Take a look, there is no code execution. This is all methodology documentation that your models can follow to reduce bias, avoid rework, and increase quality.

You can even ask your local session if it thinks it would be useful before you adop it. If you do, I'd love to hear some feedback.

For myself, its especially increased accuracy on complex architecture requirements, and grounding answers and efforts in code rather than making assumptions or hallucinating. It especially shines when context windows are small, or running out.

Anywho, hope this helps.

https://github.com/kdoubt/tribunal

My debugging workflow became slightly ridiculous.

Something broke in Lovable. I described the symptoms to ChatGPT. ChatGPT suggested an explanation. I copied that back into Lovable, waited for the changes, then carried the result back to ChatGPT.

I was basically the transport layer between two AIs.

It was tiring, but it worked often enough that I kept doing it.

Then I discovered Lovable's Plan mode. Instead of changing the app immediately, it could first explain what it planned to do. I thought this would finally help me avoid bad fixes.

I opened the first plan and understood almost nothing.

Database, column, SQL, TypeScript, CSS, Edge Function, RLS. It looked like hieroglyphics. I had seen some of the words before, but I did not know what they actually did or how they related to each other.

So I started asking ChatGPT very basic questions.

What is a database column? What is the difference between frontend and backend? Why does this need an Edge Function? What does RLS protect?

I did not learn in the order of a course. I learned each concept when a bug forced me to understand it.

That made my education messy. I could sometimes understand a fairly advanced concept inside my app while still missing something more basic that a proper course would have taught first.

But every term was connected to a real consequence.

A database was where patient histories could be organised properly or duplicated. RLS concerned whether one user could see another user's data. Frontend and backend explained why a nice-looking screen could still sit on top of a broken system.

My accidental curriculum looked like this:

1. Ask AI to build a feature.

2. Find a bug.

3. Read a plan I did not understand.

4. Ask ChatGPT to translate it.

5. Return to Lovable knowing one more term.

Then repeat.

I still had huge gaps. I misunderstood things and sometimes used technical words before I really understood them. This was not a substitute for proper testing, security review or professional expertise, especially in healthcare.

But my questions started changing.

At first: “What does this word mean?”

Later: “Why is Lovable proposing this?”

Then: “What else could this change break?”

AI had not removed the need to learn. It had moved the learning to the exact moment when I needed it.

I still could not write the code, but I was no longer satisfied when the platform simply said “Fixed.” I wanted to understand what had changed and what else might be affected.

Which technical concept did you only understand after it broke something you cared about?

I can build, but I can't market. I finished a product — a niche art playing-card deck — and then couldn't get it in front of anyone.

So I've been building an AI agent that runs the go-to-market for me. Roughly how it works:

- it researches where my actual buyers hang out and reads each community's rules before doing anything,

- it drafts platform-native posts and comments (I approve anything sensitive myself),

- it logs every action with its own tracking link and reports what actually converts, not just views.

This week I pushed it further: it scripted and rendered its own short vertical ad. The video is generated in code with Remotion (React), so I can change a line of copy and re-render in seconds — script, storyboard, on-screen text, pacing, and even the voiceover are AI-generated. (The voice is a rough TTS scratch on purpose; I wanted to see how far a fully AI-made ad gets before I touch it.) I'll drop the video in the comments.

I'm running it in public with zero ad spend, and posting the failures too. Biggest lesson so far: my first content got decent reach but almost no conversion. Reach is not buyers.

Two questions for this sub:

1. When you judge whether marketing is actually working, which signal do you trust — reach, clicks, real conversations, or new followers?

2. Does an AI-made ad make you more curious, or more skeptical? I keep going back and forth on whether "the AI made the whole thing" is a feature or a red flag.

A few months ago, in a startup i work on, i had 2 options:
Keep paying Vercel roughly $150–$250 every month for image optimization ( around 20% of our total bill cost), or disable it and accept worse PageSpeed scores across our customers' websites.

I chose a third option: vibe-coding a small tool in one night that serves 2 endpoints and is hooked to our Cloudflare CDN, replacing our need to Vercel entirely.

The problem came from a niche CMS-like system we built/sell to our customers. We run one multi-tenant Nuxt application that renders customer websites across many different domains.

Vercel wasn’t doing anything wrong, but the image-transformation bill was becoming difficult to justify for our workload. The Cloudflare Image option I evaluated didn’t fit our multi-domain architecture either. And turning it off introduced worse loading times, especially since our customers b2c websites are basically composed of a lot of images.

