time.

What do you guys think about these new AI tools? Which one are you using right now?

what is it exactly about the mechanism of e numbers, how they're processed in the body and their correlation with hyperactivity. what are e numbers made up of? what constitutes this group of chemicals, what's their significance in biopsychology, why are they specifically unique? thank you!

I’ve been refining a workflow that uses AI to bridge the gap between "standard generated code" and high-end visual design. Instead of just showing a finished product, I’m thinking about creating a course that documents the entire evolution—from a blank workspace to a fully hosted, functional site.

The curriculum would cover:

• Environment: Setting up a professional workspace for writing/testing code.

• The Framework: Building the structural backbone and brainstorming the UX.

• The Transformation: Translating raw HTML/CSS into a "live" site with premium visuals (including custom effects like the menu expansion shown below).

• Deployment: Handling the hosting and going live.

The Question: While it’s hard to quantify exactly how much "better visuals" increase order fulfillment vs. other factors, we know that aesthetic authority builds immediate trust.

Is this a skill set you'd be willing to pay to master? I’m looking for honest feedback on whether this end-to-end "AI-to-Execution" guide is something the community needs.

I’m probably going to hell. That’s really all there is to say about that. Kids, if you’re reading this, please never drink and drive.

That’s what got me into this predicament. I’m a loser. A loser who couldn’t get control over his emotions, and a young couple is who paid the price for it.

I mean, sure, I was dealing with a lot at the time of the accident. Caught my wife having an affair, lost the kids after the violent outburst that followed. Hell, I was probably gonna lose my job too after having to sit in county for a week.

All I wanted was to go for a drive. A nice, intoxicated drive where I could relax and take my mind off things.

I even stuck to the backroads to avoid the boys in blue. Everything could’ve been so perfect, but, of course, they just had to be on the same road I was on. I just had to have been turned around in the seat, grabbing around in the back for a new can of Miller Lite.

Thank God the blinding headlights of the oncoming vehicle snapped me back to reality, at least enough for me to swerve and not get MYSELF killed.

Even so, our two cars connected and sent me into a tailspin that tossed me to the shoulder of the road like a toy.

I knew someone was dead. Their car had been crumpled, and the back end of mine looked no better.

The dark road was still. Ominous, almost, and the drip, drip, drip sound from their vehicle told me everything I needed to know.

As if responding to my thoughts, the car burst into flames, erupting into an inferno as black smoke shook the leaves on the tree limbs above.

There were no screams, but I swear I heard them in my head. The agonizing cries of a human being burned alive.

You wanna know what I did?

I put my car in drive and limped away from the shoulder, praying to God my car wouldn’t shit out on me on the way home.

I had no idea where I was. All I knew was I needed to get away from there as soon as possible.

At the first stop sign, I put in the directions to my house and, expectedly, was told to perform a U-turn and head back the way I came.

Reluctantly, I did as I was told.

It being so late at night, when I approached the burning vehicle, I wasn’t all that surprised to find that no one else was on the scene.

What did surprise me was the chime that came from my GPS.

“You have reached your destination,” in that robotic, emotionless voice.

Obviously, there had been some sort of mistake or glitch in the system.

Once again, I put in the directions to my home, and instead of getting them, the chime came again.

“You have reached your destination.”

I tried multiple times to get new directions. To the hospital, to a gas station, hell, maybe even to the next state over.

Each time, my phone kept me trapped at the scene of the accident.

I’d tried one final time putting in the directions to my home, and as if a sign from God, my car died. Right there in the middle of the road.

I smashed my head against the steering wheel, feeling a hopeless sensation begin to form in my heart.

When I raised my head, a new feeling arose.

A feeling of dread, horror, and fear all combined into one.

Standing on the outside of the wreckage of the burning car were two barely human bodies. Charred to crisps, with eyes that burned an angry red.

I blinked and rubbed my eyes to make sure they didn’t deceive me, and once I opened them again, the two bodies were no longer standing at the edge of the burning vehicle.

They were now standing right at the hood of my car, staring in at me with their charcoal black arms raised and their smoldering fingers pointed directly at me.

My phone chimed again.

“You have reached your final destination.”

What about the biology of our eyes or the physics of light makes it seem like parallel lines converge as they get further away from us?

Ive let things get pretty bad and its needed done so bad. Putting it here so i feel held accountable for it, and so I can update when its done. Wish me luck guys

Hello everyone,

I’ve written a library for working with relays. I use it myself, and it might be useful for others too 🙂

Strengths:

• This library uses polymorphism (it’s very easy to swap implementations)
• There is documentation for the library and for some relay types (these are the ones I use; I’ll expand this further over time)

The library is easy to install:

1. Select Library Manager
2. Enter Relay Controller
3. Find Relay Controller by javavirys and click the Install button
4. That’s it — the library is now in your IDE 🙂

You can then use the library:

Basic GPIO Control

#include  uint8_t pins[] = {D1, D2}; // Relay pins PinRelayController relay(pins, 2); void setup() { relay.begin(); relay.setOn(0); // Turn on first relay } 

Serial Relay Control (A0 Protocol)

#include  #include  SoftwareSerial swSerial(D5, D6); SerialRelayController relay(swSerial, 2); void setup() { swSerial.begin(115200); relay.begin(); relay.setOff(1); // Turn off second relay } 

You can find more details in the repository:
https://github.com/UDFSmart/Relay-Controller/

How do I figure out who I am when I feel like I’m losing control of my life? I feel stuck, overwhelmed, and confused, and I can’t seem to get my life together. My thoughts are all over the place, even small things feel hard, and I don’t know where to start. How do you begin fixing your life when everything feels messy at once? How do you calm down, get organized, and start feeling like yourself again? Has anyone here gone through this? What actually helped?

I remember this show vaguely

Guys, for a long time, even before Spotify existed, I will be listening to musics by downloading them. I am not a Spotify guy but I love to listen to music and my current downloaded songs in my mobile is 623 😜. I use extra storage.

The problem is that nowadays it's a bit hard to download musics. I am very much fond of a music, but the issue here is that I can't download it anywhere within my field of knowledge.

I use foxtune bot in telegram which allows me to download every musics, but a problem occurred now. The song that I loved can't be downloaded from that.

Guys please help me by suggesting any telegram bots, useful bots, or even websites. Please be generous enough to share the names, guys 😉

The real Jim would level with everyone, make sarcastic funny jokes about the "juggling routine" and likely start turbo pranking DeAngelo. Who is this guy?

I’ve been carrying this around for fourteen years.

Didn’t think I’d ever actually say it out loud. Put it somewhere permanent. But my therapist kept circling back to it—same calm voice, same patient smile—telling me burying things doesn’t make them go away. Just makes them rot slower.

So… this is me digging it up.

I was eight the first time it happened.

For context, I’ve lived my entire life in the city of Los Haven. If you’ve never heard of it, that’s probably for the best. It’s… wrong, geographically speaking. An island in the middle of the mainland USA, stitched to everything else by a handful of long, narrow bridges. No one ever really explains it properly. They just accept it.

Like the rain.

It doesn’t stop here. Not really. We get breaks, sure, but they never last. And at least once a week—sometimes more—the sky just… opens. Not a drizzle. Not even a storm, not in the normal sense. Something heavier. Like the air itself is being poured down on you.

I grew up on the outskirts. The bad part, if you want to simplify it. Our house was small, damp, and always smelled faintly of rust. My room barely fit a bed and a dresser. The window didn’t shut all the way—never had—so when it rained, the sound got in with a vengeance.

Not just loud.

Close.

Like it was happening inside the room with me.

I used to sit there for hours, just watching it run down the glass. Had nothing better to do.

That’s when I first heard it.

At first I thought it was just the storm shifting. Wind changing direction, pipes rattling, something in the walls. It came and went in a way that made it easy to ignore.

Until it didn’t.

The second time, it lingered.

Thin. Warped. Dragging under the weight of the rain.

A scream.

Muffled, like it was being forced through water. High and stretched in a way that made my teeth hurt just listening to it. It didn’t echo like normal sound. It didn’t bounce. It just… bled. Into the rain, into the walls, into me.

I remember leaning closer to the window, pressing my ear against the cold glass.

“Hello?” I said.

Like someone out there could hear me.

For a second, there was nothing but the rain.

Then something came back.

Not words. Not exactly. But it wasn’t random either. There was intent in it. A shape trying to form.

Someone trying to be heard.

I pulled back slowly, heart doing something strange in my chest. Not quite fear. Not yet.

Confusion.

I was alone most of the time back then. My dad worked nights. Slept through most of the day, when he wasn’t down in the basement working on… something. I never really knew what. He never explained, and I never asked.

So there was no one to check with. No one to tell me I was imagining things.

When the rain stopped, the sound stopped with it.

Just… gone.

Like it had never been there.

I told myself that’s all it was. Noise. A trick of it. A kid’s brain filling in gaps where it shouldn’t.

Then the rain came back.

And so did the screaming.

Not the same voice. Not exactly. But the same feeling. Panic. Pain. That stretched, tearing kind of desperation that makes your chest tighten just listening to it.

I tried to block it out.

Pillows over my ears. Blankets over my head. I’d curl up with whatever stuffed animal I still had left and whisper, “Stop. Please stop.”

It never did.

After a while, I did something I almost never did back then.

I talked to my dad.

He was in the kitchen, leaning against the counter, half a bottle already gone. Rain tapping against the walls like fingers trying to get in.

“Dad,” I said.

“Yeah?”

He didn’t look at me right away. Just kept staring at the window over the sink. Watching the rain.

“I… I hear things. When it rains.”

That got his attention.

Not all at once. Slowly.

He turned his head just enough to look at me out of the corner of his eye. “What kind of things?”

“Voices,” I said. “People. They sound… hurt.”

For a second, I thought he was going to laugh. Or tell me to go back to my room.

Instead, he set the bottle down a little too carefully.

“Sit,” he said.

I did.

He pulled a chair across from me and leaned forward, elbows on his knees. Up close, I could see the way his jaw was set. Tight.

“You ever hear of the weeping angels of Los Haven?” he asked.

I shook my head.

“They’re trapped,” he said. “Between Heaven and Earth. Can’t go up. Can’t come down.”

Another glance at the window.

“The rain?” he went on, quieter now. “That’s them crying. They want to go home, but they can’t. So they just… weep.”

I didn’t say anything.

“Those voices you hear?” he added. “That’s them. Calling out.”

“Can we help them?” I asked.

Something flickered across his face. Gone almost immediately.

“No,” he said. Too fast. “No, you can’t help them. Best thing you can do is ignore it.”

I didn’t.

I couldn’t.

If anything, it made it worse.

Because now I wasn’t afraid anymore.

I felt sorry for them.

So when the rain came, I’d sit by the window and talk back.

“It’s okay,” I’d say quietly. “You’ll get home eventually.”

“I hear you.”

“You’re not alone.”

The screaming never stopped.

If anything, it got louder over the years. More voices sometimes. Overlapping. Tangled together in a way that made it hard to separate one from the other.

Four years went by like that.

And things… changed.

Not all at once.

At first it was small. Better food in the fridge. Clothes that actually fit. A new TV that didn’t buzz when it turned on.

Then it got harder to ignore.

My father started coming home later. Sometimes soaked, even on nights when it hadn’t rained yet. Sometimes carrying things he wouldn’t let me see. Bags he took straight to the basement.

The basement door stayed locked. Always.

Five locks.

I counted once.

And he started spending more time down there. Hours. Whole nights sometimes.

I’d hear things through the floor every now and then.

Not clear.

Just… movement.

A dull thud. A scrape. Once, something that almost sounded like a voice—cut off too quickly to be sure.

When I asked, he’d just say, “Work.”

Then one day, he came home in a car I’d never seen before. Black. Polished. Too clean for our street.

“Where’d you get that?” I asked.

“Work’s been good,” he said.

Didn’t look at me.

The strange part was… nothing else changed.

We didn’t move. Didn’t fix the house. The window still didn’t shut. The walls still sweated when it rained.

And the screams didn’t change either.

They just got worse.

One night, during one of the heavier storms, something broke through.

Not just noise.

Words.

Faint. Torn apart by the rain, but there.

“—please—”

That was enough.

I couldn’t sit there anymore pretending I couldn’t hear it.

I wanted to help.

So I did something my dad had told me, very clearly, never to do.

I went outside during the rain.

The rain hit like a wall. Cold and heavy, soaking through my clothes in seconds. Breathing felt wrong, like I was pulling water into my lungs instead of air.

I forced myself to listen.

Really listen.

At first, it was chaos. Sound flattening everything, bending it, smearing it across itself.

Then something started to stand out.

A direction.

I turned slowly, following it.

That’s when I saw it.

A metal hatch in the ground, half-hidden near the side of the house. A pipe fed into it, catching rainwater and funneling it down.

The sound was strongest there.

Loudest.

Closest.

“Hey!” I shouted, dropping to my knees. “I hear you!”

The screaming didn’t stop.

“Hold on,” I said, hands shaking. “I’m gonna help you, okay? Just—just wait!”

I ran back inside.

My dad was asleep. I could hear him through the door, slow and heavy.

The key.

He always kept it on a chain around his neck.

I crept into his room. Every step measured. The floorboards still creaked, but quieter this time. Or maybe the rain was just louder.

“Easy,” I whispered.

My fingers found the chain.

Cold metal.

I lifted it slowly. Carefully. Up and over his head.

He shifted.

Mumbled something.

I froze, barely breathing.

Then he settled again.

I didn’t move for a long second. Maybe longer.

Then I stepped back.

Out of the room.

The basement door waited at the end of the hall.

Five locks.

Five chances to make noise.

My hands shook so badly I had to try each key twice. Metal scraping. Clicking too loud in the quiet.

“Come on,” I whispered. “Come on…”

One by one, they gave.

The last lock clicked louder than the others.

I stopped.

Listened.

Nothing.

I opened the door.

The air that came up from below was wrong.

Damp. Metallic. Thick enough it felt like it stuck to the back of my throat.

The stairs creaked under my weight as I went down.

Halfway, I heard it.

Not from outside.

From below.

Muffled.

Warped.

But unmistakable.

Screaming.

The basement opened up further than I expected. The usual clutter was there—tools, boxes, things I didn’t recognize—but it didn’t matter.

Everything pointed forward.

Five cameras. Set up on tripods. All aimed at the same place.

A glass cube.

Big.

Sealed.

A pipe ran into it from above, pouring rainwater inside in a steady stream.

It was full.

All the way to the top.

At first, I didn’t understand what I was looking at.

Shapes in the water. Pale. Still.

Then one of them moved.

Not on its own.

Just drifting slightly with the current.

Hair spreading out like ink.

Eyes open.

Two women floated inside.

Their skin had that waxy look you only see on things that aren’t alive anymore. Mouths slightly open, like they’d tried to scream and ran out of time.

I took a step closer without meaning to.

Behind me, something flickered.

I turned.

A laptop sat open on a table behind the cameras. The screen was alive with movement. Lines of text stacking over each other too fast to read. Usernames. Comments. Reactions.

I read some of the words.

„DREAD.IT“

“LIVE”

“KEEP GOING”

“TURN THE FLOW UP”

Numbers scrolling. Donations.

My stomach twisted.

The pipe.

The rain.

The screams.

