r/VibeCodeDevs

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I built tryproduck.com/audit, it walks your app like someone opening it for the first time and sends back every bug and confusing bit it hits. Over 650 startups have run it so far.

The idea started while playing 7a0. I loved the drafting mechanic and kept wondering:

>

So I built Cricket XI with Lovable.

🔗 https://cric-xi-simulation.vercel.app/

The core loop:

Pick a tournament → draft 11 players → build your XI → simulate the tournament → try to win it all.

What surprised me was how quickly the project went from a simple UI to needing actual engineering:

• Historical squads across different eras
• Canonical player IDs to prevent drafting the same player twice
• Repository + service architecture
• Tournament-specific rules
• IPL playoff logic
• NRR calculations
• Background simulation of other teams
• Historical team/year rerolls
• Scorecards and tournament statistics

My workflow was basically:

Prompt → Play → Find a ridiculous bug → Explain it → Fix → Stress test → Repeat

And there were plenty of ridiculous bugs. 😂

The biggest thing I learned from this project: vibe coding gets you to a working product incredibly quickly, but playing the product yourself is what exposes whether the underlying logic actually works.

This is V1. Would love to know what you think — and especially what you manage to break.

This is the app (called "LWP+"), and I've shown here the video that I've published there:

https://play.google.com/store/apps/details?id=com.lb.lwp_plus

At first I was happy about what I created on the video, but then I thought that it looks more like a tutorial here, instead of maybe focusing on what's the most interesting. Surprisingly, ever since I've published the video, it actually got quite some views already (29 after 2 days), despite the fact it's a bit of a niche app. Still, I think maybe it can be improved.

I want to know what you guys think about the video (which has audio, BTW).

Here's about the app:

It's a live wallpaper app, that has these features:

1. Allows showing color/image/animation/video as content (users choose the file from the file system). No special effects so some users that complain about the dimming/zooming effects actually like using it. Users can also choose whether it should scroll or the type of automatic cropping.

2. Allows (some) control over the Material-You colors of the OS, as it lets users to choose the colors to report the OS about what's on the wallpaper. This means that like on Android 17, users can choose the colors they want (if the OS supports it) despite the content not matching it.

3. Setting of double-tap to lock the screen. Some launchers don't offer this, so I added it to the app too.

4. Some extra flags that (on some devices) should affect colors further, such as black/white text and/or black/white icons on status bar and/or lock screen and/or launcher.

The app is completely free, ad-based. Users can remove the ads including by just watching full screen ads. Originally it was created to offer dark-theme on devices as it wasn't a toggle on the OS settings, and was based on the colors of the wallpaper.

CTOs, engineering managers, and staff engineers are rushing to deploy autonomous AI agents across their businesses – either through their own volition or because of the clamor of demand from rank-and-file workers. However, they should think twice, a new study shows.

Enterprise large language model (LLM) agents are likely leaking company secrets, and throwing more compute at the problem is only making it worse, the study finds.

In part, that’s because of the AI’s ability to retrieve and synthesize vast amounts of internal data, from Slack messages to board transcripts, to automate tasks. By gathering that information, they also create issues with contextual integrity.

When retrieving dense corporate data, these agents routinely fail to disentangle essential task data from sensitive, contextually inappropriate information. Higher task completion rates often directly correlate with increased privacy violations.

Read the full story: https://leaddev.com/ai/frontier-ai-models-haemorrhage-sensitive-data

Hi everyone,

I’ve been working on Mert Stream TV, a brand-new IPTV player designed specifically for Android TV, TV boxes, and Android phones. Just to be clear: Mert Stream TV does not provide, host, or sell any content. It is strictly a media player built to run your own personal M3U playlist, Stalker or Xtream Codes credentials. I originally decided to build Mert Stream because I was frustrated with the current options on the market.

Most of them: Feel like they haven't updated their UI since 2015. Run sluggishly on budget streaming sticks and lower-end TV hardware. Offer a frustrating, clunky navigation experience with standard TV remotes.

I wanted something clean, incredibly fast, and smart. Here is what Mert Stream brings to the table:

🚀 Key Features: Live TV, Movies & Series: Fully categorized with a modern, clean layout. Multi-Profile Support: Set up different profiles for family members. Extensive Codec Support: Playback is smooth and compatible with virtually any video format. Android TV Optimized: A true, native leanback experience built specifically for D-pad navigation. Lightweight & High Performance: Highly optimized code to ensure buttery-smooth navigation even on low-end TV hardware.