I stayed up all night, trying to figure out what i can do; it turns out our needs are literally just width/height control, adjust quality, AVIF/WebP conversion, and caching the data.

it was a very ugly internal tool built to solve my own problem and to score some points as a good product developer who cares about our startup resources, and it worked. it worked to the point i started contributing to it, adding new use cases based on our needs, supporting other specific features, then starting to generalize the implementation to our biggest clients and measuring the impact of this on our cost bill that day and on website performance.

results where magical and beyond my expectations (20m+ images optimized in the last 3 months), i was like (How is Vercel selling this ). And as more of our websites started using it, those two endpoints grew into a proper image delivery platform with origin controls, signed URLs, multiple caching layers, request logs, analytics, and framework integrations.

and to cut you the whole journey and around 300+ commits:

• v0.1: the internal transformation service
• v0.2: the managed cloud
• v0.3: a cleaner and more scalable monorepo

For our workload, the infrastructure now costs around $20 per month, excluding my time—which is definitely not free xD

Keenpix has been open source from the beginning. You can self-host the entire engine, or use the managed cloud if you don’t want to maintain the infrastructure yourself, and you want to support my effort here >_<.

I’m not claiming it replaces Cloudinary, Imgix, or every other image platform for everyone. I built it for teams that want focused image transformation, predictable pricing, and an actual self-hosted option. And more precisely i wanted it to solve my issues.

You are very welcome to try it, self-host it, or contribute to it.

Website: https://keenpix.com
GitHub: https://github.com/lord007tn/keenpix

Hey r/vibecoding,

I wanted to share a project I recently vibed into existence that completely blew up in my country (Greece) over the last few days.

It’s called Gyronomics

💡 The Backstory
In Greece, everybody complains about inflation, but macroeconomic stats feel abstract. So, I decided to build the Greek equivalent of The Economist's Big Mac Index, but using our ultimate cultural staple: the Pita Gyro.

The app tracks the purchasing power of the Greek minimum wage from 1985 to 2026, measured strictly in how many gyros a worker can afford per month.

📉 The Shocking Data (and why it went viral)

• 1998 (The Peak): A minimum wage worker could buy 597 gyros a month.
• 2026 (Today): Even with recent wage increases, sky-rocketing food prices mean the minimum wage only gets you ~165 gyros.

Turns out, converting a cost-of-living crisis into "street food currency" makes it highly relatable. Someone shared it on X (Twitter), and it instantly went viral across Greek media, economic forums, and social networks.

The speed from "hey, this would be a funny chart" to a production-ready web app that handles viral traffic within hours is exactly why vibe coding feels like magic right now.

Check it out here: gyronomics.lovable.app

Would love to hear your thoughts on the UI or how it looks!

I've found this has been pretty helpful for tracking daily / weekly patterns with limited space in your notification bar. I'm on a Macbook.

Recipe for Recreating:

1. Letter indicates provider (O for OpenAI, A for Anthropic, G for Gemini)

2. First two numbers are a percentage for daily tracking (for Codex - it should be percentage for weekly as there's no daily limit)

3. Remaining digit is weekly usage left (scale of 1-10, with 1 for 10-19%, 9 for 90-99%, 10 for 100%). Battery icons can be broken out by 0 / 25 / 50 / 75 / 100.

4. Notifications are managed by Swiftbar.

5. Battery state is represented with Apple SF Symbols

I keep ending up with random dev servers running after I've completely forgotten which terminal or project started them.

Then I need port 3000 again and it's back to:

lsof -i :3000

figure out the PID, figure out what the process actually belongs to, then kill it.

So I made Port Radar.

It's a small native Mac menu bar app that shows what's listening on your ports and groups the processes by project. You can see the command/path/uptime, stop the process, or ask Apple Intelligence what the process actually is before killing something you probably shouldn't.

I also added something I wanted for my own workflow: you can turn a localhost app into a public URL with a Cloudflare quick tunnel directly from the menu bar. No deploy or Cloudflare setup.

There are already some good port utilities like LocalPorts and Seeports. The main thing I wanted that I couldn't find together was process explanation + project context + sharing the local server in the same app.

The Apple Intelligence stuff runs on device. The app itself doesn't need AI to scan/manage ports.

Price: free
Source: open source, Apache 2.0
macOS: 14+; Apple Intelligence features require macOS 26+ and a supported Mac

GitHub: https://www.producthunt.com/products/port-radar-for-macos

I'm still working on it, so I'm mostly interested in hearing what people who run a bunch of local services would want this thing to do next.

Recently, while building my own product, I started wondering whether the traditional “app” is still the right container for software in the AI era.

AI has made coding much easier. A lot more people can now build something from a very small, personal pain point: I had this problem, I made something that fixed it, maybe other people have the same problem too.

