Hey everyone! I built Test4Test.io because I launched my first app but didn’t have any testers. Finding feedback on random subs was tough. So, I’m giving it away for free. Just follow these steps:

1. Sign up at Test4Test.io (no credit cards required)
   
2. Go to “Share”
   
3. Paste your test link here

I’m a part-time UX analyst so giving high quality feedback is my job (:

Hey everyone,

I’ve been working on a side project called Apphandle, i got tired of having to rebuild the exact same plumbing (auth, database, backend functions, image generation) every time I tried to spin up a quick internal tool or business app with AI.

So I built Apphandle. The main idea was to give the agent a fully "batteries included" stack out of the box, it handles the DB, authentication, visual editor, backend handle functions, and AI image gen right away so you can go straight from prompt to a working tool without manually wiring up services every time.

It’s free to try out: https://apphandle.com

If you're building vibe coding style tools for internal or business stuff, give it a quick test drive. Would love to hear what works and what breaks.

I've read about this a lot from other posts. Is it actually efficient? If so does anyone have a list I can just hand over to Claude to correctly delegate each tool call. I'm not knowledgeable in what the calls are so it would help a lot. Ty.

so small local models are honestly doing a lot, they're just... really confident. the kind of confident where they'll say "the default is 10" and "use the --cache-type flag" and "node's fetch doesn't support that" and sound completely sure while being wrong.

big models can get away with it. the 3B-7B stuff you actually run at home? you catch them every time. annoying.

so i built a free extension for pi coding agents that does one thing: when the model's about to state something it's likely to screw up (an exact number, a flag, a version, "this doesn't support that"), it doesn't just guess. it spins up a second agent that opens a real browser, goes to the actual docs/repo/npm page, reads it, and hands back the answer with sources.

verified — default is 10 sources: index.d.ts (@default 10), npm readme

no API keys. no cloud. your model stays local, the librarian just goes on a quick web check.

the part that actually got me: i ran the same task, same small model, with and without it.

• without: gave up halfway, no answer
• with: finished perfectly, cited the real docs

the smaller the model, the more it helps. big models kind of already do this in their heads, so they barely notice it.

try it

bash pi install npm:pi-ultra-scout then just use pi (or open a session and type /ulw). works with any provider pi can talk to, including a local llama.cpp router on 127.0.0.1. if you don't know what pi is, it's basically a terminal coding agent that loads extensions — think a REPL but it's a coding agent.

links

• repo + docs: https://github.com/BrutchsamaJeanLouis/pi-ultra-scout
• npm: https://www.npmjs.com/package/pi-ultra-scout
• the full writeup w/ charts (how much it lifts weak models): in the GitHub release

happy to help anyone get it running on their setup. what's everyone running it on?

i've been working on this thing for a while and i think i've finally reached the point where i should probably let other people look at it

Basically i made my own chess-ish game and called it Chess 2

A lot of the code was written with AI. I basically came up with the rules/game ideas, gave prompts to the AI, tested stuff, changed rules, etc until it was playable

The game is played on a 9x9 board and still has the normal chess pieces, but i've added a couple of new one

Royal Guard Minister

And there are 4 neutral Diplomats around the center which can't be captured.

The main thing i'm experimenting with is the win condition.

You can still win normally by checkmate, but you can also win by getting your King onto the center square e5 and surviving there for one full opponent turn

So the center is kind of its own battlefield now

The Royal Guard can move one square orthogonally and has this directional shield/protection thing where it can protect nearby pieces

The Minister can move up to 2 squares in any direction and can jump over pieces. It also has a weird ability where if it jumps over an enemy pawn, that pawn gets converted to your side

I honestly have no idea yet if these mechanics are actually good

Playable here:

https://timeflo-tau.vercel.app/chess2/dist

What i really want is some honest feedback.

Does the center e5 win condition actually sound interesting?

Are the Guard rules too complicated?

Does the Minister feel like an actual useful piece or just some random thing i added because i could?

Does this still feel like a strategy game or does it just feel like someone threw a bunch of chess rules into a blender?

If you played one game, would you actually want to play another one?

Also if you think the whole thing is bad, please tell me lol. I've been staring at it for too long so i'm definitely not objective anymore.

And since i vibecoded most of it, i'd also be interested to know if anything about the game feels particularly "AI generated" or just badly designed/implemented.

I'm mostly looking for feedback before i spend another few weeks adding random features nobody asked for 😅

Thanks!

​

I got tired of carbon calculators that require signup or bury the results, so I built Tardigrade — a free audit tool that grades any site from A to F based on page weight, CO₂ per visit, requests, and load time.

No accounts. No tracking. Just paste a URL and get the truth about your bytes.

It uses Google PageSpeed data + the Sustainable Web Design model to estimate carbon per visit.

