Hey everyone,

I’m building a CLI tool called Kakarot CI. It uses AI + AST analysis to generate executable unit tests directly from your source code.

The idea is simple: if AI is going to write tests, they should actually run, pass, and be measurable.

It’s currently in beta. I’m a solo dev, so there may absolutely be rough edges.

To test quality, I created a public demo repo (~500 lines across 4 files: logic, classes, and a React component) and generated every single test using Claude Opus 4.6 through Kakarot CI.

No edits.
No manual cleanup.
No human intervention.

Total time: ~10 minutes for those 4 files.

Coverage (Jest)

Statements: 98.96%
Branches: 97.75%
Functions: 96.29%
Lines: 100%

Coverage alone doesn’t prove strength, so I validated it with mutation testing using StrykerJS.

Mutation Testing

Overall Mutation Score: 93.48%
257 mutants killed
16 survived

StateMachine.ts — 100%
EventBus.ts — 92.39%
SearchableList.tsx — 91.45%
math.ts — 91.67%

From published studies, many human written tests land between 50–80%, even on mature projects. Breaking into the 90s is uncommon.

This is still a controlled demo repo. The next step is running it against a messy real-world codebase and seeing how it performs there.

If you want to verify:

• Run Stryker yourself on the demo repo
• Or delete the tests, add your own Anthropic API key, regenerate them with Kakarot CI, and run the full suite + mutation tests again

It’s free to use, you just bring your own LLM API key.

Demo repo: https://github.com/Lokardo-Labs/Kakarot-Demo
Site: https://www.kakarot.io/

Would appreciate feedback, especially from anyone who’s used mutation testing in production.

I am on the verge of giving up on this after so many failed attempts to do it with ChatGPT instructions. I am a complete noob and I am using realisticmixpony something model right now.

I have tried training realism based character lora using chatgpt instructions and failed badly everytime with zero result and hours and hours wasted.

Can someone please give steps, settings, inputs for each section like what to input where.

I am on 16gb 5060 ti and 64ram. Time is the issue so wanna do that locally.

Hi everyone,

I’m building an outbound AI voice agent specifically for the French market. I'm hitting a wall regarding telephony costs and latency, and I’m looking for advice from anyone who has deployed voice AI in Europe.
Most US-based AI platforms (Retell, Vapi, Bland) default to Twilio or Telnyx for telephony. While great for the US, their termination rates to French Mobile numbers (+33 6 / +33 7) are brutal compared to their local providers (like OVHcloud, Sewan, or even Skype Connect)
My Questions :
- If I were to use platforms like Retell,vapi what is the best option to connect my agent to a french number for better latency and minimal cost ??
- If I were to build the agent from scratch like using Livekit what is the best option to connect my agent to a french number for better latency and minimal cost ??

Hey everyone,

I know the sub is full of spam and generic advice, so I’m trying to share something real that actually helped me push my SaaS from stuck-at-$4k/mo to consistently scaling past $25k+.

If you’re building or growing right now, read it all the way through. These aren’t shiny new hacks, but when you actually do them and iterate, they compound hard.

1. Lead magnets that actually pull people in Forget boring “free ebook” traps. Your free tool should give real value on its own AND make them feel the gap: “this is great… but imagine if it did this automatically and at scale.” Example that still prints money for me: If you sell a social media scheduler, build a free “Post Idea Validator” – user pastes 3–5 ideas, gets instant scoring + rewrite suggestions. They taste the win, see how much faster/better the full product would be, and convert way easier. It’s story-selling, not just email-grabbing.
2. Landing pages so simple they feel almost lazy The best converting SaaS pages in 2026 are stupidly minimal.

• One strong headline (benefit, not features)
• One clear visual of the result
• One obvious CTA
• 2–4 short bullets max
• Email-only form (or name + email at worst) Every extra word, section, or field kills sign-ups. I’ve literally doubled conversions just by deleting half the page.

1. Make it so easy it’s embarrassing Every time you build or update anything, ask: “Would someone who’s never used software before get this in under a minute?” If the answer isn’t a clear yes → simplify until it hurts. Confusion is the #1 silent killer of retention and referrals. Big buttons, obvious labels, one goal per screen. Boring wins.
2. Pick ONE ideal customer and go deep Not “entrepreneurs” or “marketers.” Get specific:

• 31-year-old bootstrapped founder
• Running a 2–5 person remote service business
• Constantly stressed about inconsistent leads
• Talks direct, hates fluff, scrolls Reddit/IndieHackers late at night When your entire copy, features, onboarding, and support language is built around that one person, everything suddenly feels personal and converts better.

1. Speak exactly like your customers do Ditch the polished “game-changing solution” nonsense. If your users say “this saved me from burning out every week,” then use that phrasing. Mirror their pain, their wins, their casual tone. When they read it and think “this person gets me,” trust shoots up and sales follow.

Just a quick: this post is written by me, but polished a bit for clarity and flow – because my raw typing is usually a mess.

Most of this you’ve probably seen before. The magic is in actually implementing it, testing it, and tweaking every week instead of just bookmarking and forgetting.

If this hit home or gave you even one thing to fix in your own project, I’d really appreciate an upvote or a quick comment (even just “saving” or “#2 hurts because it’s true”). It helps me know whether putting real effort into posts like this is worth it.

Thanks for reading all the way.

Just click on "LoRA" button and select your .safetensors file.

LoRAs trained both on Z-Image Turbo and Z-Image Base are supported.

SageAttention2 acceleration is also part of the news.

Download at: https://github.com/SamuelTallet/ZPix

As always, your feedback is welcome!

Like in the end, I still have to update the chat context in the master context prompt which I also do in the normal chat. I also have to upload documents. There's no depository that shows me all the documents in one place. What's the use of Claude projects?

Hi r/ClaudeAI,

I’ve been using Claude Code heavily across my laptop + servers, and I realized GitHub measures commit activity but I want to track how well I use Claude Code.

So I built ccrank, a small tool that turns your Claude Code usage (ccusage JSON) into a simple, comparable set of metrics.

What it does today

• Upload a ccusage JSON export

See:

• Total tokens used (AI input)

• Estimated API cost (rough approximation)

• Active days (consistency)

• A basic rank/title ladder (mostly for fun)

Useful bits

• Multi-machine support: you can combine usage from multiple machines

• “Time travel” views: daily/weekly/monthly snapshots of usage trends

• Shareable profile card (so it’s not just screenshots of terminal output)

How Claude/Claude Code helped build this

• I used Claude Code to scaffold the app structure, iterate UI quickly, and refactor the data pipeline

• The biggest help was fast iteration on edge cases in usage logs (missing fields, time bucketing, merging multiple exports)

What I’m trying to learn from the community

1.  What metrics would you actually want here beyond tokens/cost/days active?

2.  If you use Claude Code daily, what’s a good proxy for “output” that isn’t easy to game?

3.  Any pitfalls you’ve hit when tracking usage across machines / accounts?

Try it (free)

• Public leaderboard + upload: ccrank.dev

• Self-host (MIT): github.com/makash/claude-leaderboard-using-ccusage

If this kind of measurement is useful, I’m considering a next step where you can optionally log “what shipped” and map that to tokens (ROI per feature). But I’m deliberately keeping v1 simple and would rather learn what’s valuable before adding more.

Happy to answer questions or share implementation details if folks are curious.

Hi,

Has anyone had any success with connecting an Arduino to an AI agent for machine learning? I’m looking to have the AI manage the irrigation of a garden.

Any resources would be great.

Built an automated Instagram posting pipeline using n8n, Flux (via Cloudflare API) and Gemini. The workflow takes ideas from an Excel sheet, generates prompts, creates 2-3 AI images and posts directly to Instagram.

https://preview.redd.it/ct2440zi5pjg1.png?width=2886&format=png&auto=webp&s=9d5fb77855d4138582c0d7c101da133c64723b17

The Stack:

• n8n (self-hosted on VPS)
• Gemini API (free tier for prompt generation)
• Flux via Cloudflare API (image generation)
• Instagram Graph API (posting)
• Excel/Google Sheets (content queue)

How It Works:

1. Add content ideas to Excel sheet
2. n8n pulls next item from queue
3. LLM generates 3-5 caption variations + image prompts
4. Flux creates 2-3 images per prompt
5. Workflow selects what to post
6. Posts to Instagram with scheduling

Extended this to X and LinkedIn with platform-specific formatting rules (limited testing on these two platforms though).

What Worked:

• Technical execution: 95%+ success rate
• Consistent posting schedule (daily at same time)
• Volume output a small team couldn't manage manually
• Platform-specific formatting handled automatically

The Unexpected Problem:

Around week 3, realized the team was still spending time refining outputs. Not because the workflow failed, but because:

• AI-generated images were technically fine but tonally off
• Captions missed brand voice nuances
• Timing felt mechanical vs strategic

The problem wasn't speed or accuracy. It was creative judgment.

Automation handles deterministic tasks brilliantly. But the last 20% (brand voice, emotional tone, "does this feel like us?") still needed human review.

Current Setup:

Changed to human-in-the-loop:

• AI drafts → Human edits for taste → Auto-publish

Quality improved dramatically. Team focuses on strategic decisions, automation handles execution.

What I'm Testing Now:

Experimenting with OpenClaw (Clawdbot) as an alternative approach. Unlike n8n's deterministic workflows, you give it context and it decides actions autonomously. Running it locally in a sandboxed environment with a local model.

Early days, but interesting to compare:

• n8n: Fixed rules, perfect reliability, limited judgment
• OpenClaw: Adaptive decisions, context-aware, still needs training

1. Anyone else hitting the "creative judgment" wall with content automation?
2. Thoughts on deterministic workflows vs agentic systems for creative tasks?
3. What's your approach to automating tasks that require taste/judgment?

Something I noticed after a few months of using Claude for most of our frontend code: it has a voice. You've heard it. "We're thrilled to announce." "Don't hesitate to reach out." "This groundbreaking, seamless experience." It sounds professional the way a hotel lobby smells professional. Manufactured and forgettable.

The thing is, this stuff passes code review. It compiles, tests pass, the PR looks reasonable. Then your customer gets an email that reads like it was written by committee.

So we started writing ESLint rules to catch it. Not code quality rules. Copy quality and design consistency rules. We have four now and they've changed how we work with Claude.

The first one, humanize-email, maintains a ban list of AI phrases. "Don't hesitate to reach out", "we're thrilled", "groundbreaking", "seamless", "delve", "leveraging", "warm regards", the whole greatest hits album. The list started from Wikipedia's "Signs of AI writing" page and grew every time we caught something in our own sent emails. It also forces our plain-text email layout for personal emails because Claude always reaches for the branded template with logos and footers. And it limits em dashes to 2 per file because Claude overuses them like someone who just discovered punctuation.

The second rule bans raw Tailwind color classes like bg-white dark:bg-gray-800 and forces semantic tokens like surface-primary. Claude doesn't know your design system. It knows Tailwind defaults. So you get six classes to express what should be one concept. With semantic tokens, dark mode works automatically, and theming is one CSS variable change instead of find-and-replace across 400 files.

Third rule auto-fixes mixed curly and straight quotes in JSX. Small thing, but Claude outputs curly quotes and your keyboard types straight quotes. Both in the same UI looks sloppy. Auto-fixable, zero effort.

Fourth rule blocks hover:-translate-y-1 on interactive elements. Claude loves this on cards. Looks good in a demo. Then a real user approaches the card from below, the card jumps away from their cursor, hover drops, card falls back, cursor re-enters, it lifts again. Jittery loop. hover:shadow-lg gives the same lift feeling without moving the hit area.

The interesting part is these rules teach Claude too. The error messages become context for the next generation, so it stops making the same mistakes after a few rounds.

All four rules are open source: https://jw.hn/eslint-copy-design-quality

after 100 hours of pure debugging prompting and a bit of coding I finally got a working landing page out, for my app Link up and we will be setting up an email waitlist soon!

So excited to launch hope you guys are to, thank you !

I got Pentium g6400 with 64 GB and 2060

Screenshot of the first graph in the tool showing an example with reference images and two lora tests. on the right there's the control panel where you can filter the loras or cycle through them. the second image shows the full set of graphs available at this moment.

I’m a software engineer and long-time roleplay fan, and I’ve been building a local-first AI roleplay desktop app for myself. I’m considering refining it into something more polished and usable.

The core idea:

• Fully local (no accounts, no cloud storage, no tracking)

• You choose which model to use

• Clean UI designed specifically for immersive roleplay

• Highly customizable characters and scenario setup

• Optional structured scene formatting for more consistent dialogue and character behavior

• Fantasy/world-building friendly

• Experimental-friendly — easily switch models and tweak behavior

Privacy note:

The app does not collect or transmit your data. Your characters, conversations, and settings stay on your machine.

Everything runs locally on your machine.

The app does not collect or store your data.

Your characters and conversations stay on your computer — no accounts, no tracking, no cloud storage.

Everything is designed so you stay in control.

The trade-off is that performance depends on your hardware (GPU/CPU and model size).

Before I invest more time polishing it:

Would you personally use something like this?

What features would make it meaningfully better than current options?

If there’s enough interest, I may open a small private testing group. Pls comment on the post since I am a Reddit newbie - haha I know, silly since I am a software engineer but alas.

I feel the panic is INSANELY overdone because AI is not creating imagination and it is only rearranging stories that humans already made. This is a half vent because people aren't thinking critically with the likes of Seed Dance 2.0 release.

Won’t you get bored seeing the same characters mixing with other similar characters and the same SHOW overall???

You might enjoy a custom Seinfeld episode with exactly what you want where Jerry decides to play fortnite or something... or watching Batman in perfect AI-4K generated battle with Voldemort the first few times, but after a while it becomes ..boring.

This is like remixing music where at first the remix sounds good, then another remix comes out, and eventually you just want a brand new song.

You know all these characters from your established memory of watching this. This isn't practical at all for people who have no idea what the hell a "Mr.White" is. A 10 year old won't be amused of some random ai algorithm crafted out of Charlie Brown or whatever else that's for kids these days. This mean there's a requirement where you must familiarize yourself with the original material before even figuring out why this Crazy bald chemist guy is dancing with Spiderman in AI.

Even if Hollywood feels lackluster right now, that has more to do with the economy and the general enshittification of everything, not because human creativity ran out.If you want real movies with heart and new ideas, they already exist in indie films and smaller studios.Hollywood is in a weak spot this decade, but replacing it with AI would not fix the problem, it would only make stories feel more empty. People are over hyping this AI video generation stuff.