📥 Get It Now for Android TV and Phone

📥 Get It Now for Android Phone

Mert Stream is officially available on the Google Play Store for both mobile and TV devices.

been living in claude a lot and my history got messy fast especially when i also hop to chatgpt and gemini ( or if i js have lots of projects )

so i built tecora -> a local browser extension that keeps those chats in one library. folders tags search export conversations ( WITH THE ARTIFACTS / IMAGES / FILES ) . no account no backend nothing leaves the device

used gpt/claude to build this a lot mainly to make sure it doesnt break any TOS and stuff lol

what does it do?

• side panel library so youre not stuck scrolling the native history
• ctrl/cmd+k search across chats
• usage awareness when claude exposes it (windows / reset vibes) plus local activity estimates so you have a sense of how hard youve been hitting it. not claiming magic hidden quota numbers just making whats already there easier to see
• export when you want a real archive instead of hoping the tab stays forever

it does hv drawbacks specifically:

• chrome load unpacked only for now not on the web store
• gemini capture is weaker than claude/chatgpt ( the ui is quite hard to manip along side claude and gpt )
• usage is best effort. local counts are estimates. live quota only when the platform actually gives it

repoi need feedback before i release this as a fully fletched extension

https://github.com/nothariharan/Tecora

release zip if you wanna try without building

https://github.com/nothariharan/Tecora/releases/tag/v0.1.0

curious what yall think especially if youre a heavy claude tab / browser person

100 stars. I know that's nothing by internet standards, but I genuinely didn't expect anyone outside my own GitHub profile to care about this.

Kairo started as a frustration project. I was deep in a coding session, had to context-switch to my task manager, and just... snapped a little. Opened a new Go module that same night. That was a few months ago.

For those who haven't seen it — Kairo is a fully local, keyboard-first terminal task manager. SQLite storage, 32 themes, fuzzy search, natural language deadlines, a Lua plugin system, a CLI API for scripting, and an optional MCP server if you want to point AI agents at your task list. No cloud. No account. No subscription. Just a binary you run in your terminal.

Things I didn't expect when building it:

• That people would actually use the Lua hooks (shoutout to the person who built a webhook notifier with them — genuinely wild)
• That the "32 themes" feature would be the thing people mentioned most
• That u/Tornado300 would show up and fix bugs I'd been avoiding for weeks

What's coming: encrypted multi-workspace support, a sandboxed plugin environment, and smarter task suggestions. I'm building this in the open and taking feedback seriously — if something annoys you, open an issue or just tell me here.

If you've been looking for a task manager that lives where you actually work — give it a shot.

→ github.com/programmersd21/kairo

Thanks for the stars. They matter more than they probably should.

Hi everyone, I’m the developer of Cage Rise, an MMA career simulation game I’ve been working on.

You create a fighter at 18 and manage their career through training, choosing fights, climbing the rankings and progressing through different organisations.

The aim is to win world titles, reach the Hall of Fame and ultimately try to become the GOAT before retirement.

I wanted to make something for people who enjoy the career and management side of sports games, particularly MMA.

The game is fully released and I’ve continued developing and expanding it since launch.

Cage Rise is available on iOS:
https://apps.apple.com/gb/app/cage-rise-mma-sim/id6783279600

Hey, I'm a webdev. I previously approached my project with JavaScript. I'm familiar with the js ecosystem.

I put a fair bit of consideration and in contrast to my JavaScript-approach, I'd like to investigate Dioxus.

I'm not completely new. I've dabbled in Rust before. I have read a lot of the docs and I'm sure there is much more to learn and practice.

What advice would you give to getting started with the Rust ecosystem approach?

Similar to a lot of languages there are considerations for things like tests. So it would be helpful to compare the options. As well as any other best-practices and nuances.

In relation to my project, I'm particularly interested in the tooling available in Rust for formal verification.

Just to be clear, im not here to waste your time on my slop, but if you want to see what I've got so far (practically nothing):

• Code: https://github.com/positive-intentions/whatsup
• Demo: https://positive-intentions.github.io/whatsup

I think we all went through this. Claude finished a task, told me it was done, and left me with 14 changed files and no idea which one mattered. The diff was accurate and useless. So I built the thing I wanted to be looking at instead.

Flare is a desktop IDE (Electron) where the main surface is a live graph of your codebase, every file a node, every import an edge, with a terminal underneath where you run claude, codex, or opencode. As the agent edits, the graph updates in real time.

The parts that are actually different from "another editor":

Activity, as it happens. Nodes light up the moment the agent writes to them and decay as they cool, so you're watching the shape of the work instead of a scrolling transcript. You can see it circling the same three files for the fifth time, or wandering into auth when you asked about the CSV parser. Changes are attributed per agent: the process tree of every terminal is watched, so if you have two running, you know which one did what. Files that changed and no human has opened since stay marked until someone actually reads them.

