I Have a Project with ~200k Loc, Written with AI Codegen. Ama
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I have a programming background, have worn many hats including being a founder, CEO and product manager.
These days I use Codex, with GPT-5-Codex + $200 Pro subscription. I code all day every day and haven't yet seen a single rate limiting issue. Have worked with Cursor + Opus/Sonnet a lot before.
We've come a long way. Just 3-4 months ago, LLMs would start doing a huge mess when faced with a large codebase. They would have massive problems with files with +1k LoC (I know, files should never grow this big).
Until recently, I had to religiously provide the right context to the model to get good results. Codex does not need it anymore.
Heck, even UI seems to be a solved problem now with shadcn/ui + MCP or magicui + MCP.
My personal workflow when building bigger new features:
1. Describe problem with lots of details (often recording 20-60 mins of voice, transcribe) 2. Prompt the model to create a PRD 3. CHECK the PRD, improve and enrich it - this can take hours 4. Actually have the AI agent generate the code and lots of tests 5. Use AI code review tools like CodeRabbit, or recently the /review function of Codex, iterate a few times 6. Check and verify manually - often times, there are a few minor bugs still in the implementation, but can be fixed quickly - sometimes I just create a list of what I found and pass it for improving
With this workflow, I am getting extraordinary results.
The project is an "AI meets BI" tool for businesses that need to analyze lots of their business data at scale and coordinate data-based objectives called EdenLM - https://www.edenlm.com/. For that I use AI agents with access to different tools (e.g. for generating and running SQL queries).
The next "frontier" is building a code generating agent with code generating agents (very meta) in order to offer a catalog of consistent, reproducible metrics tailor-made for each specific customer.
AMA.
The author shares their experience of building a 200k LoC project entirely with AI code generation tools, achieving extraordinary results with their workflow, and discusses the potential of AI in software development.
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Sep 23, 2025 at 2:37 PM EDT
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What makes me confident is that:
a) I have tested the solution extensively with data from my previous business and BOY did I get good results. So the technical aspect works. b) I am seeing early traction, people reaching out to me once they read about what I am doing. Even big firms trying to tame their data mess.
I am still early days and the biggest challenge is not going to be the tech - although it is an amazing challenge too.