Okay so i have no idea how to code. I know this is much harder than all these people claiming “i made this app in 10 minutes and now im making 80k a month”….no.

I have apprehensions about this because 1. Idk how to code, which then leads to 2. Security vulnerabilities. Without the knowledge of coding and hosting databases etc it leaves a lot of room for error, especially for someone who really has no idea what they’re doing.

I have an idea for an app to accompany another business venture - i have the whole app visualised and how the system would work, onboarding etc etc. Really cool and unique ideas and features. I know im not capable of enough to build this app fully into production myself. But just an MVP would do.

So leads me to my question - what is your best minimal stack recommendations and other app template tools yous recommend. What AI is best (rork,claude,cursor)? How realistic is it for me to start from scratch and code the whole onboarding and back end with no experience?

Thanks

Today, I was working on a website for my first iOS application and decided to give Antigravity a try since I have Google AI account. I was blown away with the process to create the site and make modifications. In less than an hour I had my whole website up and running and didn’t spend any money except my subscription I already had. Seems Antigravity is great for quick landing pages and websites. Plus it’s only been out a little over a month. Google is winning at AI when everyone feared they would be destroyed.

Been seeing RPG fitness apps everywhere lately so figured I'd try vibing one myself.

Used ScreensDesign to generate the UI and honestly it's insane, all came out pretty clean.

Got full flows with microanimations already baked in which is sick, usually have to add those manually. Whole thing took like less than 10 mins- onboarding, dashboard, character progression, all of it.

Not perfect but way better starting point than other AI tools I've used. Thinking about feeding this to Cursor if designs hold up. What do you guys think?

I have been experimenting with vibecoding for a few months now with GPT and Claude. I have extensive programming experience so I'm good at reading code and understanding how it works and how different pieces come together. I have that shit down pat.

I have been giving ChatGPT and Claude firm instructions on what requirements I have and asking it to work within those requirements. The code almost never works on the first try if it's a complex request but refining the prompts fixes it, but the real danger is when the code seems to work but has logic flaws or security vulnerabilities.

Reviewing the code, it often becomes clear the LLMs don't have a full understanding of how the different pieces work together. For example, I recently had an issue that BOTH Claude and GPT couldn't fix until I found what the issue was and told them how to fix it.

There was a call from a render loop which would get the loading percentage from the background process which was doing the loading. There was another variable for load completion being set to true by the background thread, on the background thread, which would stop the background thread from continuing to run after it hit 100%. The problem was that this was happening before the render loop could read that it was at 100% so the loading never got flagged as complete on the render thread. In situations like this one both Claude and GPT completely failed to debug the problem because they couldn't understand the context. I had to specifically tell them what the problem was and how to fix it.

I really think the issue with AI code is how people will use it without knowing how to read code so they won't know if the output is any good or not.

At the end of the day, to an experienced programmer, AI ends up just being an overhyped form of auto complete. It speeds things up but relying on it for debugging or generating complex projects for now is still a fools errand.

Those are just my thoughts I'm open to changing my view but I'd like to hear everyone's thoughts on this.

i know literally NOTHING about coding. ZERO. and i just built a fully functioning web app in minutes

http://localhost:3000/

check it out

I want to share a project build experience (MealCost - Food Costs), because this was my first real build.

This app started as a idea on Christmas Eve,2025 — literally a “why don’t I actually know what a single meal costs?” moment. By Jan 13th '26, it was live in the App Store. That timeline still feels a little unreal.

Important context

I have no formal coding experience. I’m a systems administrator at heart — I’m comfortable with tech, infrastructure, and troubleshooting, but writing Swift (or any coding language) from scratch was not something I’d done before.

Cursor made that gap bridgeable.

What the project is

MealCost - Food Costs is an iOS app that tracks food spending by cost per meal instead of weekly or monthly totals. The goal was one clear number: what did this meal actually cost?

Tools I used

• ChatGPT - translate my ideas into Cursor prompts

• Cursor — this was the key enabler and software designer

• Xcode — local builds

• TestFlight — testing, feedback

I intentionally kept dependencies minimal. Fewer moving parts = fewer vibes broken.

How I used Cursor (the real magic)

Cursor wasn’t just autocomplete — it was more like a patient pair-programmer that never got tired.

I used it to:

• Translate intent → SwiftUI code (eg. “I want this screen to feel simple and obvious”)

• Refactor messy state when things started behaving oddly

• Ask “why is this wrong?” and actually get a useful explanation

• Generate first-pass implementations that I could then tweak

I had to review iteration after iteration of XCode builds and make decisions, but Cursor drastically lowered the energy to try new and different ideas.

Process / workflow

My loop looked like this:

1. Describe the feature in plain English into ChatGPT

2. ChatGPT would create the cursor prompt

3. Provide the prompt to Cursor and let it scaffold something reasonable

4. Build in Xcode, watch for errors

5. Provide error transcript to Cursor and have it fix

6. Repeat Step 4-5 until build succeeds

7. Run it, break it, learn why, or accept the current state

8. Start back at Step 1 with a new idea

I kept asking one question: does this help someone understand their food costs faster?
If not, it didn’t make the cut.

