World Congress 2026 Europe - Virtual Stage • Jul 2, 2026 • Session details

Living Documentation That Can't Die

Roman Liukevich

Stale documentation is actively breaking your AI coding agents by feeding them outdated instructions. Discover how a unified docs-as-code approach transforms passive guidelines into active IDE warnings.

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#1 about 2 min

Why scattered knowledge bases lead to stale documentation

Spreading documentation across multiple platforms prevents teams from knowing where the actual source of truth resides.

#2 about 3 min

The persistent gap between AI code agents and documentation

AI assistants integrated into the IDE still lack awareness of external documentation platforms like Confluence or Notion.

#3 about 2 min

Relocating documentation to the main codebase repository

Placing documentation in the same repository as code allows AI agents to read and rely on accurate context.

#4 about 5 min

Evaluating documentation folders versus Git submodules and wikis

Teams must choose between the friction of pull requests in a docs folder or the manual syncing of a separate wiki repository.

#5 about 2 min

Generating and syncing documentation automatically with AI

Configuring AI agents to read and update documentation files during code changes prevents knowledge from falling out of sync.

#6 about 1 min

Managing agent token consumption with an index file

Creating a simple index document helps AI agents selectively read relevant files instead of consuming entire documentation folders.

#7 about 1 min

Validating code style and rules against documentation

Agents can automatically check any code file against documented standards during the review and onboarding processes.

#8 about 2 min

Converting architectural guidelines into custom lint rules

Transforming lengthy lists of architectural rules into hard linting constraints ensures compliance without relying on human memory.

#9 about 4 min

Operating a unified documentation system day to day

Integrating code, documentation, and AI agents into a single automated loop drastically reduces the cost of keeping information current.

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The emergent readers of software documentation

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4:08 min

Transitioning documentation from human readers to AI agents

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2:09 min

Assessing the limitations of generating documentation directly from codebases

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3:38 min

Adopting documentation-led specification for optimal agent code generation

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2:55 min

Enhancing AI agents with trusted documentation and logical restraints

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2:22 min

Orchestrating local developer environments with AI tools

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