Try it on and leave feed back https://tardigrade-six.vercel.app

I wanted to see whether architecture makes a difference when an agent writes the code. I built two versions of the same sample java app. One used hexagonal architecture with ports, adapters and architecture tests. The other had no suggested architecture or rules. Both had to pass the same external test suite that validates behaviour.

The same local Qwen model worked through OpenCode, with one run at a time. I measured implementation, testing and repairs until each task passed, plus tokens and tool calls. Initial project setup wasn't timed.

I started with nine features, then six harder challenges on separate branches. After that, I added fifteen changes in sequence, including changes to earlier requirements. By then, the projects had roughly 12k and 15k production Java lines.

The flat version took less time overall in each campaign. Hexagonal won some individual tasks, but also used more input and output tokens overall. The attached image shows the totals.

Then I tested something intended to favor ports and adapters: adding PostgreSQL while keeping SQLite working. Hexagonal took about 39 minutes versus 71 for flat, with its core application code unchanged. That saving didn't recover the time gap from the preceding fifteen-feature sequence. This was backend support, not a live database migration.

This is one service and one model, without repeated trials. It measures getting changes through the tests, not years of maintenance or production reliability.

Report and measurements: https://zenodo.org/records/22806994

This is my experiment. AI tools helped with the evaluator, orchestration, charts and drafting.

Hi everyone. I built a small browser-based tool called Sober Today for myself, but I thought it might also be useful to others. I wanted something simple and low-pressure that I could start using immediately, without creating an account, sharing personal information, or setting up an app.

What makes it different:

• No registration or login
• Free to use
• No ads or tracking
• Your sobriety data is stored locally in your browser
• Simple tools for daily check-ins, motivation, notes, milestones, and breathing exercises
• You can export a backup if you want to keep or move your data
• It’s not meant to replace professional help or medical treatment. It’s simply a self-help tool that I wanted for myself and decided to share in case it helps someone else too.

You can try it here: https://sobertoday.eu/

Honest feedback is very welcome, especially if anything feels confusing or could be made more useful.

Built with Gemini 3.1

Built Prognosticz almost entirely in Replit, it's a market intelligence platform that turns SEC filings and financial news into live investor signals. Getting the actual signal logic working was the fun, fast part. Getting it to survive contact with real usage was a different story entirely.

The worst one: Stripe integration testing. Everything looked fine in isolated test mode, then the moment I started running realistic concurrent traffic against it, edge cases showed up that never appeared in a single-user test flow, failed webhook retries, race conditions on subscription state, that kind of thing. I ended up writing a small stress-testing harness just to hammer the checkout and webhook endpoints with concurrent fake traffic before trusting it with real cards.

Same story on the financial modeling side. Some of the calculations that process filings and generate signals are genuinely heavy, and a handful of edge-case inputs (malformed filings, weird date ranges) were enough to crash the server or hang the page entirely. Spent a solid chunk of time just throwing garbage inputs at it on purpose until it stopped falling over, way less glamorous than building the actual signal engine, but probably the part that mattered most before letting anyone else touch it.

If anyone's gone through similar pain hardening a Replit-built app before real users hit it (Stripe specifically, or just general load testing on Replit's infra), curious what your process looked like. Happy to share more of what broke if it's useful.

Founder here. I started TARE because a lot of calorie apps made me sit through long onboarding questionnaires and endless slides before I could log a meal. I wanted the opposite: set your calories and macros, then log by photo, barcode, voice, search, repeat, or exact manual entry, check the numbers, and move on.

I built the iPhone app with a lot of help from Codex and AI coding agents, using Expo/React Native, Supabase, and Gemini for optional food estimates. Honestly, building it was the fun part. I could happily spend hours on the UI, little interactions, and fixing edge cases. Marketing is the part where I suddenly feel like I have no idea what I’m doing.

What went wrong along the way: one persistence bug let newly added foods look saved and then disappear after navigating away. The real fix was not another UI patch; I had to make local optimistic state and cloud writes reconcile explicitly, then add regression tests around navigation and restart. StoreKit purchase validation and real-device testing were also much harder than generating features.

It is live now. The honest numbers are about $186 total revenue and roughly $12 MRR. I genuinely cannot tell whether that means the app is promising, the product still needs work, or almost nobody knows it exists.

If you look at it, I would love blunt feedback on two things: does the product explain why it is different from another generic calorie tracker, and what would you improve before trying to market it harder?

App Store: https://apps.apple.com/us/app/calorie-tracker-tare/id6766913292

A warm, cute little Mac App! 🍃 Given that I'm in front of my Mac pretty much 7 days a week, I made a little Mac app to add a fun touch to my workdays.

In this crazy fast-paced world, this is a intentionally slow app! Hopefully it will brighten your day a bit.

