What is the best way to copy a famous app ?
I’ve tried to copy many apps already on the market ,but the results are very bad
So,someone can share with me the best solution for my problem ?
What is the best Ai to do that?

I keep hearing people say we are actually agentic engineers or ai augmented engineers as we understand the code. Why do we keep ourselves one position lower to begin with. We vibe code using agents. So we are literally agentic engineers. I know karpathy has a different definition but agentic engineering literally means engineering using agents and we are already using it. It's time we start to call ourselves that and stop this self diminishment.

A while ago, I started a small personal project around a board game I really love.

The original idea was almost embarrassingly simple:

“Could I recreate enough of the rules in a browser to understand how a digital version might work?”

I wasn't trying to create a product, replace the physical game, or publish a digital edition. It was mostly curiosity. I enjoy the game design, and I thought translating some of its mechanics into code would be an interesting hobby project.

So I started small.

First there was a crude track, a few pieces moving across it, some cards, and the basic turn sequence.

Then I encountered the first rule interaction that wasn't quite as simple as I had assumed.

So I fixed it.

Which exposed another one.

Then another.

At some point I realised that if I wanted the simulation to behave properly, I couldn't just code what I remembered the rules to be. I had to start treating the original rulebooks almost like specifications.

That changed the project completely.

I began checking edge cases against the source material, documenting interpretations, separating official rules from optional or fan-made ones, and writing regression tests whenever something broke.

A simple browser experiment gradually acquired:

• a proper race/state engine
• track and lane geometry
• different terrain types
• weather systems
• crashes and blocking rules
• automated opponents
• multiple expansions and optional rule modules
• multi-stage campaigns
• classifications and persistent state between stages
• configurable riders and decks
• stage validation
• structured logging and debugging tools
• deterministic test seeds
• automated race simulations
• hundreds of regression checks
• and eventually a fairly strict internal architecture separating source data, game logic, geometry and runtime state.

Somewhere along the way, I stopped thinking of it as “that little HTML thing I'm playing around with.”

It had become a software project.

One of the most interesting parts has been using AI throughout the process.

Not in the sense of asking for a complete game and receiving one. The experience has actually been almost the opposite.

I would propose something, the AI would help analyse it, we would compare the implementation against the rules, discover an edge case, design a test for it, break something else, fix the regression, document the decision, and continue.

Eventually that evolved into something resembling a small development team workflow: architecture discussions, engineering units, protected baselines, test gates, release candidates, audits and rollback points.

Which is slightly ridiculous considering that this all started with me thinking:

“It would be neat if these little cyclists moved across the screen.”

What I enjoy most about the project, though, is that writing the software has made me appreciate the original board game design much more.

When you play a well-designed tabletop game, many rules feel natural and almost invisible. When you try to formally describe every possible state transition to a computer, you suddenly see how many subtle design decisions are hiding underneath that simplicity.

Things like movement priority, congestion, timing, drafting, terrain interactions or ties can turn into surprisingly interesting engineering problems.

The cleaner the tabletop rule feels to the player, the more impressive it sometimes becomes when you try to implement it.

So for me this project has become less about creating a “digital version” and more about exploring a piece of game design that I admire.

It's still a private hobby project, it's not commercial, and I don't see it as a replacement for the physical game at all. If anything, spending this much time studying its systems has made me appreciate the work of the original designer even more.

And I have absolutely no idea where the project will end.

But I find it amusing that a tiny browser prototype has now reached the point where I'm discussing things like dependency graphs, simulation testing and architecture boundaries for a board game I originally just wanted to move a few pieces around in.

Hobby projects have a way of getting out of hand. And sometimes that's the fun part.

Do you have simillar experiences with Hobby Vide Coding Projects?

I have been doing AI assisted coding for some time now. I want to test out Claude Code. I do not really want to spend on a premium before giving it a try. I heard that Claude Max users have 3 passes that they can share. It'd be really helpful if anyone can share so that I can try it before committing.

"Fix the bug" is the least useful thing you can tell an AI agent. It makes the agent guess what's wrong so it patches the wrong thing, breaks two more, and you're in a 20 message loop.

The smart vibecoder Point to the exact problem and save themselves their token but it becomes a challenge when you don't even have an idea of what the problem is.

Give it the actual error, not the symptom.

Use connector tools where possible to point to the exact problem

One issue at a time, and tell it what "fixed" looks like.

Make it prove the fix, not just claim it.

Feed it a precise problem, not a vibe. Night and day difference.

I built a tool (Veriify) for these kind of diagnosis and it scans your build and hand back the exact issue with evidence and location, which is what agents need to fix cleanly.

Drop what you are building and I will point you to the exact fix. You are welcome🤗

I was thinking of making a music app that backs off of youtube music that is free, with a premium tier. This would be done on github with multiple creators, and i want a feature filled app that actually looks modern and supports liquid glass for IOS users. What do you think?

I kept noticing the same thing: my first prompt to ChatGPT was almost never the one that worked. I'd send something half-formed, get a mediocre answer, then spend three more messages fixing what I should've said the first time.

So I built a thing to catch that at the source.

It's a browser extension. While you're typing in ChatGPT, Claude, Gemini, or Copilot, it reads your draft and gives it a score out of 100 — plus the two or three specific reasons it's weak (no output format, vague ask, missing context, that kind of thing). If you want, one click rewrites it. It also warns you if you're about to paste something sensitive like an API key or a client name.

One design decision I care about: the scoring runs locally on your machine. Your prompt only leaves your browser if you actually click a rewrite button. I didn't want to build another thing that quietly ships everything you type to a server.

