I Finally Checked What My AI Coding Tools Actually Cost. The Number Made No Sense.

Tags: ai, programming, productivity, devtools

I've been paying $200/month for Claude Code Max since January. Never really thought about it. Two hundred bucks, unlimited use, whatever.

Last week someone on r/ClaudeAI mentioned a tool called ccusage that calculates your actual token consumption at API rates. Ran it for fun.

17 seconds of staring at a loading bar. Then the number came up.

$1,428.

That's what my monthly usage would cost at API pricing. Seven times the sticker price.

My first reaction was "no way that's right." So I dug into the breakdown.

where the money goes

90% of my spend is Opus, the expensive model. Makes sense -- I use it for architecture decisions and complex refactors, not autocomplete. But I didn't realize how much that costs per token.

The weird one: cache operations eating 63% of the total. Every time an agent re-reads your codebase, every time it reloads context after spawning a subagent -- cache hit. I have a monorepo with about 40k lines. Claude reads chunks of it constantly. I never thought of "reading my files" as a cost center.

the team math got scary

This is where it stopped being fun trivia and started being a real problem.

I work with a small team. Four devs, all using AI coding tools. If each of us is burning $1,400/month at API rates, that's $5,600/month. And we're on the lower end -- I've seen reports of agentic workflows costing $10,000-15,000/month per team when you've got agents spawning agents spawning agents.

Nobody budgeted for this. Our engineering tooling line item was maybe $2,000/month total before AI. Now it's... unclear. The subscription prices hide the real consumption, which is kind of the point, but also means nobody on the team knows the actual burn rate.

the thing that bugs me

I went looking for benchmarks. How does our usage compare to other teams? Is $1,428/month normal for a senior dev or am I doing something wrong?

Couldn't find anything. There's a Wakefield Research survey saying 86% of engineering leaders feel uncertain about their AI tool ROI. Eighty-six percent. That's basically everyone admitting they don't know if the money is well spent.

And I get it. When ccusage takes 17-20 seconds to generate one report, you don't check it often. I'd been paying for four months without looking once. The subscription model makes it easy to just... not think about it.

what I still don't know

I don't know if my 7x ratio is good or bad. Maybe some people get 15x value and I'm underusing it. Maybe I could cut my consumption in half by using Sonnet instead of Opus for routine tasks and save the heavy model for when it matters.

I also don't know how to attribute costs to actual work. Like, did that $300 in tokens last Tuesday produce the refactor that saved us two sprints? Or did it produce three failed attempts at a migration I ended up doing manually?

There's no way to tell right now. It's just one big number.

I'm genuinely curious -- does your team track AI coding tool costs at all? Not just the subscription price, but the actual consumption underneath? And if you do, what does your ratio look like?

Because I have a feeling my $1,428 is not unusual, and most of us are just not looking.