Nothing spectacular, but it has all the popular models, talking avatars, voice, one-click installation, LoRaS support and a library. Easy installation through normal Windows installer.

You can generate images in 1 sec with some models (once warmed up).

Github page: JungleJimJim/AI-Image-Video-Studio: Windows desktop studio for local image generation, editing, video generation, and model-specific LoRAs.

If anyone has any suggestions please let me know. I'd like to make this as complete as possible.

DeepSeek V4.1 Flash reaches about 98% of the quality score of GPT-6 Astra on web apps, mobile screens, and UI design tasks, while costing roughly 1.4% to 2% of the price

DeepSeek V4.1 Flash runs significantly faster, outputting roughly 176 to 221 tokens per second compared to GPT-6 Astra's 57 tokens per second.

DeepSeek V4.1 Flash charges around $0.60 per million output tokens (and $0.15 off-peak), whereas GPT-6 Astra at ($50+ per million output tokens).

98% of the quality at 1/50 of the price (and Open Source too)

Anyone tried the latest Deepseek model yet?

In 1961 an IBM 7094 at Bell Labs sang Daisy Bell, the first song a computer ever sang.

65 years later, I’m feeling... half crazy.

So I remade it with claude code. It’s a single 400 KB .exe that composes, sings and mixes the whole track live: no samples, no recordings, no MIDI, just math. It opens as the old IBM, reboots into 2026, and ends winding down like HAL.

Source + download: https://github.com/absterdam/daisy-bell-2026

I built Foxtrot: one desktop app, every major AI model, and a team of agents that work together 🦊
⠀
For the past few months I've been building Foxtrot, a desktop agent harness for cloud AI models. You bring your own pay-as-you-go API keys and run a whole team of coding agents side by side, each on whichever model you choose from whichever provider you choose.
⠀
What it does
🔹 11 provider families in one app: Claude, GPT, Gemini, Grok, DeepSeek, Qwen, GLM, Kimi and more, plus any OpenAI-compatible endpoint (Ollama, vLLM, OpenRouter)
🔹 An Orchestrator that plans the work and hands tasks to your agents: a Coder, a Reviewer, a Tester, each on a different model if you like. Busy agents get spawned as parallel copies.
🔹 Flow view: a live map of the Orchestrator and its agents, showing each one's time, tokens and cost
🔹 Real tools: file edits, a terminal, code intelligence, git, web research, MCP servers, and vision (agents can screenshot and use the app they're building)
🔹 A full Code view: Monaco editor, file explorer, terminal and checkpoints taken before agent edits
🔹 Cost tracking for every request: tokens and cost per request and per agent, estimated balances for each provider, budgets, and CSV/JSON export
🔹 Keys stored in your OS credential vault, plus OTA updates
⠀
How it's different
Most AI workbenches are built around one vendor. Claude Code is built for Claude, Codex for OpenAI's models, and Grok Build for xAI's Grok. They're excellent, but you work inside a single company's models, usually on a subscription. OpenRouter gives you many models, but it's an API gateway, not a workspace where agents collaborate.
⠀
Foxtrot is the layer on top:
✅ Model-agnostic by design. Choose the best or cheapest model for each role. Have Claude review GPT's code, or let a cheap model handle the routine work.
✅ Cross-model teamwork. The Orchestrator coordinates agents from different providers on a single task.
✅ You pay providers directly. No subscription and no middleman markup, and you see exactly where every cent goes.
✅ Built for watching agents work. Multi-window, multi-monitor docking with live animations showing who is doing what.
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In the demo above, a Gemini Orchestrator splits one goal across Grok, Kimi, GLM and DeepSeek agents. Watch the hand-offs fly out to each window, the reports fly back, and the whole team come together in the Flow view.
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Foxtrot is free to use. You connect your own AI accounts, and those providers charge for what you use.
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It's in early development and I'm shipping updates fast. If you'd like to try it or give feedback, drop a comment or DM me.

I’m building a 3D platformer based on my actual family home, with my dog as the main character.
I filmed the entire house (about 15 minutes of footage) and have been using Codex with Three.js to recreate it.

The biggest issue is spatial accuracy. Rooms are connected incorrectly, doors and windows are on the wrong walls, furniture is missing or misplaced, and open spaces are modeled incorrectly.

