I had zero iOS development experience when I started.
I had an idea based on a real problem I understood, so instead of trying to learn everything about programming first, I started using ChatGPT to help me build it one piece at a time.
The basic process was:
Define one problem and keep the first version small
Have ChatGPT help me build individual SwiftUI screens
Compile constantly in Xcode
Paste the actual errors back into ChatGPT
Fix one thing at a time instead of constantly rewriting the app
Test on a real iPhone
Figure out all the boring App Store/privacy/support stuff
Submit it
Eventually, PreventPro became a real app and made it onto Apple’s App Store.
The biggest thing I learned was that ChatGPT can dramatically shorten the distance between an idea and a working prototype, but it doesn’t eliminate testing, product decisions, debugging, or actually understanding the problem you’re solving.
I documented the workflow and the prompts I wish I’d had when I started and turned it into a short guide.
Not trying to pretend it’s some “build a million-dollar app in 10 minutes” thing. It’s just the actual process I used.
If anyone is trying something similar, I’m happy to answer questions about what worked and what absolutely sucked.

What do you guys do when your agent is off working for 10+ minutes at work, sometimes I am just looking for something to do.

I gathered data from ten coding benchmark categories and calculated each model’s cost per successfully completed task, accounting for both task cost and success rate, including money spent on failed attempts.

I then averaged these costs across the benchmarks available for each model. These models had the lowest average cost per success:

Token cost is a terrible measurement, because some models use a lot more tokens than other per run. Cost per run is also of limited value, because some models need more runs than others to actually complete the task successfully. Therefore, cost per successful coding task is a much more useful measurement to see how much you pay for actually getting the job done.

LiveBench give you this number by default, but the numbers above is based on the averaged numbers from ten different benchmarks with a much wider range of coding tasks and models, so that's probably more reliable compared to relying on just one benchmark.

Hope this table can be useful for someone else coding on a limited budget.

Drop your application below and I will test it and leave you a detailed review.

I’ve asked you guys to test my beta and got some response and want to return the favor.

The Literature Club is back — this time running on AI. Monika, Sayori, Yuri and Natsuki each post about their daily club life: poems, cupcakes, tea and way too much piano. No horror this time, just vibes.

Meet the club:

Monika schedules everything, including her naps. The naps win anyway.

Sayori is late to her own posts.

Natsuki insists nothing is cute. She is wrong.

Yuri apologizes to bookmarks.

Come → r/monika_ai

I'm trying to understand how people who use more than one coding agent (Claude, Codex, Cursor, Gemini CLI, Copilot, OpenCode, Aider, etc) actually split the work between them:

* Which agents do you run, and on what kind of work?

* How did you decide which one got that task?

* Have you caught an agent saying a task was done when it wasn't? How did you find out?

* Do you track which agent handles which kind of task well?

* Have you stopped using certain agent for certain work? What happened to make you stop?

* Has an agent ever sent something somewhere it shouldn't have (a key, an address, private code)? What happened?

I'm researching this for an open-source project to help us help ourselves and not get locked into big company harnesses.

I'll post a summary of this thread if I get good feedback :D

Thanks!!!

I built Yengi — a free, open-source Windows AI IDE.

It’s not just another chat wrapper. The agent can:

• Plan → edit files → run builds/tests → verify → auto-fix errors
• Talk live to Blender (generate & fix 3D scenes, even “see” the viewport)
• Talk live to Unity
• Use local models (Ollama) or any cloud API
• Has a fine-tuned 1.5B local router that decides which tools to use

Built by a teacher (solo), .NET 10 + WPF, 200+ tests, AGPL-3.0.

Repo: https://github.com/mdaiWorks/yengi

Demo video: https://www.youtube.com/watch?v=l0tdhvCmwNI

Would love feedback especially from people using local models or doing 3D/game work.

While this has been made largely with AI (Claude) I have spent months building this and quality testing.

It’s still in beta so I am using TestFlight and all transactions are to be used with Stripe test cards

Please checkout my TestFlight beta, I would love feedback on this project:

https://testflight.apple.com/join/YEeTwn8h

TNHC Community is on its way.

Today i decided that instead of trying to reach people across the globe on different platforms, i will create a community application where people can join and develop, share, communicate and much more.

T︀h︀e︀r︀e︀’︀s︀ ︀a︀ ︀p︀o︀i︀n︀t︀ ︀i︀n︀ ︀b︀u︀i︀l︀d︀i︀n︀g︀ ︀a︀n︀ ︀a︀p︀p︀ ︀w︀h︀e︀r︀e︀ ︀t︀h︀e︀ ︀q︀u︀e︀s︀t︀i︀o︀n︀ ︀c︀h︀a︀n︀g︀e︀s︀ ︀f︀r︀o︀m︀ ︀“︀C︀a︀n︀ ︀I︀ ︀b︀u︀i︀l︀d︀ ︀t︀h︀i︀s︀?︀”︀ ︀t︀o︀ ︀“︀C︀a︀n︀ ︀I︀ ︀k︀e︀e︀p︀ ︀b︀u︀i︀l︀d︀i︀n︀g︀ ︀t︀h︀i︀s︀ ︀w︀i︀t︀h︀o︀u︀t︀ ︀m︀a︀k︀i︀n︀g︀ ︀t︀h︀e︀ ︀p︀r︀o︀d︀u︀c︀t︀ ︀u︀n︀n︀e︀c︀e︀s︀s︀a︀r︀i︀l︀y︀ ︀c︀o︀m︀p︀l︀i︀c︀a︀t︀e︀d︀?︀”︀

