I am working on a project with ~200k LoC, entirely written with AI codegen.
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.
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.
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.
AMA.
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.
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.
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.
AMA.