Things I learned

• UX clarity mattered more than features

• Cursor is not thorough and tracking potential bugs it may insert when presenting it with a prompt for a new feature, I had to complete Steps 4-5 FREQUENTLY

• App Store review + In App Purchase setup took longer than expected, 5 full days from when I first started that effort until it was availabe in the App Store

• TestFlight feedback has been mostly about confusion, not bugs — valuable

hey there, I just lost my dev job in the automotive industry. it was just a massive layoff, it had nothing to do with vibe coding.

at my workplace we where using github copilot. in a responsible manner, as a productivity booster. but nobody, even the managers where believing this could save developers.

I am just asking myself if there really are job losses where some managers believe they can vibe code something as good as a dev could do. to me it rather seems like an urban legend.

what do you think?

Hey folks. I wanted to write this up because I keep seeing people say that AI assisted coding isn't ready for real production environments. That is just not true.

For context, I am an AI SWE with about a decade of experience. I have spent half of that time at FAANG or similar big tech companies. I actually started as a Systems Engineer before moving to dev, but I have been coding for around 15 years.

Here is the actual workflow we use to ship prod code with AI.

1. The Technical Design Document You always start here. This is where the real work happens. It starts as a proposal doc. If you can get enough stakeholders to agree that your proposal has merit, you move on to developing out the system design itself. This includes the full architecture and integrations with other teams. We usually live in Google Docs for this phase since the commenting features are essential for async debate and resolving open questions before we commit to anything.

2. The Design Review Before you write a single line of code, you take that design doc and get it absolutely shredded by Senior Engineers. This is a good thing. I look at it as front loading the pain so you don't suffer later. We use Excalidraw heavily here to whiteboard out the architecture during the meeting so everyone sees the same data flows. If you can't explain the system visually, you probably don't understand it well enough to build it yet.

3. Subsystem Planning If you pass the review, you can now launch into the development effort. We spend the first few weeks doing more documentation on each subsystem that will be built by the individual dev teams. This might feel slow, but writing detailed implementation specs means you catch edge cases early. We usually link these directly to the original design doc so the context never gets lost.

4. Sprint Planning This is where the devs work with the PMs and TPMs. We hammer out discrete tasks that individual devs will work on and the order they need to happen. We track all of this in Jira (unfortunately) but it gets the job done for organizing the chaos. The goal is to make the tickets small enough that an AI agent can digest the context without hallucinating.

5. Development This is where we finally get hands on the keyboard and start crushing task tickets. We use Test Driven Development, so I have the AI coding agent write the tests first before building the feature. To speed this up, I rely heavily on voice dictation because speaking complex logic is significantly faster than typing it out. I’m testing WillowVoice right now for this since the sub-second latency and accuracy are solid for technical prompts and emails. I'm open to other suggestions, but right now it is a major accelerator.

6. Code Submission Review We have a strict two developer approval process before code can get merged into main. AI is also showing great promise in assisting with the review. We use standard GitHub PRs, but we are experimenting with AI bots that auto-comment on potential bugs or style violations before a human even looks at it. It saves the reviewer from having to nitpick.

7. Test in Staging If staging is good to go, we push to prod. We rely on Jenkins pipelines to automate the testing suite here. If the green checkmark appears, we feel confident shipping it.

The Result Overall, we are seeing a ~30% increase in speed from the feature proposal to when it hits prod. This is huge for us.

TL;DR Always start with a solid design doc and architecture. Build from there in chunks. Always write tests first. Use tools to handle the friction so you can focus on the logic.

Thinking of something in health sector or may be something on top of Splitwise what features can i add. Please suggest

I recently launched  to pentest web apps for security vulnerabilities, so far we have found and reported over 50 security issues, including 10 confirmed CVEs.

Drop your vibe coded project below and I will send you a report within 5 hours

I’ve been thinking a lot lately about where the software engineering world is headed. With AI, automation, and all these new tools, I’m wondering what the future really looks like for developers.

• Will jobs become harder to find, or will there be more opportunities?

• How will the market for software developers change over the next 5–10 years?

• What about people who are just starting to learn programming—what’s their future like?

I’d love to hear your thoughts, experiences, or predictions. Is it still a good field to get into, or should beginners start preparing for a different kind of tech landscape?

Amish people believe in simpler times, but it’s a time right before real modern advancements, but right after some decent advancements, like wells, and plows, and clothing, etc.

AI has made me this. Because I believe that’s where we’re at. Right before AI takes over, but right after it’s useful to make my life better.

I intend to stay in this phase until I die.