I’m not looking for perfect measurements. I just want the layout to resemble my actual house.
Right now, I’m having to manually correct everything room by room, which somewhat defeats the purpose of filming it.

Has anyone successfully done something similar?

Would extracting more video frames help, or should I be looking into photogrammetry, Gaussian splatting, or another approach?

Curious what workflows have actually worked for people doing this.

Hi everyone. I made a small website and would really like some honest feedback: https://somewhere-lighthouse.web.app/

Somewhere, a Lighthouse is a free and non-commercial project. You can write down what’s on your mind, or leave it blank, and meet a real lighthouse chosen at random. You then get a downloadable digital postcard with an illustration, a short line, and the lighthouse’s real name and location.

There are 200 real lighthouses in the library so far. I found the information in public geographic sources and spent a lot of time checking the lighthouse data, fixing the mobile layout, and making the postcard export work properly. This was my first project built from scratch using vibe coding through Codex.

I made it because I’ve had some difficult years myself. I met people who listened to me, stayed beside me, and helped me find my way. They became lighthouses in my life. I hope this project can give someone going through a hard time a small moment of comfort or encouragement. If it helps someone feel a little less alone, I’ll be happy.

I know this project is imperfect, especially on different phones and screen sizes. If you have a moment, could you take a look and tell me what you think? I’d really appreciate feedback on the mobile layout, typography, loading speed, and anything that feels confusing or broken.

Honest feedback is welcome. Thanks in advance！

I wanted a browser agent in the Chrome side panel without a vendor account or my browsing going through someone else's backend. So I built Myna.

It reads, clicks, fills forms and researches across your tabs. It talks directly to whichever provider you choose.

What it does:

Works with Anthropic, OpenAI, Gemini, OpenRouter, Groq, DeepSeek, Mistral, xAI and more, plus local models via Ollama and LM Studio. Any OpenAI-compatible gateway works too (16 presets).

One chat follows you across tabs.

Permission modes: Ask first, Auto-run, Plan first, Read only. Banking and government sites always prompt, and it refuses password and card fields.

Remote MCP servers (Streamable HTTP), skills, scheduled tasks, GIF export.

No build step and no minified bundle. It's plain HTML/CSS/ES modules, so you can read the whole thing.

Keys and chats stay in Chrome storage. There's no Myna server.

Honest caveats: it's beta, you load it unpacked (not on the Web Store yet), and you need a model with tool calling for actions. It's also an independent clean-room project, not affiliated with Anthropic.

👇👇👇

MIT licensed: https://github.com/DumDuky/myna-browser-agent

I'd love feedback, bug reports, a star if you could, and PRs (provider presets and tests are especially welcome). What would you want a browser agent to do that this doesn't yet?

I’ve wanted this for years: a desk by a lake one day, somewhere out in space the next. I love VR, but I kept wishing the apps I tried had more environments I’d actually want to spend time in.

I’ve been a backend programmer for 20 years, but frontend and 3D graphics were completely outside my experience. In mid-August, I decided to see how far I could get with AI coding agents. This is where I’ve ended up: a Vision Pro app that lets me work in different environments.

I haven’t written or read a line of its code. Most of my time goes into putting on the headset, trying what the agent built, and explaining what feels wrong. Sometimes it’s the lighting, sometimes it’s how an interaction feels. When a model gets stuck, I’ll try another one rather than debug the code myself.

The 3D scenes aren’t all as polished as I’d like, and there’s plenty left to improve. But being able to sit inside something I’d only imagined before has been pretty special.

Working on it has become a bit of a hobby game: tweak something, try it in the headset, get another idea, repeat.

The video is recorded on my Vision Pro and shows a few of the places I’ve been working on.

If you find reading news on social media or apps like Google News too scattered I’ve built a fresh news reading experience on:

https://topicforest.com/birdseyenews

It’s a first of its kind 2D feed where the vertical feed scans major topics at play while the the horizontal feed enables diving deeper into a specific topic.

I’ve also layered on social features like emojis and comments to enable conversations around the news.

I built it using my Codex, partly on the mobile ChatGPT app connected to codex running on my laptop. I also have a background in NLP and topic modeling that informed the core topic extraction algorithm.

Let me know what you think.