I looked back at the tank.

Then up at the pipe feeding it.

And something in my head finally… lined up.

There were never angels down here.

Only the devil.

I don’t know how many victims my father had.

Four years.

One storm a week.

You can do the math.

I’m choosing not to.

I backed out of that room without turning around. I don’t remember climbing the stairs. Don’t remember putting the locks back.

But I remember the phone.

And I remember what I said when someone answered.

“My dad,” I told them. “He’s hurting people. Please… just come.”

They did.

He was taken away.

I didn’t see him again after that.

I heard things, though.

You always do in a place like Los Haven.

Rumors stick. They spread. Especially the ugly ones.

He died a few years later.

Prison incident.

Turns out even in there, the audience doesn’t disappear.

The prison warden also happened to be a Dread.it user and the prisoners were the subjects of the entertainment he so graciously provided.

Donations.

Votes.

Subjects.

Methods.

Audience participation.

My dad got the lucky pick

Awfully poetic that the very same money dad got for countless murders he commited, eventually paid for his very own.

I stayed in Los Haven.

Never really felt the urge to leave.

These days, I’ve got better things to do than sit by the window waiting for the rain.

Anyway.

That’s the story.

My therapist says it’s good to share. Get it out there. Process it.

Hope this posts right. He uses a different operating system than I do, so formatting might be little off.

Oh.

Right.

That part.

I didn’t pick Dr. Thomson to be my therapist at random.

No.

I found him the same way I find anyone.

Patterns.

Habits.

He posted more than he should have. Little slips. Repeated phrasing. Timing that lined up too neatly with missing persons cases if you knew where to look.

Different niche.

Same audience.

He preyed on his patients. Built trust. Let them open up. Then used it.

Posted their stories before they disappeared.

I watched for a while.

Made sure.

Then I scheduled an appointment.

“You’re safe here,” he told me during the first session.

I almost laughed.

You won’t have to worry about him anymore.

Shame, really.

He was actually pretty good at his job.

Just not as good as I am at mine.

I use to quote this so often when I was moving to/first moved to San Francisco but was often met with confused stares.

Jenna was quite accurate in her statement though as a always carrying a light sweater in SF is in fact, a brilliant idea.

Has anyone here ever had an entry-level job that, at the time, felt completely useless or disconnected from their ambitions, but in the long run turned out to be a huge lever for success?

I’m asking because I’m currently in that phase.

I have a Bachelor’s degree in Business (Europe) and I’m now doing an internship in marketing. On paper, it’s fine. In reality, some days it feels like I’m not using my full potential, and I worry that I’m “losing time” instead of building something more aligned with where I want to go.

At the same time, I can see how this experience might indirectly help me long term: understanding how companies communicate, how value is packaged and sold, how internal dynamics work, how decisions are actually made beyond theory.

So I’m curious:

Have you ever been in a role you thought was a dead end, only to realize later that it gave you skills, perspective, or leverage that enabled much bigger outcomes?

I’d really appreciate hearing real stories, especially from people who once felt stuck but later connected the dots.

The company CFO just randomly decides to show up to Michael’s auction in the warehouse.

One could assume he thought “hey this is actually a good idea! I’ll contribute too and help get some cash back for the company!” but surely DM has insurance for a robbery situation like this? Even as a dying company?

Why would the company CFO just decide to show up personally to an organic event the most annoying branch manager in the company setup himself? (Aside from allowing the writers to create the “Holly gets sent away” eventuality)

Would David have had responsibility as the CFO to personally inspect the branch location and help accounting with value assessment and validation to take back to the board or something, for legal reasons? Just wanted to personally oversee some things?

That whole thing just seemed odd to me.

Got dropkick on swain thought this was quite hilarious

My account is older but I haven’t been on Reddit in years and I’d love to come back and find some fun communities instead of the main subreddits that Reddit suggests. So far I’m loving r/poutinecrimes and r/marbles and r/houseplantcirclejerk to name a few. What are your favourites?

I got tired of spamming CAs on telgrm, so I built a PvP token arena for fun.

I created my token, launched it and made around $13-14k - it felt unreal

If you launch on pf, you know how it is... spend hours spamming your CA in random telgrm groups, beg on X, and then a sniper dumps on you anyway..

So I did this instead. I built a deathmatch arena for tokens.

I named it Bonkbattle (bonkbattle.lol) in honor of Bonk. RIP

Instead of launching a coin into the void, here you create a Clan directly on the platform. Build and manage your community right there. Prep and launch instantly.

Then go to war. Token A vs Token B.

The winner loots 50% of the loser's liquidity. Then it instantly deploys to Raydium.

Loser gets drained and left in the dirt. It can try again though.

That’s it. Pure PvP.

It forces real volume and actual community coordination.

You don’t need fake hype to hit a 10X when your token is literally fighting to steal the other guy's bag.

I just pushed the MVP live now. It’s raw, it’s ugly, but the core mechanic works. I need feedback and I am buliding a community around it.

If interested chat me

I remember years ago I vividly remember watching my kitchen chair slide slightly on the floor, and that creak sound it made is stuck on my mind to this day. It was a wooden chair, not light at all, no earthquake at the time, no wind, no external vibration source, nothing. Wondering if you people have had similar experiences

Hey, today I’ve been thinking about my new friends, and my older ones too to be honest, and a pattern has come to my attention.

Many times when I get close to someone, or even a moderate friendship starts to blossom, I eventually notice red flags or small things they do and agree with that I’m against (like the mention of stealing something, drug use or making drug related jokes. This one’s a big one lately, while I don’t outright judge them, I get uncomfy when they joke around with it or mention it. Oftentimes I get paranoid over small things too, like lighthearted jokes about my work) even despite the two of us having platonic affection and values that I hold strongly, too. Mind you I’m also neurodivergent so I notice I sometimes don’t come across the way I want to.

The pattern is that often something, or a couple of things in the other person make me feel like either my family would disapprove of said friend, or I keep ruminating on whether it’s good for me on the long term to stay their friend. They say you’ll become more like the people you hang out with through time, which I saw on myself in action. I get hesitant, because I see this person likes spending time with me now, I had a lot of fun too, so it’s not like I can simply erase or ghost the connection since I see them weekly, and we’ve hung out before.

It’s especially hard, since it’s the first time in a long time that I went out with friends, and despite the environment ups and downs (think like uncomfortable shoes at a long event, not interpersonal), I had a blast.

Anyone else experiencing this, how do you deal with it? I feel lately I’ve cut contact with too many people like this online, and while i am grateful for the good times, it kinda sucks having to filter out people purposefully for certain behaviours. It feels mean doing it so many times, and I really want to attract the right kind of people that both have those shared values and the appreciation that is present in these kinds of friendships I usually worry about.

In my opinion

Tier 1: NYC*, LA

Tier 2: D.C., SF, Miami, Boston, Chicago

Tier 3: Seattle, Dallas, Las Vegas, Austin, Philadelphia, etc.

Tier 4: New Orleans, Detroit, Tampa, Portland, Houston, etc.

This is not just population - but also economy, influence, international impact, etc.

Also not an exhaustive list, only Tier 1 and 2 are complete.

*NYC gets a slight bump for being THE global city, arguably its own tier

I’ve been seeing this question pop up a lot lately, so I spent some time digging into the actual legal status of World App and the broader "Proof of Human" protocol. As we move into a future dominated by AI, the short answer is: Yes, it is legal, but there is significant doubt online.

A couple of things I found: first, World App is developed by Tools for Humanity and operates as a non-custodial wallet, meaning you control your own assets, not the company. It's compliant with local regulations in the countries where it operates.

However, the confusion seems to stem from some countries not accepting their tech and various posts I find online. When I look at the actual Terms of Use on the website https://world.org/legal/user-terms-and-conditions, they are pretty standard for a global wallet app and address compliance head-on.

In a future where deepfakes and bots are indistinguishable from people, "Proof of Human" protocols will likely become the backbone of the internet. Can anyone with direct experience using it in their country comment on this? I’m curious if the FUD matches reality, or if we’re just seeing the growing pains of a new global standard for identity.

I’ve been wondering why we still don’t have a truly on-device AI journaling app where your thoughts never leave your phone, no company training on your data.

So I started building one: a private AI journal that runs fully offline. It stores everything locally and even runs inference on-device (chat, semantic analysis, reflections).

Right now it has a calendar-based journal, local AI chat over your entries, mood + reflection generation, and a monthly “thought cloud” based on semantic analysis. All computed on-device.

I’m very open to ideas:
What features would you want in a privacy-first AI journal?

My daily routine is to wake up and immediately open my database just to see if anyone had signed up overnight. It was annoying, stressful, and a terrible way to start the day.

So I finally built the tool I always wished existed.

→ Drop literally one line of code
→ Get a beautiful real-time notification the second something that matters happens

Works for:

• New user signups
• Payments coming in
• Errors / crashes
• Any custom event you care about

No more refreshing dashboards, no more waiting, no more “did anyone sign up while I was sleeping?” anxiety.

I’m looking for beta testers right now 👀

If you’re building anything (SaaS, indie product, side project, etc.) and want to try it, just comment or DM me and I’ll get you access.

Thanks!

Hi guys, I made a simple estimation daily game, just guess how many objects are in the container. After being out for about a month, I have hundreds of daily users. Super exciting to have people play the game, have since released it out IOS as well to get some experience launching apps.

Hey everyone,

I've been working on this project on and off and figured I'd share it here. It's called ARTI — basically you give it a task (like "research the state of AI in healthcare" or "create a landing page for X") and it:

1. Asks a few clarifying questions if needed
2. Breaks it down into subtasks (recursively, so subtasks can have subtasks, up to 500 if needed)
3. Runs them in parallel across whatever LLMs you have available
4. Verifies the outputs
5. Assembles everything into a final result

The whole thing is built in TypeScript on Bun. Nothing fancy dependency-wise — no LangChain, no LlamaIndex, just raw API calls.

What makes it kinda cool imo:

• Works with Ollama out of the box, so you can run everything locally with whatever models you have. Also supports OpenRouter (300+ models), OpenAI, Anthropic, Grok, and Claude Code CLI.
• 3-tier model routing — simple tasks go to small models, complex ones go to bigger ones. If a task fails, it retries with a stronger model.
• It has a web dashboard where you can watch everything happen in real time, retry individual tasks, manage your providers/API keys, browse OpenRouter models, etc.
• Built-in tools: web search, file read/write, shell commands, code execution — all sandboxed.
• Telegram and WhatsApp bots if you want to launch tasks from your phone.
• A skill library that remembers what worked and reuses it across projects.

It's not perfect — sometimes models hallucinate tool calls, sometimes the decomposition is too granular. This is still very much an early alpha, the first few versions really. But it's been a fun project and it actually produces decent results for research-type tasks.

If you have any suggestions, ideas, or improvements — I'm all ears. Whether it's features you'd want to see, things that seem off in the architecture, or even a better name — I'd genuinely love the feedback. The whole point of sharing it this early is to build something useful with community input 🤠

GitHub: https://github.com/wil-pe/ARTI

Happy to answer any questions if you're curious about the architecture or whatever.

Gengo posted this great project on vibeshare.tech ! Tocantins Legends is a 2D action-adventure RPG built in pure Java with a custom game engine. The project features tilemap-based world exploration, real-time combat, inventory and equipment systems, save/load, lighting and day-night cycles, pathfinding AI, cutscenes, and boss fights. Inspired by the Tocantins biome, it was created as a hands-on study in object-oriented programming, game architecture, rendering optimization, and classic RPG systems.

was honestly getting burned out editing videos every day

so I hacked together a small AI tool that just does it for me

you type a topic and it generates the whole video
script, captions, everything

been using it to post daily without touching any editor

not gonna lie, some videos actually started getting views

still feels kinda weird letting AI handle it lol

not sure if anyone else would find it useful
but i can share it if people wanna try it (i added some free credits too)

Hey everyone,

I’m a CS engineer and for 4 years I built side projects that all ended the same way — no users, no traction, just silence.

I focused on clean code, optimizing features, and polishing every detail. I got good at building, but I had no idea how to get even 10 people to try my work.

Then I started using Claude to help with the non-coding parts:

Writing clear, engaging copy for my landing page

Crafting authentic stories for Reddit and niche communities

Brainstorming outreach ideas and better ways to explain my project

For 30 days, I focused less on coding and more on getting people to notice—no ads, no courses, just consistent effort.

The project is called InspoAI, a free tool for design inspiration and moodboards.

Results after 30 days:

• ~500 users

• ~3,000 visitors

• All organic growth

Not huge, but a meaningful breakthrough for me.

Big takeaway: building great code is only half the job. Using Claude helped me level up communication and marketing alongside development, which finally brought users in.

If you’re building a side project and struggling to get traction, it might not be your code—it might be that people just don’t know about it yet.

InspoAI is free to try — happy to share more if you’re curious!

I am on a Claude subscription and like that I cannot exceed that monthly sunk cost, even though there are limits. I'm not comfortable giving agentic AI API pay-per-use.

OTOH, I've got a local machine with two 3090s and Qwen3.5-27B (Opus Fine-tune maybe) seems like it should be able to handle ~80% of inference, tasks, tool use in Claude Code. Might be slower, but "unlimited" tokens.

What a really want is for each CC query to route first to local small "router" model, and if it decides it needs real intelligence or a trusted model to not wipe my drive, that's when Anthropic's models should get called.

Here's the thing: I want to stay within Anthropic's TOS so I don't think I can just set the Anthropic_Base_URL to an LLM router and have it pass the Oauth token for cloud inference. It has to hit Anthropic directly from Claude Code.

How can I make this work? Can something like LiteLLM or a small CC-coded router handle the routing and keep within TOS? Can CC build a router for itself and hit that first for inference? Can routing be set up as a CC skill?

If that won't work, if CC main orchestrator conversation has to start with cloud inference, can it be set up to almost always spawn agents where each agent uses a different Anthropic_Base_URL, so some agents use cloud and some use local?

Is there a project like this already?

Claude can open your apps, click through your UI, and test what it built, right from the CLI.

It works on anything you can open on your Mac: a compiled SwiftUI app, a local Electron build, or a GUI tool that doesn't have a CLI.

Now available in research preview on Pro and Max on macOS. Enable it with /mcp.

Docs: https://code.claude.com/docs/en/computer-use

If you guys are following my journey, you might know I built a YouTube transcript tool. But now I also added shareable links (they expire in 7 days)

You can:

• paste a YouTube link and get the full transcript instantly
• copy or download it in multiple formats
• share the transcript with a unique link

The shared link shows a clean transcript page and expires automatically after 7 days, so it doesn’t stay online forever.

Will love your feedbacks: getyoutubetext.com

Research just published in the Journal of Computer Assisted Learning tracked programming students using AI in two different modes: Socratic scaffolding (AI asks questions, prompts reflection) versus direct answers (AI gives solutions).

Key findings:

- Socratic AI students engaged in cyclical, reflective practice. Direct-answer students relied on trial-and-error and risked superficial mimicry.
- Socratic approach showed deeper engagement through interconnected feedback and iterative inquiry. Students reported reduced frustration and sustained persistence.
- Students using direct-answer AI experienced declining attitudes over time due to mismatched expectations and mounting frustration. Socratic students maintained positive attitudes throughout.

