TL;DR
Most AI automation tools run your agent cold on every single execution
Cold starts mean the agent re-diagnoses the same problem, replans the same steps, and burns tokens it already spent yesterday
Costs don't stay flat. They pile up linearly, run after run
EasyClaw's local-first harness reasons through a task once, then executes the compiled path natively at zero extra tokens on every run after
Full architecture breakdown and setup sequence in the source article, linked below
An automation engineer built a browser agent to check competitor pricing and update a spreadsheet every morning. Worked fine locally.
By day four in production, it was stuck. Same dropdown, 47 clicks, same wrong answer, every single morning.
The prompt was fine. The model was fine. The OpenAI bill had already spiked $600 past budget before anyone caught it.
The agent had no memory of the previous run. Every execution started cold, re-read the page from scratch, and walked back into the exact same dead end it hit yesterday.