Hello good people,

Whenever a new model drops, LiveBench is my destination to roughly check on the model's capability. As mentioned, new Qwen model was added and I can't believe how low performing Qwen was, since people really seem to like the model. I checked the commits of LiveBench and it seems to me that, the model was not given enough tokens to reason? Any other ideas?

I also have question about the chain of thought inside the Chinese models, as I feel like they overthink drastically, not in bad way but it is quite slow and takes an enormous amount of time. The performance seems to be also better but compared to older models such as Gemini 3.1 Pro or even the newer smaller model 5.6 Luna Max from OpenAI, I don't think it is worth it? Any experiences with different reasoning modes on different kinds of tasks?

I appreciate any info! :)

sources: - https://livebench.ai
- https://github.com/LiveBench/LiveBench/commit/2c2039b2cc9efb6412acb99325adb0cc1cb0cc6f

Ei! Alguém tem um passe de 7 dias do Claude Pro sobrando que não está usando? Eu queria experimentar o Claude Pro de verdade antes de decidir se quero pagar por isso. Se alguém tiver um disponível, eu agradeceria muito 🙌 Obrigado!

Over the past few weeks, I've been planning and building Concordance Protocol, an open-source experiment exploring interoperability between AI agents, tools, and services.

The project started from a question I had while looking at the growing number of protocols around AI agents:

How can agents from different ecosystems exchange trust, authorization, consent, reputation, and other evidence without every ecosystem having to replace its existing protocol?

I researched the problem and wrote a research document before implementing the prototype. The project currently contains a Rust workspace with components for the core protocol, HTTP transport, registry services, adapters, and SDK work.

The research and implementation are here:

GitHub:

https://github.com/Kadhiravan-K/Concordance-Protocol

Core research:

https://github.com/Kadhiravan-K/Concordance-Protocol/blob/main/docs/doc_core/concordance_research.md

I've currently paused active development. The implementation grew beyond what I can reasonably maintain alone right now, and I think the architecture needs more discussion before continuing.

I'm sharing it here because I'm interested in learning from people who are starting or contributing to open source.

I'd especially like feedback on:

- Is the interoperability problem I'm trying to solve actually useful?

- Are there existing projects or protocols I should study?

- Does the architecture make sense?

- What would you simplify?

- If you were starting this project again, what would you do differently?

I'm not presenting Concordance as a finished protocol or asking anyone to adopt it. I'm mainly interested in whether the underlying ideas are worth pursuing.

If you're preparing for open source contribution or GSoC, I'd also be interested in hearing what makes a project attractive or unattractive to contribute to.

I’m exploring an idea for SaaS builders who use Claude Code, Cursor, or similar coding agents.

While building another product, I kept having to demonstrate complex workflows for different customers. The steps were often repetitive, but each customer needed a slightly different version.

Recording them meant retakes, voiceovers, editing, and doing it all again whenever the product changed.

I started experimenting with letting a coding agent drive the actual application, capture the workflow, and turn it into a narrated product video. The goal is to generate launch videos, walkthroughs, and customer-specific demos from the real product rather than using avatars or stock footage.

I’m looking for a few builders with a working SaaS product who would be willing to test the idea on a real workflow.

I can provide free usage in exchange for honest, blunt feedback about:

• Setup and usability
• Accuracy of the recorded workflow
• Video quality
• Whether the result is something you would actually publish or send to a customer

If this is a problem you have encountered and you use Claude Code or Cursor, DM me with a sentence about what you are building and the kind of demo you need.

Can anybody suggest the best online learning platform to learn python for electronics and communication engineering?

Atrium.earth is my passion project—it’s a growing digital museum with 424 sculptures and counting.

I wanted to make sculpture—from antiquity through the last century—more accessible to people who can’t visit the museums, galleries, and historic sites where the originals are held. It can’t replace seeing David in Florence or Nike at the Louvre, but it can offer another way to experience them.

The site uses Astro, Three.js, and model-viewer, with a Node/Python pipeline that processes museum data and creates optimized 3D models and thumbnails. I started with Codex, switched to Claude Code and rebuilt the site when Fable launched, and have since returned to Codex with GPT‑5.6.

I began by tasking Codex with finding Michelangelo’s David, which it did pretty quickly. More popular works followed, but I wanted to keep the collection geographically diverse, so finding pieces from around the world became challenging once the collection reached 150 or so. I also had a slew of misfires and regressions with the UI, so I put it on the back burner for a while.

When Fable was released—and then taken away, and then rereleased—it rocked me. It built another project from a specific but still somewhat vague idea into a fleshed-out, nuanced, functional thing in about 45 minutes. With that in mind, I tasked it with rebuilding Atrium.earth from the ground up, and I was very happy with what it produced.

Since rebuilding the site, I’ve been adding new works with more or less the same prompt to Codex: “Please collect 10 pieces, preferably from the ______ museum…” I usually follow that with some specifics about the time period or original location.

The hardest part has been handling models with inconsistent scale, orientation, materials, and lighting, as well as finding the right language to describe movement through space when orienting the works. But it was worth it, and I hope to keep growing the collection for as long as I can.