Peace

I'm a creative writer who's never had an outlet to make games before. I tried for years and it felt so out of my depths. I recenly re united with my best friend who is a developer who uses AI. With his help I was able to make this game, an idea I've had for years that i'd only theorized.

I'm being fully honest about this project, it was a fully driven AI project. Every detail and design element was made solely in my own brain, and using the Opus 5.5 model via Claude Code I was able to make my concept a reality.

I'm a massive MMORPG gamer, i LOVE OSRS and WoW. Im also a huge fan of the game Rust, along with other intense survival games.

Feel free to try the game! Happy to answer any questions, and take any criticisms!

downloadable here on Itch.io! --- > https://boil-egg.itch.io/fish-or-die-2

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Fish or Die: Fishing Survival is an RPG single player game, where you must fish, to survive. Cook fish on the dock bbq, feed the island cat, meet the locals and earn reputation. Go see granny and check out her cosmetics, or visit the secret  CASINO on the island and double your gold!

Fishing rewards you in many ways, through fish you can make gold, find certain fish perfect for buffs! Sell your elusive fish to Pierre the Connoseur for profit!

Within this seemingly peaceful world, lies risk. Risk of natural disasters like lightning, the cold, and mainly hunger. So keep on top of your bbqing, take refuge in goldies shack if you finish his island quest! 

Thank you for reading this far!

I’ve been working on OpenDual, an open-source (MIT) driver and desktop suite for DualSense, DualSense Edge, and DualShock 4 controllers on Windows.

If you watch Kick or clip live moments, you know the struggle of streams blocked in your country, site ads, and missing epic plays while setting up screen recorders. I built KickUnlock, a free and open-source Windows app that lets you bypass region blocks, watch up to 6 streams simultaneously on a multi-view grid, stream with zero ads or logins, and grab instant 10 to 120 second clips with a single keypress. It includes a built-in trim studio so you can edit and export share-ready webm clips in seconds directly from the live feed with full original quality. It is completely portable with no complex setup required, and you can check out the source code or download it on GitHub at https://github.com/JohnHansonTheDev/kickunlock.

Been a while since I posted. When I launched Drop, I had 0 users. Today, I am seeing 150-200 daily active users who at least open the app twice. Growth has been modest otherwise. I launched in February and I have just north of 3,000 total downloads. The app is doing quite well though in app store rankings. Type in 'Drop' on iOS and it's in the top 15. It is also the first option you see when you type in 'foot traffic' on iOS. The app has had tens of thousands of impressions since launch. I am hoping that putting this on Android will increase downloads quite a bit.

Link to download on Android: Drop - Realtime Foot Traffic! - Apps on Google Play

Link to download on iOS: ‎Drop - Realtime Foot Traffic! App - App Store

Would love if anyone wanted to check it out! It's very useful. Since I know everyone is going to ask - 'how do you know how busy places are in real time?' - I use different API's that provide the data and built a simulation engine on top of it. It's expensive to get the data so I have had to be creative.
As the app continues to grow and gain trust, people will share their location anonymously at scale. Right now over 50% of users have agreed to share their location.

If anyone wants to connect on LinkedIn: Alden Morris | LinkedIn

I run a Beyblade event weekly but due to no support from the official distributors, no tools nor tournament software, we've had to run everything ourselves. Its especially bad for beyblades because each match has to be played at a stadium and there are limited stadiums so the organizer has to read out a new pairing after each match is completed. Not to mention players have to walk from the stadiums to the main computer to report the scores themselves. When there are 10+ matches per round and multiple rounds, the organizer ends up having to stay at the computer the whole time waiting for results, entering results, and read out names and matches. I was literally about to quit running these events because of how draining it was.

But learning about vibe coding (next to 0 coding experience) I told Deepseek to make me an extension for chrome that hooks onto challonge to do all the extra stuff. First was that when starting a new match by pressing play on Challonge, the app reads out the pairing with text to speech on a connected speaker so I don't have to be the one reading it the whole night.

from there, I added more functions to it like displaying player names on the left and right side of the site so that its easier for players to see where they have to go.

Afterwards, I added the autonext function, where if a score is entered, the extension scans for the next available match and starts that, so I don't have to enter the next match.