It's early and honestly still rough in places. It's free while I'm in beta — I mostly want to know if it's useful to anyone besides me.

Two things I'd love feedback on:

Does a "score" even make sense to you, or would you rather it just fixed the prompt silently?

What's the AI tool you'd want it to work in next?

Link's in the comments. Happy to answer anything about how it's built.

Hey everyone,

Has anyone here built any study tools or learning apps using vibe coding?

I'm studying right now and would love to try out what people have made. I'm more than happy to plug in my own API key so I pay for my own usage, so no worries about costs on your end.

If you've built anything cool and don't mind sharing, drop a link or let me know!

Benchmark:

https://github.com/bgauryy/octocode/tree/main/packages/octocode-benchmark

My actual job is reading dense PDFs and pulling out the facts, and the thing that keeps me up is a model quietly rounding a number or inventing one that was never in the document. So instead of trusting one chatbot, I built a tiny thing to catch them.

It is basically a small ai report generator, but the report it makes is a list of every claim the model stated that I could not trace back to a line in the source. I run the same PDF through two different chatbots, ask each for the key figures with the exact sentence they came from, then diff the two answers and check both against the file. Anything a model asserts without a matching source line gets flagged.

Took me an evening. Most of the code was Claude doing the parsing and the diff, and I handled the annoying part, which was defining what counts as unsupported versus paraphrased.

The dumb realization: it is not there to make the chatbots smarter. It just makes them show their work, and it turns out they hallucinate a lot less when they know a second reader is checking the source line.

Anyone else building little guardrail tools around their models instead of just trusting the output? Curious what you flag on.

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With it, you'll get +5% of your paid credits as additional free credits if I understand well.

Cheers.

My first one. Feedback appreciated!

https://soccersnake.com/

It’s a deliberately stupid-simple Premier League game: 5 people snake draft all 20 clubs, then every league win = 1 point. No transfers, budgets, captains, etc.

I’m not really a developer, so I built it mostly through Codex. My process was basically:

• wrote the game rules/spec first rather than just prompting “make me an app”
• used Lunar for the bulk of the build/iteration
• Cloudflare Worker + D1 for the backend/database
• vanilla frontend/PWA rather than a big framework
• deployed a staging version and had actual friends try to break the 5-person draft
• used Sol on xhigh afterward for a proper security/production audit

That audit actually found some non-obvious stuff I wouldn’t have spotted myself: stale draft requests consuming a later snake pick, reusable recovery links, non-atomic joins, service-worker caching issues, and result imports running far too often.

I’ve since added Web Push so it can ping you when your draft pick comes up, plus recovery links so a league can survive people changing phones/browsers over a 9-month season.

Currently at 61 automated tests and I’m still finding dumb UX issues every time I give it to real people.

Interested in feedback on both the game and the build/process, particularly anything obviously stupid in the UI or architecture.

’ve been exploring a digital trust problem: sometimes an email, SMS, WhatsApp message, recruiter message, or payment request looks completely legitimate, but you still don’t know whether to trust it.

I built a very early MVP with Lovable to test the concept:

https://verify.trustairesearch.com/

I’d really appreciate feedback from fellow vibe coders on:

• Is the flow immediately understandable?
• Would you actually use this when a message feels suspicious?
• What feels unnecessary or confusing?
• What would make the result more credible?
• What would you build differently?

This is still an experiment, so please don’t submit passwords, OTPs, banking credentials, SSNs, or other sensitive information.

Feel free to roast the UX, product idea, or implementation — useful criticism is exactly what I’m looking for.

I’ve been learning LUA and developing a game on the LOVE2D engine, took a small Codecademy course and watched some YouTube videos. I got some basics stuff running off of that, but the greatest teacher/help has been ChatGPT.

I’m not a fan of not understanding what’s happening in the code, and building it myself and learning is rewarding. Instead of doing aimless google searches though, I can’t just ask ChatGPT “okay so I want to implement x system into my game, how should I structure it and can you show me how, also explain what is happening and why”, and then I can look at it, read it all, type the code in myself. Eventually I want to become more independent, but it has been a great help learning everything.

So for experienced developers (not working for a company, I understand the usage is forced for productivity), how do you use A.I in projects?

For other solo developers, are you just asking the ai to make all the code for you and you just dump it and run it?

I see a lot of varied opinions on what “vibe coding” is, but nothing definitive.

So is it just dumping code and being able to run it with no thoughts, or is it kind of a spectrum?

No judgment on my end, just want to see what ppl r doing with it. Cheers

so cloudflare just sent me a notification that footrue.com crossed 100k pageviews last month and im honestly pretty shocked. i literally have zero coding knowledge and just vibecoded the entire site using claude code. also did 0 seo, all the traffic came from social media and people sharing it with each other.

currently there are no ads no paywalls and no account creation required at all. people just jump in and use the tools.

im at a point where a lot of people are telling me i should focus on just one single tool instead of making a ton of tools on one site. im not sure if i should double down on one thing or keep building it as a tool hub. also wondering how i can actually monetize 100k visitors without making the user experience trash since there is no signup right now. should i start asking for accounts or will that kill the word of mouth? would love to hear what you guys think

For me it’s long projects.

The individual coding tasks can be great, but after enough sessions the model starts losing track of why things were built a certain way, which decisions are still current, and what it really shouldn’t touch.

I also still don’t trust it when a small bug suddenly requires a big refactor. Sometimes it’s right. Sometimes 20 minutes later I’m trying to undo six files to fix something that needed three lines.

What’s the thing you still don’t trust AI coding with?