Reading comments, I’m curios why would someone spend thousands for LLM coding? What are you building to justify these skyrocketing token consumption? I’ve been using AI coding since GitHub copilot was in beta, used all IDEs in the market, and had very few occasions when I passed the $20 subscription limit. And when I did, that was when I decided to move from cursor to CC and Codex, and still, using them everyday and…
That meant we can go from 17 minutes on 32 cores to 5 minutes on a few hundred. And because it's distributed compilation we don't have to provision each developer with an overpowered build system they won't be using most of the time.
It could also eliminate our CI backlog because autoscaling. Over a few hundred engineers building this codebase this probably a few thousand hours of waiting a week.
This took me about 2 weeks as someone who graduated 9 months ago. Most of the tokens were spent in several hour long debugging sessions relating to distributed systems networking and tracing through gRPC logs because the system wasn't working until it did.
I think I'd need several years of experience and 6 months as a full time engineer to have accomplished the same thing pre-AI.
Since I work at a semiconductor company near Toronto there's nobody around with the distributed systems experience to mentor me. I did it mostly on my own as a side project because I read a blog post. I literally wouldn't have been able to complete this without AI.
I'm sure the actual solution is terrible compared to what a senior developer with experience would've created. But my company feels like it's getting ROI on the token spend so far even though it's double my salary.