Good luck to all you vibe coders. Bless your hearts. But I’ve found where I’m comfy. What comes next won’t affect me. I’m putting on my amish hat and eye flaps, and ignoring the oncoming programming apocolypse. ✌🏻

Hey all! I’m fairly new to vibe coding.
I've been hearing that Replit or Horizons is good options for beginners.
Is Horizons a good choice to start a project, or should I jump ship to something else before I get too deep? Would love to hear what you all think

Hi everyone 👋

I’m Elena, PM on a new JetBrains product called Matter. We’re a small team building a web-based “vibecoding” environment for existing codebases, so PMs, designers, and devs can prototype or make small changes directly in real code – no local setup needed.

The core idea:
You connect a repo once → Matter spins up a live preview → non-dev folks can iterate by prompting, clicking around, and leaving feedback. Developers can jump in when needed, and everything stays reviewable.

A few things we focused on:

• No local setup: Connect a GitHub repo, get a live preview, start experimenting. Setup usually takes ~2–5 minutes (even for large monorepos).

• Works with real-world stacks: Supports common frontend setups (React/Vue, Vite/Webpack), plus more complex environments like Docker-based projects and custom backends.

• Non-dev friendly (by design): Versions are tracked automatically, so you don’t need to understand git upfront or worry about breaking branches.

• Safe experimentation: Everything runs in an isolated sandbox. Nothing touches production until a dev reviews it.

• Collaborative workflow: Share live preview links (think Figma-style sharing), invite teammates, leave comments, and iterate together.

• Easy handoff to engineering: When something looks good, Matter can generate a spec and open a GitHub PR for review.

Matter already integrates with Figma, and Linear integration and Storybook support are in progress.

This is still early, and we’re actively looking for feedback – especially from folks who work closely with engineers but don’t want to set up a local dev environment just to prototype or tweak.

If this sounds interesting, you can check it out .

If you prefer a walkthrough, we also showing how Matter works end-to-end (demo starts at )

Happy to answer questions or hear skepticism too. 🙂

Hey everyone,

I’m sharing a project I made called .

The idea came from trying to save on my energy bills. I was getting fed up with hanging laundry out on "sunny" days, only for it to stay damp because the humidity was too high, which usually meant I gave up and threw it in the dryer anyway.

I always looked online for a better way to check the "real" drying conditions, but I was disappointed by websites being too complicated to answer the simple question “Should I dry my clothes outside today?”

I wanted a tool that told me exactly when I could get away with a free outdoor dry, so I built one.

How it helps save money: Instead of just checking for rain, it pulls real-time data for humidity and wind speed to calculate the actual evaporation potential. It basically tells you if the air is actually capable of drying your clothes today.

Features for the frugal-minded:

•Indoor Tip: If it's a "NO" day, it gives a quick tip on the most efficient way to dry indoors.

•Day Outlook: A grid to help you plan your "big wash" for the cheapest/best day of the week.

It’s totally free and I don't run ads. it’s just a tool I built for myself to help lower my own bills, and I thought it might help some of you out too.

I have 27 years in as a professional software engineer, mostly in the game industry, and I've been vibe coding from a "pretend I don't know anything" standpoint to explore capabilities.

I've been impressed, especially with Opus 4.5 and I'm convinced we're at a point with code that assembly language was at when I first learned to make games. Namely, if you were making shareware or freeware games independently for selling, learning, or fun, you could get by without knowing assembly.

There were still some limitations (Many AAA games back then had too many sprites on the screen [and a bit later they were 3D] to work well without assembly optimizations, just like it would probably be impossible to fully vibe GTA 6 or irresponsible to fully vibe software for hospital equipment) and very few studios would hire game developers who didn't know assembly.

Fast forward a few years later and nobody cared if you knew assembly language - which I expect to repeat with knowing how to code (and yes, I'll take flak from developers rightly pointing out that compilers are deterministic while AI is probabilistic, but when the probabilities get high enough the effective difference will be negligible).

That said I think learning to properly engineer and architect software will remain critical in order to stay ahead of the "AI is eating software" wave as long as possible. We're headed towards a time when models get good enough and cheap enough that we'll just ask them to directly to solve the problems we create software for.

For example.

1. I don't need a word processor, spreadsheet or presentation software if I can give my data to a model and have it spit out a perfect annual report for my stock holders.

2. I don't need amazon's app to shop if I can just ask a model to search the web to find the best product at the best prices for my needs.

3. If I get tired of asking a model for edits, the model will be able to generate an image editor on the fly tailored to my exact preferences based on what it knows about me.

Until then, ,and I have no idea how long we have, I firmly believe that (unless you're vibing for learning, fun, or just looking to win the app lottery) learning to properly design engineer and architect software will allow you to ongoingly build the more and more complex applications that can deliver value over what a frontier model can give you directly.

Decided to give this a try as a developer of ~15 years. Wanted to start a project and see how far (and fast) I could get without doing much coding myself.

I'm 3 days in and I'm already at 30% of my premium monthly usage with the lowest paid plan for CoPilot. Doesn't seem very sustainable as I'm not looking to break the bank for kicks & giggles. Are there better options out there or are you all just burning through tokens like an 8 y/o at Chuck E. Cheeses?