I kept saying the same thing for months:
"AI got expensive. That's just how it is now."
Turns out I was wrong.
The pricing changed, sure. But most of my cost spikes were self-inflicted: messy prompts, context switching, doomscroll breaks, and rerun loops.
I’m a solo Mac dev building and shipping fast. I thought the problem was model pricing. The real problem was workflow quality.
What was actually burning money
1) Context chaos
I was pasting giant briefs, random logs, and half-decisions into one prompt. The model did its best, but I paid for noise.
2) Retry spiral
"One more try" became five tries. Each retry had worse context than the last.
3) Attention leakage
I’d bounce from coding to feeds for 3–5 minutes, come back, lose thread, and restart the same task with a worse prompt.
That cycle was expensive.
The system that fixed both spend and output
I changed to a tiny operating system:
-
Session budget before run
- I set a hard cap for the next 60–90 minutes.
-
Small, clean briefs
- One task, one success criteria, one output format.
-
No-feed build window
- If I’m in a coding block, algorithmic feeds are gone.
-
Post-run review
- Keep / kill / retry decision in 30 seconds.
Simple, boring, effective.
The two tools I built for this
I built these because I needed them myself:
-
TokenBar — https://tokenbar.site ($5)
- Live token/cost visibility in the Mac menu bar.
- Stops the "surprise bill" effect.
-
Monk Mode — https://mac.monk-mode.lifestyle ($15)
- Feed-level distraction blocker for Mac.
- Keeps useful app surfaces, removes algorithmic scroll traps.
The combo changed my workflow from reactive to intentional.
The result
I stopped optimizing for "cheapest model" and started optimizing for clean execution.
When execution got better:
- retries dropped,
- prompt quality improved,
- spend per shipped task went down,
- and I actually finished more work.
If your AI bill feels random, check your workflow before you blame pricing.
Pricing matters.
Workflow matters more.
Top comments (0)