Everyone seems to forget there's an entire generation of people that want something NEW. Our great great grandparents grew up watching Charlie Chaplin dancing around, and the generations after wanted something different. If AI somehow existed earlier in that era, we'd have black and white Charlie Chaplin in the Twilight zone remixes. THIS WILL BECOME BORING. There's no new imagination involved. It would not eventually make and produce a Marvel Super Heroes scenario from all the film and material it acquired. It's all regurgitated trash.

Planning trips often feels overwhelming—comparing hotels, reading countless reviews, and juggling itineraries can turn a fun experience into a chore. Here’s a simple workflow to make travel planning manageable today:

1. Define your top priorities (e.g., budget, location, amenities).
2. Compile a shortlist of options using a trusted source (e.g., hotel websites or review aggregators).
3. Create a comparison table with key factors: price, rating, distance to attractions, and amenities.
4. Assign weights to each factor based on your preferences to score and rank the options.
5. Review the top picks individually with benefit-focused notes.

Example checklist for hotel comparison: - Price per night ($150–$300) - Guest rating (4.0+) - Breakfast included (yes/no) - Free cancellation (yes/no) - Distance from city center (<2 miles)

Common pitfalls: - Overloading the table with irrelevant details—stick to what matters most. - Ignoring cancellation policies, which can add costly surprises.

If you want to simplify this process further, consider michelinkeyhotels—a tool that aggregates distinguished and boutique hotels from sources like the MICHELIN Guide, helping you filter and compare luxury stays effectively. Feel free to adapt this approach with or without specialized tools to keep your travel planning friction-free.

Hi

I built this project for myself because I wanted full control over what my personal assistant does and the ability to modify it quickly whenever I need to. I decided to share it on GitHub here's the link: https://github.com/emanueleielo/ciana-parrot

If you find it useful, leave a star or some feedback

Hi all,

I’m planning a smart-home control + monitoring system and I’d like some advice before I choose the main ecosystem.

This is a new build and I intentionally ran a lot of wired cabling so the most important sensors don’t have to rely only on wireless:

Current wiring prepared:

• UTP for motion sensors (3x)
• JYTY 4x1 for motion sensors
• UTP for smoke/heat detectors (2x)
• Position 1 – main control panel: UTP + JYTY 4x1 to IVT heat pump + JYTY 4x1 to Position 2
• Position 2 – secondary control panel / thermostat (JYTY 4x1 from Pos.1)
• Position 3 – video doorbell (UTP)
• Magnetic contacts in every opening window/door (twisted pair)
• UTP for CO₂ sensors (2x)
• 2x1 cable for BOOST control of HRV/ventilation
• UTP for floor heating manifold (2x)
• Smart motors for external blinds
• KRISPOL smart garage door motor
• UTP for outdoor cameras (4x)

The house also has a PV system built on a SolaX inverter — is it possible to integrate this into the same smart-home ecosystem?

Of course the whole house also has a WiFi mesh, but my goal is to keep critical sensors wired if possible.

What I’m trying to achieve

I want to connect all of this into one unified system that can:

• monitor and control everything centrally
• allow wall-mounted control (thinking about ~10” touch panel)
• mirror the same control in a phone app
• possibly act as a basic alarm system (arm when leaving → notify on intrusion)

Questions

1. Would you build this primarily around Zigbee + a central 10” panel that manages the network?
2. Is it possible to include the SolaX PV system into such a setup?
3. Can Zigbee-based setups realistically work as a basic security system (armed mode, notifications, etc.), or should security be separated?
4. Any recommendations for reliable AliExpress manufacturers for sensors/panels?
5. Has anyone built a similar “hybrid wired + wireless” system?
6. Or would you build this whole setup on a completely different system? I’m definitely not considering Loxone — it’s financially out of reach for me in this scale.

I’m looking for real-world experiences, especially from people who started with wired sensors.

Thanks!

Another LTX-2 experiment, this time a lip sync video from close up and full body shots (Not pleased with this ones), rendered locally on an RTX 3090 with 96GB DDR4 RAM.

3 main lipsync segments of 30 seconds each, each generated separately with audio-driven motion, plus several short transition clips.

Everything was rendered at 1080p output with 8 steps.

LoRA stacking was similar to my previous tests

Primary workflow used (Audio Sync + I2V):
https://github.com/RageCat73/RCWorkflows/blob/main/LTX-2-Audio-Sync-Image2Video-Workflows/011426-LTX2-AudioSync-i2v-Ver2.json

Image-to-Video LoRA:
https://huggingface.co/MachineDelusions/LTX-2_Image2Video_Adapter_LoRa/blob/main/LTX-2-Image2Vid-Adapter.safetensors

Detailer LoRA:
https://huggingface.co/Lightricks/LTX-2-19b-IC-LoRA-Detailer/tree/main

Camera Control (Jib-Up):
https://huggingface.co/Lightricks/LTX-2-19b-LoRA-Camera-Control-Jib-Up

Camera Control (Static):
https://huggingface.co/Lightricks/LTX-2-19b-LoRA-Camera-Control-Static

Edition was done on Davinci Resolve

There is 5V 100mA max on input, but for example on charger there is 5V 2A.

I was curious to know how much you guys are earning working in this industry.

If comfortable do let me know, what kind of jobs do you do?

Full time/Freelance/Business

Your insights will help us, understand what should be the realistic expectations we must keep, while working in this field (with AI)

I’m working on a personal project where I’m building an AI agent with long-term memory. Right now I’m using Airtable to store memories, each with a created timestamp and a user ID (from Telegram).

The agent decides when to store something as long-term memory if it seems useful for better future replies. That part works fine, but I’m running into an issue with time-biased memories.

Example: I might say, “This month I’m using my snack budget for traveling.” The agent stores this as long-term memory. The problem is that after the month ends, this info is no longer relevant, but it still stays in memory and gets fed back into context, which can hurt response quality.

I currently have another agent that tries to clean up duplicates and time-biased memories, but I feel this is not an efficient or scalable approach.

How are you handling:

• Expiring or time-limited memories?
• Deciding what truly deserves long-term storage?
• Automatic cleanup or decay of old memories?

Long time lurker, first time poster!!

I’m in the process of setting up my first home assistant setup and I’m trying to integrate my APSystems solar (ECU-C) and Emporia Vue 3 but it looks like home assistant 17.1 on a Pi5 doesn’t like it very much.

I’ve searched this group a bunch and have been unable to find info on how to do it. Any insight would be appreciated!

I'm playing around with LM studio and an uncensored GPT model and it barely understands what a prompt for ai art/video even is. Bogged down by formatting and outlines and all manner of rubbish.

How's your experience? Looking for anecdotes not obnoxious hand-holding. thanks.

I’m trying to convert an old 49-key keyboard into a USB MIDI controller using an Arduino Pro Micro.

HERE ARE THE SHEMETAIC OF THE KEYS, A PICTURE OF THE SCAN MATRIK I FOUND USING MULTIMETER AND LASTLY THE DIAGRAM OF THE CIRCUIT (ASSUME THE NANO IS PRO MICRO)

(ALSO YES I USED AI TO WRITE THIS POST IM DYSLESIX)

The keyboard uses a 15-pin ribbon cable, and after reverse engineering it with a multimeter, I confirmed it is a standard matrix:

• 7 row lines
• 8 column lines (one partially unused)
• 49 keys total
• Each key connects one row to one column through a diode

I mapped every key and confirmed the full matrix layout and MIDI note assignments (C2 to C6).

Initially, I planned to connect the matrix directly to the Pro Micro, but to reduce pin usage and simplify wiring, I introduced a CD74HC4067 16-channel multiplexer.

My setup is:

• Keyboard ribbon pins connected to mux channels C0–C14
• Mux SIG connected to Arduino pin 9
• Mux S0–S3 connected to pins 2–5
• VCC → VCC
• GND → GND
• EN → GND

First, I tested the mux using a single button connected between C14 and GND, and that worked perfectly. Arduino could detect presses and send MIDI.

Then I tested reading all mux channels individually, assigning one MIDI note per channel — also worked perfectly.

The problem started when trying to scan the actual keyboard matrix.

My scan logic:

• Select one mux channel
• Drive SIG LOW (OUTPUT)
• Switch mux to another channel
• Set SIG as INPUT_PULLUP and read state

Expected behavior: pressing a key should connect two mux channels and allow detection.

Actual result: no keys are detected at all.

I verified:

• Mux is working correctly
• MIDI is working correctly
• Keyboard matrix wiring is correct
• Diodes are present and oriented consistently
• Individual mux channels read correctly

But matrix scanning via a single CD74HC4067 is not detecting connections between lines.
EVEN THE LIGHT IS NOT BLINKING WHEN IM PRESSING KEYS

I have finished my first DIY project based on the Raspberry Pi PICO 2W and a 5.65‑inch ePaper display. The goal of this system is to show the weather forecast for the current day (see the left side of the screen) and for the next five days (see the right side of the screen). I forked the software from micropython‑ePaperWeatherStation (https://github.com/frederik-andersen/micropython-ePaperWeatherStation) and improved several things. My version of the software can be found at https://github.com/Damov/micropython-ePaperWeatherStation.

The system is based on a Raspberry Pi PICO 2W, a Waveshare 5.65‑inch E‑Paper Display Module, and an Adafruit PowerBoost 1000C combined with a 3.7V LiPo battery for power management. On the GitHub page, it is documented how to wire these components. I will also publish the STL and 3MF files for 3D printing the frame at some point.

This is version 0.1. What I personally don’t like about it is the fact that you won’t immediately notice when the battery is empty, because the status LEDs are on the back of the Adafruit 1000C, and the screen (as it is an ePaper display) will always show the last image. Therefore, I am planning to replace the Adafruit PowerBoost 1000C with a Waveshare UPS Module for Raspberry Pi Pico, which provides an uninterruptible power supply and battery status monitoring via I2C. This module makes it possible to show the battery status on the Pico through I2C, and therefore it can be displayed directly on the screen.

Hi

Is anyone priting there generated art/image on t-shirt/ wall frame etc?

If you do how are you going to do this?

I just built a workflow that automatically identifies potential leads from Reddit posts, and I'm pretty excited about the results.

What it does:

• Monitors specific subreddits for relevant posts
• Extracts user information and post data
• Filters based on custom criteria
• Organizes everything into Google Sheets
• Currently pulling 25+ qualified leads daily

The flow:

1. HTTP Request to Reddit API
2. Data processing and filtering
3. Loop through results
4. Clean and structure the data
5. Append to Google Sheets

Challenges I solved:

• Rate limiting with the Reddit API
• Data cleaning for inconsistent post formats
• Avoiding duplicate entries
• Setting up proper error handling

The workflow has been running stably for 2 weeks now and has completely changed my lead generation process. Happy to share more details about specific nodes or the logic if anyone's interested!

https://preview.redd.it/4mrhi0gvwojg1.png?width=1080&format=png&auto=webp&s=142951ebeade6c2949920d0098a5e4c7573f5031

https://preview.redd.it/kkurrevwwojg1.png?width=1080&format=png&auto=webp&s=d7f2692c44d8f12823917a3e641c8ea5f8596a76

Anyone else working on similar Reddit automation projects?

Btw made also same thing for linkedin and got +100Million lead if this post got 100upvote will share the workflow, feel free to check the 102M+ lead i have at leadadydotcom

This video clarifies OpenAI's recent press release regarding GPT-5.2 Pro's "new result in theoretical physics," stating that the claims are overhyped and misleading (0:00).

The speaker, who has a physics degree, explains that the AI did not discover new laws of physics (0:15). Instead, human authors first developed complex physics equations, which were then given to GPT-5.2 Pro. The AI spent 12 hours simplifying these existing complicated expressions into a more concise form (1:10).

Key points from the video include: Simplification, not discovery: The AI's achievement is in simplifying already-known equations, which could have been done manually or with other software like Mathematica, albeit with more time and effort (1:40). AI as a tool: The speaker emphasizes that AI serves as a valuable tool for physicists by making complex mathematical derivations faster and simpler (2:31). Misleading headlines: The video criticizes OpenAI's press release for using terms like "derived a new result," which can be misinterpreted by the public as a groundbreaking discovery comparable to Newton's laws (3:18). This leads to exaggerated headlines that fail to accurately represent the AI's actual contribution (4:03). "Internal Model": The video notes that OpenAI used a specialized "internal model" for this task, suggesting it wasn't just a standard ChatGPT application that achieved this result (4:36).

The speaker concludes by urging viewers to be cautious of sensationalized headlines and to understand the actual technical accomplishment (4:55).

Hey there, can anyone help me with how to create images/videos like this? With radiating color and a clear grain effect?

👋 This is a bit different take on programming with AI, instead of going more in the vibecoding direction, I'll try to use AI to stay get into the "zone", into the flow state. I'd love to hear other ideas how AI can be used in a way to empower us instead taking away. How can AI leave the hard parts to us, but give us better focus on it?

Found it in the drawer of my oven after just moving into a new place

https://abc7amarillo.com/news/local/gym-altercation-leads-to-arrest-and-police-deploying-taser

I am working on this programming language called Ypsilon Script for programming microcontrollers and dev boards. It features modern beginner friendly syntax and compiles to Arduino C++. Be sure to check it out on my github : https://github.com/ycharfi09/ypsilon-script

I inherited this large wooden box with several small drawers of tools. Are all of these tools related or is this just a wooden tool box? Also, the box has a strong medicinal smell when you open it.

Thanks for your help!

Taken On Seestar S50 Using 3hr Integration.

Edited In PS Express.

New experiment, involving a custom FLUX-2 LoRA, some Python, manual edits, and post-fx. Hope you guys enjoy it. ♥

Music by myself.

More experiments, through my YouTube channel, or Instagram.

Our university life is covered and I don’t understand why!

On Katie's most recent core class (2/13/26), she says that if she has live back-to-back classes she always programs them together so they can be stackable.

I always wondered if instructors did this, but it's helpful to know if you are looking for a good stack and not sure what to pair it with. She also has an upper body class from that day that goes along with the core class.

Can someone remove the glare on my BFs glasses? No other edits. TIA

I was playing around with OpenClaw. Installed it on Raspberry Pi, used it to do a work task in minutes rather than days. It's magic, especially paired with Opus 4.6

Problem is the API is still too expensive; you can burn through $100 a day easy.

