What running AI agents actually costs

Sun, 24 May 2026 11:12:41 +1000

I wanted to know if my AI subscription was earning its keep. So I repriced 30 days of real usage at pay-per-token rates and compared it to what I actually pay.

The answer: $96 USD equivalent in tokens consumed. My subscription costs $100 USD a month. That’s not a rounding error - that’s a subscription running at near-full utilisation.

Not a prototype. Not a weekend experiment. A system I actually depend on - morning briefings, task management, research, document work, health tracking, portfolio analysis. The Autonomi, as I call it, runs continuously and does real work.

The plan I’m on

Claude Max is a flat-rate subscription at $100 USD a month - billed in Australian dollars at the monthly exchange rate. It gives you five times the usage capacity of Pro, which matters once you start running agents at any real volume.

Flat-rate sounds simple. The trap is that you lose visibility into where the cost actually goes. When there’s no per-session invoice, it’s easy to assume you’re well inside your limits and never check. I wanted the actual picture.

The breakdown is where it gets interesting.

73% of the equivalent token spend is Opus 4.7 output. Not input. Output.

This is the thing people miss when they estimate AI costs. In a chat interface, input and output are roughly balanced - you write a paragraph, you get a paragraph back. In an agentic workflow, the ratio inverts. The model is reasoning through multi-step tasks, generating tool calls, writing structured results, checking its own work, producing long-form outputs from short prompts. You send a few hundred tokens in. Thousands come back.

The model is working. And working costs more than thinking out loud.

What the 5x headroom actually buys you

The practical benefit of the Max plan isn’t that you pay less per token. It’s that you stop rationing Opus.

On a standard Pro plan, heavy Opus usage burns your quota quickly. You start making decisions at the model selection screen - is this task worth Opus, or should I use Sonnet? That’s friction. It’s also the wrong question, because some tasks genuinely need the best model and others don’t, and you don’t always know which is which until you’re in them.

With 5x capacity, I use Opus when the work calls for it and don’t think about it. Investment research, meeting prep, long-form analysis - Opus. Scheduling, structured data extraction, short-form drafts - Sonnet or Haiku. The model choice gets made on merit, not quota anxiety.

I’ve only hit a hard limit once in recent memory - a two-hour pause after an unusually intensive session. That was a vibe coding run where I was pushing hard. One timeout in months of daily use is a reasonable ceiling.

What the agents are actually doing

My system runs a morning briefing agent, a Todoist integration layer, a scheduling system and a session tracker, plus whatever I throw at it through Cowork across the day. In a typical week that includes data munging, investment research, health data analysis, document generation and correspondence.

The expensive work isn’t the mechanical stuff - structured data in, formatted output out. It’s the analysis: synthesising across multiple sources, adapting to new constraints, producing work that requires judgment. Every time Opus produces a backtest summary, a meeting prep note or a long-form post, it generates thousands of tokens on the output side.

I’ve already replaced one agent that was using the top-tier model unnecessarily - the morning briefing, which was hitting context limits and breaking. A deterministic Python script now handles it for almost zero cost. The output is cleaner. The agent was solving a problem it had partly created.

The honest number

$96 USD equivalent consumed against a $100 flat-rate plan. In periods when I’m vibe coding hard, I’d expect that number to be higher - the subscription absorbs it. That’s exactly what a flat-rate plan is for.

$100 a month for a personal AI system that does the kind of work a part-time researcher and assistant would do is, by any reasonable measure, extraordinary value. The question isn’t whether it’s expensive. It’s whether you’d pay $100 a month for the same output from a human.

The answer to that one is obvious.

Rambling Rows

What running AI agents actually costs