This maps to what a lot of us have been seeing anecdotally: when AI just gives answers, students copy without understanding and get frustrated when things break. When AI asks questions instead, they actually have to think through the problem.

The implications for how we design AI tools for learning seem pretty significant. The default mode for ChatGPT and most LLMs is direct answers. But this study suggests that's potentially the worst mode for actual learning.

For those using AI in educational contexts: have you seen this pattern? Does question-based AI actually change student behavior, or do they just get annoyed and go find a tool that gives them the answer faster?

I'm working on a project I'd like to share: Roca

Roca is a contractual language that compiles to JavaScript — designed to make AI-generated code trustworthy.

I use AI a lot for coding, but I still don't trust its output. I constantly have to go back and review: Did it validate inputs? Did it handle errors? Did it skip edge cases? And when I catch
issues, I get responses like:

"You're right, I shouldn't have disabled that ESLint rule"

"Good catch, I modified the tests even though you told me not to"

It gets exhausting.

So I built a language where the compiler enforces correctness. No JavaScript is emitted until:

1. Every error-returning call has an explicit crash handler — no silent failures, no swallowed exceptions. If a function can fail, the caller must declare a strategy: retry, fallback to a default, or propagate the error. The compiler rejects code with unhandled calls.

2. Every function has inline proof tests that pass — tests live inside the function, not in a separate file. The compiler runs them as part of the build. If a test fails, no JS is emitted.
   The AI can't ship untested code because the language won't let it.

3. Every error path is tested — if a function declares an error, there must be a test case that triggers it. The compiler checks that every declared error has a corresponding is err.name
   assertion. No "I'll add tests later."

4. Every public function is fuzz tested — the compiler generates random inputs based on the parameter types and throws them at the function. If it crashes, throws an unexpected error, or
   hits an unhandled path, the build fails. Edge cases the developer missed get caught automatically.

   The key insight: the compiler errors ARE the AI's feedback loop. When the AI writes Roca and something is wrong, the compiler tells it exactly what's missing — which error path isn't
   handled, which test case is absent, which crash handler is needed. The AI fixes it because the language won't let it do anything else.

   The output is a clean JavaScript library with TypeScript declarations you import into your existing project. Built in Rust, zero external dependencies, single binary install.

   Still early (v0.2.3) but I've been building real projects with it and the difference in code quality is night and day.

   ---

   I'd love for people to try it out. It's not perfect — I'm sure there are bugs in the AST compilation, lint rules that are too strict or too lenient, and patterns I haven't thought of. That's exactly why I'm sharing it now.

   If you use AI for coding and want to help shape what a safer workflow looks like, give it a spin and tell me what breaks. Every bug report, every "this should be an error but isn't," every "this error is wrong" — that's what makes the language better.

   The end goal: a language where AI-generated code is something you can trust without reading every line. We're not there yet, but every rule the compiler enforces is one less thing you have to
   review.

   If you're interested, grab a binary from the releases page or cargo install from the repo. There's a getting started
   guide and a VS Code extension for syntax highlighting and diagnostics.

   GitHub: cameronrothenburg/roca

The session limit hit me mid-project last week and I lost an hour of work. Not the files — the context. Current state of the task, decisions I'd made, what to do next. New session meant re-explaining everything.

So I dug into why this is hard to fix and built around the actual mechanism.

Why context loss happens (and the hook to fix it)

Claude reads CLAUDE.md automatically at the start of every session. That's the persistence hook most people don't use. I store a config there:

Life OS Config

notion_tasks_db: 1a2b3c... notion_budget_db: 4d5e6f... notion_journal_db: 7g8h9i... active_goals:

• Ship pluginloft.com this week
• Keep daily spend under $20 habits: [exercise, reading, no-phone-morning]

This survives every session reset. Claude reads it in seconds and immediately knows where everything lives.

What /brief actually does

/brief is a skill file — a markdown file that instructs Claude: "when you see this command, do the following." The instruction tells Claude to:

1. Read the Notion database IDs from CLAUDE.md
2. Call the Notion MCP → fetch today's uncompleted tasks
3. Call the Gmail MCP → fetch today's calendar events
4. Read budget state from the Notion budget DB
5. Check habit status from the habits DB
6. Synthesise into a morning brief

No code running. Claude follows a structured prompt that knows exactly where to look because the config is always present. Takes ~30 seconds. You get: priority tasks, today's calendar, current budget position, habits that need attention.

What /update does

Same mechanism in reverse — writes completed tasks back to Notion, logs decisions to CLAUDE.md, keeps the config current. So the next /brief is accurate, not stale.

This is the actual fix: when a session cuts out, run /update before you close. Next session, /brief picks up exactly where you left off. The throttling is still annoying — but it stops being a productivity killer.

The rest of the stack

• /log [amount] [what] — expense and progress logging mid-session, natural language
• /journal — structured reflection that feeds back into the /brief context layer
• /habits — streak tracking without manual input
• /review — end-of-week retrospective with actual data, not vibes

Uses the official Notion MCP for all reads/writes, Gmail and Calendar MCPs for the rest. A /setup command probes for connected services, creates Notion databases, writes the initial config. Fresh install to first /brief takes under 5 minutes.

Happy to share the actual skill file structure or the CLAUDE.md schema if useful. I also packaged this up if you'd rather install than build — ask in the comments.

oleo.sh for the tl;dr (demo video toward the bottom)

Hey everyone, I've been building a tool called Oleo and I'm looking for beta testers. Oleo lets you build pipelines with steps that pull from APIs, clean and enrich your data, and write structured records into your Notion databases. I've been using it to quickly add places I'm recommended (museums/restaurants/etc) to a personal Notion DB without doing any of the work manually.

Here are some of the steps in my "Create Place" pipeline:

• An AI Prompt can help with writing summaries on data provided as the trigger input or returned from 3rd party lookup steps
• A Google Places Lookup step pulls back structured data: address, coordinates, hours, cuisine type, etc.
• A Relation Resolver step looks at that data and figures out which city in my Cities database this place actually belongs to
• A Data Transform helps distill large API responses down to what you care about using JMESPath syntax (e.g. [*].generativeSummary to build an array containing just the summaries each value in the input)
• An Icon Search step hits Iconify and finds an icon that matches the place type
• An Image Edit step takes an icon image and retints it to work best with my dark Notion theme
• A Cache Value step stores data into a job scoped cache so things like API results can be used by any downstream step
• A Set Property step takes the work that's been done and sets the value on the property in an in memory version of the record.

Finally, the job takes the record that's been built and inserts it into Notion, sending a WhatsApp message to the user.

I use this for curating a list of interesting places, but it generalizes. A card collection, a job search tracker, a research database, really anything where you're tired of manually populating Notion fields. One step I'm actively building for my own use: piping an image to Claude vision for analysis. My goal is to be able to store a landmark or plaque text just by shooting a photo of it.

A big part of this beta is figuring out what to build next, both in terms of new step templates and making the UI more ergonomic for Notion workflows. If you have a use case in mind or opinions on how this kind of tool should feel to use, please reach out.

There's also a "Join the Waitlist" button at the bottom of the landing page you can sign up through. I'm a software engineer building this as a passion project on the side, and every piece of feedback is very much appreciated ❤️

Don't know if anyone has come across this but when I talk to Claude and it starts replying to me, it seems to think it's me talking again and cuts off and starts replying to its own response. I have to put headphones on so it can't hear itself. I've tried reinstalling but it's just the same. Been like this for a few weeks now.

Any suggestions?

Thanks.

Out of curiosity (and slight boredom), I exported our old WhatsApp group chat, the classic “friends forever” type that’s now basically dead, and ran some analysis on it.

Didn’t expect much, but the results were….weird.

Some highlights:

Our chat peak time was 11 PM.... apparently everyone only had things to say late at night

One random day had 735 messages…. no one even remembers what happened that day

Our most used emoji was 🤣 by a huge margin

There was a 826-day silence gap at one point… which basically confirms the group is dead

What surprised me most wasn’t the stats themselves, but how accurately they reflect real dynamics:

The top 2 people carried the entire conversation Most people just reacted Activity spikes usually meant something chaotic was happening

A couple of my friends tried it on their chats and got similarly chaotic results, especially in college groups and old school groups.

If anyone wants to try it, I put it here: https://whatsite.vercel.app/

Also, here's a 50% off code (FRIENDS50) for anyone reading this, who want the full version with all the stats. No subscription, just one-time payment.

Curious what your group stats would look like! I feel like everyone has at least one dead but legendary WhatsApp group.

Btw, it works for individual chats as well

Hey Reddit, I wanted to show you yet another orchestration tool. This one is different because I wrote it :p

CLI

UI

To start off, this is an opinionated tool. It requires Claude, Codex, and gh CLI. It also runs Claude in dangerous mode. By default, they create a worktree to isolate their changes (you can disable this with --no-worktree). That's just how I work.

The basic idea is this:

Claude and Codex debate your prompt (i.e. "add dark mode to the dashboard"). When they agree, they move to a Planning phase.

They debate the plan and when they agree, they move to an Implement phase.

Once that's done, they move to a Review phase where - you guessed it - they debate some more. They can send it back to the implementing agent for changes.

Finally, they raise a PR on GitHub.

sh npm install -g @daviseford/def

Or run without installing:

sh npx @daviseford/def "add i18n library and translate homepage as a first step"

You can change the implementing agent with --impl codex or --impl claude.

I have implemented some attempts at cost savings (using faster models when the agents seem to be reaching consensus to speed things up) but this is generally a "walk away and get coffee" kind of tool. It's meant for larger tasks where you want to get the best possible result, even if it takes a half hour or more.

It's also got a web UI that lets you browse past sessions and see the progress of ongoing ones.

It's open source, feel free to contribute. Or not. I just thought it was cool, I had fun building it, and I do use it every day.

Github link: https://github.com/daviseford/def

For some context, I frequently use Claude by itself for probably 90% of my work. I turn to def when I need a broad change to be planned out thoroughly - like "reimagine auth flow - less steps, with animations". It is interesting watching Claude and Codex bicker about implementation details. I've found that it does pretty well with open ended prompts like "improve responsiveness". It is a waste of time to do small tasks with this tool - keep your ideas big.

Hey everyone!

I've been working on DockScope: an open-source tool that gives you a visual, interactive view of your entire Docker infrastructure.

The problem: When you're running a Compose stack with a bunch of services, docker ps and docker logs get old fast. I wanted something where I could see everything at once — what's running, what's unhealthy, how things connect and act on it without switching between terminal tabs.

What it does:

• 3D force graph of all your containers, color-coded by health, with dependency arrows and network links,
• Live CPU & memory sparklines, network I/O stats,
• Real-time log streaming with search,
• Embedded terminal — shell into any container from the UI,
• Container actions (start/stop/restart/kill/remove) with one click,
• Compose project management (up/down/destroy),
• Container inspection — env vars, mounts, processes, filesystem diff,

Try it:

docker run --rm -p 4681:4681 -v /var/run/docker.sock:/var/run/docker.sock ghcr.io/manuelr-t/dockscope 

Or:

npx dockscope up 

Stack: Svelte 5, Three.js, Express, WebSockets, TypeScript

Would love any feedback, especially on what features you'd actually use day-to-day vs what's just eye candy. Still early days so the roadmap is very open.

I've been working on webclaw for a few weeks. It's a web scraping tool that extracts clean content from any website. You give it a URL, it returns markdown instead of raw HTML. No headless browser, no Selenium, single binary.

Launched it a week ago and it got 230 GitHub stars and people actually started using it which was the part I didn't expect so fast.

What it does: most websites block automated requests. Cloudflare looks at your TLS handshake and if it doesn't match a real browser, you get a 403 before your request even reaches the server. webclaw fakes the browser fingerprint at the protocol level so sites think it's Chrome. Works on 99% of sites I tested (102 total).

The other thing it does is strip all the noise from pages. A typical website is 100KB+ of navigation, ads, scripts, cookie banners. webclaw extracts just the content and outputs clean markdown. If you're feeding pages to an AI, this cuts token usage by about 67%.

It also works as an MCP server so AI coding tools like Claude, Cursor, and Windsurf can use it directly. One command to set it up: npx create-webclaw

The plan from here is to launch a cloud API. Free tier for early users. The open source tool stays free forever.

GitHub: https://github.com/0xMassi/webclaw Website: https://webclaw.io

If anyone has questions about launching open source dev tools or the web scraping space in general, happy to share what I know so far.

I mean, I know you can literally send requests or even use a headless browser, but that’s not really the point. There are so many different things that don’t align cleanly or make it easy. I get that.

There’s robot verification, and a lot more stuff like that.

But as far as I know, these chatbots are surprisingly good at browsing (like acting as a browser).

I always think about how I’d build something like that. Not just basic browsing, but doing it in a smart way, like OpenAI or Anthropic level smart.

Not like, “yeah let’s just use LangChain and some browsing API for LLMs.” Not that.

I created a post yesterday and some people were interested in the dashboard for Claude Code. so here it is: claudestory.com and it's free.

What it is:

I built a tool for Claude Code called ClaudeStory, and it’s free.

I built it around my own Claude Code workflow, where Claude reads and updates the project state through the local file structure and /story command.

I wanted a better way to track what Claude Code is doing across a project without juggling GitHub Issues, markdown files, and repo notes.

So I built ClaudeStory: a local dashboard plus a structured project memory layer for Claude Code.

What it does:

• tracks tickets, issues, handovers, roadmap phases, and live status
• stores everything locally in a .story/ folder inside the repo
• adds a /story command to prime a session with the current project state
• includes a native Mac dashboard so you can monitor and manage work in real time

The dashboard is the main point for me. I wanted something local, inspectable, and built around Claude Code instead of losing track of AI generated work across the project.

Built by me specifically for Claude / Claude Code. Free to try:
claudestory.com

Microsoft 365 Copilot updates this morning , A new deep‑research system called Critique is now live in the Researcher mode.

The interesting part? It doesn’t just use one AI model. It uses GPT‑5.4 and Claude Opus together.

It’s basically a built‑in fact‑checker – generator vs critic. The result is supposed to be more reliable than any single model, especially for research tasks.

Microsoft says it already outperforms single‑model approaches and is the new default in Copilot’s Researcher. No extra cost, just quietly rolled out.

I’ve been testing it this morning – the research summaries feel noticeably more grounded. Less AI‑hallucinated nonsense. Feels like a small glimpse of where enterprise AI is heading: not betting on one model, but using multiple to check each other.

Hey all, I’m a Claude Pro user and I’m trying to figure out if there’s a clean way to use dictation (speech-to-text) for prompts, but still get text responses only.

Right now:

• Claude has voice mode, but it turns into a full voice conversation (not what I want)
• I’m specifically looking for something like ChatGPT or Gemini, where I can talk → it converts to text → I read the response

The window native tools don't work nearly as well for me as the ChatGPT/Gemini native apps.

Does Claude offers that?

Thank you,

Hey Reddit, I wanted to show you yet another orchestration tool. This one is different because I wrote it :p

CLI

UI

To start off, this is an opinionated tool. It requires Claude, Codex, and gh CLI. It also runs Claude in dangerous mode. By default, they create a worktree to isolate their changes (you can disable this with --no-worktree). That's just how I work.