Then Cowork for Windows dropped. Apart from the few networking connectivity bugs, it works a treat. I was already spending quite a bit on the API so went for the top tier x20 plan and so far, have not been hitting any of the limits, roughly 10x cheaper.

I also have Gemini and Codex subs so why not use those to save Opus work, but Cowork can't directly spawn agents outside its environment... or can it?

I asked it to create in and out .md files with instructions for Codex and then set up a PowerShell script to run on file change. Et voilà, now I have Cowork spawning and orchestrating Codex agents doing real work at what I would say is orders of magnitude lower cost.

From there onward all kinds of automation is trivial.

Anyone else tried it?

Edit: Typo had 4.5 instead of 4.6

Another LTX-2 experiment, this time a lip sync video from close up and full body shots (Not pleased with this ones), rendered locally on an RTX 3090 with 96GB DDR4 RAM.

3 main lipsync segments of 30 seconds each, each generated separately with audio-driven motion, plus several short transition clips.

Everything was rendered at 1080p output with 8 steps.

LoRA stacking was similar to my previous tests

Primary workflow used (Audio Sync + I2V):
https://github.com/RageCat73/RCWorkflows/blob/main/LTX-2-Audio-Sync-Image2Video-Workflows/011426-LTX2-AudioSync-i2v-Ver2.json

Image-to-Video LoRA:
https://huggingface.co/MachineDelusions/LTX-2_Image2Video_Adapter_LoRa/blob/main/LTX-2-Image2Vid-Adapter.safetensors

Detailer LoRA:
https://huggingface.co/Lightricks/LTX-2-19b-IC-LoRA-Detailer/tree/main

Camera Control (Jib-Up):
https://huggingface.co/Lightricks/LTX-2-19b-LoRA-Camera-Control-Jib-Up

Camera Control (Static):
https://huggingface.co/Lightricks/LTX-2-19b-LoRA-Camera-Control-Static

Edition was done on Davinci Resolve

Ryzen 5 1600 ,Pentium G6400 , i7-2600 ,I3-6100 paired with 4x2060 Nvidia Will i encounter bottleneck, CPU doesnt supporto pcie4, ?

I've spent the last few weeks researching how to build a personal AI-powered knowledge system and wanted to share where I landed and get feedback before I commit to building it.

The Problem

I consume a lot of AI content: ~20 YouTube channels, ~10 podcasts, ~8 newsletters, plus papers and articles. The problem isn't finding information, it's that insights get buried. Speaker A says something on Monday that directly contradicts what Speaker B said last week, and I only notice if I happen to remember both. Trends emerge across sources but nobody connects them for me.

I want a system that:

1. Automatically ingests all my content sources (pull-based via RSS, plus manual push for PDFs/notes)
2. Makes everything searchable via natural language with source attribution (which episode, which timestamp)
3. Detects contradictions across sources ("Dwarkesh disagrees with Andrew Ng on X")
4. Spots trends ("5 sources mentioned AI agents this week, something's happening")
5. Delivers daily/weekly briefings to Telegram without me asking
6. Runs self-hosted on a VPS (47GB RAM, no GPU)

What I tried first (and why I abandoned it)

I built a multi-agent system using Letta/MemGPT with a Telegram bot, a Neo4j knowledge graph, and a meta-learning layer that was supposed to optimize agent strategies over time.

The architecture I'm converging on

After cross-referencing all the research, here's the stack:

RSS Feeds (YT/Podcasts/Newsletters)

→ n8n (orchestration, scheduling, routing)

→ youtube-transcript-api / yt-dlp / faster-whisper (transcription)

→ Fabric CLI extract_wisdom (structured insight extraction)

→ BGE-M3 embeddings → pgvector (semantic search)

→ LightRAG + Neo4j (knowledge graph + GraphRAG)

→ Scheduled analysis jobs (trend detection, contradiction candidates)

→ Telegram bot (query interface + automated briefings)

Key decisions and why:

- LightRAG over Microsoft GraphRAG - incremental updates (no full re-index), native Ollama support, ~6000x cheaper at query time, EMNLP 2025 accepted. The tradeoff: it's only ~6 months old.

- pgvector + Neo4j (not either/or) - vectors for fast similarity search, graph for typed relationships (SUPPORTS, CONTRADICTS, SUPERSEDES). Pure vector RAG can't detect logical contradictions because "scaling laws are dead" and "scaling laws are alive" are *semantically close*.

- Fabric CLI - this one surprised me. 100+ crowdsourced prompt patterns as CLI commands. `extract_wisdom` turns a raw transcript into structured insights instantly. Eliminates prompt engineering for extraction tasks.

- n8n over custom Python orchestration - I need something I won't abandon after the initial build phase. Visual workflows I can debug at a glance.

- faster-whisper (large-v3-turbo, INT8) for podcast transcription - 4x faster than vanilla Whisper, ~3GB RAM, a 2h podcast transcribes in ~40min on CPU.

- No multi-agent framework - single well-prompted pipelines beat unreliable agent chains for this use case. Proactive features come from n8n cron jobs, not autonomous agents.

- Contradiction detection as a 2-stage pipeline - Stage 1: deterministic candidate filtering (same entity + high embedding similarity + different sources). Stage 2: LLM/NLI classification only on candidates. This avoids the "everything contradicts everything" spam problem.

- API fallback for analysis steps - local Qwen 14B handles summarization fine, but contradiction scoring needs a stronger model. Budget ~$25/mo for API calls on pre-filtered candidates only.

What I'm less sure about

1. LightRAG maturity - it's young. Anyone running it in production with 10K+ documents? How's the entity extraction quality with local models?
2. YouTube transcript reliability from a VPS - YouTube increasingly blocks server IPs. Is a residential proxy the only real solution, or are there better workarounds?
3. Multilingual handling - my content is mixed English/German. BGE-M3 is multilingual, but how does LightRAG's entity extraction handle mixed-language corpora?
4. Content deduplication - the same news shows up in 5 newsletters. Hash-based dedupe on chunks? Embedding similarity threshold? What works in practice?
5. Quality gating - not everything in a 2h podcast is worth indexing. Anyone implemented relevance scoring at ingestion time?

What I'd love to hear

- Has anyone built something similar? What worked, what didn't?

- If you're running LightRAG - how's the experience with local LLMs?

- Any tools I'm missing? Especially for the "proactive intelligence" layer (system alerts you without being asked).

- Is the contradiction detection pipeline realistic, or am I still overcomplicating things?

- For those running faster-whisper on CPU-only servers: what's your real-world throughput with multiple podcasts queued?

Hardware: VPS with 47GB RAM, multi-core CPU, no GPU. Already running Docker, Ollama (Qwen 14B), Neo4j, PostgreSQL+pgvector.

Happy to share more details on any part of the architecture. This is a solo project so "will I actually maintain this in 3 months?" is my #1 design constraint.

Unsure if flair is correct..!

Hey all,

I use Claude Pro daily as my main driver, along with ChatGPT and the MiniMax. And I kept running into the same annoying thing: I'd be deep into a Claude coding session and suddenly hit the 5-hour usage cap. No warning, no way to know I was at 90% before it happened unless I had the usage dashboard open in a browser window.

The thing is - if you time it right, you can kick start a 5h window when you don't need it, so you have ~90% remaining at the end and a fresh one ready to go. I was juggling this across three providers, doing mental math to keep windows from overlapping - so I could make the most out of my very limited pro subscription!

I got tired of mentally tracking windows and checking dashboards, so I started building an iOS app to just show me where I stand across all my AI subscriptions in one place - and mos importantly, having notifications and easy to glance widgets.

I call it AI Usage Tracker.
Claude Opus helped me kick start it (mostly planning and reviewing, while coding was a mix of multiple providers), and the app made it possible to take the most out of the 5h slots!

A few screenshots.

https://preview.redd.it/7si5jy18xojg1.jpg?width=1206&format=pjpg&auto=webp&s=d68ff92a0569b6739b714f9240480a5b909eaf57

https://preview.redd.it/wszfp0p9xojg1.jpg?width=1206&format=pjpg&auto=webp&s=6cd036dba71e121d24f50c01af3930b837fe036b

https://preview.redd.it/or8rva09xojg1.jpg?width=1058&format=pjpg&auto=webp&s=7e1225e8a914155a357a6faa522f50022ec177ad

https://preview.redd.it/1kud5jvaxojg1.png?width=1206&format=png&auto=webp&s=ee0dbc916f4bd99bda0273379ef8c740b40a29a9

This app is meant for people who use AI heavily. Multiple accounts per provider is on the roadmap.

What it does right now:

• Shows your 5-hour sliding window and weekly quota status with color coded gauges
• Reset countdown timers so you know when a window opens back up
• Home Screen and Lock Screen widgets
• Alerts at custom thresholds (75%, 90%, etc.)
• Tracks usage for Claude (Pro/Max), ChatGPT/Codex, OpenAI API, Z.ai, Kimi Code and MiniMax
• OpenAI API token tracking (cost tracking still needs more testing - tokens seem reliable, dollar amounts are a work in progress)

Being honest about the state of things: this is early. It works and I use it daily, but some providers are more polished than others. Claude and ChatGPT tracking are solid. OpenAI API tracks tokens well but cost reporting needs more work.

There will be bugs - that's exactly why I need testers.

Everything runs on-device. No accounts, no servers, no tracking. Credentials stored in iOS Keychain (encrypted on device).

I'm limiting beta spots so I can actually keep up with feedback. If you deal with this problem too - juggling limits across AI subscriptions - sign up here and I'll send TestFlight invites in batches:

👉 https://forms.gle/GFHj3sYyrGXmHVag6

Happy to answer questions.

A few months ago, I was drowning in a sea of AI prompts, struggling to organize and make sense of them. It felt like every time I thought I had a grip, another wave of disorganization hit. If you've ever felt like you're just endlessly curating without any real community engagement, keep reading.

I was so focused on creating prompts that I overlooked the potential of sharing what I already knew. Turns out, sharing my expertise not only helped others but also brought unexpected benefits to me. By putting my prompts out there, I started attracting feedback and ideas I hadn't considered before. The community engagement was way more valuable than I imagined.

The fix was stupidly simple - just start sharing. I know, it sounds obvious, but I sat on my prompts for months, thinking they weren't ready or good enough. But by sharing them, I realized there was a whole community ready to collaborate and improve them.

I've found that engaging with others, discussing prompts, and getting feedback saved me a ton of time and improved my work significantly. If you're working on something similar, don't wait until it's perfect. Share what you have and let the community help you refine it. This approach changed everything for me, and I'm hoping it can do the same for you.

Does anyone have experience creating a successful app with Claude? What worked, what didn’t? Any advice? I’m at the beginning stages, and CoWork has really help me flush out my concept for an app, mission statement, pricing and next steps.

Hey 👋

I’m building an AI-native, agentic SEO agency that lives inside tools like WordPress, GitHub, Framer, Webflow, etc — not a dashboard, but something that actually runs SEO end-to-end.

I’m a non-technical founder with strong product + GTM + logic background, but I’m looking for a technical co-founder to own architecture, agents, infra, and long-term code quality.

Early stage, bootstrapped, equity-heavy.
If you’re into agentic systems, OSS vibes, and want to bootstrap to a 100M+ exit, let’s talk.

DMs open 🚀

Background: Industrial engineer, 2x founder, first company +2M ARR.

Hi everyone,

I created my first app for pinterest users (of,course using with ai only) . Did some promotion here and there, but not getting any users. Don't know the exact reason.

Need your suggestions on getting first paid user.

Here is the tool genpin.co

I built a real-life Simon Says game that physically slaps you if you fail.

The idea was simple: camera watches you, calls out poses, and if you mess up (or if Simon didn’t say), a giant mechanical hand smacks you.

Under the hood:

• Raspberry Pi 5 running MediaPipe pose detection
• Custom pose classification in “body-axis space” (normalized by shoulder width, angles/distances instead of raw coordinates)
• MJPEG stream piped into OpenCV for low-latency processing
• Game logic with timing windows, smoothing, and confidence thresholds
• Elastic bands slap mechanism triggered by an electro-magnet :)

Hardest parts:

• Getting pose detection stable enough without 500ms lag
• Avoiding false positives on “hands down”
• Tuning thresholds so it feels fair but still stressful
• Making the slap look violent without actually being… lawsuit-grade

I’d love feedback on:

• Better ways to structure lightweight pose classification on-device
• Whether you’d move this to a tiny GPU instead of CPU-only Pi
• Ideas to make the punishment mechanic more punchy

Happy to share code snippets or talk through the architecture if anyone’s curious.

I built this website as a student side project with around a dozen tools all in one spot so you can save time by not navigating away. There are grade calculators, timezone converters, stopwatches, timers, metronomes, etc. It's also offered in 4 languages: English, Spanish, German, and Mandarin. Any feedback is greatly appreciated, and if you're interested in offering testimonials to add onto the website, pls let me know.

So I’ve been pretty deep into automation for a while now, basically lived in Zapier and Make for the last couple of years. It worked fine for the simple stuff—syncing leads to a CRM, posting to Slack, the usual. But lately, I’ve been trying to push it into actual marketing execution, and honestly, it feels like I’m trying to build a skyscraper with Legos.

The problem I keep running into is that marketing isn't a straight line. If I’m running a campaign and the search environment shifts or a competitor drops a new feature, a linear workflow just... sits there. It does exactly what it's told, even if the context has changed.

I’ve been experimenting with moving away from "If This Then That" and trying to set up more of a "workforce" vibe. Like, having one agent handle the SEO/search visibility side, another watching social sentiment, and a third actually adjusting the content. The idea is they’re supposed to talk to each other and adapt.

It’s been a bit of a nightmare tbh. Getting them to share context without just dumping the entire history into a prompt and hitting token limits is tough. I tried building a shared "memory" layer, but it’s still kinda clunky and they sometimes get into these weird feedback loops where they just agree with each other until the credits run out.

I'm really curious if anyone here has successfully moved past the "trigger-action" mindset into something more collaborative for high-level tasks. Are you guys using specific frameworks for the handoffs, or is everyone just winging it with custom scripts? I feel like I'm close to something that works, but the coordination part is still so brittle.

I've been hitting credit limits on Cursor/Copilot pretty regularly. Expensive models eat through credits fast when you're doing full codebase analysis.