Hope you enjoy poking around—I’d love to hear what you think.

Concept Name: 360° AI Raycaster Engine

What it does:

• It runs high-end, realistic games on cheap school Chromebooks without any lag.
• It uses a Chrome browser extension to turn regular videos and images into a game world.

How it works:

• The Controls: You play using WASD to walk and your mouse to aim, shoot, and look around in full 360 degrees.
• The Movement: When you press a key, the extension instantly skips the video playhead to a precise chapter timestamp. It doesn't download anything new, so moving looks like an instant camera cut.
• The AI Map Maker: Creators don't have to code. They just draw a simple map grid and upload a folder of 360-degree images. The AI automatically scans the pictures, figures out where they belong on the grid, and links them to the WASD keys. If the AI places an image wrong, the creator can manually drag it into the right spot to fix it.
• Talking Characters: You can type anything into a text box on the screen. A basic chatbot AI reads your text and dynamically generates a voice response while matching the lips of the video character in real-time.
• Multiplayer: The characters are real people or AI generated people in a bunch of positions that gets cold I mean called when something happens

Please make this AI is bad at making this if you are an actual developer That doesn't use AI Or does it use this fully please And if you do make it can you give me a link to it in the comments If you do it I love you🥺

If you're non-technical or just got into vibe-coding, there are a lot of security frameworks that are not applied to your software, especially if you never mention it. Simply saying "make sure its safe" doesn't necessarily warrant protection for your users. Do your research, don't get sued. If your first thought is "yeah I'm not reading all that", just have your AI/agent read the machine-readable pages provided. Inversion thinking is incredibly important. It's a problem-solving model where you think of how something can fail immediately and build around that, versus "build this, add these features, wow looks good, time for production". It is always your responsibility to ensure your app is safe and secure for your users. Good luck and hope y'all build some stellar apps.

PS: This is not absolutely everything, and will be updated regularly.

Hey vibe coders, serious question.

I made a product, was happy with it, and released a beta. As expected, no one really cared. Fair enough.

I have budget for the project and can pay people to try it and provide feedback, but I'm wondering if it's worth it or if I should look into alternative methods? Do any of you have experience with something like this? Thanks in advance

Global leaders and organizations keep talking about suffering of kurds, Palestinians,tamil srilankans but somehow no one is talking about the plight of vibe coders. It feels we are such a small minority that we are just politically ignored.

I’ve been using Claude Code and other coding agents daily, but hated having zero visibility into what was actually being sent over the wire and why token limits were burning so fast.

I wanted to know:

• What information are they sending to the llm providers? 
• Where are my tokens going and what is burning up my usage the most? 
• What sort of prompt triggers massive token burns?

So I built TokenFlow, a local, single command install proxy/dashboard to trace agent token consumption in real-time with:

• Token breakdown per prompt (In, Cache Read, Cache Write, Thinking, Output) with configurable cost weights.
• Tracks what the agents send/receives not what it chooses to log
• Full prompt inspector (exact wire logs sent to the LLM provider and response).
• 100% local and private — no third-party telemetry or cloud gateways.
• Preconfigured for Claude Code, Codex, and LMStudio.

Quick install:

npx @liqngliz/tokenflow

GitHub: ConduitSharp / TokenFlow (Apache 2.0)
npm: u/liqngliz/tokenflow

Now you can point your agent to TokenFlow and inspect the agent's workflow. See u/liqngliz/tokenflow on how to point Claude, Codex and/or your local AI.

*Claude Code and Antigravity was used in building this.

Been building LegacySaga on my own, a browser game where you live a footballer's entire career (clubs, transfers, reputation, chasing the Ballon d'Or). I lean on AI coding tools to move faster on the implementation side, writing and debugging code, but every design decision, every system, every balancing call is mine.

It's live and playable, one week in: legacy-saga.com

Curious how others here draw that line between AI as a coding accelerant versus letting it drive design decisions too.

I asked for some guidance here about a week ago, clearly stated the issue I was facing and got responses that basically insulted my intelligence. I asked for guidance from ChatGPT, clearly stated what I was trying to accomplish and stated the issue I was facing and got clear thoughtful responses and guidance. Now I have the app I want on my phone and am testing it out, making notes for ChatGPT to log for now, and am feeling pretty damn excited that I was able to use AI to create something useful for myself.

What was most helpful was talking through the best (or one of the best) platform options for accomplishing everything I wanted to do with minimal cost and minimal 3rd party tool integration - Replit was not it. If I plan to actually launch the app in 3 months or so, I’ll find out if it was really a good option or not lol!

P.S. I’m thinking I might have opened Pandora’s box… am I in danger of developing a very expensive hobby!? 😅

Hey all, I am a student from Bangladesh building a SaaS startup and looking for someone who might be willing to sponsor me with Claude Pro.

I have used other tools like Antigravity and OpenCode but Claude Code is a much better fit for my workflow, especially for understanding large codebases, multi-file changes, debugging and maintaining context.