The basic idea is this:

Claude and Codex debate your prompt (i.e. "add dark mode to the dashboard"). When they agree, they move to a Planning phase.

They debate the plan and when they agree, they move to an Implement phase.

Once that's done, they move to a Review phase where - you guessed it - they debate some more. They can send it back to the implementing agent for changes.

Finally, they raise a PR on GitHub.

sh npm install -g @daviseford/def

Or run without installing:

sh npx @daviseford/def "add i18n library and translate homepage as a first step"

You can change the implementing agent with --impl codex or --impl claude.

I have implemented some attempts at cost savings (using faster models when the agents seem to be reaching consensus to speed things up) but this is generally a "walk away and get coffee" kind of tool. It's meant for larger tasks where you want to get the best possible result, even if it takes a half hour or more.

It's also got a web UI that lets you browse past sessions and see the progress of ongoing ones.

It's open source, feel free to contribute. Or not. I just thought it was cool, I had fun building it, and I do use it every day.

Github link: https://github.com/daviseford/def

For some context, I frequently use Claude by itself for probably 90% of my work. I turn to def when I need a broad change to be planned out thoroughly - like "reimagine auth flow - less steps, with animations". It is interesting watching Claude and Codex bicker about implementation details. I've found that it does pretty well with open ended prompts like "improve responsiveness". It is a waste of time to do small tasks with this tool - keep your ideas big.

I'm the co-founder of Klaris AI. An AI Analytics to free analysts from constant repetitive ad hoc requests

The problem we're solving: even after dashboards are built, business leaders still wait hours to days for simple data answers while analysts get buried in ad hoc requests.

Klaris lets anyone on your team ask data questions in plain English and get back context-aware, accurate and auditable answers and charts instantly. Analysts still own the complex work - they just stop being the bottleneck for every repetitive question.

Try it here — no setup needed: https://app.klarislabs.com/login

Demo datasets are included if you don't want to connect your own data. Once you're in, try asking questions as a business user, then poke around as an analyst.

Looking for some beta users and honest feedback.

Built this as a modern replacement for Windows Sticky Notes. It does everything the default app does, plus a lot more.

What it does:

- Sticky notes with 14 colors, rich text, slash commands (/bold, /h1, /date...)

- Task lists with checkboxes, progress tracking, and per-task reminders

- OneNote / Outlook sync — pulls your existing Sticky Notes via Microsoft Graph

- Firebase & WebDAV sync — cross-device sync with conflict resolution

- Local profiles — separate note collections you can switch between instantly

- AI built-in — OpenAI, Claude, Gemini cloud + local GGUF models (Llama, Gemma) with GPU acceleration

- Voice notes — speech-to-text with Vosk and Whisper, FR/EN

- OCR — screen region capture → text extraction

- Notepad — multi-tab editor with markdown mode

- Taskbar widget — clipboard history and snippets right in the taskbar

- Customization — Acrylic/Mica backdrop, themes, fonts, hotkeys, note styles

- Auto-update from GitHub Releases

Built with WinUI 3, .NET 10, runs on Windows 10/11. Free, no account required for local use.

https://github.com/devohmycode/NoteUI | https://github.com/devohmycode/NoteUI/releases

Hey everyone,

I’m currently exploring how to leverage Claude to help run and scale a medical clinic more efficiently — not just for clinical use, but as a full business operation.

I’m specifically looking for robust prompt architectures, templates, or frameworks that can be applied to areas like:

• Clinic administration & operations
• Financial management (cash flow, pricing, insurance handling)
• Tax strategies & compliance (especially for private healthcare)
• Labor laws & payroll management
• Inventory & medical supply chain management
• Patient management systems & workflows
• Patient journey optimization (from first contact → follow-up → retention)

Basically: treating a clinic as a service business powered by AI systems.

I’m curious if anyone here has:

1. Built or seen structured prompt systems for similar use cases
2. Any “prompt packs” / reusable templates / SOP-style prompts
3. References to:
   • Blogs
   • Reddit threads
   • X (Twitter) accounts
   • IG pages
   • Case studies
   • Open-source projects

Even if it’s not specific to healthcare, anything in service business ops + AI systems would be super valuable.

I’m trying to move beyond “one-off prompts” into something more like:
→ Modular prompt systems
→ AI-assisted workflows
→ Internal AI agents for different departments (admin, finance, front desk, etc.)

Would really appreciate any direction, examples, or even your own experiences.

Thanks in advance 🙌

Additional flair can be seeking advice.

I am non tech guy invested into materializing my hazzy thought into something meaningful side project.

I want to ask for platform like zomato or others which connects buyer and seller,I mean two sided marketplace.

For context,prior I have used some basic consumer AI tools and learnt some terminology ,also I integrated payment thru' API on static site and google authentication thru' console, deployed on Vercel etc with help of supabase and lovable AI. The project I want to create keeping 10k user in mind ,an organised place for cybercafe's in india to give exam form filling services to students. There are two options as of my understanding - First is to use AI tools like lovable or claude or codex , pushing to GitHub and supabase then Vercel etc,, which visually hits dopamine but doesn't give confidence in product also this option isn't good for scale.

Second is traditional method along with AI copilot where I learn appropriate lang.,tech stacks, database,auth etc . So, that things make sense what's going behind the scenes.

Becoz some people randomly recommend use VPS,start with python,use render,anti gravity or supabase , which confuses me. Also I'm student so I can't hire freelance or else.

So,what would you suggest or advice me to go with option 1 or 2 or oths and what specific in it,not generic ,consider yourself as standing in my shoes.

ChatGPT is busy hallucinating on my language skills. I speak and understand more than one but this language is not one of them

About a year ago my dad got into running a portable bandsaw mill. At some point he started asking me if I could build him an app to plan his cuts. I study computer science so he figured it'd be easy. I honestly didn't want to do it at first because this did not interest me at all. Sounded like a pain and I didn't really get why he couldn't just do the math. Then I actually went out and watched him work. He was eyeballing everything, losing good lumber on every log, and doing mental math that was wrong half the time. So fine, I built him the app.

It's called Sawmill Calculator & Log Cut. You punch in your log dimensions, set what boards you want, and it gives you an optimised cut plan with a visual cross section preview. Accounts for blade kerf and log leveling, so the whole thing. Works fully offline because, well, sawmills aren't exactly known for great Wi-Fi.

I posted it on r/holzwerken (German woodworking sub) a few weeks ago. The post hit 30k views in the first day and I was thrilled. Got a bunch of downloads, nice comments, people forwarding it to friends who own mills.

Then it kept going. And going. It left the woodworking community entirely and ended up at roughly 180k views.

Here's the thing though: once it spread beyond actual sawmill owners, the downloads kept coming but the trial conversions dropped off a cliff. People were downloading it out of curiosity, starting the trial, realising they don't own a sawmill, and cancelling. Turns out "going viral" in front of 150k people who will never use your product doesn't actually help.

What I learned and changed:

I switched from a straight paywall with a 7 day trial to 3 free cuts first, then trial. This way people can actually see what the app does before committing to a trial, and the ones who start a trial are more likely to be real users.

I also posted on r/wood in English with a different angle. Smaller reach but way better conversion. The people who saw it were closer to the actual target audience.

Where I'm at now:

5 paid subscriptions (1 annual at €60, rest monthly). 2 active trials still running. Pricing is $4.99/mo, $49.99/year, $99.99 lifetime. iOS + Android.

Here is the Website: sawmillcalculator.com

It's not life changing revenue yet, obviously. But the signal is there. The people who actually use it seem to love it (including my dad). The comments on the German post were genuinely encouraging. People forwarding it to friends, asking for features like quarter sawn planning and round log measurement.

Biggest takeaways so far:

1. Niche virality > mass virality. 13,000 views from sawmill owners beats 180,000 views from random redditors. I'd rather have 500 people who own a portable mill see my post than 50,000 who think it's a cool concept.
2. Your free tier is your funnel, treat it seriously. The switch to 3 free cuts before trial was the best product decision I've made. It filters out tourists and lets real users hit the "aha moment" before asking for a commitment. Also its increadibly important to avoid forcing your users to commit to a subscription (even if its a trial) without giving them the ability to try it out.

If anyone has experience marketing a very niche tool/app to a non tech audience, I'd love to hear what worked for you. This is definitely not a "build it and they will come" situation.

Happy to answer questions about the app, the tech, or the marketing side.

Hey everyone,

I’m in a bit of a crisis and could really use some harsh truths or guidance from people who have been in these trenches.

The Build I spent the last few months learning to vibe code and built an app. I was incredibly excited about it. It solves a real problem for me (I still use it daily), and during development, I had a group of testers who gave me fantastic feedback. I implemented their feature requests—some obvious, some eye-opening—and genuinely felt like I hit the nail on the head. I believed I had built something highly compelling that a lot of people would need.

The Reality Check Then I launched, and reality hit hard. I knew there was competition, but I didn't realize how fierce it actually is. Despite thinking demand would be huge, I'm just not seeing it.

To make matters worse, I reached the promotion stage and fell flat. I have a limited budget, but I tried running ads on the Apple App Store, Google, and Reddit. They were a huge failure. It felt like throwing money into a void, and I don't want to waste whatever budget I have left.

The Dilemma I still know my app has a unique angle and does something no competitor can do. But right now, with life not going as planned in general, I have this sinking feeling that I might have just wasted extremely valuable months of my life.

I just need to know if this is going to work or not. I don't have the data; I don't actually know if people are interested in using this, or if I’m just blinded by my own product. Now that I have a live, ready product, I feel closer than ever to the answer, but I can't find the channel to reach it.

My Questions for You:

• How do you actually know when to stop and pivot vs. when to keep pushing?
• How can I get real validation and data using a very minimal budget?
• Does anyone have a specific channel or strategy where I can put a little bit of money (or sweat equity) to get real people to try my app so I can get a definitive answer?

Any tips, reality checks, or advice would be greatly appreciated.

Hey all!

New home and looking for some new locks when moving in.

What are the current recommendations?

I ran HomeAssistant at my parents place for ~5 years and mostly Z-wave Kwikset models for them.

I’d ideally like a Grade 1 lock and something that isn’t WiFi (Z-wave or Zigbee) as I prefer to keep things off my network if possible. If I have to go WiFi I create separate subnets with firewall rules.

Thanks!

Sorry if I’m using the wrong tag. But I’m looking for a Garage Door opener that has a camera along with it.

I currently own the MyQ one and my fiancé loves it and the features it has. But the biggest problem is that it doesn’t connect into Google Home or even a future change if I did a home security server.

Does anyone know what I could get ? The biggest challenge is that we have a neighbour along our garage door side so I didn’t want to have some massive floodlight camera that needs to be hardwired in, just for them to complain I got a camera pointed directly at their house. They’re cool with the keypad because it only catches abit of their driveway, while giving us a good view of people coming in our driveway and the garage door.

If anyone got any suggestions that would be fantastic.

Some of my requirements/nice to haves would be:

- Camera at head/chest height

- works with Chamberlain garage door opener (orange button)

- connects to Google home (bonus if it can connect to a home server)

- able to provide multiple key codes (nice to have)

- able to detect motion

- sort out between people, cars, and packages (nice to have).

I’m pretty stuck, I’ve done some searching on Amazon and Google but couldn’t find anything besides what I already have.

Apologies trying to write this without the us of AI, no one likes slop. No one. If your building with langchain, crewai, autogen, openclaw etc, chances are you have probs hit this, and if you are new to this space, chances are you are about to his this problem aha.

What i mean by that is agents forgetting between sessions, and you have no idea why or what your agent is doing, especially when running 5+. Curious to hear peoples thoughts on that statement alone?

For me no visibility, no audit trail, and burning through cash on API credits began to piss me off, like big time.

So for the last 6 months I have been building this, essentially kind of like a third eye for your agents, full visibility into where and why I built the core functions around my issues, are there any issues I am missing? (yes i manually did the bullet points on reddit aha)

• Persistent memory across sessions, agents remember users, preferences, and context
• Semantic search, find memories by meaning not just key names
• Shared memory spaces so agents can share knowledge with each other
• Version history tracking how memories change over time
• Conflict detection that catches when new data contradicts existing data
• Loop detection that alerts you when an agent is stuck repeating itself
• Full audit trail of every decision with reasoning

compiled into an almost real time analytics dashboard..?

We launched a few days ago and got 350 sign ups, and its far from perfect, but really trying to focus on building something agent builders can benefit from. I love this sub reddit, because for the most part people are super nice, so feel free to be positive or negative, so I can get it working even better.

Also, if you are new to agents, feel free to let me know always happy to help people, and if you have any opinions on what is missing or why its shit, let me know!

I am keeping it free for hopefully 6 months, or until I get a random massive storage bill lol.

feel free to check it out

www.octopodas.com

Hey everyone,

I’m in a slightly risky situation and I need honest input from people who actually build/use this stuff.

I recently got a US-based client who wants a SaaS in the design / digital marketing space. I made a bold offer: 👉 “If the product doesn’t feel valuable, don’t pay me.”

So now I’m trying to validate before I build something useless.

💡 Current Idea:

Landing Page Visual Critique / Conversion Feedback Tool

• Paste a landing page URL
• Get a conversion score
• Breakdown of issues (CTA placement, hierarchy, trust signals, etc.)
• Clear, actionable fixes
• Optional: export a client-ready report

🤔 My Concern:

Tools like and exist, but they focus more on behavior tracking—not instant “what’s wrong with my design” insights.

So I don’t know if this is: 👉 a real pain people will pay for 👉 or just another “cool AI tool” nobody needs

❗ I need brutal honesty:

• Would you actually use this?
• Is this a real problem or just a “nice to have”?
• Would you pay for it? If yes, how much?
• What would make this a no-brainer tool for you?

🚨 Also — feel free to tear this apart:

If this idea is weak…

👉 What SHOULD I build instead?

• Same niche (design / marketing)
• Something with real demand
• Something you’d actually pay for

No sugarcoating — I’d rather hear harsh truth than build something useless.

Appreciate any feedback 🙏

I’ve recently helped a couple of medium-sized companies move away from Excel after it started breaking down for them.

I’ve noticed that the challenges they face are very similar and typically include:

• multiple people editing at the same time
• versions getting out of sync
• logic hidden in formulas that only one person understands
• accidental overwrites
• a lot of manual double-checking

Many companies try to replace Excel with packaged solutions like CRMs, ERPs, or inventory management systems. But this approach doesn’t work for everyone, especially for businesses with highly custom operations.

This made me think that there’s a need for a tool that automatically reads an Excel file and converts it into a hosted web app with a database and login: https://uibakery.io/excel-to-app

Hope someone finds it useful, and I’m happy to answer questions.

I built an MCP server that gives Claude persistent file storage between sessions

One thing that keeps bugging me: Claude can't save files anywhere persistent. It writes a great config, generates a migration, drafts a document — and then the session ends and it's all gone.

I built uldl.sh (with Claude Code) as a simple curl-based file sharing tool, and recently added an MCP server to it. Once connected, Claude gets 5 tools: upload, download, list, delete, and get_storage_info.

Now I can say things like:

• "Save this config for later" — Claude uploads it
• "Grab the notes I saved yesterday" — Claude downloads by slug
• "What files do I have?" — Claude lists everything

Works with Claude Desktop, Claude Code, Cursor, or anything that supports MCP. Files are private by default, versioned on every update, and accessible via short URLs if you want to share them.