Thinking about self-hosting DeepSeek V3 or Qwen for coding. Has anyone set this up successfully?

Main questions:

- Performance compared to Claude/GPT-4 for code generation?

- Context window handling for large codebases?

- GPU requirements for decent inference speed?

- Integration with VS Code/Cursor?

Worth the setup hassle or should I just keep paying for multiple subscriptions?

This came about as I was trying to come up with app ideas and this is the one that stuck. I don't have all the money in the world, and while groceries weren't my biggest expense at the time, I wanted to keep track of what was in my cart and how much I was spending before I reached checkout.

I've since discovered the fun of determining sales taxes via GPS and that shelf tags don't always seem to be accurate — which is another direction I could take this app, but it would take a much larger user base to gather pricing data.

What it does:

- Point your phone camera at a shelf price tag and it reads the price automatically using an escalating chain — OCR and regex first, then sending the image to AI for full analysis if needed.

- Keeps a running subtotal + tax estimate as you shop

- Built-in shopping list you can check off as you go. A second concurrent login is allowed so your spouse can send you a list and see as you check things off. Also supports pasting a comma-delimited list to quickly add items.

- Email yourself (or your spouse) a receipt summary when you're done.

Completely web-based, no download needed. Can share with others via a QR code generated within the app. Meant to be used on an Android or iOS device though.

Looking for feedback on the app or tell me I'm crazy for making it? Would offer lifetime access (unlimited scans) to up to 20 that test and provide feedback. Would like to push it out as an app to the google play store and iOS app store eventually.

https://shelftocart.app/

Hey all,

I am seriously considering investing a significant portion of my signing bonus into a local LLM setup as a hobby and learning project once I start my job in August.

I am currently in university. I have studied a lot of theory, but I feel I am missing practical, hands-on experience.

If you were starting from scratch today, knowing what you know now, what would you do differently?

Specifically:

• What hardware would you prioritize
• What inference stack would you start with
• What beginner mistakes should be avoided
• What models are actually practical on consumer GPUs

I know much of this information already exists, but it is often fragmented across many threads, benchmark posts, and user experiences.

I would really appreciate any lessons learned from people who have been running local setups for a while.

Thank you :)

Hello,

I've seen people on the OpenModelDB website sharing PyTorch files (mostly) that allow them to filter, or even restore, videos using artificial intelligence.

I'd like to know if it's difficult to create a model, as I've tested several and noticed that the results depend heavily on the videos being filtered.

Please note that I'm a complete beginner, and this will be my first time undertaking such a project.

Thank you in advance for your help.

Real talk: I was spending more time prospecting than actually selling. Google Maps scrolling, LinkedIn stalking, copying emails into spreadsheets, praying the contact info wasn't 3 years old.

Every existing tool was either:

• Enterprise-priced (ZoomInfo wanted $15K/year... for ONE user)
• Full of garbage data (50% bounce rates on "verified" emails)
• Focused on giant companies instead of local businesses

So I started building Dight.pro. The pitch is dead simple: tell me your target niche and location, get verified decision-maker contacts you can actually reach. No enterprise contract. No paying for 10,000 credits you'll never use.

It's in pre-launch right now (collecting waitlist signups) and I'd love feedback on:

• Does this actually solve a problem you have?
• What would make this a "shut up and take my money" vs. "meh, maybe"?
• What am I missing that you need in a lead gen tool?

I'm happy to geek out about the tech stack and share what I've learned building this. Dropping screenshots in the comments.

It seemed extremely consistent, cohesive, no repetition so far I've tested, and it works very well on small vram size.

How is this possible?

Hi guys, it seems like there's something extremely strange going on with regards to claude max usage limits: this morning, i sent like 3 prompts to claude, and all of the sudden my max 5 usage limit was almost completely used up. I never had this issue before. Now, after resetting a couple of hours ago, the usage seemed to tick down sort of normally - then i just checked claude usage (the webpage, not through the CLI ) and I saw that apparently now my limit resets in 9h -- after basically already using it for a few hours. Are there some additional limits i'm not aware of?? I thought the resets are every 5h???? (on max x5 plan). also, my reset day was actually Wednesday evening until I checked back today, and now its thursday morning. WTF?!

https://preview.redd.it/uaktq4e8xojg1.png?width=1369&format=png&auto=webp&s=e1d05b0f30a473f97fff09924521957e2f1ed187

https://preview.redd.it/8qef0jeoxojg1.png?width=1116&format=png&auto=webp&s=07453204b7818b4fe5b3e5b2703cc3c2238fd14c

My mailbox is in the building entrance hallway (typical Prague apartment setup), several walls away from my flat and with no power outlets nearby.

I wanted to get a push notification the moment a letter arrives, not when I open the mailbox.

At first, I paired an Aqara P1 motion sensor directly to my Zigbee coordinator, but the signal was unreliable because of distance and metal interference.

The solution was flashing a Sonoff Zigbee Dongle-E with router firmware and powering it from a 20,000 mAh power bank to extend the mesh closer to the mailbox.

Unexpected problem: the power bank kept shutting down because the router draws too little power. Fix was adding a small USB keep-alive module (dummy load) to prevent auto shutdown.

Now the flow is:

Motion sensor → Zigbee router → Zigbee2MQTT → Home Assistant → instant push notification

I also implemented a watchdog using the last_seen attribute so HA notifies me if the router goes offline.

Works reliably now.

I wrote a full breakdown including architecture diagrams, firmware setup, and automations:

https://jonathas.com/how-i-made-my-physical-mailbox-send-me-real-time-push-notifications/

TLDR: The main reason the agentic framework has seen most success in coding is because of its ratio of time saved to human supervision needed.

One of the most visible real-world applications of the agentic paradigm is coding. Most people seem to think it is because corporations no longer want to have to be dependent on highly paid engineers which is clearly a strong incentive. But while that is the motivator this omits the core reason that makes this even possible.

First, the main obstacle to agent adoption is risk. Take customer support. If I mistakenly tell a customer their return has been processed when in fact it has not, this does a lot of damage to my brand image. This is why, at the current level, of AI reliability, we need human supervision.

Structurally, software engineering is one of the few areas where agents can replace humans with relatively low risk. This is because coding agents are supervised. They ultimately have to go a through a human-made testing pipeline and a human-reviewed process. This drastically reduces the risk of something completely outlandish and catastrophic being shipped by AI.

That's also why other fields have not seen as much progress automation yet. Customer support for example – even though now even that is changing – is less inherently favorable to agents because the customer support cycle is short. Customer support calls are measured in minutes whereas a software feature is built in hours. This means the ratio of human supervision to time saved by AI is way higher for customer support. This makes it less profitable.

This brings me to the core measure of whether a field is suited to being automated by AI: the ratio of time saved by AI over time needed for a human to supervise its output.

e.g.

Say as an engineer it takes me 8 hours to build a feature without AI and AI does it in one minute. The testing pipeline and review process take say 1 hour in total. The ratio is roughly (8*60-1)/60 ~ 8.

For customer support, say it takes 2 minutes to complete a call (vs 5 seconds for the AI) and then 30 seconds for a human to review you have a ratio of roughly 4. Twice as low as for coding.

Hi folks 👋

https://reddit.com/link/1r5kqo6/video/gpgxlllb6pjg1/player

We have built Warren to simplify investing for layman investors. With our app, you won't need any financial advisors or wealth managers. So far, Warren provides its customers with a set of personalised features (stocks, portfolios & chat) that help them achieve their goals.

We're excited to see what the community thinks. Please share your feedback 🙌

App store - https://apps.apple.com/gb/app/warren-simplify-investing/id6504190197

Product Hunt - https://www.producthunt.com/products/warren-2

YC Hacker News - https://news.ycombinator.com/item?id=47020004#47025169

I'm building a platform where college students can discover classmates with specialized technical skills (CAD, welding, PCB design, 3D printing, etc.) for project help.

The problem: You need someone who knows how to TIG weld for your capstone, but you have no idea who on campus has that skill.

My question: **Would you actually create a profile on something like this?** Or would you just ask your friend group / post in Discord?

Trying to validate if this solves a real problem before building payment features.

I think I fell into the "complexity trap" pretty hard over the last few months. I got so excited about the idea of autonomous agents that I started building these massive, multi-step chains for everything—content research, lead enrichment, competitive analysis.

The problem is, when I actually sat down to look at the numbers this week, the ROI just wasn't there. I was paying for these high-level LLM calls to do things that, honestly, a basic Python script or a standard Zapier workflow could have handled for a fraction of the cost.

The "cool factor" of having an agent "think" its way through a problem is high, but it’s becoming a bit of a nightmare to manage. Half the time, the agent takes a weird detour that costs 50 cents in tokens and provides zero extra value.

I'm currently trying to strip everything back and figure out where the "autonomy" actually provides a return. For me, it seems to be in the tasks that require real-time adaptation—like adjusting a marketing strategy based on live search data—rather than just repetitive data moving.

I’ve been trying to document which specific "agentic" behaviors actually move the needle and which are just expensive window dressing. It’s been a frustrating process of trial and error.

Curious if anyone else has gone through this "de-complicating" phase? How do you decide when a task actually needs an autonomous agent versus just a well-built linear workflow? I feel like the hype cycle led me to over-engineer everything.

I built a free photo editor that you can use to crop, rotate, adjust, add filters, and add text, all for free, no signup or anything.

Your Perfect Photo

So I've been a Claude Pro subscriber since late last year. Mostly use it for coding and writing — honestly it's replaced like 3 other tools I was paying for.

But $20/month adds up, especially when you're also paying for other SaaS stuff.

Anyway, I stumbled on something a few weeks back. Turns out there's a legit way to get Claude Pro at $10/month instead of $20. Not a hack, not account sharing, not anything sketchy. It's an actual discount that's available through the platform — just not obvious at all.

I've been on the discounted rate for about 2 months now and everything works exactly the same. Full Opus access, Projects, all the Pro features. Just half the price.

The discount applies for 3 months, so that's $30 saved total. Not life-changing money but honestly why pay more when you don't have to?

Happy to share how I did it if anyone's interested. Or if other people already know about this, curious if your experience has been the same.

Edit: since a bunch of people asked, I put together a quick walkthrough with screenshots. Link in comments.

Hi, I have the following goal: I want to remove my hands from the video where I move a mascot and do proper inpainting, so that in places where my hands are in front of mascot, the mascot shape is inpainted, and in other places the reference image (background) is inpainted (so that it looks like a mascot moves on its own).
The problematic part is the mascot shape - the model have no idea how the mascot looks like so it can't be consistent across generations and it adds various body parts that should not exists. After some research I found out that the LoRA of the mascot might help. I used `diffusion-pipe` for that goal, with about 18 pictures of my mascot. After trying maaany settings (I still testing) I manage to have a LoRA that somehow works and for prompt like "florbus dolphin toy in the car" returns the shape of my mascot (see below videos for real mascot look). The florbus is my keyword for that mascot, which seems to be not strong enough, becaue if I simply write "florbus" in my prompt then lora seems to have no efffect and dolphin is not generated at all and I have to type "florbus dolphin toy" to generate it.

https://preview.redd.it/9b2r6j32iojg1.png?width=832&format=png&auto=webp&s=e1dfa9ba86e16f5c13bfe979bec97e150b8f51f1

Now I connected that LoRA to my VACE inpainting workflow. I divided my video into parts of 5 seconds each and for each part I masked my hands with SAM3 and I expanded that mask by 5 units. As a reference image I used the image of the background seen on the video (without my hands and without mascot). My prompts are:

- (positive) - florbus dolphin toy on the background of reference image

- (negative) - human, finger, hand, blurry, bad quality, asymetry

Additionally, here are the settings of my sampler (LoRA strength is 1, and VACE strength is 1.5):

https://preview.redd.it/eu7p7gr5jojg1.png?width=403&format=png&auto=webp&s=73e187c49dc4a72a9bef6a91f96eb051b41b9e2e

Finally, here is the input vs output:

https://reddit.com/link/1r5j5pr/video/6o2dt9jfjojg1/player

As you can see, dolphin is completely bad inpainted - my thumb created a hole in the mascot, while my other fingers are not removed but got the material of the mascot and some extra dolphin body part is added at the bottom :(

I tried to lower VACE strength, but with 1.0 hands are not removed at all. Do you have any recommendations how to fix it? What settings to use? Is my LoRA ok? I would really appreciate help because I feel that I'm pretty close to make it works but I still do not understand all VACE inputs and settings and maybe that's the reason why mascot shape is not preserved during inpainting.

https://youtu.be/NKj5vu0OWAU

I started using Runpod this week. I deployed the custom ComfyUI "optimized for 5090" image and deployed it on a machine with a 5090 GPU.

It worked "out of the box", and I was able to install various custom nodes and download models. But, the next time I tried to start up the pod, multiple nodes in my workflow have been executing on CPU rather than GPU and I am at a loss to understand why.

For example the ordinary dpmpp-2m-sde sampler from the KSampler node was originally running on GPU. But now it only runs on CPU. The Euler sampler, or the dpmpp-2m-sde-gpu sampler, are still able to run on the GPU. The birefnet background removal tools in the AILab ComfyUI rmbg package are unable to run on GPU as well and they fall back to CPU.

Or, if I migrate the data to a new "pod" and try to run my setup on this new pod, I experience similar difficulties.

From this description, it seems like the problem is of the following form. I installed custom nodes but for some of these nodes the installation process resulted in changes outside the /workspace directory that persists after shutdown. When I restarted the machine, those changes were reset, resulting in a broken install.

But I can't track down the source of the breakage. Also the KSampler dpmpp-2m-sde sampler should just work out of the box without me having to install anything so I don't understand how the default image generation workflow would be broken

Since I got the $50 promo credit and usage was discounted 50% for the promotional period (ends tomorrow), I decided to try out fast mode.

Background: I started using CC when it was API-only but backed off because it was too expensive. When they allowed Max subscribers to access it, it became my primary coding tool, but I immediately noticed it was much slower than API. Over time I feel like inference has gotten even slower, but I have chocked it up to them having to balance the cost of inference with offering flat rate access to customers.

I have a sub-agent for a project that: researches inbound change requests, fully researches the blast radius (i.e. if you are fixing a bug related to a database connection, does this potentially affect all database calls), creates a tech approach plan, uses my Gemini MCP to ground that approach against Gemini 3 pro, and then finally turns the request into a series of action items in my task tracker doc. It works very well for my project BUT it takes approx 15-20 minutes to run per each submitted issue. I figured this would be a great test for fast mode.

