I’m unclear how you’re hitting $1k/mo in personal usage. GitHub Copilot charges $0.04 per task with a frontier model in agent mode - and it’s considered expensive. That’s 850 coding tasks per day for $1k/mo, or around 1 per minute in a 16hr day.

I’m not sure a single human could audit & review the output of $1k/mo in tokens from frontier models at the current market rate. I’m not sure they could even audit half that.

You don't audit and review all $1k worth of tokens!

The AI might write ten versions. Versions 1-9 don't compile, but it automatically makes changes and gets further each time. Version 10 actually builds and seems to pass your test suite. That is the version you review!

—and you might not review the whole thing! 20 lines in, you realize the AI has taken a stupid approach that will obviously break, so you stop reading and tell the AI it messed up. This triggers another ~5 rounds of producing code before something compiles, which you can then review, hopefully in full this time if it did a good job.

I can easily hit the daily usage limits on Claude Code or Openai Codex by asking for more complex tasks to be done which often take relatively little time to review.

There's a lot of tokens used up quickly for those tools to query the code base, documentation, try changes, run commands, re-run commands to call tools correctly, fix errors, etc.

Audit and review? Sounds like a vibe killer.

Do people actually use GitHub copilot?

At any rate, I could easily go through that much with Opus because it’s expensive and often I’m loading the context window to do discovery, this may include not only parts of a codebase but also large schemas along with samples of inputs and outputs.

When I’m done with that, I spend a bunch of turns defining exactly what I want.

Now that MCP tools work well, there is also a ton of back and forth that happens there (this is time efficient, not cost efficient). It all adds up.

I have Claude code max which helps, but one of the reasons it’s so cheap is all of the truncation it does, so I have a different tool I use that lets me feed in exactly the parts of a codebase that I want to, which can be incredibly expensive.

This is all before the expenses associated with testing and evals.

I’m currently consulting, a lot of the code is ultimately written by me, and everything gets validated by me (if the LLM tells me about how something works, I don’t just take its word for it, I go look myself), but a lot of the work for me happens before any code is actually written.

My ability (usually clarity of mind and patience) to review an LLMs output is still a gating factor, but the costs can add up quickly.