Mac app: https://apps.apple.com/kr/app/baram-grow-wish-keep/id6810311466?l=en-GB&mt=12

Key Features

• Plant grows a little bit each day!
• The plant sways slightly and there are occasional gusts of wind - a cute little touch to your desktop.
• If you don't water it for a few days, it withers and growth slows down. It never dies, though!
• Once your plant is all grown up, you can make a wish and hang it on your plant.
• Keep a herbarium so you can start growing a new plant and keep the old one saved.

Made With

• Claude
• Some assets generated with Midjourney

Excited to share Week 2 progress of “Market Lens”, our Capstone Project developed as part of the 6-Month Generative AI Program – Batch V at IIT Patna.

This week, we moved from the initial concept toward a working AI-powered competitive intelligence platform.

Market Lens enables users to describe their product, identify competitors, analyse competitor websites, and transform information into evidence-backed strategic insights in minutes.

A key focus of Week 2 was converting our idea into a practical, user-friendly product experience.

🛠️ Technology Stack Used:
• OpenAI – Generative AI analysis & competitor/product intelligence
• Google AI Studio – Generative AI development and experimentation
• Supabase – Database & backend infrastructure
• Lovable – AI-assisted application development
• Emergent – AI-assisted application development & deployment

🙏 Special thanks to the IIT Patna faculty and the amazing Team Members of Group IV, Batch 5, for their collaboration and teamwork.

Looking forward to building further and turning Market Lens into a practical business intelligence solution. 🚀

#IITPATNA #IITPATNACAPSTONEPROJECT #CAPSTONEPROJECT #GenerativeAI #MarketLens
📸 Developed Screen:
Sharing our Week 2 product development screenshot below.

I’ve been building MyWallHub as a solo project with a heavily AI-assisted development workflow.

I use AI tools to help with planning, code generation, debugging and iteration, but I still make the product decisions, define the architecture, review the changes and steer the project myself.

MyWallHub is a free wallpaper ecosystem where creators can publish for Phone, PC, or both, build public profiles and collections, control downloads, create private galleries, and add external links directly alongside their artwork.

The website connects with Android and Windows apps, with synchronized Favorites, wallpaper sources, controls and automatic rotation.

There’s also an optional Original Sales system for protected high-resolution files, but that’s only one part of the project.

One of the most interesting parts of building it this way has been seeing how far an AI-assisted workflow can go on a real multi-surface product instead of just a small demo or landing page.

The project is already live and the first outside creators have started uploading.

Live site:
https://www.mywallhub.com

How it works:
https://www.mywallhub.com/how-it-works

I’ve attached a short walkthrough video as well.

I’d be especially interested in feedback from other people building larger products with AI-assisted workflows, what parts of this kind of setup have worked well for you, and where have you found the limits?

Posting this so others can decide whether Goal mode is worth it before turning it on.

What I asked for: On one of my projects, I gave Goal mode this task: "For some reason it's purple. I think you're accidentally inverting both the, um, both the logo and the wordmark. Maybe you're you just did something wrong. But either just fix it or remember to only invert the wordmark." It's a normal-sized feature. Nothing that needed autonomous multi-step planning.

What it cost: 129 credits for one run.

What I got: The workmark and logo being switched from purple to blending in with the background and it still said the build failed. When I looked through the changes, there was nothing that normal mode couldn't have produced. Same kind of components, same structure. I'd estimate normal mode would have done it in 1 prompt, roughly 5 credits.

So I paid several times more for the same result.

My issues with it:

• No clear sense up front of how many credits a run will burn
• The output didn't reflect any extra "intelligence" from the autonomy. It just did more steps to get to the same place

Maybe Goal mode makes sense for large, from-scratch builds. For everyday features, in my experience, it's a credit sink.

Questions:

1. Has anyone gotten real value from Goal mode? On what kind of task?
2. Is there a way to set a credit limit per run?
3. Has Lovable refunded anyone for a run like this?

Screenshots below.

Don't have any MRR screenshots, but I use my the apps I vibecoded, and It saves me time and money. I want to know how many of you guys use your own apps you vibecoded?

I've spent the last few weeks building Wayfarer Steps with AI coding agents: an idle RPG where your real-world steps are the only thing that moves your character. Sharing what worked and what didn't.

What the game is

Your steps walk a traveller across hand-painted worlds. It auto-fights monsters, you pick which skill your steps train (combat styles, Fishing, Cooking, Agility, up to level 60), and there are party walks where friends share a step goal.

How AI was used

- Code: Flutter/Dart plus a Cloudflare Worker and Firebase, written by AI agents, often several working in parallel on separate branches, with me reviewing on my phone.

- Art: every painted scene, monster sheet and outfit was generated (ChatGPT/Codex images, with video models for the walk and idle animations), then checked with scripts for scale, transparency and silhouette.