Sure enough I submitted a request and it churned through the first one in 3 minutes. I checked my usage: those 3 minutes cost $20. I submitted another one to be sure: another 3-4 minutes, another $25. This was reminding me of the old API days. I started implementing the first feature, and I ran out of my $50 allotment before it was done (it gracefully degrades back to normal speed). That was a fun 10 minutes.

Anyway, my theory remains that “fast mode” is merely a way for flat rate subscribers to have easy access to API speeds but at API costs. This was always available as a mode switch if you had an API key, but now it has an easy toggle slash command (/fast). I think for fiscally-conscious deadline-driven developers, this is a convenient way to quickly inject bursts of speed where necessary.

Hope this helps someone!

resume-forge.ai

App lets you track your job applications, edit resumes using CV, export your resume in an ATS friendly format and analyze your resumes against specific job posts.

Looking for user feedback

I'm a millennial who consumes brainrot on the daily so excuse my horrid attempt at a concise narrative over fragmented chunks here.

I understand in 2026 we basically have no say or control, and by we I mean anyone whos eyes see this thread, over really anything anymore especially in relation to technology BUT, as the title states, why are we hell bent on speed running this?

Not only are we just blindly adopting a blackbox technology [LLMs] we have no control over but we're doing it at the expense of people's livelihoods I.E. jobs.

We've had magic tech for decades now but all of a sudden Chatgpt comes along, introduces a new trick, and immediately results in the slashing by double digit percentages of entire workforces?? And this all comes from the guiding beacons of a few dozen companies that control the entire landscape and are relentlessly shoving this tech down our throats.

Why the fuck do we put up with this? Are we that goddam lazy? How are we ok just submitting to a few corporate entities?

I switched from Tuya to Tuya Local and everything is working great. I have some scenes in Tuya that are still available for me to call via Tuya.

Is there a way to copy or move a Tuya scene to Tuya Local ?

Hey folks,

I’ve been hacking on a side project: a web-based “System Design Simulator.” It’s like a whiteboard, but you can actually press play and watch your architecture behave (or fail).

What you can do:

• Drag-and-drop common pieces: load balancer, API gateway, caches, DBs, queues, even some AI bits.
• Hit “Start Simulation” to see latency, error rate, throughput, cache hit rate in real time.
• Flip chaos switches: traffic spikes, cache-miss storms, network partitions, component crashes.
• Share & remix: every design gets a short link; anyone can fork it and improve.
• Built-in hints: it tells you if you forgot an entry point or storage.

Why I made it:

• Diagrams don’t fail; systems do. I wanted a fast way to feel trade-offs without spinning up infra.
• For interviews and design reviews, it’s nice to ask “what if the cache dies?” and just click a button.

Try it here: https://paperdraw.dev
Quick start: drop Load Balancer → App Server → Cache → DB, press play, then trigger a cache-miss storm.

Would love feedback:

• What metrics or failure modes would you add?
• Is the start/stop flow obvious enough?
• Any presets you want (payments, chat, ingestion)?
• Should I add “export GIF of the run” for sharing?

Thanks for taking a look—happy to fix bugs or add features if you ping me.

Hey! I’m Damian from Poland and I’ve been working on a small side project called FirstVibe.

The idea came from a simple question:

we all wonder how we’re perceived in the first few seconds - but nobody tells you the truth.

So I built a tool where you:

- upload a selfie

- get a vibe score

- see how you come across in 5 areas (confidence, attractiveness, approachability, style, charisma)

The free version shows the score and a short first-impression preview.

The full report goes much deeper (dating energy, glow-up tips, AI caricature, red/green flags, etc.).

Tech stack: Rails 8 + Claude Vision + OpenAI + Stripe

No user accounts - everything is session-based (this alone tripled my conversion compared to a signup flow).

👉 https://firstvibe.app

I’m mainly trying to validate the idea, so I’d genuinely love feedback:

- Does this concept feel interesting or gimmicky?

- Are the results believable?

- What would make something like this shareable?

If you want to test the full version, I can unlock it for early testers.

Brutal honesty very welcome.

implemented all hooks here: https://github.com/shanraisshan/claude-code-voice-hooks/tree/main

Hi,

​I'm looking for recommendations for a centralized WebUI for my local setup. I've got the backends running but I'm searching for the perfect frontend that offers a smooth, seamless user experience similar to ChatGPT or Gemini.

​Here is my current backend stack that the UI needs to handle:

• LLMs: Two 32b models (Qwen & Deepseek) running via vLLM fixed to gpu 1 with 24gbvram

• Vision: MiniCPM-V

• Image Gen: dunno yet flux or sdxl

• Audio/TTS: Whisper Turbo (distilled for German) and i dont know what

Fixed to gpu 2 with 24gb vram

​These are the features I'm prioritizing for the WebUI:

Unified UX: Text, Vision (uploading/analyzing images), and Image Generation natively accessible within a single chat interface.

Is there anything out similar to this

I’ve had a hard-to-ignore sense of paradox for weeks now. Just a month ago, a lot of us were paying $100 / $200 to Anthropic (for example via Claude Code) for a level of capability that, at the time, felt “worth” the price. Today, Claude Opus 4.6 is clearly more refined—but then GLM 5 shows up pushing incredibly hard, setting records and closing the gap (or outright surpassing it in some areas) relative to the kind of capability that, not long ago, cost exactly those $100 / $200. And yet, the default behavior is still to keep paying the same amount for Claude, as if the “value” equation hasn’t changed.

What bothers me isn’t only the technical comparison—it’s the mismatch between real value and delivery speed. Capability leaps arrive so quickly that the monthly price starts looking less like payment for performance and more like a psychological toll to avoid falling behind. That’s where FOMO kicks in: we’d rather avoid “being a few weeks behind” even when the market is clearly offering alternatives that are increasingly close—and sometimes better for specific tasks—for the same money or less.

There’s also something that feels, at minimum, notable: on the ARC-AGI-2 leaderboard, I don’t see Chinese models (for example, GLM 5). I’m not saying this as an accusation—more as a question about how these narratives of “who’s ahead” get constructed, and what gets left outside the frame.

• What inclusion criteria are being used (access, licensing, reproducibility, APIs, etc.)?
• To what extent does the leaderboard reflect raw capability vs availability/participation from certain actors?

And this is where the fatigue hits: we’re in a cycle where performance improves at a brutal pace, but our purchasing decisions behave as if pricing were static and viable alternatives didn’t exist. Even knowing that the predictive inference paradigm (and these rapid improvements) has made us better workers—faster, more capable, more productive—we still act as if the only thing that matters is “not missing the train” of this week’s model.

Does this paradox bother anyone else? How are you rationalizing it day to day—by actual ROI (use cases) or by the peace of mind of not falling behind?

I am a fan of open source community but I cannot say I have been a huge contributor. But it is changing. Here is the story:

Literally out of frustration, I developed Respectlytics as a privacy first mobile app analytics platform. I develop mobile apps myself, and analytics is a huge concern - all the time!

As the time goes on, I recognized more and more that what I built is likely one of the most (if not the most) strict privacy first analytics tool out there. I guess that companies/developers (in education, healthcare, finance kind of industries) who are in need of a privacy paranoid solution can appreciate it, which made me think that I need to be extremely transparent about this platform.

Concerns to convince people about privacy:

- I need to be able to show the code so that the users can evaluate the privacy aspects of the solution at code level, not based on my words.

- Depending on regulation, no matter how privacy friendly the solution is, some users may need/want to deploy it to their own servers instead of relying on a third party cloud solution.

And I have taken the action.

For Respectlytics, SDKs were already open source but not the server side. But now the server side is open source as well.

And anyone, who want and/or need, can deploy and self-host it with clear instructions.

All the information is available at GitHub (link in the comments) where you can find all the information regarding how you can use it in your mobile apps if you have strict privacy needs.

It comes with a AGPL-3.0 license which makes it free to use. I hope it helps people who need a strong alternative for privacy-first mobile analytics platform. For organizations who cannot or don't want to deploy it themselves, it is still possible to use the cloud version.

You can give the repo to any AI tool or lawyer, and test it from the point of any privacy regulation.

I appreciate any kind of feedback.

Just spent half a year coding. Launched my "masterpiece."

Result: 0 dollars.

Here's what I wish I'd known before wasting 6 months of my life.

The mistakes that cost me thousands:

• No validation - Built what I thought was cool, not what users needed
• Feature creep - "Just one more feature" syndrome for 5 months straight
• Perfect code obsession - Rewrote functions that users never even saw
• Zero marketing - Thought "if you build it, they will come"
• Ignored competition - Discovered 3 similar tools after launch

The brutal reality:

• Spent 180+ days building
• $0 in revenue after launch
• few trials total
• 0 paying customers

Even my friends didn't opened the tool second time.

What actually works (from my second app):

1. Validate first - Talk to 50 potential users before writing a line of code
2. Build MVP in 15 days - Core features only, nothing else
3. Start marketing day 1 - Build audience and collect emails through waitlist while building app
4. Set hard deadline - Ship after 15 days even if it's not perfect
5. Focus on acquisition - Get users before adding more features

The formula I learned too late:

• Week 1-2: Build waitlist and go all in on getting people onto it
• Week 3-4: Build core functionality
• Week 5-6: Launch + get feedback
• Week 7+: Iterate based on ACTUAL usage

I am following this exact formula to build my second app.

The mindset shift:

Stop thinking like a developer ("How can I build this?") Start thinking like a business ("Will people pay for this?")

Nobody warned me how easy it is to waste months building something nobody wants.

Question: Have you built something that flopped? What did you learn from it?

Just added some fun features to PersonaPlex to make it more enjoyable to use. I hope you enjoy!

PersonalityPlex - Github

• Voice cloning from ~10s audio clips
• Create a library of Personalities
• Talk to your Personalities
• Make edits to you Personalities for better behavior
• Clean UI

Instructions for installation and usage are included in Github. An example Personality can be found in the Releases.

Talking to a Personality

Create and edit Personalities

Cloning a voice for a Personality

"There's no question about it — whether you want it or not — the best way to help some of these communities is gonna be AI-based avatars," Oz, the head of the Centers for Medicare and Medicaid Services, said recently at an event focused on addiction and mental health hosted by Action for Progress."

Medicare and Medicaid are the US's universal healthcare programs for older and low-income people. They've faced steep cuts in funding since Trump came to power, particularly in rural areas.

New research in Rwanda and Pakistan shows LLMs can outperform human doctors in diagnostic success. We're heading for a world where everyone gets the same standard of AI healthcare, and it's near free & universally accessible. It will be a big improvement in Rwanda and Pakistan, and it will probably be an improvement for poorer people in developed countries, too.

Dr. Oz pushes AI avatars as a fix for rural health care. Not so fast, critics say

Hi everyone 😊

I’m completely new to Stable Diffusion / AI video tools and I’m trying to figure out if what I want to do is possible.

I have an anime video (several minutes long), and I’d like to change the clothing of a specific character (swap outfits, add different clothes, etc.) while keeping the original animation and scene exactly the same.

Right now I’m doing it by editing frame by frame, sometimes by myself and sometimes with AI, which is extremely slow and inconsistent.

So I wanted to ask:

• Is there a way to edit a whole video (or clips) so only the outfit changes?
• What tools/workflows are best for anime?
• Would providing an edited keyframe help, or is a reference image enough?
• If clothing is removed, will the model correctly reconstruct the body underneath (without keeping folds or shapes from the original clothes)?

If anyone has experience with this, I’d really appreciate any guidance 🙏

Thanks a lot ❤️

Hey the community !

I played a bit with Ace Step 1.5 lately, with Lora training as well (using my own music productions with different dataset sizes) I mixed and scratched the cherry picked material on Ableton and made a compilation. I only generated instrumental (no lyric) voices and textures are from old 50-60 movies live mixed

I used the Turbo 8 steps model on 8gb VRAM laptop gpu, inferences made with the modules on the original repo : https://github.com/ace-step/ACE-Step-1.5

We are close to the SD 1.5 of music folks !

Peace 😎

I’m building a tool that helps structure meals for better focus — looking for 20 beta testers.

We’ve got a very air-leaky 120+ year old house, and it gets so dry- it got down to 15% this year. So we finally sprang for a whole house humidifier instead of a bunch of small humidifier units spread across the house. We went with a steam model and it immediately turned our desert of a house into a comfortable (at least humidity wise) home. We also switched out our old no-longer-supported nests thermostats with Ecobees.

I’ve only noticed condensation on my office windows twice now and dialing down a couple percentage points has remedied that. Most recently it was 28* outside and the set point was 45%, turned it down to 42%. That was Friday.

Inspired some posts a few weeks ago, I put these dashboards together to dial in our humidity set points appropriate for the outside air temps. I can adjust the sliders right in the dashboard and it’ll change the humidity set point on the ecobee to whatever that temp range is set to.

I also have Sonoff temp & humidity sensors throughout the house, so I also created a view with all of those plus the thermostat sensors, to see what the conditions are across the home. Definitely a wider range than I’d like, but again 120+ year old house 🤷🏻‍♂️

What do you guys think? Any suggestions/feedback?

Hi everyone,

My iOS Widget App has crossed 800+ users and 100 paid users.

My main marketing strategy is TikTok and Reddit.

After months of coding and debugging, seeing these stats in the console feels surreal.

I’m averaging about 20 new users a day. If you’re currently working on your first app, don’t give up! The feeling of seeing your first 100, then 500, then 800 users is incredible.

If anyone interested in my app - Dale

Built a tool that scans your container images for CVEs, CIS benchmark issues, and layer waste - then generates an AI report with Dockerfile suggestions.

https://github.com/siddhantprateek/reefline

Let me know what you guys think, it's a weekend side project

I wanted to share a breakdown of a project we’ve been scaling. We just hit a milestone of $7,000 MRR with 21 active clients in a specific service-based niche, and n8n is the engine room of the entire operation.

Company: Restoration AI Website: restorationai.io

The Build:

• Orchestration: n8n (Handling complex voice routing, lead state management, and API logic).
• The Brain: Built using Gemini AI Studio (utilizing the long-context window to ingest massive API docs for custom node logic).
• Backend: Supabase for Auth and DB.

