Agents
Docs for
AI agents
A practical landing page for teams exploring how documents need to change when future agents must work from them, not just read them.
Search intent
Agent readiness
For teams asking what kind of documentation actually helps agents produce aligned work.
Best for
Execution-ready context
Especially useful when you want goals, constraints, and workflows to survive beyond one chat session.
Why normal docs are not enough
Most documentation systems were built for human reading and manual upkeep. Agents need something stronger: context that stays structured, updated, and operational rather than frozen as a static page snapshot.
If the reasoning lives in chat, the constraints live in someone’s head, and the workflow lives in a different tool, the agent is forced to reconstruct the work from weak fragments.
What agents actually need
Durable goals and constraints
Agents need explicit objectives, boundaries, and quality bars that survive beyond a single prompt.
Connected decisions
A useful system keeps the rationale behind decisions near the place where future work will depend on them.
Reusable workflows
Recurring ways of working should become structured patterns rather than being rewritten for every new task.
Visible correction loops
When humans rewrite, reject, or refine output, the system should preserve that alignment signal for later work.
Read next
What Agents Need From a Document System
The deeper article on how agent-ready docs differ from traditional documentation.
AI-Native Doc System
Start here if you need the broader product category and why it exists.
How to Keep Documentation Updated as Context Changes
A practical explanation of why agent-ready docs must stay current as decisions and context move.
How to Build Long-Term Memory for Product Work
A concrete example of the durable context layer future AI work needs to inherit.