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Last updated September 18, 2026
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Documentation used to be described as a map for the next person.
In an AI-assisted repository, it is also input to the next implementation.
When code and documentation disagree, an agent may use either one. A stale feature page, architecture rule, API
example, or decision record can produce a new change that is internally consistent with an old system.
Documentation drift is therefore not only a communication problem.
It is state corruption.
Identify documents from the diff
Do not ask an agent to “update the docs” without a map.
Use the changed code to identify affected knowledge:
- public API or schema;
- feature behaviour;
- architecture boundary;
- data model;
- dependency;
- deployment or operations;
- security assumption;
- design system;
- decision record;
- onboarding and workflow instructions.
The result should be an affected-document list with reasons.
Update the right source
Repositories often contain several descriptions of the same concept.
Before editing, determine:
- which document is authoritative;
- which files are generated from another source;
- which page is a summary;
- which example is executable;
- which legacy document should be retired.
Updating every matching sentence can create a consistent set of wrong copies.
Verify documentation against live behaviour
Different document types need different proof.
An API example can run as a contract test.
A CLI command can execute in a test environment.
A generated schema can compare with source.
An architecture boundary can have a structural test.
A feature description can map to acceptance criteria.
A decision record requires human confirmation and a review trigger.
The document-maintainer agent can propose changes. Verification should use the strongest available source.
Record intentional non-changes
Not every file containing a keyword needs an update.
For reviewed candidates left unchanged, record why:
- the document describes a different scope;
- the behaviour remains compatible;
- the page is generated elsewhere;
- the change is internal and has no document impact;
- a separate follow-up is required.
This stops the next run from repeating the same uncertain search.
Prevent documentation from legitimising drift
Documentation sync can become dangerous when it simply updates the prose to match any new code.
Before syncing, check:
- Was the specification approved?
- Did the change stay inside scope?
- Did architecture and security review pass?
- Was the new behaviour requested?
- Were exceptions recorded?
Documentation should describe accepted reality. It should not make an unapproved shortcut look official.
Maintain repository legibility
OpenAI’s harness-engineering account describes repository-local knowledge, plans, architecture documents, verification
status, and mechanical checks for stale material. It is one internal, first-party account.
Its useful principle is that information unavailable or unreliable in the repository weakens both human and agent
reasoning.
Keep a small entry point, clear ownership, current links, and progressive paths to deeper material. Remove obsolete
documents rather than leaving contradictory context for the agent to resolve.
Make documentation part of the receipt
The final feature receipt should show:
- affected documents;
- updated documents;
- verification performed;
- intentional non-changes;
- unresolved drift;
- owner for follow-up.
“Docs updated” is too vague to audit.
How paqad-ai treats documentation
paqad-ai’s workflow includes a documentation-sync stage after implementation and checks. It is designed to detect
affected documentation, update repository knowledge, and keep the result in the evidence chain.
The value is not automated prose.
It is treating documentation as a state that must remain consistent with the code and decisions the team accepted.
When future agents read the repository, current documentation is part of code quality.
Install paqad-ai: https://github.com/Eliyce/paqad-ai/
Source notes
- OpenAI, Harness engineering, first-party internal account.
- Product mechanism: first-party details from the current
Eliyce/paqad-ai repository.