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Developer Shares 'Codex Maxxing' Workflow to Turn AI Agent Output Into Verifiable Work

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A developer has detailed a structured workflow called 'Codex Maxxing' that treats the use of OpenAI's Codex not as a one-shot prompt tool but as a repeatable, inspectable skill. Inspired by Jason Liu's original essay on the concept, the approach introduces a routing layer that decides whether to work directly, ask clarifying questions, investigate, plan, or bring in an independent reviewer. The workflow follows a loop covering preflight checks, task routing, scoped handoffs, verification of actual diffs, and storing lessons as repository memory. The method is designed to be asymmetric — keeping small, clear tasks lightweight while adding structure only for vague or high-risk work. A ready-to-install SKILL.md file is provided so others can adopt the workflow directly inside their Codex environment.

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Developer Shares 'Codex Maxxing' Workflow to Turn AI Agent Output Into Verifiable Work · ShortSingh