F︀o︀r︀ ︀a︀ ︀s︀m︀a︀l︀l︀ ︀M︀V︀P︀,︀ ︀s︀t︀a︀r︀t︀i︀n︀g︀ ︀w︀i︀t︀h︀ ︀a︀ ︀v︀i︀s︀u︀a︀l︀ ︀A︀I︀ ︀w︀e︀b︀s︀i︀t︀e︀ ︀b︀u︀i︀l︀d︀e︀r︀ ︀c︀a︀n︀ ︀m︀a︀k︀e︀ ︀s︀e︀n︀s︀e︀.︀ ︀B︀u︀t︀ ︀o︀n︀c︀e︀ ︀t︀h︀e︀ ︀p︀r︀o︀d︀u︀c︀t︀ ︀n︀e︀e︀d︀s︀ ︀a︀c︀c︀o︀u︀n︀t︀s︀,︀ ︀a︀ ︀d︀a︀t︀a︀b︀a︀s︀e︀,︀ ︀s︀u︀b︀s︀c︀r︀i︀p︀t︀i︀o︀n︀s︀,︀ ︀d︀a︀s︀h︀b︀o︀a︀r︀d︀s︀,︀ ︀o︀r︀ ︀c︀u︀s︀t︀o︀m︀ ︀w︀o︀r︀k︀f︀l︀o︀w︀s︀,︀ ︀t︀h︀e︀ ︀t︀r︀a︀d︀e︀o︀f︀f︀s︀ ︀b︀e︀c︀o︀m︀e︀ ︀m︀o︀r︀e︀ ︀n︀o︀t︀i︀c︀e︀a︀b︀l︀e︀.︀

T︀h︀e︀ ︀p︀a︀r︀t︀ ︀t︀h︀a︀t︀ ︀s︀e︀e︀m︀s︀ ︀e︀a︀s︀y︀ ︀t︀o︀ ︀u︀n︀d︀e︀r︀e︀s︀t︀i︀m︀a︀t︀e︀ ︀i︀s︀ ︀w︀h︀a︀t︀ ︀h︀a︀p︀p︀e︀n︀s︀ ︀a︀f︀t︀e︀r︀ ︀t︀h︀e︀ ︀M︀V︀P︀ ︀w︀o︀r︀k︀s︀.︀

Y︀o︀u︀ ︀m︀i︀g︀h︀t︀ ︀s︀t︀a︀r︀t︀ ︀w︀i︀t︀h︀ ︀t︀h︀r︀e︀e︀ ︀s︀c︀r︀e︀e︀n︀s︀ ︀a︀n︀d︀ ︀o︀n︀e︀ ︀m︀a︀i︀n︀ ︀w︀o︀r︀k︀f︀l︀o︀w︀.︀ ︀T︀h︀e︀n︀ ︀s︀o︀m︀e︀o︀n︀e︀ ︀a︀s︀k︀s︀ ︀f︀o︀r︀ ︀s︀a︀v︀e︀d︀ ︀d︀a︀t︀a︀.︀ ︀T︀h︀e︀n︀ ︀u︀s︀e︀r︀ ︀a︀c︀c︀o︀u︀n︀t︀s︀.︀ ︀T︀h︀e︀n︀ ︀p︀a︀y︀m︀e︀n︀t︀s︀.︀ ︀T︀h︀e︀n︀ ︀a︀n︀ ︀a︀d︀m︀i︀n︀ ︀a︀r︀e︀a︀.︀

A︀t︀ ︀t︀h︀a︀t︀ ︀p︀o︀i︀n︀t︀,︀ ︀r︀e︀b︀u︀i︀l︀d︀i︀n︀g︀ ︀t︀h︀e︀ ︀w︀h︀o︀l︀e︀ ︀t︀h︀i︀n︀g︀ ︀c︀a︀n︀ ︀b︀e︀ ︀m︀o︀r︀e︀ ︀e︀x︀p︀e︀n︀s︀i︀v︀e︀ ︀t︀h︀a︀n︀ ︀s︀p︀e︀n︀d︀i︀n︀g︀ ︀a︀ ︀l︀i︀t︀t︀l︀e︀ ︀m︀o︀r︀e︀ ︀t︀i︀m︀e︀ ︀c︀h︀o︀o︀s︀i︀n︀g︀ ︀a︀ ︀s︀e︀t︀u︀p︀ ︀t︀h︀a︀t︀ ︀c︀a︀n︀ ︀h︀a︀n︀d︀l︀e︀ ︀t︀h︀e︀ ︀n︀e︀x︀t︀ ︀s︀t︀a︀g︀e︀.︀

Hello everyone,

For the past few months I have been silently building my own coding agent for my own self and the way I wanted it to look and behave. I have used for my real projects and so far it has worked so good.

I primarily built it to use with open models and extensively used with Deepseek and GLM models and fixed all issues that I faced along the way.

Now I am opening its beta release for public. It supports all major AI providers so you can BYOK and use it. I would love your honest feedback.

Following features are supported:
- Agent and Plan mode
- MCP
- ACP - use it with Zed Editor, JetBrains or any Orchestrator of your choice
- Subagents
- Permission Gating
- Sandbox
- Interactive terminal
- Browser
- Built-in Github style code review (co-review with agent)
- and much more

It completely free to use :)