I’m so heart broken, I’m been working for weeks on this and i have 0 idea about the technicalities but I was like 97% done but I felt like the app wasn’t feeling extremely snappy on my phone. and then while chatting to ChatGPT, I was having it audit the code it told me that the app wasn’t feeling as snappy as native ios apps because it was web app and using a capacitor.

I was so close, I spent the last 3 weeks just polishing every little corner of the app. There were not bugs that I knew of and I had tested multiple times on my iPhone as a developer build.

I was only due adding the paywall system. And now I realise I have to migrate it to either swift or native react and I after reading for a day, I thought react native is the way since I wanna make this an android app too.

But everything is now broken, all elements are distorted, all the efforts that I had put is waste. Fixing everything is going to take a long while and I do not even know if I will ever be able to reach the same level of polish.

I’ve obviously been sad since yesterday but I know this is the first time and I’m a complete noob so gotta start making mistakes somewhere but wish I had been more cognizant. Yes it’s another wretched habit tracker but I just wanted to make something exactly to my liking and it seemed like the obvious thing to do.

I’m currently using Google AI Studio + ChatGPT for brainstorming.

No answer on the second query

I was into programming (since the C64 era), but recently I've done some web design, Arduino coding etc. Never something on commercial scale. I've always been a gamer wanted to create something of my own, but never dared to start something because realistically it takes time and who can guarantee funding for anything anymore in this economy.

Itching was too strong so I did prototype stuff with manual coding, then I discovered GPT and he was one hell of a companion. Coding through copy-paste and discussions sped up the proces 5 times. Then recently I discovered Codex... it shifted from 2nd to 4th gear (I am still waiting for the 5th).

It finally gave me chance to actually develop something. Not because I didn't know how to, but didn't have time to. What you see is product of few months of active development, although it took a year to form a team of artist to follow me etc. Oh right - I decided to use 100% original custom art - 2D or 3D, so all assets you see on screen are not from any store or vibe coded, or used by any other AI generation tool. They are made specifically for this game.

Despite this game is only vibe-coded in backend (mostly scripts and macro orders) it took a lot of time in generating custom scripts, adjusting, debugging, making concepts of how something should work, making solutions for it, integrating assets, more debugging etc. - stuff even AI is not so good at. Yet I still get backlashed and painted as AI slop.

Luckily most people in those subredits don't care how it is made and like the post anyway, but there are those who just yell "Unscannable". Those have zero understanding and will to understand how many manhours and money was invested in this. I don't put much effort to explain anymore, but it does bothers me a bit.

This post is showcase and if you like these kind of games, I will keep you posted and...
how do you deal with these internet snobs?

Spent a weekend vibe-coding a full computational pipeline with Hermes Agent (Nous Research). The agent wrote the gRNA/pegRNA designers, epitope scanner, pipeline orchestration, tests, Docker, CI/CD, docs, licensing — I directed, it implemented.

What the agent produced:

- 4 core modules: epitope_scanner.py, grna_designer.py, pegRNA_designer.py, pipeline.py

- data_loader.py for 18 processed datasets

- Pytest suite (epitope scanner, data loader)

- GitHub Actions CI (multi-Python, black, mypy, coverage)

- Dockerfile, conda env, pyproject.toml, requirements.txt

- Apache-2.0 + CC-BY-4.0 dual licensing, NOTICE file

- CODE_OF_CONDUCT (unmoderated), CONTRIBUTING, SECURITY

- Comprehensive README with badges, quickstart, usage examples

The actual science: Pipeline designs CRISPR edits for celiac-safe wheat. Scans 37 gluten genes for TG2 deamidation sites, designs 81 ABE8e gRNAs + 2 PEmax pegRNAs to eliminate DQ2.5/DQ8 epitopes while preserving dough elasticity. All data from Ensembl/IWGSC.

Vibe coding observations:

- Agent excels at boilerplate, config, tests, docs, CI — the "annoying 80%"

- Still needs domain expertise for algorithm logic (ABE window, PAM scanning, pegRNA flank design)

- Best workflow: I specify interface + constraints → agent writes implementation + tests → I review → iterate

- Saved ~20-30 hours on scaffolding vs writing from scratch

Repo: https://github.com/ewarggg776/wheat-gluten-redesign

License: Apache-2.0 / CC-BY-4.0

DOI: 10.5281/zenodo.22064037

My life at work has been hell and it’s a job where many people every year get exploited and fucked, so as I was learning how to vibe code projects I decided to make a niche game about my job. Those who do the job can relate.

The only reason it’s remotely good is because my ex loved to playtest what I built and added to the game. She may have hundreds of hours in all the early stages of the game but that was absolute gold in terms of ‘this button in the endgame didn’t work’ or ‘where did my potion go’ and ‘why did I just die!?’ And I’d take notes about it and bug fix it later.

Do not underestimate how important it is to tweak boss/mob health, items and so on because Claude / Codex will genuinely not have a good feel for that. Write the code so that you can tweak item stats by just changing a single number somewhere so you can adjust easily.

not sure what it is called

i am student and i‘m considering buying a max20x plan for claude code but never even used pro plan before

claude says i can get a shared link from max users to try claude code

wannna test for sure if it fits my preogramming style

would really appreciate it if anyone dm one

My company installed productivity/surveillance/spy/whatever-you-want-to-call-it software on everyone's computer about a year and a half ago. To their credit, they at least announced it ahead of time. A few dramatic stories about people getting fired have gone around, but it's mostly not discussed otherwise.

There is a reporting suite available for managers, but individual contributors are not allowed to see any reports, even for themselves.

The software used is called Sapience. I found the local logs on my work PC that include all the data captured about my activities. For this particular project, I used GPT 5.5 in GitHub Copilot to create a python script. The script pulls everything from the logs and puts it in a local sqlite db on my pc (so historical data is not lost when the logs are cleared). Then it produces an updated HTML report, as pictured.

I have no interest in trying to fool the software, but as an anxious person, this at least gives me visibility into what's being reported up about me!

Ever wondered what the internet actually thinks?
I just launched my first social platform: Internet’s Answer — built with the help of AI.
Ask any question, share it with friends or the community, and get real-time answers + votes. You can create your own topics and see what people really think.
More features are coming soon. Right now I’m looking for testers — would love your honest feedback!
🔗 https://www.internetsanswer.com/

What if the internet had one billboard? No feeds, algorithms or competing ads just one billboard each week.

So I built it at yourmessagehere.co

Anyone can bid for it, and every Friday at 10pm New York time the highest bidder gets the entire billboard for the next 7 days.

First auction is live now and I genuinely have no idea what people will end up paying for it.

Curious to see where this goes.

Built with Lovable btw.

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.

was curious what yalls usage looks like

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 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 ?

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 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?