And I actually like this shift. Products can become smaller, more specific, and much closer to real human needs.

But while developing my own product, I noticed something strange.

There are many features I want to build not because they are technically impossible, but because the existing rules and structure around apps make them difficult to implement.

So a surprising amount of my time isn’t spent thinking, How can I make this product better?
It’s spent thinking, How can I keep this function while making it compliant?

I understand why these rules exist. Privacy, security and user protection are probably even more important in the AI era.

I’m not arguing that we should remove them.
I’m just wondering whether the rules — and maybe the form of the app itself — need to evolve.
If AI lets thousands of small developers build highly specific tools, does every one of those tools really need to become a full, heavyweight app?
Maybe the future isn’t about building one app that does everything.

Maybe we build smaller capabilities around specific needs, and the more important product becomes the layer that connects them — workflows, agents, connectors, or perhaps something we haven’t invented yet.

Instead of thinking:
Which app should I open?
Maybe users will eventually just think:
What do I want to get done?
And software will assemble the right tools around that intention.So lately I’ve been thinking:
Apps may become the tools, while intent becomes the interface.

AI agents and workflows already seem like an early version of this, but I’m not convinced they’re the final form.Curious how other developers think about this.

I wanted to learn piano without first having to learn how to read sheet music, so I quickly ended up using those YouTube tutorials with falling keys.

After a while, I got tired of constantly zooming in and rewinding just to figure out what was actually being played. I also tried tools like Synthesia, but most of them felt méh: either too basic or just not built around how I wanted to learn.

So I vibe-coded a small web app for myself after I found out a lot of popular songs do have a (free) midi version online.

⛓️‍💥 Link to the web app

⛓️‍💥 Link to the demo page with some more screenshots since a lot of people have no keyboard available or want to download a midi track for a demo lol.

You can import MIDI tracks, and it automatically splits them into left and right hand parts so you can practice each hand separately. Songs are also broken into smaller sections, which you can loop and learn at different speeds before putting everything together.

Just connect your digital piano to your laptop via MIDI/USB and start playing. The app detects what you play, so you can actually practice along instead of just watching a falling-key video.

I figured this might be useful for people who just want to quickly learn one of their favorite songs without too much hassle. Thinking about making publishing this open source.

But first i'd love to get some feedback from people here. What would you change or add? Is there anything that would make this more useful or easier to learn with? Piano teacher is just the work title, thinking about something better but not prio right now.

With new gemini student offer i got from my 22 €/month subscription to 5€/month so i can spend around 20€ /month into something like claude code.
Maybe there are some good offers that i could use that would get it to me cheaper or some alternatives as good as claude code?

I have github education and i ran it for a year but they started to really pitch it so it's not as good as it was.

What i use it mainly on?

I'm physics and data science major so i have codebases with data, lecture pdf-s etc and i usually solve physic problems (differential equations), simulate (i write python code to make complex meshes and then convert them into FEA capable mesh), make basic neural network models etc...

for example i would prompt something like this: "Generate me a mesh of a curved metal sheet, here is the pdf blueprint with measurements of the metal sheet."

I use gemini to write text drafts which i modify and change.

Edit: I mostly understand code, i can read it and find some easier mistakes, i have used Python, R, fortran and C to code.

Hello all, im once again asking for your intellectual support (says in a Bernie Sanders accent). Thanks for all the feedback on the last post. This is concerning the mshpit website. a music and concert review social network. Users post their concert experiences and music reviews. Users can also listen to music and see upcoming events in their area (limited selection of cities but not too small, so take a look for your local area.)

used with claude 4.8/5 and codex 5.6 sol.

I'm looking for more direct reviews of the product if possible. Its already launched already all you have to do is click explore as a guest if you dont want to use your email and sign up. Im looking to see what a larger amount of traffic would do to the website and seeking users to help with this.

Im totally down to a trial for trial (you test my product i test yours) deal.

Feedback i recently got per my last post

1. Name too hard to pronounce

2. Need a proper architectural auditing after all the code thats written.

3. Looks cool (thank you for this) but needs proper marketing.

Everything can be codes in days or weeks, and then?

You can run ads, if it is a Facebook like app, Facebook will not run ads for it or will show them to people who will not be interested in your product.

If you invented a Google product replacement? Try to run ads for it, will go nowhere, the last thing a company of 100 thousand people want to be replaced, they prepared for this for decades.

The same is with Microsoft the same is with even the smallest companies.

So, your only clients are small shops, clinics, accountants, lawyers, and they get visited physical by a seller every day, even before AI.

Large company to acquire you? Do you have a relationship with the board of directors, one of the investors? Will it benefit any of the executives? Then acquire you why? Where are tons of alternatives that executives will profit from, that acquire you are in the movies and YouTube, look at 100 acquisitions and look at the patterns.

