Its easy when you spawn a couple of subagents in a homelab with a rack with 5+ servers.

This is how one of my claude code session looks like right now, one prompt from yesterday:

  ◯ lean-tracks  ▰▰▰▰▰▰▰▰▰▰▰▱▱▱▱▱▱▱▱▱  7/12 · 18h35m · ↓ 3.1m tokens
  ◯ lean-tracks  ▰▰▰▰▰▰▰▰▰▰▰▰▱▱▱▱▱▱▱▱  6/10 · 17h47m · ↓ 2.6m tokens
  ◯ lean-tracks  ▱▱▱▱▱▱▱▱▱▱▱▱▱▱▱▱▱▱▱▱  0/1 · 4h49m · ↓ 275.9k tokens
  ◯ lean-tracks  ▱▱▱▱▱▱▱▱▱▱▱▱▱▱▱▱▱▱▱▱  0/1 · 4h30m · ↓ 395.0k tokens
 ◯ lean-tracks  ▱▱▱▱▱▱▱▱▱▱▱▱▱▱▱▱▱▱▱▱  0/1 · 3h50m · ↓ 490.3k tokens

I swear I have the same question in my head always when I read such statements! I have never once reached 90% that includes everyday usage across multiple repos, artefact generation, device debugging, long running harness work!

I am not saying OP is not telling the truth. I just really want to understand!

Not OP, but I used to run out in a few days, for me it was a matter of suboptimal code review practices with many subagents looking at different aspects, often expanded to look at more than the diff.

not reviewing its ongoing work and spawning subagents that end up looping each other

Loading tons of MCPs and never compacting

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I can drain a $200 OAI plan in 2 hours flat working on my 10 projects simultaneously.

Maybe you're not being ambitious enough with these things? They are at their most fun when you spec out sprawling architecture documents and watch 1+8 astras buzzsaw through it.

I'm only at 260B for the year, though. I'm sure someone who has used more will be along shortly to chime in

E: The other subthread talking about tests is correct. Expensive models should not waste a single second waiting on tests or validation. If you cannot assign a single cheap model to be the test bitch, then just tell them to frontload everything and clean up later as a single wave.