
AGENTS.md for Codex: project instructions that last
Make repository conventions discoverable, verifiable and locally relevant so Codex can work more consistently.
Practical guides to AI, Codex, Claude Code, agents, automations, software and digital design — clearly explained and ready to apply.

Make repository conventions discoverable, verifiable and locally relevant so Codex can work more consistently.

Give Claude Code the context every session needs without building a second internal wiki.

Make agent work reviewable with a clear assignment, narrow change surface and evidence that the outcome works.
Follow a subject from first principles to a practical workflow through guides that build on one another.
From language models and governance to useful applications inside your team.
Work better with Codex, clear instructions and controllable workflows.
Practical patterns for context, tooling, planning and safe execution.
Build agent instructions that make teams, repositories and automations reliable.

Build an evaluation set from real work and combine outcome, process evidence and human judgement.

Restrict triggers, tokens and write scope so automated review remains a control rather than a new attack surface.

Map data flows, retention and contractual choices before source code and business information enter an agent workflow.

Use hooks for deterministic controls, not as a hidden collection of scripts nobody understands.

Combine approval rules, isolation, safe defaults and review so one mistake never receives broad reach.

Separate research, implementation and review only when task boundaries, permissions and hand-offs are clear.

Design what an agent sees, retains and retrieves at each moment instead of stacking all information into one prompt.

Design AI connections as clear contracts with minimum permissions, explicit consent and traceable data flows.

Use fixed automation for predictable work and agent behaviour only where interpretation justifies added variability.