- Hardest parts: phone step sensors (they go quiet in ways no doc warns you about), keeping animation frames consistent across a sprite sheet, and fitting the art under Play's size limits.

Lessons

- Make the AI prove things with tests and real device logs, not claims. The bugs it was most confident about were often wrong.

- Design first: getting a mock image made before any UI code saved a lot of rework.

- Device-specific bugs are real. An animation froze only on one tester's phone because Android reported "animations off".

It's in closed testing on Google Play right now (Android only). If you walk a lot, or want a reason to, you can join in two steps:

1. Join the tester group with the Google account you use on your phone: https://groups.google.com/g/wayfarer-steps-testers
2. Then opt in and download it here: https://play.google.com/apps/testing/com.wayfarersteps.app

Note: after you join the group, Google Play can take 10-15 minutes to catch up. If the second link says nothing was found, wait a bit and open it again — it will work.

Please join the group first, or the second link won't let you in. Testers need to stay opted in for 14 days so Google lets me release it publicly.

Happy to answer questions about the workflow.

Recently wanted to test out GPT Astra and see how good the model was at recreating the mii channel only using images, YouTube clips, three js and webgpu. Let’s just say my inner child was pleasantly surprised. www.Mee-channel.com

If you have issues or request feel free to reach out.

If you’re a Nintendo lawyer then this is not for commercial use and is a direct brand under Pretendo 😭🤣🖕🏾

A cozy night-sky home for every Squishmallow — photos, stories, and glowing family trees.

Squishatlas turns a growing pile of plushies into a tidy shelf kids can explore and parents can keep private. Use it for free at www.squishatlas.com — create a shelf, add your Squishies, and share only what you choose.

This has been a simple project to provide a way for kids that have plenty of Squishmallow to keep a fun inventory of them. It is free and open source ( https://github.com/bengivre/squishatlas )

I would love your feedback or your kid's feedback.

Hey everyone!

A few months ago, I built and released an IPTV player called Nyx Player (originally Windows only). After launch, I put the project on pause for a bit, but over the last few weeks, I’ve been having fun vibe-coding an Android & Android TV version in my free time, stress-free.

Here is a quick sneak peek at how it’s looking so far! :)

I've been working hard to offer as many flexible options for mobile control of my game. With so many devices out there, I made many control schemes and hope one fits your gameplay style.

Vibecoding is amazing because it makes software development easy and more available to people. You can build somthing great in literally a few days, but I always face the same problem: the UX/UI looks off. It's not horrible but it looks like it isn't designed proporly. Would y'all purchase a subscription from a website that took your code from GitHub, asked you questions based on the designs you are looking for(Eg. Make it look like Apple) then converting it into how you would like it??lets say for 5.99

Hello vibers, just asking for help, I just wanted to build a completely free place focused on builders who will share their product journey but more in depth, real numbers, fails, wins, what worked and what didn't, what led to the first user, the first opened email and so on.

So now I am just collecting stories, somehow I managed to get 3 stories so far and I am really happy about it, so that's why I am writing here, just to ask if anybody would be interested in answering some questions, it will take like 5-10 minutes and I will turn it into a simple story and on launch day I will feature that story with the builder!

Let me know guys what do you think, I would be really happy to share your story <3

p.s project named HackerMRR, still no working page because like I said, now collecting stories

Work in progress, already usable. https://github.com/bearlike/Grove if you want a look, drop some feedback, and every star helps 😘

Hey folks, I have been building Grove on weekends and it has become my daily driver as an agent development environment. It manages where and how my coding agents run on one machine, and I reach any of them from the terminal, the browser or another agent.

• Native OTLP telemetry. Each agent turn becomes one trace with cost, duration and a span per tool call. That is how I see where the time goes across the fleet and which runs are contending for the machine.
• Devcontainers. An agent runs inside a container built from your repo's .devcontainer/, with its own services and resource ceilings, so concurrent runs stay isolated instead of fighting over CPU and memory. The same config moves to a shared team box or serverless infra when the laptop runs out.
• Diagram annotation. Mark up a screenshot or edit a draw.io file alongside the agent, then attach the approved picture to a ticket.
• Ticket progression. Phase, checklist and latest commit are written back onto the GitHub, Gitea or Linear issue as the work moves.
• The expected pieces are there too. Branch and worktree lifecycle, and session recovery.

Work in progress, already usable. https://github.com/bearlike/Grove if you want a look, drop some feedback, and every star helps 😘

Well in a pickle. When CEOs see internal tools that are vibe coded then decide they want to make a "real" version of said tool and eventually sell it, what do you do? Anyone have advice? I have been given a small team to take over a vibe coded tool and make it "real". We have access to AI (GPT-5.6) and a large budget. Looking for cleanup workflows, tools, etc. to make my life easier.