AIOS Daily Loop

A daily operating cadence for getting value from an AI Operating System while continuously improving it. Based on Nate Herk's own practice.

The daily loop

1. Morning: open Claude Code and say "help me plan my day" — the AIOS reads calendar, tasks, comms, and drafts a priority plan [src-013]

2. During the day: execute using the AIOS; note where it gets things wrong or needs correction [src-013]

3. End of day: review — "What skills did I use today? What did I have to correct my assistant on?" [src-013]

4. Patch: update skill files, context files, or guardrails based on corrections — "Tomorrow, you can patch some of that stuff up" [src-013]

Success criteria (when the AIOS is working)

  • Team members start asking to talk to your AIOS rather than to you
  • You stop opening new browser tabs to look things up
  • Knowledge moves out of your head and into the system
  • You find yourself pasting questions into the AIOS before answering them yourself — "because my AIOS had more data than I did" [src-013]

Related concepts

Source references

  • [src-013] Nate Herk — "Build & Sell Claude Code Operating Systems (2+ Hour Course)" (2026-05-01)

Robin Cartier perspective

This page is part of Robin Cartier's working AI knowledge graph: a practical research layer for production AI, recommendation systems, experimentation, GEO, and agentic web readiness.

The useful next step is to connect this concept back to applied product leadership and operating models.

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