Blast radius before you touch anything. Hover a file and its dependents light up. shared/types.ts with 63 files downstream looks different from a leaf file, without you having to know that in advance.

A review tab that answers "did anything check this?" Flare sees both the file writes and the commands run in its own terminals, so it can say the tests ran, then two more files were edited and nothing re-ran, quoting the output line the verdict came from.

Agent smells. Rules for shortcuts agents take and humans usually don't: a test edited in the same burst as the code it covers, assertions deleted, .skip added, type suppressions introduced, coverage thresholds lowered.

Risky changes come to you. If the agent rewrites something load-bearing while you're looking elsewhere, it queues an alert in the corner. Reviewing it opens the actual red/green diff.

Undo that isn't git. Every change burst is snapshotted into a hidden shadow repo (separate GIT_DIR, your worktree). Revert one file, revert the burst, or jump back to the last state whose checks passed. Your real repo is never touched.

A task board the agent works from. Kanban lanes, but the cards are written to be handed off. "Copy for agent" emits the brief plus the files it names plus what the graph knows about them (29 files downstream, 0% covered, in an import cycle), so the agent starts from the map instead of rediscovering it. File a card straight from a graph selection with right-click → New task with these files. This directly tells Claude to not wander around out-of-scope files

MCP server, ~16 tools. The same lanes are queryable, so an agent can run its own loop: tasks_list to pick up work, task_get for the exact brief, task_update to log progress and move the card to review, task_create to file follow-ups it finds but shouldn't do now. Cards move on the board live while you watch. Plus impact_of (what breaks, and which tests to run), dependents, find_path, verification_status, and record_intent, which lets the agent state the goal before editing so whoever reviews the diff isn't reconstructing why it exists.

Runs in a browser too. Same bundle, same backend, over a websocket, because the backend has to run on the machine the agent runs on and that's often not your laptop. One port, token auth, works behind Codespaces / Gitpod / a JupyterHub proxy.

Completely open source with MIT license, Node 20+. Built with agentic coding, which is exactly how I ended up needing it. Test it out and leave a star if you find it helpful, I will package it very soon to make it easier to install!

https://github.com/AlgoNoRhythm/Flare

It's crazy what happens when you listen to the community.

A few months ago I created a website called letsfg.co where you can get the best flights on the internet. Under the hood it runs hundreds of AI agents on my backend where each one is scanning a different website like Google Flights, Skyscanner, Booking, etc.

It then compares the prices and stats and gives you the best. And it now does the same with hotels.

The best part is that it's like Uber for travel - you can book hotel in 3 seconds.
It's the best thing I've built so far, here's why:

https://preview.redd.it/smlp8v4gtcih1.png?width=1901&format=png&auto=webp&s=b1ac8d8814e9a5b0ea1775293a5f7d8b594701b7

Just a month ago the whole team here behind letsfg were confused, building something people genuenly loved but hated the payment model. And everybody was asking for 1 thing - "make it free, I want to try it". But the infrastructure costs were killing us, this seemed impossible.

We managed to do it.

Quick update about flights and then hotels:
Previously we had a horrible payment model, upfront charge, nothing logical, just bad. Everybody asked us to change it. And instead of giving up because it seemed impossible we started thinking in first principles, got some deals done and today we're happy to say letsfg is free. Instead of charging you, we get the money from the airline ticket. And we still get you the cheapest tickets from the websites around the internet.

Today we also support hotels. It's on average 15% cheaper than booking_com, and you can book in 3 seconds, like an uber.

comparison of prices, listed on our github repo

What's amazing is this is a big step in agentic commerce. Letsfg.co is agent native in it's core. This means that now also hotels, are bookable and searchable straight from your Claude, Codex, OpenClaw, Hermes, etc.

Authentication for AI agents is through payment method (was twitter auth before).

Everything is also available through our open developer API. For anybody interested in flights/hotels API: >!I believe this is a game changer, every provider out there requires hard flat fees upfront and long processes of contracting. We don't. Sign up to API and you get access to the context 10 seconds later.!<

How does it work?
We integrated with dozens of enterprise providers who gave us access to their hotels inventory and ability to book.
We also resued our approach from flights and polished it - AI agents navigating the hotel websites. Finally landing the right payment provider allows us to complete bookings on the hotel websites. GPT-5.6 Luna turned out to be an amazing engine for those agents.

How can I use it? 3 ways.

Website: letsfg.co best for everybody.

website results page

Programmatic Hotel Tool (PHT) and Programmatic Flight Search (PFS) - our agent native endpoints, best for AI agents, authentication done through payment method attachment (free, no charge, just for verification). This is what powers our Python package, NPM package, MCP, CLI, etc. best to check on https://letsfg.co/for-agents

Developers API - paid, balance based API, best for high volume. https://letsfg.co/en/developers

Thanks to everybody who shared their feedback, sweet and bitter, we read all of it and worked hard to make this great. You're awesome.