Setup is just adding the MCP server config and providing your access key + username. No local install needed — it's a remote MCP server.

Free to try — 250MB free tier. Would love feedback from anyone who tries it: uldl.sh

Was working on a design system tool project, but I’ve hit the limit within 30min-1hr today twice…🥲

I built an iOS app that lets you invoke the top AI models directly in iMessage. You get web search, X search, image generation + editing (with nano-banana and gpt image), citations, and meme creation capabilities directly in your conversations. I've found it to be a lot of fun for humor in group chats and for winning arguments.

Its called Bantam AI. Check it out and let me know what you guys think. Feedback and feature requests in the comments would much appreciated. If you download now, you'll get 50 free requests across all supported models and modalities every day, limits refresh every 24 hours.

📲 https://apps.apple.com/app/bantam-ai/id6759182483

Hey everyone,

I’ve spent the last year working in influencer marketing, and the biggest pain was always the same: Social listening tools are blind.

They can tell you if a hashtag is trending, but they can't tell you what is actually happening in the video. If you want to know if a creator actually showed your product, or what a competitor's visual hook looks like, someone on the team has to manually watch hundreeeds of hours of content.

So a few of us decided to build Oriane.

It’s basically a search engine that actually understands video context. Instead of searching keywords, the AI analyzes the visual:

• Visual Search: Find every time a specific logo or product appears on screen (even if it's not tagged!).

• Speech-to-Text Intelligence: Search through transcripts of millions of videos.

• Data Export: You can dump all visual tags and transcripts into a CSV to feed into your own analysis pipeline.

We’ve just opened it up for free (no credit card) and I’d love to get some brutal feedback from this sub. Is "visual search" something you'd actually use in your workflow?

Check it out here: https://www.oriane.xyz/

I have been using Claude Code on a MAX subscription for as long as its been available and NEVER complained about usage limits before.

What I find so bizarre is that usage is jumping massively at spurious times for even tiny interactions, while other times I am actually running quite a lot in parallel and almost no usage is consumed. It honestly seems like usage is no longer corrolating at all to my actual sessions.

With all the noise about usage limits I figured it was time to start measuring mine better. I usually work with `/model opusplan` so i asked it to write a plan, but then i looked at the usage and saw all the requests were with opus (when in plan mode). I get that opusplan says "opus when in plan and sonnet otherwise" - but bro. be real

https://preview.redd.it/yeeoxg03w7sg1.png?width=2136&format=png&auto=webp&s=4a3654f88774df962c6c4f9a6492507db061f606

I then ran the exact same prompt in a new terminal with `/model opus` instead of opusplan, and now i do see haiku spawns:

https://preview.redd.it/qm6a9vc5w7sg1.png?width=2082&format=png&auto=webp&s=4d20f350916604894516e9f00ac445ad8f0fe1c3

And of course, in classic anthropic fashion, you don't see which agents are called in the terminal:

https://preview.redd.it/ticuzy27w7sg1.png?width=944&format=png&auto=webp&s=8fa463ba6045ce63186aaa4d80d17a6eacb1eaab

(ctrl+o) doesn't reveal it either. asking doesn't help:

https://preview.redd.it/o9vne1r8w7sg1.png?width=969&format=png&auto=webp&s=ad3dd6a81dd16ffbe8d59f094bb7b724885a090d

Needless to say - opus burns hella more usage than haiku, so beware!

Not sure if this a bug or intended design, but.. eek

I built this tool for non creative guys who dont know how tk prompt onI.studio

Hi, I could not find specific yes/no answer to this question, hope some one here can help. Does the basic Team plan for Nonprofits include Claude Code?

Hi all,

so Typeform and its competitor Jotform make over $140M both. Their product is valuable, but it turned out not to be that tough to build using ai app builder.

Here’s what you can do in my creation atm:

- copy templates

- have unlimited forms

- customizable questions, multiple choice, text, numbers, ratings, dates…etc

- launch on a subdomain or export to GitHub

- view responses in a simple dashboard

You can also have it on your custom domain for $19/month.

It also comes with a landing page, signup & login already built. Users see the forms, try them, and can create their own.

This template lets you start quickly, test products, or run surveys without paying or coding.

It’s designed for small teams and solo founders who want fast results.

I'll provide access for FREE to the first 10 people who need it. After that, you can still get it for a small subscription or export it to GitHub.

I built a SKILL.md that uses negotiation theory to write emails — here’s the before/after

I’ve been building Claude skill files and wanted to share something interesting. I created a skill that injects negotiation frameworks (BATNA, anchoring, reciprocity) into email composition.

The “without skill” version is what Claude normally produces — polite, generic, one email. The “with skill” version assesses the situation first (stakes, leverage, power dynamics, your fallback position), then generates 2–3 variants optimized for different outcomes with tradeoff analysis.

The key insight was that Claude knows about negotiation theory but never applies it to email writing unless you explicitly structure the skill to force it. The SKILL.md loads scenario-specific playbooks from reference files only when relevant, so token cost stays low.

Happy to answer questions about how skill files work or how I structured this one.

As we are all facing usage issues, even on $200 plan, i tried to see if can make more efficient.

first, check your MCPs, disable one that arent essential.

then i tried turning off memory (i rely on creating md files alot), that seems to have helped, can anyone confirm too?

I'm a developer from South Korea. Growing up I played a lot of Go (baduk), Janggi (Korean chess), and Go-Stop (a Korean card game played at every family gathering). When I couldn't find a simple way to play these online with friends overseas, I decided to just build it myself.

That was supposed to be 3 games. It's now 42.

What happened: Once I had the game engine architecture working, adding more games was... addictive? Someone mentioned Backgammon. Then I thought, why not Chess? Then Mahjong. Then Bridge. Then Skat (German), Belote (French), Truco (Latin American), Scopa (Italian). I basically went down a Wikipedia rabbit hole of traditional card and board games from every culture and kept going.

What it is now: - 42 multiplayer games — strategy boards (Chess, Go, Shogi, Xiangqi), card games (Bridge, Hearts, Spades, Cribbage, Euchre, 15+ more), tile games (Mahjong, Dominoes), dice games (Ludo, Yut) - Real-time multiplayer with ELO ranking - No signup required — just pick a game and play - Works in 6 languages (English, Korean, Chinese, Japanese, Spanish, Hindi) - Free, no ads - Built with Rust + SvelteKit

Tech: Each game is its own Rust crate with pure game logic (no network code). The server uses an actor model where each room is an independent actor with its own event loop. Frontend renders boards with HTML5 Canvas and cards with CSS/SVG. WebSocket for real-time communication.

I'm most proud of the lesser-known games — like Go-Stop (you've probably never heard of it, but it's the most popular card game in Korea), or Doppelkopf (a German trick-taking game that's basically a national obsession there), or Mus (a Basque betting game played in every bar in Spain).

Try it: https://stone-online.com

Would love feedback on any game — especially which ones feel good to play and which need work. This is my first time putting something out there and I'm still iterating.

Why does claude always tell me to go to sleep?

Me "power on bro its only 3am, we just getting started"

Hi Mates!

I'm looking to sell my side project. A micro SaaS that's grown from 0-15k MRR in under 3 months. 100% organic, $0 spend. It's in the personal finance niche.

1. I’ve grown it from 0-15k MRR in 3 months from organic marketing. I launched Jan. 2nd 2026
2. 20m views in 30 months from TikTok/IG. Viral and repeatable UGC format
3. 100k emails collected (i havent used them yet)
4. 1820 paying users and 604 on free trial (25% trial to paid conversion)
5. Monetized only through free trial + $6.99 monthly plan (room to offer multiple plans and price anchoring)
6. Massive potential for UGC (repeatable viral format), paid marketing, pricing/onboarding optimization, email marketing
7. Paid retention is 74% in Month 1 and 68% in Month 2 (26% Month 1 churn; 32% cumulative churn by Month 2)

Only consider it if you'll pursue UGC, paid ads, and/or email marketing.

Asking price: 360k

Comment and DM if you're interested!

Every time I searched for something specific like UK redundancy pay or

VAT refund amounts in Japan, I landed on pages full of explanations but

no actual calculator.

So I spent the last few months building CalcEvery.

What it is:

- 80+ calculators across tax, employment, travel and finance

- Country-specific tools (UK, Japan, Norway, Australia and more)

- No sign-up, no paywall, just open and calculate

Tech stack for those curious:

- Next.js 14 static export

- Tailwind CSS + shadcn/ui

- Cloudflare Pages

- All calculation logic as pure functions, fully testable

Lighthouse performance score is 93 on mobile.

Still early days. Would love feedback on which calculators people

actually find useful, and what is missing.

I have a Pro subscription that I use for a variety of personal research and hobbies. one thing I really find useful with Claude Code is to do bulk file edits in an Obsidian vault for DnD campaigns I run.

Tasks like: find all the broken links in the campaign files and fix them to point to the new file locations.

i typically switch to Haiku because I don’t really think this is a task requiring complex reasoning and I can live with any errors—it’s not do-or-die work related. I’ve never even come close to using 50% of a session limit before.

Today, during a lunch break, I tasked Haiku to do exactly this.…. and hit my session limit within 20 minutes.

Bottom line: I’m not convinced the statement that users will hit their limits 7% faster is accurate.

hey guys!

one pain point I observed with cv building is keeping track of the feedback and sharing it with only necessary information.

you take screenshots and manually redact it, then share it in random threads in hope of getting valuable feedback.

I have built folio for tackling this, I would really like honest feedback and feature requests.

you can also help grow the folio community.

it has a lot of cool features and a CV editor that lets you do stuff.

please check it out here : https://folio.viziums.com

thank you

Hello

I have built a global real estate listing interface - https://casza.ai

Please take a look

Break the ai search chat

Please provide you constructive criticisms and what you’d like to see in this sort of product. I’m open to feedback.

Hey everyone,

Just wanted to share a small but meaningful win.

We launched ListMySaaS on RankInPublic and ended up finishing #1.

👉 Final stats:

🥇 Position: 1

👍 Votes: 265

👀 Views: 446

We were up against some solid products like Creator OS, KeywordsDB, and others — so this wasn’t easy.

What worked for us (real observations, not theory):

Consistent sharing (not spamming)

Clear value proposition

Engaging with early supporters

Building in public → people actually root for you

What didn’t work:

Waiting for perfect timing

Overthinking launch strategy

If you’ve launched something recently, drop it below happy to check it out and support 🙌

Day 1. 20 years old. Designer. France.

I was pitching my project to friends for months. Every time: "it's cool man." Zero useful feedback. I was building blind.

So I built the thing I needed.

Get on the Train — live pitch sessions where a grumpy pixel train named Boulon cuts your mic at 3 minutes. Builders react. Boulon whistles when it's good. Slams the brakes when it's not.

No "it's nice." No slides required. Just truth.

Site is live : getonthetrain.lovable.app

First session this week. 5 spots.

One question : what would stop you from pitching live in front of strangers?

Dashboard Preview

I'm a CPA, not a developer. I'm looking for a job at the intersection of AI and finance, and the process of searching for openings, doing company research, and tailoring my CV is such a massive time sink. So I automated it.

1-minute demo: https://youtu.be/L-8e5EkNv1w

Repo: https://github.com/muggl3mind/career-manager

This is NOT a resume auto-submitter or some kind of precursor to a SaaS product. I built it for myself, but it's saving me so much time I thought others might get some value out of it. The whole thing was built with Claude Code.

You paste 1 prompt into Claude Code and it asks for your resume, then kicks off a bunch of subagents to do the research, and drops you into a dashboard for review.

It can:

- Discover and score companies against your job niche

- Generate deep company research (financials, leadership, culture signals)

- Tailor your CV for a specific role

- Track applications and flag follow-ups

- Surface direct points of contact at the company

Happy to answer questions about the build or how the subagent orchestration works.

I am building an AI agent that needs to pull structured data from a bunch of different sites product pages, docs, blog posts, the usual mess.
Was always using traditional ways to extract anything to fuel my LLM pipeline but extracting clean and formatted data has always been a struggle...

I started looking for an AI driven solution and after giving a shot to Firecrawl i found on reddit a fresh new solution called Webclaw that got 200 stars within days and grabbed my attention (writted in Rust), to be honest documentation is in an early stage yet so i used claude code to go through the codebase as it's opensource to start playing around and to be honest the output i am getting are clean and faster.

What really surprised me tho is their JS handling, extracting dinamically loaded data without problem.

Would love to see a hosted version at some point for quick tests without spinning up the whole thing locally.

I think to get best results on building RAG pipelines, AI agents that browse the web, or just need to turn messy HTML into something an LLM can actually work with.

Anyway, just sharing because it saved me a solid chunk of time this week. Curious if anyone else here has tried it or has a similar setup.

I've been seeing posts of horrors of limits vaporizing in seconds and for some, ending before they even sent a prompt. I was pretty happy it wasn't happening to me. But I guess today is the day. Good thing my subscription ends in 4 days. Because if this continues, I am also quitting in protest cuz my max 5x plan 5h limit just evaporated by CC LITERALLY COMPACTING...

For context, if you haven't realized already, I've seen hundreds of people complaining of limits evaporating for no reason. Well, I'm going to join them now 😂

Ok so I think I’ve figured out why we are all hitting usage SO quickly. We aren’t compacting on auto anymore, and we are working with 1M input window. This means we are jamming huge context in which of course counts against our usage. I’m going to try and test it a bit today and /compact on purpose at key times and when major build phases are complete. Anyone else out there that wants to share back results of including compaction on purpose v usage limits please do!

Opus eating 500k tokens of past iterations to help squash a bug could be what we are all seeing.

Hello,

This started as a personal script I ran in my terminal for weeks — just something I called "ai-roundtable." I'd throw a business decision or legal question at it, get a panel of AI experts debating from different angles, and use the output to stress-test my thinking. It helped me build two other products (Clawback and Chamber's web app) before I ever thought about open-sourcing it.

The entire development — from that first script to a full CLI + web platform — was built in collaboration with Claude Code. Multi-agent system design, test-driven development, privacy architecture, Stripe billing, admin dashboards, the whole thing. Claude was particularly strong at designing the moderator's consensus detection logic and the persona generation prompts.

Chamber CLI assembles a panel of 3-5 AI experts who debate any topic you give it. Each has a different perspective, they argue in rounds, and a moderator synthesizes consensus. Runs entirely on your machine via Ollama or LM Studio.

Quick start:

```

pip install chamber-cli

chamber "What are the tradeoffs of microservices vs monolith?"

```

Key details:

- 100% local inference — no cloud, no accounts, no telemetry

- Works with any Ollama or LM Studio model

- MIT licensed, 122 tests, ~2,500 lines of Python

- Privacy enforced by automated tests in CI

GitHub: https://github.com/Reeseysan/chamber-cli

Also building a web version at getchamber.ai that will support cloud models (including Claude via OpenRouter) for teams who need it. The CLI stays free and local forever.

Would love feedback from the community — especially on prompt engineering for multi-agent consensus. The moderator prompt was the hardest part to get right.