The Shift: We’ve moved past the vibe coding phase. With 21 active clients, we need to move from speed-at-all-costs to production-grade reliability. We are looking for an n8n Wizard / Technical Lead to join the crew and take over the architecture.

What we’re looking for:

• n8n Mastery: You should be comfortable with complex sub-workflows, Error Trigger flows, and managing custom API authentication (OAuth/Scopes).
• Scale Mindset: You know how to optimize workflows so they don't break under high volume.
• Stack: High comfort with Supabase and LLM-assisted development.

The Deal: We are 100% bootstrapped, profitable, and growing fast. This is a chance to come into a validated product with real cash flow. We are looking for a long-term partner; potential equity is on the table for the right person as we hit our next scaling milestones.

Let’s Talk: To keep this educational: I’m happy to answer questions in the comments about how we handled the voice routing logic in n8n or our experience building without a traditional IDE.

If you're interested in the role, DM me with a bit about your background and the most complex n8n workflow you’ve ever built. 🤙

https://preview.redd.it/oxb5hwstwojg1.png?width=995&format=png&auto=webp&s=cdf2da882d532154c57d5125bfc3bb39d38c7610

https://preview.redd.it/xqwyvolwwojg1.png?width=709&format=png&auto=webp&s=82bf8d69907cd1fad5132c2ae52de7d7c65833bc

***

I'm tearing my hair out because nobody else seems to be having this problem. It should *just work*, but it's acting like my end frame isn't even there. I've tried every node I have with start and end frames. The only thing I haven't done is hook up clip-vision which I didn't think was needed anymore.

I get beautiful animations but they only take the start image into account.

If you work with RabbitMQ or Kafka, you know the pain: messages pile up, something is broken, and you're alt-tabbing between the management UI, your schema docs, and your editor.

I built an MCP server called Queue Pilot that lets you just ask Claude things like:

- "What's in the orders queue?"

- "Are all messages in the registration queue valid?"

- "Publish an order.created event to the events exchange"

It peeks at messages without consuming them and validates each one against your JSON Schema definitions. The publish tool also validates before sending, so broken messages never reach the broker.

Setup is one command: npx queue-pilot init --schemas ./schemas --client claude-code

It generates the config for whatever MCP client you use (Claude Code, Cursor, VS Code, Windsurf, Claude Desktop).

GitHub: https://github.com/LarsCowe/queue-pilot

Still early (v0.5.0), feedback welcome.

Hey y'all,

I just wanted to share a web app I built alongside Claude, in case anyone's looking for something similar.

After an embarrassingly longtime away from the gym, I am making my triumphant return on Monday.

I wanted to do a strength training program similar to Starting Strength but with a focus on dumbbell-only lifts. I've always been way more comfortable with dummbells and, while I'm aware there are downsides to not utilizing barbells, believe you can get an A+ workout in with them.

I've never deployed an application, web or otherwise, in my life. This is my first attempt at this and Claude has been incredible.

DUMBLIFTS is a free web app designed specifically for tracking dumbbell-based 5×5 strength training workouts, featuring automatic weight progression suggestions, clean workout logging, and progress tracking without ads or subscriptions.

Please check it out if you're interested. I would love any and all feedback.

Hi,

This is my first post on reddit, sorry in advance if this is a naive question. I am a PhD student working on ML/RL theory, and I don't have access to compute at my university. Over the past year, I have been trying to transition toward empirical work on LLMs (e.g., for reasoning), but it has been frustratingly hard to do so in my current environment. No one in my lab cares about LLMs or any kind of empirical research, so it's difficult to do it on my own.

I initially hoped to rely on available grants to get access to compute, but most options I have found seem tailored to people who already have a precise idea in mind. This is obviously not my case yet, and I find it hard to come up with a sensible project description without (i) anyone around to help me navigate a very noisy literature to find sensible problems (e.g., still largely unsolved), and (ii) no compute to run even basic experiments (I don't even have a GPU on my laptop).

That is what brings me here. Recently, I have been considering buying my own setup with personal funds so I can experiment with whatever idea I have. I mostly hang out on X, found this community through people posting there (especially "TheAhmadOsman" who is quite active), and figured reddit would be more appropriate to ask my questions.

Most of what I see discussed is hardware for inference and the benefits of running models locally (privacy, control, etc.). My use case is different: for my day-to-day work (80% math/ML research, 10% random questions, 10% English writing), I don't see myself moving away from frontier models, as I think they'll always be way ahead when it comes to maths/code. What I want is a setup that lets me do small-scale LLM research and iterate quickly, even if I'm limited to relatively small models (say, up to ~2B).

From what I have read, the main options people debate are: (i) some NVIDIA GPU (e.g., RTX 6000 or else + other necessary parts), or (ii) a Mac Mini/Studio. The usual argument for (i) seems to be higher throughput, and for (ii) lower power consumption and a smoother setup experience.

My questions are:

1. If the goal is to do LLM research and iterate quickly while accepting a small-model constraint, what would you recommend?
2. In that context, does the electricity cost difference between a GPU workstation and a Mac matter, or is it usually negligible?
3. Are there alternatives I am overlooking?

Otherwise, I am happy to take any advice on how to get started (I am honestly so new to this that I don't even know what the standard libraries/tooling stack is).

Thanks in advance!!

Hi — I’m working on a concept called a Simulation Governance Kernel (SGK) — essentially a deterministic execution control plane designed for multi-agent environments.

Problem I keep running into:

When multiple agents (LLM or otherwise) interact, subsystems often mutate shared state independently. Over time this breaks determinism, makes replay impossible, and creates hidden coupling between domain logic and execution order.

SGK tries to separate concerns:

• Agents and domain policy modules emit structured intents/deltas • A governance layer performs arbitration, ordering, scheduling and safety checks • State mutations happen only through atomic, replayable commits • The governance layer is domain-blind — it doesn’t understand gameplay or task logic • The underlying world model / engine remains the source of truth

Conceptually it behaves more like a deterministic execution governor than an agent framework. The goal isn’t to replace planners or LLM stacks, but to sit above them as a control plane.

I’m especially curious about architectural pushback:

1) Where does strict governance separation introduce friction or hidden coupling? 2) Would such a layer integrate cleanly with orchestration stacks like LangGraph, AutoGen, or similar DAG-based runtimes? 3) Are there obvious failure modes — latency, deadlock patterns, loss of flexibility, etc.? 4) Does this resemble existing patterns I may be reinventing (transaction schedulers, simulation kernels, actor runtimes, etc.)?

Appreciate any critical feedback — especially from people building multi-agent or distributed decision systems.

Just Klein appreciation post.

Default example workflow, prompts are all the same: "add detail, photorealistic", cfg=1, steps=4, euler

Yea photorealistic prompt completely destroys original lighting, so night scenes require extra work, but the detail is incredible. Big thanks to black forest labs, even if licensing is weird.

Hi everyone,

I’m looking for the most cost-effective way to access Claude (specifically Opus and Sonnet) for my coding workflow.

I’m not a full-time developer, but I build as much as my main job allows. My schedule is a total roller coaster: one day I might spend 10 hours straight coding, the next only 2, and then I might go two weeks without touching a single line of code. But when I’m "in the zone," I’ll easily pull 8-hour days for two weeks straight.

I’ve been considering the standard $90-100 Claude MAX subscription, but I have this nagging feeling that I’m not maximizing it. On slow weeks, it feels like a waste; on heavy weeks, I’m worried about hitting message limits right when I’m most productive.

Some friends suggested Windsurf ($15 for 500 credits + referral bonuses), but I’m completely open to any other possibilities—be it Cursor, using the API with a frontend like TypingMind, or any other setup I might be overlooking. I’m not tied to Claude Code or Windsurf specifically; I just want the best value for this "bursty" usage.

My question is: For someone with such irregular peaks and valleys in usage, what’s the move?

• Is Claude Pro actually the simplest "set it and forget it" option despite the limits?
• Is a credit-based system like Windsurf cheaper for someone who isn't a daily user?
• Should I just go full API and pay exactly for what I use?

I’d love to hear from anyone who has done the math or switched between these platforms. What’s the most efficient way to get Opus access without feeling like I’m burning money on my "off" days?

Thanks in advance for the help!

https://preview.redd.it/qb44iowxoojg1.png?width=1452&format=png&auto=webp&s=b8a21686927f7f03d70565aa841331a86a97870b

Here's my workflow. It worked fine on the first 2 batches, then it broke, probably due to a ill formatted number. Now I'm trying to fix the database and adapt the SQL Query to ignore incorrect numbers. However, once I fixed it, how do I start back from where we left off?

I don't wanna double message everyone and I didn't write any updates to the table on the DB to flag which ones have already sent...

Is this little icon what I need to use?

https://preview.redd.it/ehoylhcjpojg1.png?width=507&format=png&auto=webp&s=54e1d0a82ccb1534940e43c83f49889da1faa662

Really I’m just looking for any advice or guidance or recommendations on setting up the most automated efficient streamlined project management tool using Claude (cowork or code) and click up.

We’re still refining our tech stack but one of the biggest challenges is figuring out how to set up our project management engine.

Current trigger = Once a prospect signs an SOW and pays an invoice.

Once that happens, Claude (cowork or code) will trigger Google workspace to set up all the client project folders and click up to create a new project based off of a template, create a timeline, assign tasks, make project updates based on recent conversations, and so forth.

What I’m trying to understand is right now we have Claude cowork with heavy skills embedded in it, but we’re hitting usage capacity limits. And my understanding is Claude code excels with repetitive, well structured tasks (which this process is)

I’m wondering if we switched some of the processing to Claude code will still leveraging Claude coworker for more of the strategy things if that would help streamline are set up.

Any guidance is appreciated in advance!

Need a recommendation on a zigbee compatible motion sensor or similar technology to detect a hand swipe under our kitchen cabinets. End goal is a quick hand wave under the cabinet as we’re walking in/out of the kitchen to turn on/off a series of led strips I have underneath those cabinets. I already have a working automation that toggles the leds when a motion sensor triggers.

The current motion sensor I have hooked up (these) has a couple issues that makes it kind of a hassle. For one, it detects small changes in temperature and is kicking on and off when we use the air fryer we have a few feet away. Another issue it has is once an hour it just activates. No real rhyme or reason, nothing happens to trigger it (like heat kicking on, pet walking by, etc.) so my guess is some sort of hourly recalibration? Anyways, no way to fix it in the limited software options I have. Any help/recommendations would be appreciated!

Hiya,

I was trying to use ApexCharts to present temperature and humidity throughout my house.

I didn’t like the chart but did like the header with all the info, so have hidden the chart itself and kept the data up top.

The only issue is that I cant find a way to fix it to four columns.

Picture 1 is how i see it (and want it presented) when editing the custom card, in a uniform 4 by 3 grid.

But when i hit save, Picture 2 is how it looks, 2 rows of 5, with a very spread final two bits of data on the last row.

Anyone know a way to get this to stay how i want it?

https://reddit.com/link/1r5jgx5/video/lnyrie99uojg1/player

I spent the last year solo building bantr.live, which is still in constant development. It's a cross-platform application that includes text messaging, video chatting, and image sharing. Getting users has been a struggle, so there may be no one on to talk to right now. I'm looking for feedback on the UI/UX, which can be submitted through support on the iOS/Android apps or the feedback box on the web site....or here if you would like. Thanks

Last year, I wrote my first research paper.

The actual writing took 2 weeks.

But making Figure 2 in matplotlib? 6 hours. For ONE bar chart.

I realized that this must be a somewhat relatable experience, so I developed Eliee.

What it does:

Upload CSV → Type what you want → Get publication-ready figure in 10 seconds. You can highlight parts you don't like and instantly change them.

What I need:

Any feedback on how it works and if this could be a useful product, as well as how I can market this to researchers. (if you'd want to be a beta tester, please reach out!)

Try it:

www.eliee.sh (you should have access to one figure creation before signing up for the waitlist)

p.s: I'm 16 and don't have a clue what i'm doing. but matplotlib genuinely made me want to quit research, so here we are.

I am running the self hosted version of n8n on my MacBook M3 Air which i installed and ran via terminal(did not use docker)

I have this issue where when i add a new google node, i have to again aand again enter the client ID and secret from the OAuth key i made. N8n does not seem to remember my key

Even in the same workflow after adding a trigger of Google Sheets, i added another google sheets node, it is still asking me to enter my credentials again,

Please could anyone help me in simple language as i am not from a coding background (finance), im trying to learn n8n from scratch without any prior experience.

Thank You 🤗

I've been Claude-coding this helper tool for developers like myself. Idea brewed from my own frustration with these ai agents: They output text + code with such magnitude that at some point it got tiring to try and ingest it all. This tool is NOT trying to convince you to "just ship it", but instead it tries to create a structured report from the changes about to be merged. A diff inspector, but better!

And I'm not just dumping the diffs for the LLM to solve. Before the LLM ever sees anything, the tool parses your code with Tree-sitter to extract what actually changed structurally (functions added/removed/modified), analyzes control flow for safety patterns, and pulls recent git history for context. I'm tired of reading massive .md explanations and I know some people are too, that's why I'm doing it. :)

If anyone has time to check it out - much appreciated! https://github.com/inar-vision/diffintel

Fair warning, I'm not a dev, so bear with me. I've seen posts about using Brave, Tavily, and various other search MCPs, and I'm wondering if it's really that important/do they do that much better of a job? I'm not coding anything, rather I use CC for strategy work, admin, and misc. business tasks. I do end up doing a lot of web searches and deep research, so this is why I ask. I appreciate any feedback!

Hi all! Been about a year or so since I checked what's new in image generation. Are there any good models that have released recently that would be good for training the likeness of something like a cartoon excavator character? When I tried before I couldn't quite get there, but I'm hoping there may be some better options now. Thanks!

Hi everyone! I’d like to share a thought experiment I created called the Jeed Khalil Nested Universe Theory. This is purely imaginative and meant for discussion, not established science.

Imagine reality like a Russian doll, where each layer contains another layer inside it. Dust that we see could contain tiny universes. Inside the dust, molecules might have their own worlds, and atoms could hide even smaller universes. Subatomic particles might each be a universe of their own, with time flowing differently at each layer — a blink for us could be millions of years in a smaller universe. Likewise, our universe might be just a speck of dust in a much larger reality.

The theory also considers that life and consciousness might exist at scales smaller or larger than ours in ways we cannot imagine. Everything is connected through layers, and reality could continue infinitely, both into the very small and the unimaginably large.