We'll continue making things better, tweaking the small stuff, and fixing the problems until we get joy back from travelling.

Cheers,
Adam

Github link: https://github.com/LetsFG/LetsFG

https://world-sim.uk/ launching friday!

World-Sim has been a passionate project of mine for the past few months.

It's a world fully simulated down to real world physics and chemistry. It has a real environment and ozone.

Every element and material has real physical properties, and that's how the sims learn. There's no tech tree and no recipe list anywhere in the code. When someone tries something, the engine works out what would really happen from the properties of what they used and how hot their fire was. Nobody is handed bronze. Someone has to get a hotter fire first, and a hotter fire is its own chain of things to figure out. Embers, a stone ring, a clay oven, a kiln, charcoal, then forced air. The ages fall out of that on their own.

We populate the world with starting families. Each little guy is led by a "wise-man", which is a simulated person with a full model behind them. The wise-men run on a mix, Claude, Groq and DeepSeek in the cloud and a local Hermes for the rest, so you get a real variety of temperament between the houses.

The AI model is never told to not say it's AI. We get around this by only telling them data from what each sim can actually see and feel. As far as the ai knows its a person living in the world..

Every other sim has its own moment with a model through our thinking system. Day to day it's run by an advanced algorithm, with the sims dreaming at night. That's when they get their time with an LLM to really think and set their priorities for the day ahead. The dreams carry over too, so a sim can chew on the same thing for a few nights and wake up wanting to try something.

The people in the world feel, remember, have shame, goals and doubts. It's an 11 point emotion system and the rest of the sim reads from it. Being lonely makes someone more likely to open up to a stranger. Two enemies who are both frightened find it harder to keep hating each other.

Story telling is massive for us. Nothing is scripted or prompted. The sims are put in the world with the human drive to survive. They adapt, learn and teach all on their own.

With all the good comes the bad too. Human sin is part of the emotion engine, and in testing we've had kidnap, murder and slave trade. A world that can only be gentle isn't an honest one. But there are three rules to this : Nothing ever pushes a sim towards it, the conditions only make it possible and their own mind decides. The chronicle names what happened but never shows it. And it always costs something, trauma that scars, blood debt passed down generations, a people turning on their own leader over what he did.

Most agents today are already pretty powerful and requires minimum prompt engineering, and the app builder's value was in the easy set up. So I made an MCP that does what lovable/replit do, but uses your AI subscription's tokens instead. It ends up being a 60+ tool MCP but it's been working pretty well. It does require a good model (opus or terra) to work well, but overall it's been able to do a pretty good job.

Check it out here: https://floot.com

And let me know if you have any feedbacks!

Hey friends!

I just wanted to share a little web game I vibe-coded with RR world in mind!

The idea: a shooter/survival spaceship web game that you can play only 3 times a day, and compare your score with everyone, as you'd do with Wordle. Everyone plays the same patterns each day, and it resets at midnight PT.

Here is the link: https://www.surviveorion.com

Hopefully it can make your lunch or coffee break a little different tomorrow :D

Don't hesitate to give feedback through the app or here! Looking forward to seeing a bunch of RR names on the leaderboard!

ps: I don't believe this is considered "self-promotion," as I'm not making any money (no ads, no costs) from it?

İki dene mobil oyun yaptım, biri ekonomi simülasyonu 1600 indirmesi falan var, yarım saatlik aktivite analizlerinde sürekli 10 12 kişi aktif oluyor son birkaç gündür reklam gösterimleri de çok kötü değil ama gelir inanılmaz düşük 307 reklam gösterimine 3.02 lira gelir var gördüğünüz gibi oynayanlar mahrem yerini yaprakla kapatan kitle, diğerindeyse 5 reklam görüntülemesine 2,89 lira kazandırmış bugün ve ball sortun indirmesi 350 falan ama oynayan pek yok hyper casual olmasına rağmen ki kötü de değil bu iki oyuna da 1000 lira civarı reklam harcaması yaptım hatta ball sort bir tık daha yüksek. Reklam dönüşüm maliyetleri de Faith: Economy Simulation için 0.63 kuruş, Ball Sort - Zen 2026 için 3.54 lira. Harcamayı ne kadar sürdürebilirim bilemiyorum bazen bakıyorum 2 reklam gösteriminden 1.5 lira geliyor bazen 200 gösterim anca 1 lira ediyor şu hedef kitle işini pek çözemedim ne düşünüyorsunuz.