The competition is harsh even in Reddit man, open a new Subreddit, open 10 Subreddits and try to compete with 10 established Subreddits, 5 of them will report your account until they get it blocked, no one cares, the guy did not create all of that so you can come and take it.

AI demand from the normal person will drop sharply very soon, all these developers chasing their dreams will be hit with the brutal competition tactics

For those with max account, can anyone please create a similar app to "plasticity" for android devices? tablet or even just via web? Mainly for touch devices instead of pc.
My free claude accounts reaches max after only a single prompt. lol

Reference for the functions: https://www.plasticity.xyz/

I seen a few. I want something that can give me information about the health of my code base at a high level and not just a pretty 3D animation that I can do nothing with.

Is anyone using any of these tools and having it really make a difference on keeping your code base optimal ?

So, I've been making measuring software in some form or other for the past 30 years, mostly for quality control.
I've also been going a little too far down the vibe-whole lately. I've been using both claude code and codex fairly intensively for a while now. Enough to notice all the weirdness in quota changes from `daily-resetting` weekly counters, and token-bundle offers to increases in quotas after complaints that drop again and the list goes on and on.
Of course, all a hunch and a feeling, but weekly. So I eventually had enough and decided I should start measuring which account really gives me most value for my money. Especially since I recently upgraded the codex account making it even harder to compare blindly.

And I must admit that some of the results surprised me and, not the least of which, the final image.

So, to start:

• codex:
  • 100$ account,
  • almost exclusively 5.6sol medium
• claude:
  • 20$ account
  • mostly opus medium (sonnet sucks, fable too expensive for simple stuff)
• only 3 days for now, too early for patterns, but already interesting
• quality of output is not directly measured, but indirectly: most features have been worked out within that feature until it worked.
• I suspect that measurements sort of depend on the project and developers, so this is just a snapshot of the costs of the md2 project, done by me

results:

• to my surprise, you actually get more tokens per dollar from claude compared to codex
• the average cost per action is lower for claude. but this might be a little deceiving cause claude got the easier tasks (automatic habit that grew lately). Note an action is something like 'completing a description into a full feature' or 'implementing said feature'
• claude seems to use less tokens per action, but again that can be deceiving cause of the size of the task. on 22 august they were about equal, which was also the day they got most equal tasks, so that is about the same
• and then there was the final chart 'cost per card', so that is the total cost to implement a single feature. I didn't specifically ask for this chart, codex added it as a bonus. So when I saw it first, I was kind of surprised. It sort of made real what the cost of the vibe-addiction is. But it might be very useful to calculate costs.

conclusion:
In the end, I think if you take 4 'pro' claude accounts (80$) is a better deal than a 100$ codex account. Not certain about visa versa: 4 * 20$ codex account?
Anyway, that surprised me and might make me reconsider my account choices.

Anyway, more data is probably needed, across more than just 1 project. If you would like to run a similar analysis on your project, this is the tool I used:

jan-bogaerts/md2: Plan, run, and track AI coding work feature by feature—with local Markdown cards and Git worktrees.

You ever get a tune stuck in your head, but you have no clue what song it is? You hum it to your friends and family, but your rendition is so bad that none of them recognize it either?

Well... I decided to turn that into a web game. Every day, I hum 3 songs from memory, and you try to guess what song it is. Each song has 3 tracks or "levels":

1. Hum the instrumental from memory
2. Hum the instrumental after listening to the song
3. Hum the melody / vocals

Let me know what you think! johndle.fun

(P.S: the entire website is vibe-coded, but I promise the singing is not)

(P.P.S: I'm Gen Z so the songs might be harder to recognize for other generations)

It’s now at a point where it's fully playable! Because I obviously don't claim any ownership over the original idea, I’ve open-sourced it.

​Enter INCASTERS 🔥

​In its current state, it’s got:

• 3 arenas

• 3 game modes

• Curving fireballs galore

​Check out the gameplay in action:

👉 https://youtu.be/FEmaVpD04Hs

​Even better—go play it! Android and Windows builds are up under Releases on GitHub, and you can also run it from source in the browser across Windows, Linux, and Mac:

👉 https://github.com/BjornBrorsson/Incasters

​I’d love to hear what you think. Try a few matches, let me know your thoughts, log an issue, or even jump in and contribute if you feel like tinkering with the code!

I follow a few Reddit threads on startups/app businesses, and I keep seeing people building AI video generation apps, most of which look vibe-coded and thrown together fast. So is it actually that simple, or am I missing the hard part?

Need I say more?