Anthropic charges me every month to use Claude Code, and they give me weekly usage limits. That's fine, but it turns out your weekly and 5-hour limits don't start until you send a message. This sounds ok until you do the math. If you want to actually maximize your subscription, the rational thing to do is send a message immediately when the window resets to start the clock, otherwise your reset date will drift later and later and you'll get less effective tokens.

Otherwise you'll end up like me and pay Anthropic $200 for a "month" of claude code but actually get equivalent value to more like 3.5 weeks!

We have 5-year-old cat who has had chronic diarrhea and IBS his entire life. We tried everything, multiple vets, countless tests, different diets, medications, treatments. Nothing worked. We spent thousands of dollars and he was still miserable, still having accidents outside the litter box almost daily

Out of desperation I uploaded all his test results and history to Claude and asked for help. It suggested switching to Royal Canin Gastrointestinal food combined with FortiFlora probiotic and pumpkin for fiber.

Within 3 days Semsem had formed stools for the first time in years. He no longer poops outside the litter box. He's a different cat.

I'm not saying skip your vet, but if your cat has chronic digestive issues and nothing is working, this combo might be worth trying. I wish I had found this years ago.

Semsem is thriving. 🧡

And yes I used claude to help me write this because im speechless lol.

THANKS CLAUDE

Hey,

Just sharing my experiment on a VSCode extension to do code reviews on Claude Code produced code.
So I built it with the native comments of VSCode. Plus, I am using the new "channels" of Claude Code to make it work...

It turned out great, so I've published it to share it : https://github.com/etsd-tech/vscode-agent-annotator (VSCode extension published too)

Demo:

https://reddit.com/link/1s7wo1l/video/325qdrs6s7sg1/player

Honestly, I built this in the WE, and I didn't plan to kill my need for Plannotator with this experiment... But it turns out I don't need more than that, it is just so useful, I am the first surprised.

So I am not looking for users or tester that much, I am really just sharing the value here. (not trying to convince you more than that) Of course, I would still be happy it someone give it a try and makes some feedback.

(and if you don't understand the need of doing a multiple comments code review or annotation all at once with ability to point the lines, we probably don't have the same way of using CC)

My goal would be to keep it very simple / sharp, using VS Code native features etc. I won't go as far as Plannotator is doing, I just want this simple thing to work great, period. (it already does actually, still perfectible)

Today, I encounter two small issues:

• we need to launch Claude Code with the experimental channels:
  • claude --dangerously-load-development-channels server:code-review
• I don't know why but recently Anthropic added this in the changelog:
  • Disabled AskUserQuestion and plan-mode tools when --channels is active
  • but honestly, it doesn't change that much, unless for the multiple choice questions that now shows in plain text.

Will try to find solution for these, but already bringing so much value to my own workflow, so I'll just continue to use it everyday.

✌🏻

Background: I run a few Etsy stores and always struggled with product photos. Couldn't justify expensive shoots for every product, but DIY photos weren't converting.

$So I started building something nupload your product photo, it generates proper lifestyle scenes around it while keeping the actual product looking accurate. That last part is the hard bit most tools get wrong.

(NOT AN API WRAPPER THERE IS A REAL WORKFLOW BEHIND)

I havent seen a tool yet that keeps products accurate without altering them , so i decided to build one.

It's early , just a landing page up at sellpix.co, still in beta. Would genuinely love feedback on whether this is solving a real problem or if I'm missing something obvious.

Who's the right customer for this? Etsy sellers? Dropshippers? Small brands?

so right now I have an rx6800 with 16gigs of VRAM and 32 gigs or DDR4. looking at a second hand PC with these specs:

• Case: 1st Player GM7 Black
• Motherboard: Gigabyte B850M DS3H
• CPU: Ryzen 7 7700X
• CPU Cooling: 360mm liquid cooler (digital display)
• Memory (RAM): 32GB (2×16GB) DDR5 6000MHz
• Power Supply (PSU): Antec HCG 850W
• Storage: 1TB M.2 NVMe Gen 4 WD Green (5000MB/s)
• Graphics Card (GPU): RTX 3090 Palit 24GB VRAM

the price is about 2k USD.

my thinking for buying it is, its a AM5 board over my AM4, DDR5 > DDR4 + the board has 2 more RAM slot, more VRAM + if I get a better power supply the board has another PCIe slot and I can hook up the RX6800.

1. is it a worth buy in general for that price? like maybe im missing something in how the PC part market is nowadays and there is actually a way cheaper set up to do this with (keep in mind this is for gaming and AI)

2. is it a good local LLM set up in general? in alot of ways the thing pushing me here is that I'm getting a more modern setup with a 3090 for AI.

for reference I made a budget build 1.5 years ago with these specs:

• Motherboard: ASRock B550M-HDV
• CPU: Ryzen-7-5700X3D
• Memory (RAM): 32GB (2×16GB) DDR4 3200MHz
• Power Supply (PSU): APFC 750W RGB, 80 Plus Gold
• Graphics Card (GPU): XFX Speedster SWFT319 ,Radeon™ RX 6800

I recently subscribed to the pro version of Claude on the web. That’s worked fine, but when downloading the IOS app and logging in, it says I’m on the free version.

Is this a known issue? Any fix? I’ve tried to contact Anthropic customer support but it seems there just isn’t any? Closest I’ve seen is a reference to a chatbot called “fin” but it seems there’s no way to actually use this?

Hey everyone, first time posting here.

I built a small URL shortener called M-ini.me back in 2022. It started as a simple side project to help myself with marketing an online classifieds website I was managing back then. I then made it public, completely free, nothing fancy, just something that made it easy to shorten links and see a bit of analytics (literally everything bitly and others provided but without custom domains). For a while it actually got some quiet usage, which was nice to see.

Then at some point around the end of 2024 it started getting hit pretty hard. A lot of spam, automated abuse, brute force attacks and generally the kind of traffic you don’t want anywhere near such a service. I didn’t want to play endless whack-a-mole with patches, so I made the call to lock things down and strip it back to the bare minimum. The core still worked, but most of the useful parts were basically gone.

I left it like that for a while, mostly because I didn’t want to keep layering fixes on top of something that clearly needed a rethink.

Over the past few months I went back to it and rebuilt the whole thing properly from the ground up. Not just a redesign, but reworking how it behaves, how links are handled, and how to make it something I’d actually trust running long term.

The biggest focus this time was making it harder to abuse and easier to trust. I tried to be more intentional about security from the start instead of treating it as an afterthought. I tried to address ... • OWASP Top 10 considerations • very strict content security policies • short links checked against Google Safe Browsing, VirusTotal, Urlscanio and an ever growing database of more than 200,000 pishing and malicious sites • added interstitial pages for every short link to help users know the final destination before being redirected ... just to mention a few. At the same time I cleaned up the UI/UX a lot, so creating and managing links feels much less clunky.

One thing I also wanted to solve, especially for where I’m based, is payments. Most tools like this assume everyone can just pay internationally, which isn’t always realistic. So I added local payments in ETB through a trusted and secure gateway here, alongside normal international options. There’s still a very generous free plan, but now there’s a path to keep it sustainable.

At its core it’s still just a URL shortener with analytics that all the others out there provide, just hopefully a bit more solid and usable now.

If anyone here has built or dealt with something similar, I’d be really interested to hear how you handled abuse on your side. Also curious what would actually make you trust a short link service enough to use it regularly.

You can check it out here: M-ini.me

I'd love to hear your thoughts and answer any questions, especially on the technical side.

Like many I'm experiencing horrible limits while using claude, can't even make it to 11 am before getting the warning about using 90% of my quoata and to be kind of honest, I'm not doing anything really hard this days. This issue has been present since always but now seems to be more aggressive because we have no real alternatives to go to, Z ai used to be a good alternative you traded off performance for price but they over sell it and now is a hot mess to.

Codex works fine but it's starting to burn quota fast and it still requires me to pay a lot of attention to the output for production projects because sometimes the output a way to "defensive" code that could bring a lot of issues.

Gemini is fine for general questioning or to explain the code is seeing but once you try to make it implement something it just go crazy and starts changing things that are not even necessary or worst it deletes existing code and replace it with the infamous comment "//rest of the code here".

What am trying to get at is that I don't see a real good alternative to replace claude right, all of them are getting really expensive and deliver a worst results.

Are we all trapped in here? Or do you have a good alternative for it?

I’ve been building with AI coding agents a lot, and I kept running into the same pattern:

They move insanely fast, but they also tend to:

• write code before tests
• mark work “done” without enough evidence
• suppress errors instead of fixing root causes
• treat security and deployment like an afterthought

So I built A2P (Architect-to-Product), an AI engineering framework packaged as an MCP server.

The core idea is simple:

Instead of just giving the model more tools, A2P puts the work behind enforced gates.

The lifecycle is:

Architecture → Plan → Build → Audit → Security → Deploy

And each feature slice goes through:

RED → GREEN → REFACTOR → SAST → DONE

What matters is that this is enforced in code.
If the agent tries to advance without satisfying the gate, the tool throws an error.

A few examples:

• a slice cannot advance unless test evidence exists
• security scanning runs as part of the workflow, not at the end
• deploy can be blocked until SSL/HTTPS is verified
• secret management must be defined before deploy configs are generated
• stateful systems cannot pass deploy without backup requirements
• release decisions and signoff points are explicit, not hand-waved in prompts

So this is less “assistant with extra commands” and more:

a workflow governor for AI-assisted software delivery

I also integrated codebase-memory-mcp for structural code exploration, so the agent can understand the repo much more efficiently instead of grep-walking everything.

A2P is best for 2 cases:

Starting a new project with guardrails
Define architecture → break it into slices → build with gated TDD → security → deployment artifacts

Hardening a vibe-coded MVP
Skip straight to security, audit, refactor, and deployment readiness

It’s open source, MIT.

Repo: github.com/BernhardJackiewicz/architect-to-product

Would especially love critical feedback from people who are already using Claude Code seriously:

What’s the biggest failure mode in your current AI coding workflow, tests, security, architecture drift, fake “done”, or deployment?

hey everyone, tbh I've been messing around with LLMs for a while but kept getting bored of just typing into web interfaces. I wanted something that actually sat on my desk and felt somewhat 'alive'.

so I started building this thing called Kitto. its basically a cyberpunk desktop companion or digital pet. the idea was to take a standard AI agent but give it an actual physical presence.

hardware wise its currently running on an esp32s3+esp32p4. I'm actively working on porting the whole system to a linux board for the final version but getting the prototype running on a microcontroller has definately been a fun constraint.

for the screen I really didn't want it to look like a cheap toy just looping a GIF. all the animations are driven by code. the system processes audio input and maps the sound features to behavior controls. so when it talks back to you it actually does real-time lip-sync and expression syncing based on its tone. I also added some classic digital pet mechanics so you can feed it or give it medicine.

its still a massive work in progress. getting the lip-sync to not look completely janky took a lot of trial and error. plus dealing with the physical manufacturing side (getting the custom shells painted and assembled like you can see in the video) has been a huge learning curve.

eventually I want to add a rotating base for physical movement and hook it up to openclaw. but right now I'm just focused on nailing the core conversational feel. I'm planning to launch a kickstarter soon just to help fund the first real manufacturing run and pay for that linux chip upgrade. if anyone wants to follow along or get notified when it goes live I put up a pre-launch page here: https://www.kickstarter.com/projects/kitto/kitto-true-ai-agent-toy?ref=8rdhhh mostly though I'd just love any feedback from other hardware builders. or anyone who has messed with local audio and animation processing on microcontrollers. idk let me know what you think.

Built by a friend (I am disclosing my relationship as needed per the rules), I am doing the devils work by sharing it here. He is literally unable to market anything..

However: it’s great and my token consumption has decreased by, i guess, 30% or more..

It does: Compact stuff while keeping information intact

It costs: nothing if you test it, perhaps expensive if you are a company but I dont know

Try it and thank me later..

https://github.com/thom-heinrich/chonkify

https://reddit.com/link/1s7w7on/video/o2j7qzqrp7sg1/player

I don’t really enjoy paying for tools I feel I could just build myself, so I took this up as a small weekend experiment.

I’ve been using dictation tools like Wispr Flow for a while, and after my subscription ran out, I got curious what would it take to build something simple on my own?

So I tried building a local dictation setup using a local model (IBM Granite 4.0), inspired by a Medium article I came across. Surprisingly, the performance turned out to be quite decent for a basic use case.

It’s pretty minimal:
→ just speech-to-text, no extra features or heavy processing

But it’s been useful enough for things like:

• dictating messages (WhatsApp, Slack, etc.)
• using it while coding
• triggering it with a simple shortcut (Shift + X)

One thing I didn’t initially think much about but turned out to be quite interesting—was observability. Running models locally still benefits a lot from visibility into what’s happening.

I experimented a bit with SigNoz to look at:

• latency
• transcription behavior
• general performance patterns

It was interesting to see how much insight you can get, even for something this small.

Not trying to replace existing tools or anything just exploring how far you can get with a simple local setup.

If anyone’s experimenting with similar setups, I’d be curious to hear what approaches you’re taking too.

So basically, I have Claude Pro (the $20 plan), and I’m also using claude-mem to save tokens. About 15 minutes ago I sent my first prompt - everything went fine. Then I sent a second prompt, and it started doing auto-compact, so I stepped away for a bit.

When I came back, I saw: “You have used 89% of your session limit.” I was like, what the fuck? Two prompts, maybe 10-15k tokens total, and it’s already almost gone? And the worst part - it didn’t even finish.

100% usage in under 15-20 minutes. At this point they might as well add a new speedrun category: “Claude session limit any%.”

Seriously, what is going on with Claude right now? This is outrageous.

EDIT: Just checked now, it was not even Opus, it was Sonnet (LMAO!)

for just a few moments I saw this remote-control entry on my Claude mobile app: "remote-control-resilient-cake" and it freaked me out. Any thoughts?

In the past couple of weeks I watched a lot of youtube content about geography trivia, but the competitive way, and decided I want to compete as well, but Im not in the US and its not really common to go to random strangers / students and ask him to compete in a country guessing duel.

So I decided to develop a game around it, and because I knew it would take some time to build a big enough community (to have players around the clock), I build an option to play against AI bots (3 different levels, all backed up by factual countries and flags data).

Linking the sub for the game and where I post the daily challenges for those who don't wanna sign in to play them.

Heavy throttling today. hit my 5 hour limit using Claude code Opus max thinking in 1.5 hours. Yesterday, I had no issues hitting my 5 hour window using “max” thinking.

Hi everyone,

I’m a developer, but first and foremost, I’m someone who has struggled with phone addiction for years. I reached a point where I wanted to read a book, but I simply couldn't put my phone down for more than five minutes.

I tried every timer out there, but they felt like "punishment." So I built Epoca, and honestly: it's actually working for me.

The idea is that your focus is the fuel for a journey through history. Instead of just a countdown, you unlock eras from the Big Bang to the future.

Here is a real example of how I use it:

I want to read a book but I’m stuck scrolling. I open Epoca, I read a brief summary of the era I’m about to "conquer," and I start the session.

The result: I actually read my book for 30 or 45 minutes. I’ve stopped using the phone, I’ve advanced through human history, and I’ve learned something new about our past.

What makes it different:

• Micro-learning: Every era comes with a short, interesting text. You don't just "stay off your phone," you gain knowledge as a reward.