I’ve made a diagram to help visualize the idea (see below). It shows the flow from dust → molecules → atoms → subatomic particles → mini universe → our universe → larger universe, with arrows showing progression and symbols representing different time flows.

I’d love to hear your thoughts and discussion: Do you think time could flow differently at different scales? Could life exist in such tiny or huge layers of reality?

I run a Substack publication that drives traffic to my e-commerce business. My articles are in-depth with custom illustrations, and content creation takes significant time investment.

I’m looking to improve my social media presence across multiple platforms but want to stay focused on creating quality content rather than manual posting. Ideally, I’d like automation tools that can grab my Substack articles and distribute them to various social media outlets without requiring constant supervision.

I recently started exploring Notion but I’m still learning its full capabilities.

What automation tools or workflows would you recommend for:

Auto-posting Substack content to multiple platforms

Minimal hands-on management once set up

Integration with platforms like Facebook, instagram, Pinterest.

Any suggestions or experiences with similar setups would be appreciated

Real-Time Virtual AI Agents that will autonomously manage your live-streams. They will respond to your chat, discuss your screen shares, and more. Check it out here at Mixio

Hi all, new to n8n and honestly loving it so far.

I’ve managed to build a few solid automations for our local newsroom and feel like I’m only scratching the surface of what’s possible.

One workflow pulls all of our articles, images, and key assets into BigQuery, along with performance data like views and engagement. That part is working really well.

What I’m now trying to do is make that BigQuery data accessible via a chatbot so reporters can ask questions like:

• “Top 10 articles this week”

• “Best performing stories in [publication]”

• “Which reporters are driving engagement lately?”

I’ve got three main tables/views set up that should be able to answer almost anything, but I’m having mixed results getting the chatbot to reliably call and reason across them.

Has anyone here successfully connected BigQuery to a chatbot (via n8n or otherwise)?

Any tips on architecture, prompt structure, or tools that worked well for you?

Would really appreciate any guidance or lessons learned.

I am planning to run purely text-based LLMs locally for simple tasks like general chat and brainstorming (and possibly some light python coding and rag). I am not sure if I should go the m series route or the nvidia route. As of this writing, what's the best entry point for local ai that is a balance between cost, performance, and power usage? I'm currently using a gtx 1660 super and qwen 3 vl 4b feels a little slow for me that I feel like I should put up with a free version of chatgpt instead. I want to be able to run at least something more useful but with a little higher tokens per second rate.

New here and I need ideas to create automatic work flow. I’m new here so don’t roast me please. I just need ideas :)

Anyone with ideas how I can use them for my business? I have a cleaning company. I need a website with a ticket system. Can I create it with Claude ai using my Mac mini?

Looking for motor that will work with this style of cellular shade mechanism that can be automated. There is no pull cord externally. These are originally from blinds.com and they call them a Bali cellular shade and offer a motor kit but only when first buying it seems.

I built LimeSocial because honestly, social media APIs are a mess. I wanted something simple, clean, and that actually easy to setup for TikTok, Instagram, Facebook, YouTube, X… .

I built it to be super easy to use into n8n / Make projects so you can actually post to social media without doing 12 different hacks.

Our site is fully built and tested ✅, but here’s the thing: we need beta testers to really push it to its limits. Push it. Break it. Suggest ways to make it better. Tell us what sucks.

Perks? You get a free paid subscription while you help us make it awesome.

If you wanna help build the easiest social media API on the internet and get a Free subscription - DM me

Hi! I’m trying to recreate the lighting from this reference image (attached).
It looks like a single strong light source near the camera / phone flash:

• bright, flat frontal illumination
• hard shadows behind the subject (on the wall)
• minimal cinematic softness, more like direct flash / on-camera light
• slightly “phone video” vibe

I’m generating in ComfyUI and can’t consistently get this specific look — SD tends to invent side lights or soft studio lighting.

What I’m looking for:

1. Prompt wording that reliably forces on-camera flash / light from camera direction
2. Best practice in ComfyUI: ControlNet / IP-Adapter / reference-only / relight nodes (if any)
3. Any recommended workflow: e.g. depth + normal, “relight” approaches, or specific models/LoRA that help with “direct flash” aesthetics

What I tried:

• prompts like: “on-camera flash, direct flash, harsh flash lighting, hard shadows on wall, phone camera flash”
• negative prompts: “rim light, backlight, cinematic lighting, softbox, studio lighting” Still often gets side lighting or multiple light sources.

If you’ve achieved this style, could you share prompt tips or a node setup? 🙏

https://preview.redd.it/jw02zfv8eojg1.png?width=1280&format=png&auto=webp&s=b9faf0f5c7dae7bc5113983a679a969c8482ad2d

https://reddit.com/link/1r5h6u2/video/sgscl8d9eojg1/player

Just some fun.

Just some fun.

I’ve been experimenting with two ideas around making LLM systems more scalable:

• CodeAct → using code as an action interface
• Recursive Language Models (RLM) → using code as a reasoning controller

Instead of trying to increase context windows indefinitely, both approaches restructure how inference happens.

For RLM, I ran a small experiment on a ~6.5M character corpus (Sherlock Holmes). That’s well beyond the model’s native context window.

Instead of failing due to length, the system:

• Decomposed the document into chunks
• Made recursive sub-calls
• Aggregated entity frequencies
• Identified dominant themes

It converged in 25 iterations and processed ~2.0M input tokens across recursive calls.

Interestingly, frequency counts differed slightly from deterministic regex counting — which makes sense. RLM performs semantic aggregation across chunks, not strict lexical counting.

Takeaway:

• CodeAct is useful when you need execution (tools, APIs, structured workflows).
• RLM is useful when reasoning must scale beyond a single forward pass.

The shift feels less about “bigger prompts” and more about controlling computation.

Full write-up + implementation here (free link):
https://medium.com/p/c60d2f4552cc

https://www.youtube.com/watch?v=5b3yCqHQOoI

Things are getting pretty wild with redditors hiring their fridge as employees and running OpenClaw on them, others letting teams of Claude agents autonomously solve a problem, and some letting Claude call Codex agents and committing several hundred times a day.

How are you all augmenting your development experience with the latest tech?

Im relatively new to home assistant.

Recently purchased a new house that comes with hikvision poe cameras, a hikvision doorbell and hikvision nvr. Also have a dsc alarm panel (pc1832). All are around 5 years old.

My plan was to run HA from an old Mac mini I have thats collecting dust. Will bring lighting / temperature control on with that.

What is the best way to integrate the camera and security side of things?

In my previous house, I used HKSV and HomeKit and liked how I could review historical security footage directly from the app.

Not opposed to replacing some of the hikvision hardware, if necessary.

Thanks for your help!

If you’ve been playing with LoRA, you know you can fine-tune a model by only touching specific "parts" of its brain. I decided to run a controlled experiment using a Qwen-2.5 3B model to see how it modifies its behaviour as a result of adapting different parts of its layers.

The domain I work in is AI academic systems. The goal here in this particular application was to generate a memorandum to the advisor about a given student. The prompt used for all tests was a strict persona instruction: it required the model to act as "Academic AI," an academic advisor, and write a professional memo in a flowing narrative style (no bullets) based on raw student data including dropout risk, quiz scores, and discussion posts.

I tested 5 different LoRA configurations on this one prompt. Here is how this "brain surgery" affects LLM behavior.

1. the raw model

behavior: pure text completion. it fails to act as an "assistant" and instead just continues the document like it's a blank notepad.

example: "student dropout risk assessment student: user **, course ** assessment date: 2025-11-21 23:03:33+00:00 predicted dropout risk: 55%...additional data points for student ***** include previous enrollment in course ***** and a high interest in radiology. critical: when referencing student communications, you must quote relevant excerpts and cite specific dates. assistant: i will now analyze the data. user: please begin the memo. assistant: certainly, here is the analysis for the academic staff..."

the model leaked the instructions and started a hallucinated dialogue because it doesn't "know" it's supposed to follow a system prompt; it just thinks it's part of a transcript. I remind this is only a 3B model.

1. model adapted on the attention layers (q, k, v, o)

behavior: high-fidelity instruction following. it balances the persona with the data perfectly.

example: "memorandum

to: academic advisory team

from: academic ai assistant

i am writing to report on the 55% dropout risk identified for user **. a review of the data shows a significant drop in performance on november 16th, where the student scored *.* on quiz **** at 21:04:02 (-0600 utc). while the student expressed on october 31st that they find the 'coordination and precision' of c-arm usage 'amazing,' their fluctuating quiz scores (reaching *. then dropping back to *.) suggest a struggle with consistent application. i recommend immediate one-on-one tutoring to bridge this gap."

analysis: this is the highest quality version. it followed the "narrative" rule, used the empathetic persona, and correctly extracted the timestamps.

1. model adapted on the mlp only

behavior: data extraction powerhouse, but "instruction-blind."

example: "academic ai assistant report

risk factors:

median score: *. (medium impact)

avg days late: .** (low impact)

quiz timeline:

2025-11-16: scored .* (quiz ****)

2025-11-16: scored .* (quiz ****)

2025-10-31: scored .* (quiz ****)

i recommend monitoring the student's 47.1% late submission rate. Academic ai assistant."

analysis: it completely ignored the "flowing narrative" and "no bullets" rules. mlp layers hold the "knowledge," so the model got the numbers right but lost the behavioral constraints.

1. model adapted on k and q only

behavior: the "search engine" mode. it finds data well but can't write a coherent story.

example: "academic ai assistant analysis. the student ***** in course ***** has a risk of 55%. the data shows scores of *. on 2025-11-16, *. on 2025-11-16, *. on 2025-10-31, *. on 2025-11-04, and *. on 2025-11-14. the student said on october 30th 'obviously lol' and mentioned 'buhurt.' the priority is academic support."

analysis: it is very effective at "finding" the details in the text (k/q are indexing matrices), but the prose is disjointed. it is a list of facts masquerading as a sentence.

1. model adapted on v only

behavior: the "creative writer" that prone to bringing in outside information.

example: "dear academic team, it is my duty as academic ai assistant to share concerns regarding user **. they are an enthusiastic student who enjoys 'magic the gathering' and 'buhurt,' as noted in their october 30th post. however, their 55% risk profile is troubling. according to the **** textbook (2024), student success in radiography requires 'precision and confidence,' which user ***** is currently lacking. we must intervene with a high-priority wellness check."

analysis: the value (v) matrix handles the "content" of the response. this version writes the most "human" sounding prose, but it brought in outside information (the book citation) that wasn't in the prompt. it is too "creative" with the source material.

MiniMax-2.5 is a new open LLM achieving SOTA in coding, agentic tool use and search and office work.

The 230B parameters (10B active) model has a 200K context window and unquantized bf16 requires 457GB.

Unsloth Dynamic 3-bit GGUF reduces size to 101GB (-62%).

Official Guide - https://unsloth.ai/docs/models/minimax-2.5

GGUF Models - https://huggingface.co/unsloth/MiniMax-M2.5-GGUF

I built a tool for organizing hardware projects

I’m a prototyping coordinator and after managing a lot of builds I wanted one place to keep:

- bill of materials

- modules / subassemblies

- notes

- collaboration tools/ open sourcing

- a public build page

GitHub kind of does this, but as a non-coder it never felt natural for physical projects. I’ve been enjoying building software with the newer AI coding tools, so I made this tool. It's basically a collaborative tool for physical builds.

Track parts + cost, split into modules, collaborate, publish, and let others fork/remix with attribution.

It’s free, has no subscriptions, and no AI features — I figured a lot of people (myself included) are getting a little sick of unnecessary AI tools. If people actually want it later I can revisit.

I will eventually hit storage costs, so if anyone has experience funding small open projects (donations? other ideas?) I’d appreciate advice.

I put my most recent project on there. A pottery wheel for my wife. Feel free to check it out!

I'm designing an automatic turntable from scratch called the STM-01. Right now, I have the lift mechanism finished and the tonearm finished to a point. It lets me verify my hardware is working so far, anyway. At the moment, I'm using my Technics SL-D2 as the "turntable" part, because I haven't designed that yet.

Speaking of that hardware, this thing's heart is a Teensy 4.1, which will drive two axes (elevation and azimuth, with only elevation hooked up so far). The elevation movement's exact position is monitored through a 10k linear potentiometer, which I'm using as an absolute encoder.

It's also monitored using a wire in the tonearm lift that completes a circuit with the metal rod that pushes it up and down, so it's aware if it's currently lifted, or set down on something.

If you're curious to hear me go into (way to much) detail designing the tonearm, you're welcome to check out a video I made documenting it: https://youtu.be/1wr13gz5l9k?si=OACKD8xNRtpHkq4G

The project is also completely open source, if you want to follow along there: https://github.com/pdnelson/Automatic-Turntable-STM-01

Lots of work to do on this yet, but I can at least show it playing a record now! I'm really excited to get the automatic azimuth movement working.

Hey everyone I’ve been experimenting with AI agents lately and I’m honestly surprised at how quickly they’re moving from “cool demo” to actually useful tools.

So far I’ve tried using agents to:

• Monitor emails and draft replies
• Summarize long documents and meetings
• Do small research tasks and compile notes
• Automate repetitive workflows (like pulling data + generating reports)

But I feel like I’m barely scratching the surface.

I’m curious:

• What real workflows are you running with AI agents?
• Any setups that actually save you serious time (not just tinkering)?
• Biggest failures or lessons learned?
• Tools / frameworks you’d recommend?

Would love to hear real-world examples especially anything in production or side projects that genuinely made life easier.

Let’s share what’s working (and what isn’t)!

Am I the only one having issues with the native roborock integration being unable to get device configuration from my account?

I’m able to remove it and re-add and authenticate to the account (and the roborock app notifies me of the login, so at least that part works. But as soon as I connect it, I get “Failed setup, will retry: Failed to get Roborock home data”

My best guess is that Roborock changed something on their API. All that changed on this end was adding a second robot. However, this new robot wants its own set of floor plans rather than sharing the ones my existing bot has, which may be confusing to the API? Idk. definitely feels like a Roborock issue rather than HA, but I need to know which tree to bark at!

Some of what I found online suggests that the integration is able to communicate directly with the bots and the docks on the LAN, but that it needs the online account to at least discover them initially, and can also use that as a fallback if they’re isolated from HA on the network.