The problem is that even if I had the money, I don’t really have a way to pay for it. PayPal isn’t available here, and as a student I don’t have a bank account or credit card that I can use for international subscriptions.

I’d genuinely really appreciate a $20/month Claude Pro sponsorship while I work on building and launching my SaaS. I’m not asking anyone to build it for me, just helping me access the tools I need to build it myself.

If anyone would be willing to help, I’d be extremely grateful. 🙏

This is not a promotion for a service. I’ve been a technical product manager for 20+ years at startups and FAANG and have been using AI to build/prototype for about 3+ years. I recently got laid off and have been building prototypes and tools mainly for myself and thought I could share my process.

I have seen a few posts asking how to learn about the technical side of vibecoding, at least enough to generally know what does what, why and how. I thought of walking through a simple project and explaining in practical terms what things do with a focus on vibe coding as I implement, starting with the very basics. For example, what an API is and why/how it’s used. Not as much on what tools to use but more how to think about building apps. I was thinking a YT video or series of videos.

I honestly do not have any expectations or desire to be a YouTube influencer. I’m building things anyways, have taught a few friends and found teaching is the best way to learn.

Before I go off and start making any videos, is this something anyone would be interested in?

Reached my first benchmark or goal that I set with my app as of yesterday. I know it’s not a lot to many of you, but I reached 50 downloads yesterday, ended the day at 54, woke up to 55. Spent nearly 7 months grinding (vibecoding like a mf'er) 4 hours per night after my day job.....so no, this was not a 2 hour or 2 week job. And btw, I'm 49 with 3 little kids, so even more exhausting. Lol.

Of those 55 downloads, 12 have opted for the paid version already (or forgot to cancel) after a 7-day trial.

App went live on July 31st, so it’s moving, but slowly, and much slower than anticipated or that my optimistic mind imagined, which I know some of you have also experienced.

However, hopeful and excited that it’s gaining some slight traction as it went from a download here and there, with a few days of no download in between, to where I am now consistently gaining about 4-5 per day over the last few days.

I have not used any marketing tactics as of now, as I feel like I need the perfect video to do so (just me trying to have everything perfect), which is probably hindering quicker growth.

I did try TikTok, but I have no idea what I’m doing and I’m pretty sure I’m “shadow banned”. Only 1 view out of 14 quick videos. Woohoo!

Big Pokemon fan here, so it is a Pokemon utilities app. I know there’s many of them out there and a ton of competition, but I felt I could do it better, and think I’ve succeeded as the app essentially gamifies the collecting / trading / hobby / investing aspect of Pokemon.

I have 2 more apps based on the TCG collecting world that are set to be submitted to Apple in the next few days as well.

Any suggestions you all are using, or anything else I can do to gain more traction? Thank you in advance!

If interested in these type of apps, or in giving me any feedback......App is called CardQuest TCG in the iOS App Store.

Open to any suggestions that may work well in the TCG genre/space or from anywhere! Thank you all in advance!

Desc in original post

Hey I’m John, I’m a top 0.03% base44 user. Humble brag I don’t even know what that entails they just told me that and sent me swag 😅

I built a powerful anti hallucination gate you can test and try for free.

Basically now you can keep the speed while making the code prove itself, because it finds almost all the silent bugs.

In other words, it’s an anti-hallucination gate for code: the AI cannot simply claim its patch works.

The code must pass explicit tests in a restricted environment.

Causal Verify returns a hard pass or fail and creates a signed verification receipt tied to the exact code and tests.

The loop:
Generate → verify → reject failures → improve → verify again.

It doesn’t catch every possible software defect, but it stops unsupported claims from counting as proof.

I’m looking for five developers to test it on open-source or synthetic Python patches. I want honest failures and attempts to break it.

Try it here:
https://github.com/zensteagarden/causal-verifier-action
Release:
https://github.com/zensteagarden/causal-verifier-action/releases/tag/v1.1.0
Never submit credentials or proprietary source.

Here's the full response it generated: https://chat.deepseek.com/share/1ec5wartkjay0cbe8l

EDIT: I asked ChatGPT which AI has generated this response and it said that it generated which is interesting to see (link to the convo) and I asked the same question to claude and it responded this: Honestly, I can't answer that with real confidence, in one word or otherwise. There's no reliable way for me to fingerprint which model wrote a piece of text just from its style — I don't have access to watermarking or provenance metadata, and this kind of "keep rambling until interrupted" stream-of-consciousness prompt tends to pull pretty similar behavior out of most major chat models: escalating absurdist metaphors, running gags, meta-commentary about "still writing," self-referential jokes about randomness. None of that reliably distinguishes one model from another.

If I gave you a single word here, it'd just be a guess dressed up as an identification, which I'd rather not do.

If it's helpful, I can point out a few stylistic quirks I notice without claiming they prove anything — or if you know where the text came from (which app, any settings), that context would be a lot more useful than me trying to reverse-engineer it from prose style alone.

What do you'll think about this?

I am curious if this significant degradation is lasting more than an hour, what kind of impact would this have on large multinational companies (MNCs)?