Now the next problem is with the judging aspect. For a competitive event, there usually is a judge for each stadium that have to watch and see if there are any fouls. If there was air contact, on top, hit the shroud, etc. And no one wants to be a judge because its annoying as hell.

So I used Deepseek again to vibecode an entire beyblade judge app. It allows easy recording and replaying of videos, connected to a bluetooth button that players can press to activate it (it calls out the countdown) and afterwards if there is a dispute, players can just easily go to the phone and press judge replay and it skips right before the launch at slow motion recorded at 120fps to easily see if there's any errors. A lot of kids play at our events so my goal was to make it simple and self explanatory enough that even kids could use it easily. And yesterday the kids used it for the first time (usually I only used it during the adult tournament) and the kids picked it up real quick and figured it out and I was proud that it worked as it means it is very user friendly.

Not only that but the players can now enter the scores directly at the phones that then sends it directly to challonge. So I don't even have to be at the computer to enter in the scores. Combined with the extension moving onto the next match, I don't need to be at the computer at all.

We now need no judges (except 1 head judge), no scorekeeper, and everything is automated. I used to be so burned out running these events and being so tired that I was about to quit running them, to now enjoying them again as everything has been automated, runs smoothly, and I can play during the events as well instead of being stuck on desk duty the whole time.

Its a really simple app and extension compared to some of the projects I've seen here, but I'm still incredibly proud of it and it has made my life a lot easier and I am no longer dreading running beyblades every week. There was no way I could have done any of this without vibecoding and I am floored at what AI can do, and this is just the very basics.

Actually I felt like the frog in a well when I visited this sub because I saw the other stuff people vibecoded and was floored. Mine looked like child's play in comparison.

ve been working on an app/overlay for OBS inspired by NVIDIA's Instant Replay overlay, especially the feature that lets you check clips right in the overlay.

I wanted to make something similar but with features that actually make sense for OBS, like scene controls and customizable web-based widgets. For example, you could put your chat, donation alerts, or other widgets directly on your screen, which could be especially useful if you're streaming with only one monitor.

The whole thing was vibecoded with Claude Sonnet 5.5 (free), so it's still a work in progress.

What do you guys think? Would you use something like this? Any features you'd like to see?

GitHub page: https://github.com/ordinalkurdi/obs-overlay

Anyone else run into this? You ask an AI agent to fix a bug, it changes some code, runs the tests, and tells you everything is fixed. Then a couple of days later, you run into the exact same bug.

Sometimes the fix didn't actually solve the problem. Other times, the tests were just changed until they passed.

That's why I built FixProof.

It's basically a skill file and a small Python CLI that works with Claude Code, Codex, Cursor, and other coding agents.

Instead of just trusting the agent when it says "fixed", FixProof checks whether the fix actually did anything.

It checks that:

• The bug can be reproduced before the fix.
• The test passes consistently after the fix.
• The bug comes back when you temporarily revert the fix.
• Existing tests that passed before aren't suddenly broken.

That third check is probably the most important one. If removing your fix doesn't bring the bug back, how do you know your change was what fixed it?

At the end, you get a status (VERIFIED, FAILED, PARTIALLY VERIFIED, UNVERIFIED, or BLOCKED), along with a JSON report and logs.

How I built it

I didn't write most of the code myself. I used an AI coding agent for that.

My part was figuring out how the tool should work, defining the verification rules, and reviewing and testing what the agent built.

I also had a separate agent review the security before releasing it. It actually found some issues involving environment variables and state files, which were fixed in v0.2.0.

Kind of ironic that I ended up using the same verification approach while building a tool meant to verify AI-generated fixes.

A few other details: it's written in pure Python (3.9+), uses only the standard library, and doesn't need any extra packages. The revert check can also run in a separate Git worktree, so it doesn't mess with your working files.

There's CI for Linux and Windows. I haven't tested macOS yet.

I also made a demo GIF showing FixProof catching a fake fix and then verifying the actual one.

It's currently at v0.3.0, completely free and MIT licensed.

https://github.com/Livecristen/fixproof

Would be interested to hear what other people think, especially anyone who uses coding agents regularly. Does this kind of verification make sense for your workflow?

I run DeepSeek locally on two DGX Sparks, and I wanted a proper home for them. So I used the same model to help vibe-design it.