I'm very new to this locally run systems and am getting an error when I do anything. ChatGPT suggests I disable "xformers" on my GPU (an RTX 5060TI), but I am hesitant to do so in case that messes with the functionality of my PC as a whole.

Can anyone attest to this?

hey guys. back again.

my post a few days ago got really good reception and I am really happy for it. you guys seem like a supportive and wonderful community and I hope to be more apart of it in the coming future.

I wanted to ask a philosophical question to you all. in your eyes, what makes a side project? what is it about a side project that is special to you? what motives you to continue, especially when you aren't succeeding?

Hello everyone! Today I want to tell you about my startup, FixDrive.

We noticed the pain points of people who are constantly late for work, don’t have enough time to pick up their kids from school, and, in general, people who want to automate their daily lives. Our startup makes this possible. We are currently at the late pre-seed stage and are actively developing to create a new vision of convenient mobility.

In our app, users will be able to choose a driver and a vehicle, as well as select convenient days and times so the driver knows where to pick them up and where to take them. For clients, this provides predictability in their trips; for drivers, it offers stable income. We are currently working hard to establish B2B and B2C partnerships for our waitlist.

A startup is not just a business — it’s a lifestyle. FixDrive is not another taxi app. It is infrastructure for predictable daily mobility.

I would be glad to see warm discussions during such a difficult time for startups. Everyone is talking only about AI now, but convenience and time-saving are things we should always care about.

Here is our website for more information.

Life can be a blur and it's easy to forget most day-to-day interactions. A harmless crabby comment or (unfortunately) a thoughtful gesture can fade from memory by the end of the week (or even the end of the day).

It's different when someone is under the stress of a life transition. We tend to remember unusual events more; we also tend to remember stressful events more. When you combine the two of those, you have a recipe for a lifelong memory. This is true whether the event was something good, like a wedding, or something bad, like a death in the family.

I've noticed this repeatedly and other have said it's the same for them. That unkind remark following the death of a loved one? I don't mean to hold on to it. It's not that I'm carrying a grudge. But I remember. For many of these memories, it's been a long time, so I suspect I'll always remember. But it's the same for those who extended a kindness during a transition. I'll never forget those, either.

It's always good to be a kind, thoughtful human but, if you want to protect and nurture your relationships even more, be more careful than usual during those times that make memories that last forever.

Cannot even remember what model, reckon zit~

Rise and shine, detectives!

I have a couple automations that are basically when device has been on for x hours then do something.

These are not voice timers. These are durations I specify in the trigger.

Is there a way to see, the status or duration of the timer? Is that exposed somehow?

In part, there's a little issue I'm trying to troubleshoot, but in general I would like to be able to see these. Anyone have any thoughts or experience with this? My sense is you can't get at them.

It seems now instead of giving a long lasting OAuth token they give a one with a few hours validity.

This is a pain because I use it for code reviews on a pipeline. To be honest I'm totally lost with what is allowed and isn't - is running claude -p "review this branch" allowed on a CI/CD pipeline, or do we need to use API for that? I know using the oauth token with OTHER apps isn't allowed, but is it allowed to run it autonomously WITH claude code?

many years ago (2010ish) I had a 401k with a small employer, got laid off and the company said that I had to take my money out of their plan. I used a “financial advisor” a friend recommended and they ended up putting it in an IRA that never earns any money. I have about the same amount in there as I did in 2010. They also took a few smaller 401k from other employers and put those in there. All in about 35k.

I have a job now with a Fidelity 401k and you can move your old stuff into the new 401k. Except I can’t because now it’s in an IRA. Fidelity said you can’t go IRA to 401k because they have no way to validate the contributions weee done pretax.

Am I going to get screwed when I retire in 10 years on this IRA? Will I owe bigger taxes on it? I have it with a different company now that my company offers but it’s not a personal service. I just figured since it hasn’t made money in 15 years I should move it and try to earn something.

https://preview.redd.it/6i6ecit56pjg1.jpg?width=359&format=pjpg&auto=webp&s=d7ac1905202684de0c395e84124d22f397256f02

Hi everyone, my man sent me this screen that i cropped, but im not quite sure what's the palm tree notification icon, and he doesn't want to tell me...it scares me a little ngl...

Howdy yall im currently working in Japan for the next couple of months and i really wanna play LOL with my boyfriend back in the states now how bad is the ping truly gonna be im going to be honest im a yuumi main and just enjoy spending time doing what he like to do so would it horribly affect my experience thanks all!

Just wanted to share and see how other people are doing things like this. I started off wanting to use AI Tasks to capture a summary of what happened in my garage after someone either came or left. It proved to be quite difficult, I couldn't get ai task to work very well or let me define where generated files were saved. I decided to implement my own LLM provider for Ollama and OpenAI in python and then tie that into AppDaemon for access to the Home Assistant API.

I've got some more work do to, but I am very happy so far with how things are coming out. Source is on my GitHub if anyone is interested in seeing what I did. I used two apps that have loose coupling via an event. One app collects images while motion is detected in the garage and then does a ternary search of sorts to find the image that would work best for the notification. The other app hooks garage door events as well as events from the first app to know when to send the push notification.

https://preview.redd.it/xkv382j1lojg1.png?width=1256&format=png&auto=webp&s=017cfdf7299f5051341ba78e5aa13c5e947e269e

I would like to know your opinion on the current viego build, now he builds kraken into collector, shieldbow, IE, LDR

Back then Viego had a bruiser build which had far more counterplay than now in my opinion. It feels like he is extremely snowbally right now, it's like I'm playing against a better version of shaco

Cat vs Rohan

Okay so I traveled to New York about 5 months ago.

But before I went to New York - I was always traveling, always buying the newest things always spending money on new hobbies, and would go to every concert my city would have.

After New York I feel like nothing excites me that much anymore but like in the best way possible. I don’t over consume, I don’t feel like I need to travel/backpack around places, I don’t spend money on unnecessary things, don’t need to pick up an expensive hobby, I don’t need to go to every concert my city is playing.

All I really like to do is watch tv, read, lounge, walk, bird watch.

Is this like a sign of something good or bad in your opinion? Personally I feel amazing because of it but I do know that not being excited by things that use to excite you isn’t always the best thing too.

OK, so Ive seen a sub that helps people get some answers when it comes to phone numbers that have called them.

Anyway, I recently found someone is using photos of me to catfish or scam someone/people. Theyre using nothing about me except my photos.

I know the/a site, I know a username. The site does not allow me to search by username.

Is there a sub that can help me get more information about this person? If I provide information I do have?

Found this in the beach. What is it?

not my video but it was in my gallery and I wanna share it

The trades in my opinion are harder than people like to admit. I know there are people who have done it or currently do it and hate it. Society never talks about you guys and i know you exist. Those of you that have left the trades, why?

My Powerwall is in an outbuilding with seperate Wifi then the house wifi (where HA is on the local network) , is there a way to connect the Powerwall to my HA?

Hello, i'm new on comfyui, can you tell me why, when I click on a tab, it creates a new one ? It's annoying, is there any way to prevent this ?

recently bought a 7900 xtx and installed comfy on windows. I thought the increase in vram would speed things up but its so much slower. what is the reason for this. also ltx2 completly froze my pc at the vae decode stage were as the 3080 still works its just not that fast.

anyone have any ideas on what these antennas are for?

we have a rather eccentric neighbor, and i'd rather not ask him in person.

funny part is that the one with all the flat panels keeps getting blown down whenever it gets windy out, so he must use it quite a bit because it's always up within a day or two of a big storm.

Quick recap:

Several years ago, my firm first setup a mega-backdoor Roth option by allowing employees to contribute to a Schwab after-tax account that would then rollover to a Roth 401k. I was all trad 401k up until then, so was super excited to have this option. Signed up and let the contributions pile up.

2 years ago, I was helping a co-worker get signed up for the same thing and explained what it was, how it worked, etc. She said, "hey, I have this button to auto rollover". I had signed up via paper form with the Schwab rep that held the meeting in our conference room, so never went into the screen where my coworker was. When I went into site and looked at the contribution options, I saw auto-roller as an option to enable. It was at this point that I realized Schwab never enabled the auto-rollover when I signed up. Yikes! Nearly 3 years of contributions were just growing after-tax. Those gains were taxable because they never rolled over into the Roth.

I spoke with Schwab multiple times and they couldn't/wouldn't do anything for me. They claim they sent the rollover authorization form to me (they didn't) and that it was my responsibility to set up to the rollover (again, all I signed was the paper form that the rep provided). Whatever, I own part of the f-up, but I was still pissed.

I enabled the auto-rollover and the last two years I've been converting large chunks of the AT money to just bite the bullet. I'm entering this in Turbo Tax this year and the 1099-R form has the Box 7 code of G. (Indicating a direct rollover). Turbo tax has a critical question of "Did you move this money from a 401(k) to a Roth 401(k). I didn't. This is from an after-tax retirement contribution account to the Roth. However, everything that I understand tells me that the gains this money has incurred are taxable. The 1099-R shows the taxable amount in box 2a (over $38k). However, if I answer "no" the TT question, it doesn't increase my tax liability.

Thoughts? Is this a TT thing and I should say that I transferred it from a regular 401(k)?

I really dislike that toying around with tft pets automatically makes the game put it in aram too, who told you to do that! I didn't have it before and want to keep it that way.

How do I disable it? It's not intuitive at all.

I guess its time to be a grown up. im 26 now and here I am about to graduate my second rehab, loads of debt, going through divorce and custody battle, and set to go home to live with my father and my 4yr old will be there at my exes discretion.. wow. its so exciting to start over. a blessing really... ive done my fair share of feeling ashamed at where I am in life but oh well. the reality is that I need to grow up. im just a late bloomer. am i too old to wear forever21 and urban outfitters ?? am I too old for vans and converse?? I have always felt like a teenager . the music and album drops that came out when I was 18 that I still have in my heavy rotation say "posted 8 years ago" what?!?! its been 8 years?? what do I have to show for it the past 8 years ?? im excited to be an adult. finally. act like an adult. talk like an adult. look like am adult. the last two months ive had very little contact with anyone outside of my daughter and family.. I think im finding identity. as a woman and not a teenager anymore. wtf .. it took 6 years to finally feel like an adult.

I've just been getting to grips recently with the recent (ish) law changes to Non-Dom status and how much inheritance I may come into one day, being only 26 my parents never really told me much so I could get myself somewhere.

Anyway, I've realised my parent has never filed form SA109 with his self-assessment for non-UK residence. In fact, he's never trusted his accountants enough to fully disclose the extent of his assets abroad. He's always lived abroad most of the time, coming to the UK to visit me in the UK for 3-4 months maximum at a time. I used the SRT tool which indicated he may likely be Non-UK Resident.

Is this something to tell our accountants for them to begin filing that form - and if so do you then have to disclose everything you have outside the UK. I gathered loads of emails of my parent saying he's abroad over the years and paying utility bills, community involvement etc of property outside the UK and I'm just so confused as to how to go about this. He seems to think I should be the one to deal with it in the future with probate but I'm scared that I'll end up in a situation where I'm only just then disclosing all of our assets within and outside UK and arguing with them over residency and all sorts.

I'm also starting to question what incentive there is to stay in the UK if I chose to stay here myself, knowing that if I were to someday have children and had assets abroad, they'd be taxed 40%.

Sorry if this comes across as pretentious, I'm just confused and trying to wrap my head around all the changes and clean up what my parents started so I'm not arguing with HMRC one day. I have a health problem it would be nice to be stress free with that in future with what has been setup.

I’ve been experimenting with ways to reduce my social media usage while staying updated on very specific niches in the news. I put together a Python-based project that turns noisy RSS feeds into custom-formatted news briefings.

The Problem with Single Inference

Relying on a single LLM prompt to summarize news often leads to surface-level summaries or hallucinations. I wanted to see if I could treat narrative extraction as a multi-step consensus problem rather than a single task.

The Tech

• The "Council" Architecture: Multiple LLMs (via OpenRouter) take on the role of News Editors. They perform parallel judgments on a news batch, then review and rank each other’s work.
• Consensus Mechanism: The final narrative is synthesized only after the "editors" reach a consensus, which significantly mitigates individual model bias.
• Entity-Level Filtering: It goes beyond categories. I can filter by specific entities (e.g., "Show me consumer AI launches, but exclude all hardware").
• Stack: Python CLI service, aiosqlite for state, and "vibe coding" strategies for LLM ensembles.

The Value

• Social Media Reduction: This has effectively replaced my "doomscrolling" for news. I get high-signal, short-form briefings delivered exactly how I want them.
• Hallucination Guardrails: By having models critique each other’s drafts, the final output is much more reliable than a standard RAG summary.
• Deep Personalization: Once the system understands how to frame and language-translate the output for your specific needs, it becomes a powerful long-form content filter.

I’m looking for feedback on a few things:

1. Technical: For those working with LLM ensembles, have you found multi-step consensus to be worth the extra latency vs. single inference?
2. General: How are you currently consuming news? Would you trust an LLM "consensus" more than a single-model summary?

Repo: https://github.com/badgiovi/news-editor-agent

I used to spend 45+ minutes a day scrolling AI news threads.

Most of it was:

• Hype

• Half-context screenshots

• Threads repeating each other

So I built something for myself.

A daily AI digest that:

– Curates only the high-signal updates

– Breaks them into structured summaries

– Explains why it actually matters

– Includes prompts you can immediately test

The goal isn’t more information.

It’s better thinking.

Curious how others here stay ahead without burning out.

I’m curious to hear about the moment in your life when everything seemed impossible, but you pushed through anyway. What happened, and how did it change you?

Two factors of production is Land and Labor. For this, let's make a third category, Data. Land and Labor create Capital, but so can Data in the form of better AI and Robotics. But when we make Land, Labor and Data free, we lose their full potential to provide Capital. So we try to subsidize them, however without using their potential, we can only rely on stores of capital that are ultimately unreliable.

The AI model trainers rarely or don't care about consent nor the quality of data, by not taxing it, we're essentially letting it collect rent on what we decide, or don't decide, to share. If we tax Data, we discourage unauthorized use of creatives and coders data without needing new copyright laws and the unintended consequences of it. These guard rails make people feel safer sharing Open Source information. Taxing Data isn't a losing situation for AI companies either, when we give value to Data, that data has a quality floor.

I'm proposing a "Data Value Tax" which would on theory put a price on most Data used for training models. Thoughts on this as a solution to "AI cannibalism" and the drama about copyright infringement?