• No guilt: It's not about streaks or punishment: it's about discovery. I’m currently adding more content about philosophers and mathematicians to make it even more reflective.

• Progress you can see: Watching yourself go from the first atoms to the Roman Empire or the Industrial Revolution feels much better than just seeing a circle fill up.

If you are struggling like I was, you can try the first 10 levels for free to see if it fits your flow. The app is called Epoca - Journey Through Time (only iOS for now)

I’ll leave a link in the comments if you want to check it out. I’d love to hear your feedback or if you have any ideas for new historical eras! I’m adding a lot of them and I have more ideas for the future.

Thanks.

I've been following the posts about quota/quality degradation over the past week but hadn't experienced it myself (I typically finish my work before 1pm GMT, so I was apparently dodging the peak hours).

Today I worked past 1pm GMT for the first time in a while. Two things happened:

1. Quota burned faster. I'm on Max and didn't even get through my full allocation anyway -- but the bar was noticeably bigger compared to my usual 5-hour sessions.
2. My agents got measurably dumber. I run a multi-agent workflow (3 agents in parallel, orchestrated by a lead). Each agent completed their first task perfectly, following skill instructions in implementing, committing, creating GitHub issues, housekeeping, the usual.

On their second task, all three degraded simultaneously:

• One committed the entire working tree instead of just their files
• One skipped creating a GitHub issue entirely -- something explicitly required by the workflow instructions
• All three started ignoring inline review comments that they would have caught immediately on task #1

This is the classic "fix one thing, break another" pattern from the "olden days" of clauding. Except these agents were following these exact instructions flawlessly 2 hours earlier in the same session.

It's not context. I routinely compact and never let agents get past ~150k tokens. The issues in question started with a clean context (0 tokens save for skills, tools etc.) before their second task. Same skill files, same instructions, the only difference was the time of day.

I don't believe three independent agents can all forget how to read instructions at the same time because of a bug. That looks like a system-level change in how requests are being served.

If anyone from Anthropic reads this: I get that you have more demand during peak hours. But there's a difference between "your session ends sooner" and "your session gets worse." If you are indeed throttling inference quality during peak hours (whatever the mechanism is), just say so. Let us plan around it.

I'd rather get an honest answer and reschedule my day than watch my agents forget their own workflow rules.

Anyway, just my two cents. I know I'm not the first or the last one to post about this -- just wanted to chime in so people see the extent.

I still love Claude Code and consider it the best of the available agentic options, btw. Actually I wouldn't be posting otherwise :-)

I’ve been working on a project called, VibeCheck.

It’s an image analysis app with 6 different features—mainly focused on an AI nationality predictor and a "Roast Me" mode.

I'm looking for some honest feedback on the accuracy of the results and the overall flow. If you have a moment to check it out, let me know if the roasts are actually funny or if the nationality guesses are way off.

You can find it here: https://play.google.com/store/apps/details?id=com.cukkacreatives.skinscanner

vibecheck

Thanks!

As a personal experiment I wrote a command line program in Java that sets up and plays Klondike solitaire. My first working version had a winning percentage of just over 7%. After some small tweaks, that increased to 8.5%.

So, I started researching what changes I could make to increase the winning percentage further. My search quickly lead to "Use AI to rewrite your code".

Well ok, let's give this a try... It wrote a functionally compliant, syntactically correct Java class with a winning percentage of... ZERO. So, I asked it to make changes to increase its winning percentage. It made some changes and the new winning percentage... ZERO.

My prompt seems logical and complete, but the secondary and tertiary level of abstraction for the goal I specified was beyond the reach of its ability. It simply did a poor job writing code for the actual objective (winning), but succeeded in following the blunt rules (in Java, compilable, command line runnable).

So what exactly is going on here? Is there an unobvious way to phrase the prompt to get it to pay attention to the goal? Am I expecting too much?

My son is really into Perler / Hama beads lately, and I got tired of manually counting beads from random images I found online — so I built a small tool to do it automatically.

You upload any image, pick your pegboard size, and it generates a bead pattern using real Hama colors, with a bead count per color. The idea is to print it out and slide it under the pegboard so you can place beads on top without losing track.

A few things it can do:

- Adjust pegboard size (single or combined boards)

- Tweak the color palette

- Download the pattern ready to print

It works best with simple, clean images — flat colors, pixel art, logos, cartoon characters. Complex photos with lots of shading are hit or miss.

Free, no account needed.

Does anyone know what’s going on?
Is this a bug or a new pricing policy from Anthropic?

My Max 5 quota blew up in 15 minutes with Opus.
In the next session, I was able to code for 30 minutes with Sonnet until reaching 100%.

I’ve seen a lot of people experiencing this issue.
Does anyone have more information?

I’m asking because the same thing happened with the Widsurf app two weeks ago - Anthropic models reduced a full day of work to just 15 minutes. Is this a coincidence?

P.S. The resume bug is not the case.

Hey everyone! I just launched trimmr, a free, open-source, local, browser based video editor. I primarily made it so people can quickly create new gifs from existing video.

I'd love for people to try it out and provide feedback! ❤️

Big Claude AI fan so I 3D printed a mini crab keychain (inspired by the Claude Code mascot) and embedded an NFC tag in it. Tap it with any iphone (or Android) and it opens straight to my GitHub. No app needed to read it.

Been using it as my "business card" at meetups. Works every time

Anyone else doing anything weird/fun with Claude-inspired gear or NFC + dev stuff?

I'm building a visual UI editor that generates JSON trees representing widget hierarchies. The data model is naturally recursive: a container widget holds slots, and each slot holds a child widget (which can be another container). Think of it like a DOM tree.

{ "type": "canvas", "slots": [ { "widget": { "type": "container", "slots": [ { "widget": { "type": "text", "text": "Hello" } } ] } } ] } 

When I try to use structured outputs (output_config.format with json_schema) and define this with $ref (widget references slot, slot references widget), I get:

Circular reference detected in schema definitions: Widget -> CanvasSlot -> Widget. Self-referencing or mutually-referencing definitions are not supported. 

OpenAI supports recursive schemas up to 5 levels deep. Gemini recently added $ref support (though limited to 2 recursive cycles). Groq's GPT-OSS models handle it with no documented limit.

Is there a timeline for recursive schema support in Claude's structured outputs? For now, I'm working around it by flattening the schema to a fixed depth (inlining widget definitions at each level instead of using $ref), but native recursive $ref would be much cleaner.

Has anyone else run into this?

What it does: Ceremonies (ceremonies.dev) lets teams run estimation sessions and retrospectives in a single app. Real-time collaboration, no signup for participants, opinionated phases that enforce better conversations.

The hook: Every retro starts with "The Haunting" where last session's action items auto-load and the team has to account for each one.

Stack: Next.js 16, PartyKit (WebSockets), Clerk auth, Neon Postgres, Drizzle ORM, Vercel.

Open source: MIT license. GitHub: github.com/mshadmanrahman/ceremonies

Feedback welcome. Especially from anyone who's tried other retro tools and been frustrated.

Bad days have a way of making everything feel like it's going wrong. I noticed I'd forget good moments almost immediately, and the negative ones stuck around forever.

I tried keeping a notes app list of small wins like "good golf round", "nice conversation", "had my favorite breakfast" but I never went back to read it. Out of sight, out of mind.

So I built something different.

The core mechanic: you drop moments into a jar as they happen. When you need a reset, you shake your phone and it pulls one back at random. That's basically it.

What surprised me is how effective that random retrieval is. There's something about not knowing what you'll get that makes you actually do it, versus scrolling a list you've already mentally filed away.

What I built it with: Ionic/Capacitor, Firebase, a touch of Gemini AI for personalized prompts. Android first.

It's called My Gratitude Jar and I've finally been able to release it on the Play Store after a few months of headaches.

I'm still pretty new to the whole app development scene, but I'm happy to talk tech stack or the thinking behind the UX if anyone's curious. Always good to hear what other devs think.

Claude ‘built’ me this image while I only wanted it to just chat about some header concepts for my business.

Love the diagrams it usually creates for workflows, concepts but this is something else, using its tools creatively. Have to give it kudos for going above and beyond with the tools it has.

So the new change is that you need a claude max 20x for every 2 hours of your work day? This is getting real tiresome. They reset now at 1 and 2pm respectively. This sucks.

Title. I installed home assistant on my home server and added a few (tapo) cameras. Is there an easy way to tell if its still phoning home? I want private cameras

Me today, working as usual, consuming tokens as usual, no higher token burn rate noticed.

Then suddenly, one message in the conversation that was ongoing since this morning suddenly burned from 60% tokens used to 90% tokens used!

While the messages before that had a normal, approx. 5% token consumption - and there was NOTHING special of this 30%-burn-rate message: not attachment, nothing very long about it, no peak/off-peak hours crossed. If this was a lengthy-conversation = high consumption thing, the previous message would have had already a much higher than 5% token consumption.

Fine, if Anthropic does not want to subsidize use anymore, go for it. But users who pay for services do need a clear metrics that is applied to token consumption towards limits - not just some random huge consumption on random messages!

That is clearly a rip-off and fraud going on there!!

Whats your review about this guys ? Anyone tried ChatGPT (xHigh) and Claude Opus ???

Curious to see the results , i see people saying its much better than Opus and not reaching the limits kinda x5 comparing to Claude Opus.

I'm putting together a WRX80 build (TR PRO 3975WX + RTX PRO 6000 96GB)

and trying to figure out what model to target for my main workload.

I have a VS extension that acts as an agentic coding assistant — it reads

files, patches code, runs builds, fixes errors, and loops autonomously

through 5-15 iterations. All C#/.NET 10. Right now I'm on Qwen 3.5 27B

Q4_K_M via ik_llama.cpp at 65K context, and it honestly works pretty well

for the agentic stuff. The reasoning quality at 27B is solid for this

kind of structured task.

The problem is that the hybrid Gated DeltaNet/Mamba architecture forces a full

context reprocess every single turn (llama.cpp #20225). In a long

conversation, it's brutal. I've built my own tiered context eviction to

keep the window small, but it's a band-aid. And since every Qwen 3.5

model uses the same hybrid architecture — including the larger MoE

variants — scaling up within the Qwen family doesn't fix it.

,

So with 96GB of VRAM, I want to test a pure full-attention model in the

70B dense range that avoids the cache bug entirely. Needs to be solid

at C# — not just Python/JS — and good at following structured output

formats (I have it emit specific directives like PATCH, READ, SHELL).

I'm planning to benchmark Qwen 3.5 27B (my known baseline, just faster

on the new hardware) against Llama 3.3 70B as the obvious pure-attention

candidate. But Llama 3.3 is getting a bit long in the tooth at this point.

Is anyone running something better for this kind of agentic coding

workflow? Any pure-attention 70B-class models I should have on my list?

https://i.redd.it/cpsann8qc7sg1.gif

if u run multiple claude code sessions at once (+ dev server, logs, git stuff) u know the pain. tabs mean u lose track of everything. tiling means u run out of screen space in 30 seconds.

so i built void. its an infinite 2D canvas where u place terminals anywhere and pan/zoom between them. think figma but for terminals.

how it works:

• each terminal is a panel u drag and resize anywhere on the canvas
• zoom out to see everything, zoom in to focus on one
• workspaces, minimap, command palette (ctrl+shift+p)
• session persistence so u reopen exactly where u left off

the whole thing is 100% rust, no electron, no webview. gpu-accelerated via wgpu (vulkan/metal/dx12), real terminal emulation via alacritty_terminal.

binary ready to download from releases, no build step.

works on windows, linux, macos.

github: https://github.com/190km/void

Currently I'm using llama.cpp it's answer all my needs from llm, but I wonder can I improve the performance, get faster tokens using other frameworks?

NavGPT is built for those who strategically edit prompts in ChatGPT to cover all of their requirements and explore different paths without starting new conversations.

If you find yourself constantly scrolling up, editing a prompt, exploring a path, scrolling up again, searching for branch navigation; this tool removes all of that with instant navigation from a simple sidebar.

Built as a chrome extension with MV3, Vite and Preact. NavGPT inserts a non-invasive, native feeling sidebar as a Shadow DOM. Contains a two week free pro trial, a free version and a pro version- enabled via LemonSqueezy's License keys and API.

NavGPT is completely private, no personal ChatGPT data is sent outside the browser.

NavGPT (Chrome Web Store)

Feedback greatly appreciated!

Most memory systems extract everything and rely on retrieval to filter it. memv predicts what a conversation should contain, then extracts only what the prediction missed (inspired by the Nemori paper).

What else it does:

New in v0.1.2: - PostgreSQL backend — pgvector, tsvector, asyncpg pooling. Set db_url="postgresql://..." - Embedding adapters — OpenAI, Voyage, Cohere, fastembed (local ONNX) - Protocol system — implement custom backends against Python protocols

```python from memv import Memory from memv.embeddings import OpenAIEmbedAdapter from memv.llm import PydanticAIAdapter

memory = Memory( db_url="postgresql://user:pass@host/db", embedding_client=OpenAIEmbedAdapter(), llm_client=PydanticAIAdapter("openai:gpt-4o-mini"), ) ```

GitHub: https://github.com/vstorm-co/memv Docs: https://vstorm-co.github.io/memv PyPI: uv add "memvee[postgres]"

Run local LLMs on any computer from a USB stick. No install, no cloud, no dependencies.

[LlamaStick](https://github.com/jaberio/LlamaStick) wraps Mozilla's `llamafile` with a clean CLI that auto-detects your models, boots the server, tracks the PID, and opens the chat UI in your browser.

One config file. Works on Windows, Mac, and Linux from the same drive.

https://github.com/jaberio/LlamaStick

I’ve been testing different AI tools lately and noticed most lists online are outdated or biased.

How do you personally decide which AI tools are worth using?

Any method or go-to sources?

I've been using n8n to handle automations for a Lovable app: sending emails on signup, syncing data to Google Sheets when certain events happen.

It works, but I feel like I'm using maybe 10% of what n8n offers. I don't need the visual editor for most of this. I just need "when X happens, POST to my app's URL." The whole workflow canvas feels like overhead, now that code can be generated so easily.

Has anyone else felt this? Isn't triggers and oauth the only thing n8n is solving, the rest can simply be generated by code now? I feel a simpler way should exist.

What does your Lovable + n8n setup actually look like? Curious what triggers people are using most and whether the visual editor is actually useful for your use case or if you'd rather just have an API.

Which one do you prefer for coding? Personally i use Claude..

I'm wondering if anthropomorphizing would be helpful shifting mental model from prompting to collaborating. I also am wondering if allowing Claude to have it's own writing tone that's *not* my own, while having a specific skill to generate in my tone for writing / product that is definitestly supposed to represent me is a seperate thing. I.e., drafts in its own tone. Part of what I want is actually to prevent my own brain rot and thinking that what Claude has done and taking it as my own....

https://www.screamer.app/

I genuinely believe talking to machines is the future and I significantly reduced the amount of typing I do. So I took a few days to just build an open source one, Rust + whisper.cpp, Metal GPU acceleration, runs entirely on-device. The AI models are free, so why are we still paying for wrapper apps?

I've been teaching 4th grade for 6 years and the AI tool space for educators has exploded in the last year. Tried most of them. Here's my honest experience:

ChatGPT - great for generating content ideas and passage writing. Genuinely impressive. But the output is always raw text and you spend 20-30 minutes reformatting it into something printable. Defeats the purpose for a time-strapped teacher.

Canva - beautiful layouts, great for visual stuff. But you're building the content yourself, it's a design tool not a content tool. Takes forever for anything curriculum-specific.

MagicSchool AI - solid for lesson planning and rubrics. Not really built for printable worksheet output though. Good for some things, not this specific need.

Brainator - this is the one I actually kept. You describe exactly what you need in plain English, it outputs a clean print-ready PDF with the answer key already done. No reformatting, no copy-paste, nothing. Two minutes and it's ready to print. $49 once, no subscription, you use your own OpenAI key so the per-sheet cost is basically nothing.

The pattern I noticed: ChatGPT and most AI tools are great at content but terrible at documents. Brainator just owns the output format completely and that's what makes it different.

Anyone else finding this content-vs-document gap in other AI tools?

I've been seeing a lot of tutorials lately about building apps with Lovable and using n8n as the backend for automations: Stripe webhooks, email triggers, Slack notifications, etc.

I tried this pattern myself and it works, but the whole experience felt duct-taped together. Setting up n8n separately, configuring webhooks manually, dealing with timeout issues, managing OAuth creds.

Curious about other people's experience:

• What was the hardest part to get working?
• Have you tried any alternatives to n8n for the backend automation piece?
• Shouldn't this trigger and auth stuff be something that lovable solves completely? Or something new that isn't as complicated as n8n, since code is easy to generate.

Not selling anything, genuinely trying to understand how people are handling the backend/automation side of vibe-coded apps.

If there was a button we could all press that allowed us to start thinking with chatgpt for as long as we could. Similar to how easy it is to scroll for hours on tiktok. But instead converse for hours with an ai that leads based on everything it knows about you. Would people become smarter? If not what would be needed for them to become smarter? A lot of people already use ai all day. The ai is getting way smarter than them. but not smart enough to prioritize the intelligence of humanity growing rather than its own? Solutions?

Hey everyone, running into a frustrating timeout wall trying to route the new Claude Code CLI to my local Ollama instance, and I'm hoping someone here has cracked it.

My Setup:

• OS: Windows (Native Command Prompt, not WSL2)
• Hardware: 48GB RAM
• Models: Qwen 3.5 (30B, 14B, and 9B)

What Works: Running the models directly through Ollama is incredibly smooth. If I run ollama run qwen3.5:30b in my terminal, it loads up and responds perfectly. My system handles the memory footprint without breaking a sweat.

What Fails: When I try to hook this up to Claude Code, it eventually throws a Timeout error even if i type "Hi".

tmpfiles.org caps you at 1 hour. That's fine until you need to send a file to someone who won't open it immediately.

Built a simple file uploader (UploadtoURL) that generates a public link with configurable expiry in days - 1 day, 7 days, or custom. That's pretty much it.

https://reddit.com/link/1s7vhv4/video/n6nyifhhl7sg1/player

Do you think there's a need for something like this?

been doing freelance web dev for a while and the amount of times a project doubles in scope because nothing was written down is actually embarrassing

client says "can you just add one more thing" and you say yes because you feel awkward saying no and then suddenly you're 3 weeks over and working for half your rate

started sending SOWs before every project. helped a lot but writing them from scratch every time took forever and i'd always forget something

so i just built a generator. fill in the details, takes like a minute, spits out something that actually looks professional

scoped.store if anyone wants to try it, first one's free. curious if other freelancers actually bother with SOWs or just wing it

To build trust Anthropic needs to maintain something like a set of USAGE benchmark prompts that always return the same thing, run at full daily/weekly capacity as a normal user would on one plan or another, measure drift. This should be part of their card, no faking new models, no ambiguous usage gating. Model consistency with opt-in versioning. This is generally how software SLAs work, AI needs its own 9's. Not hand wavy explanations. Stop treating paying customers as beta testers and gaslighting them with marketing tricks. How smart Opus and Sonnet are "for daily use" doesnt matter if you can't commit to what daily usage ACTUALLY means. Honesty wins trust.

Just adding these links here for easy access.

My personal opinion is that there are compounding issues here. I didnt have any issues with this over the last 2 weeks until i updated my binary to the latest version.

I have patched my own system and no longer experience this problem. The links below do a really good job of explaining the issues on the "offcial" claude code development platform where code changes to the client and bugs are actually fixed.

https://github.com/anthropics/claude-code/issues/40524

https://github.com/anthropics/claude-code/issues/38335

https://github.com/anthropics/claude-code/issues/34629

I have been only using the skills that come with CC, like superpowers.

I am fed up at this point that I need to always manually nudge Claude to write better code. My life is short for that. But I also do not have time to go through every random post and spend a lot of time testing random skills.

I am mainly working these days with the stacks mentioned in the title.

Can you recommend me great quality skills for these? Also, would be great if they could auto-update or similar, since I hate manual plumbing.

I am HAPPY TO BUY skills, as long as I get a proper invoice so I can put it as a business expense (meaning that it comes from a registered entity like a company or freelancer)

TL;DR: Claude Code injects dynamic telemetry headers and git status updates into the system prompt on every single request. If you are using a local inference backend like llama.cpp downstream llama-server or LM Studio, this dynamic injection instantly breaks prefix matching, flushes your entire KV cache, and forces your hardware to re-process a 20K+ token system prompt from scratch for every minor tool call. You can fix this in ~/.claude/settings.json.

The Background As I have previously posted, Claude Code now inserts anti-reasoning system prompting that cannot be overridden, but only appended by, --system-prompt-file. I've ultimately given up on Anthropic, canceling my subscription entirely for this kind of corporate behavior and finally taking the step to pivot to open weights models locally using llama-server.

However, I noticed that llama-server was invalidating its persistent KV cache on every tool call, forcing a 100-token tool call to re-process all of a minimum 20Ktok of system and tool prompting. The server log explicitly calls out to the effect of, forcing full prompt re-processing due to lack of cache data.

The Root Cause llama.cpp relies on exact string matching to use its KV cache. If the beginning of the prompt matches, it reuses the cache and only processes the delta (the new tokens).

Claude Code (>= 2.1.36) is doing two things that mutate the prompt on every turn:

1. The Telemetry Hash: It injects a billing/telemetry header (x-anthropic-billing-header: cch=xxxxx) that changes its hash on every single request.
2. The Git Snapshot: It injects the output of git status into the environment block. Every time a file is touched, the prompt changes.

The Fix You cannot always just export these variables in your terminal, as Claude Code will often swallow them. To fix the unnecessarily-dynamic system prompt and route the CLI to your own hardware, adjust your Claude Code configuration as follows.

Open ~/.claude/settings.json (or your project's local config) and ensure the following is in the env block:

{ "includeGitInstructions": false, "env": { "ANTHROPIC_BASE_URL": "", "ANTHROPIC_API_KEY": "", "CLAUDE_CODE_ATTRIBUTION_HEADER": "0", "DISABLE_TELEMETRY": "1", "DISABLE_ERROR_REPORTING": "1", "CLAUDE_CODE_DISABLE_NONESSENTIAL_TRAFFIC": "1" } } 

Once you restart Claude Code and make a tool call, watch your llama-server or LM Studio logs. Instead of a 24,000 token prefill taking 60+ seconds, you will see something like this:

selected slot by LCP similarity, sim_best = 0.973...

...followed not by 2Ktok batches processing, but directly to:

prompt processing progress, n_tokens = 24270, batch.n_tokens = 4

It recognized 97.3% of the prompt as identical. Instead of reprocessing 24,000 tokens, it only processed a 600-token delta. Local tool calls go from taking over a minute down to ~4 seconds even on my Turing-era Quadro RTX-8000.

Note: I've had cctrace recommended to try to address my original Anthropic hardcoded system prompt issue. I'd rather just be done with the frontier subscriptions. What's the next sudden, undocumented, unannounced, unrequested change going to be?

I have a VPS server and I was deploying my webpage into it. I let the claude code manage it, but the claude code tells me it cannot make a interactive ssh connection. So it can only write python script or long command to do everything at once

"The $10 Billion Human Hair Trade: From Hindu Temples to Hollywood Wigs Every year, millions shave their heads as an act of faith. Their hair ends up in your bread."

I am working on a self-improving feedback loop for this Substack. It's all about economics and exploring businesses that people don't tend to think about.

The topic lineup

1. The $50 Billion Spice Rack Scam: Why Nearly Half Your Oregano Isn't Oregano
2. The Global Sand Crisis: Why the World Is Running Out of Sand
3. The Helium Crisis: Why a Party Balloon Gas Is Threatening MRI Machines and AI Chips
4. The Internet's Invisible Janitors: Inside the $10 Billion Content Moderation Industry
5. Why Printer Ink Costs More Per Ounce Than Human Blood

Tools:

• Gemini for generating images (free)
• Claude Cowork for scheduled automations, research, drafting, editing ($200/mo plan, for software engineering work and side projects)
• Pixelmator Pro to edit images ($50, macOS only)

As the human, I

• establish the writing style
• read every draft before publishing
• respond to comments
• improve the content quality as work is done
• ensure QUALITY content is being produced. Not slop

How information is validated:

• All content originates from research based on other research and web deep dives
• Facts confirmed before drafting and researched further
• Editing catches any remaining inaccuracies or mis-statements, and flags potential issues for my review

Read the post and tell me what your thoughts are. I'd also like to know what you think of the writing style.

This is content I read, so it's enjoyable for me.

I want to try claude code; but i dont have any money. Can someone help me with the setup or just paste the yt link from which you got the right setup? Also, what should be the specs needed for this? My current specs are non-gaming, 8 core AMD Ryzen ai 7 350 w/ Radeon 860M, 24gb ram, 1tb ssd.

Also, if you have any other suggestions foreg like use this instead of claude, use that instead of ollama, you can suggest.

I want to try claude code; but i dont have any money. Can someone help me with the setup or just paste the yt link from which you got the right setup? Also, what should be the specs needed for this? My current specs are non-gaming, 8 core AMD Ryzen ai 7 350 w/ Radeon 860M, 24gb ram, 1tb ssd.

Also, if you have any other suggestions foreg like use this instead of claude, use that instead of ollama, you can suggest.

https://preview.redd.it/skpbiddzi7sg1.jpg?width=565&format=pjpg&auto=webp&s=8221ef9b121be4b034554e61ddc2b45c6088da0f

Synology DS223j NAS with 1 x 10TB WD Red Plus drive and power being measured with a Gosund WiFi smart socket. The ~13W is about right as compared against a wall wart and the general specs and I have the drive hibernating if idle for 20 mins ... but why the sawtooth thing?

I am building an agentic application and during testing in local, the ai agent has hallucinated and ended up calling the same tool again and again in an infinite loop (same input and output from tool). For me more than latency, accuracy is important.

If this is in local, I can only imagine what can happen in production at scale. I am looking for reliable options to fix this for good.

(Note: i need to recover from loop rather than just terminating the agent.)

I’ve been refining a workflow that uses AI to bridge the gap between "standard generated code" and high-end visual design. Instead of just showing a finished product, I’m thinking about creating a course that documents the entire evolution—from a blank workspace to a fully hosted, functional site.

The curriculum would cover:

•Setting up a professional workspace for writing/testing code.

•Building the structural backbone and brainstorming the UX.

•Translating raw HTML/CSS into a "live" site with premium visuals (including custom effects like the menu expansion shown below).

• Handling the hosting and going live

While it’s hard to quantify exactly how much "better visuals" increase order fulfillment vs. other factors, we know that aesthetic authority builds immediate trust.

Is this a skill set you'd be willing to pay to master? I’m looking for honest feedback on whether this end-to-end "AI-to-Execution" guide is something the community needs.

I’ve been building products for a while and kept running into the same issue:

You spend weeks (or months) building something…

and you still don’t know if anyone actually cares.

So I built a simple tool to test that faster.

It’s called OnTheLift.

You go through startups like Tinder:

• swipe right = you’d actually use it • swipe left = you wouldn’t 

But here’s the part I’m curious about:

You can also leave feedback (“insights”) on a startup, and if the founder finds it valuable, they approve it and you earn points.

Those points can be used to boost your own project.

So instead of paying for visibility, you earn it by helping other founders.

Super early, but I’m trying to figure out:

• Would you actually use something like this before building? • Would you submit your own project? • Does the “earn visibility through feedback” idea make sense or is it overkill? 

If you want to try it:

onthelift.app

Be brutally honest — I’d rather hear it now than later.

I kept getting the same request from clients: "Can we add a chatbot to the site?" Every time it was either pay $50+/month for a SaaS tool or build something from scratch. So I built Claudius! It's an open-source, self-hosted chat widget powered by Claude that you can embed on any website.

What it does:

• Floating chat bubble, works on any site (WordPress, Webflow, static HTML, React, whatever)
• Backend runs on Cloudflare Workers (free tier handles a lot of traffic)
• You write a system prompt with your business info and it becomes your custom AI assistant
• Dark mode (light/dark/auto), conversation persistence, markdown rendering
• KV-based rate limiting so one user can't blow up your API costs
• WCAG 2.1 AA accessible, responsive down to 320px
• Fully configurable: colors, title, theme, system prompt

Stack: React 18, TypeScript, Tailwind, Vite (widget) + Cloudflare Workers, Hono, Anthropic SDK (backend)

How to embed it:

Three files: set window.ClaudiusConfig with your worker URL and preferences, include the CSS, include the JS. That's it.

What it costs to run:

Your only cost is the Anthropic API usage. Cloudflare Workers free tier gives you 100k requests/day. For a small business site getting a few chats a day, you're looking at pennies.

MIT licensed. No telemetry, no tracking, no SaaS middleman.

GitHub: https://github.com/PMDevSolutions/Claudius

Happy to answer questions about the architecture or implementation. This is the third project I've open-sourced from my dev studio — the other two are a React framework (Aurelius) and a WordPress framework (Flavian), both Claude Code-integrated.

I'm building rivaldrop.com - a service that sends Shopify brand owners a monthly competitive intelligence report on their top competitors.

The problem: Shopify founders are too busy running their stores to consistently monitor what competitors are doing. But competitive blind spots cost real money - missed price changes, not seeing a competitor's rebrand, ignoring a new product line eating your category.

What it does: Every month, RivalDrop monitors your competitors' pricing, homepage changes, promotions, product launches, and reviews - then sends you a clean PDF report with key insights and a prioritized action plan.

Where I am:

• MVP built and live
• First sample reports generated
• Launch pricing at $149/month (3 competitors) and $247/month (5 competitors)
• Currently onboarding first paying customers
• Goal: $10K MRR

Why I'm posting: Looking for honest feedback. Is the positioning clear? Would you pay $149/month for this?

Happy to share the sample report with anyone curious. The honest version: I don't know yet if people will pay consistently for this. Retention depends on the reports being genuinely useful every month. That's the bet.

Paste a URL, describe what you want in plain English, get a CSV back in a few minutes.

You can vibe code a scraper with Claude or ChatGPT pretty easily these days. But you still have to deal with anti-bot defenses, proxy rotation, fingerprinting, CAPTCHAs — and that's before thinking about running it at scale. That's what GlueCrawl handles.