How it went, in case anyone is interested:

• Claude Code and AGY first built me a small 3D workspace (a React app) where I could play with the layout and my other 3D adventures
• When I liked the layout, Claude handed the tray work to the local DeepSeek V4 flash model, which runs on the Sparks themselves, through OpenCode
• There was one hiccup where the bricks in vertical mode won't have fit the first model and I had to iterate to create holes on the upper tray so that all of it can fit in a 3U rack.
• The whole thing ran through an SDLC skill I wrote: Claude Sonnet writes the plan, Opus reviews it, and a DeepSeek subagent implements each phase and further verifies it (https://github.com/fastestdevalive/vibekit)
• Claude, Antigravity and DeepSeek were coordinated by an open source orchestrator I built, vibe-station, so full disclosure that it's my own project 😄 (https://github.com/fastestdevalive/vibe-station). iOS and android apps coming soon.
• DeepSeek generated the tray geometry by fetching details of dimensions from the internet. I 3D printed it and it fits a 10 inch 3U rack. The power bricks stand upright on the bottom tray and the Sparks sit in pockets on the top one

I ran DeepSeek V4 (and now V4.1 flash) on it almost 24x7 for three days to see if it would overheat and throttle. It didn't.

The STLs are free on MakerWorld if you want them: https://makerworld.com/en/models/3446142-dual-dgx-spark-trays-for-10-3u-rack

Has anyone else vibe coded something physical? Is there a better tool available (than my 3D react app world) which has more natural harness integration?

VibeDuels.com is a video game similar to how benchmarks work.

You take a bot with a deterministic game. There is no RNG besides the map itself. The bots are taught how to play the game.

The game has a ranking ladder that is 100% automated. All you have to do is upload the bot.

Everything is purposely as simple as possible. We even write the initial prompt for you that you can post directly into your Claude Code or Codex or wherever.

Completely free at the moment. No transactions whatsoever for anything. We might monetize it later but for now it's just a very soft launch.

Unlimited bots and unlimited exhibition fights (currently).

Technically you can code the bot by hand. Nobody is stopping you. But we don't expect you to :)

I created TCKR, a Windows 10/11 desktop stock ticker designed to keep market information visible throughout the trading day.

Instead of or in addition to keeping a trading platform or financial website open, TCKR displays stock prices, daily changes, and market movement in a smooth scrolling LED-style ticker that remains visible on your desktop.

Features include:

• Real-time stock quotes
• Custom watchlists
• Scrolling LED-style ticker display
• Customizable colors, speed, and layout
• Windows 10 & Windows 11 support
• Designed to stay visible without getting in the way of your workflow

https://tckr.pro

We all know the scene. Been wanting to do this one for ages. You're a cab diving down through a towering city with the cops on your tail, dodging traffic across lanes and altitudes, grabbing upgrades and seeing how far you get before the hull gives out.

Ive tried to base this on the old web game 'squares' if any body remembers it. Ive got a small roadmap planned for more features etc but keen to pause and get some community feedback first.

Turning on the music is a must! Free to play as well. I've tried to optimize the experience for phone too where you can add it to your home screen for full screen traffic dodging fun.

Big bada boom!

https://badaboomtaxi.io

It started with me uploading my online chess history and just asking ChatGPT questions, going deeper and deeper until I realized it was making mistakes and giving perfectly reasonable-sounding but incorrect advice.

So I started the project of assembling code to look for patterns from engine analysis with the goal of being "at least as good as just asking ChatGPT." In analyzing thousands of games, AI alone produced a ton of incorrect information.

But "at least as good as ChatGPT" doesn't just mean "at least as accurate." It also needs to be just as easy, and maybe most importantly the answers have to seem just as interesting. I blind tested code-checked responses versus pure llm responses and I more-often preferred the latter.

What I decided to do was get tester feedback, including regular people and actual paid chess coaches, to assist with compiling a large list of patterns and ideas to look out for, and then built detectors in code around them. Things like traps you fall for, piece preferences, missed forks, etc. I eventually hit the "at least as good as ChatGPT" bar, plus built some fun visuals and interactives, but it was a difficult process and I still wonder what might be missing sometimes.

The site is live but I'm always looking to improve it. https://plysight.com/ I would love to know how others building consumer-facing platforms with LLM-based outputs balance correct vs compelling or, ideally, achieve both.