Automation

Agent systems scale only when you define what is automatable, what is semi-automatic, and what must remain human-controlled.

Codex is excellent at repetitive, well-defined work, but it should never be the last person deciding behavior in critical system code.

A practical framework for deciding where AI agents should run autonomously and where human review remains non-negotiable.

A practical breakdown of using Codex for software work: strong for scaffolding, weak at final architecture decisions, and happiest when paired with guardrails.

A practical integration of autoresearch-style loops into an agent workflow with structured evidence checks and reproducibility gates.