Doc generation

Doc generation is the LLM-driven workflow of producing API references, SDK pages, code examples, or product docs from structured sources (OpenAPI specs, code annotations, repo content) — Fern, Mintlify SDK, ReadMe, Stainless are 2026 implementations.

Manual API docs decay: every code change risks orphaned doc pages. Doc generation flips this: docs are derived from source (OpenAPI spec → reference, JSDoc → method docs, examples folder → quickstart). LLM adds: prose polishing (raw OpenAPI is robotic; LLM rewrites into reader-friendly prose), code-example generation (auto-create Python / TypeScript / Go calls for each endpoint), version diff narratives (LLM compares two OpenAPI versions, drafts the changelog). Tools: Fern generates SDKs + docs from OpenAPI; Stainless does SDK gen; Mintlify SDK generates Python / TS / Go SDKs; Speakeasy similar. Trade-offs: generated copy can be bland, need human polish on landing + concepts.

When to use doc generation

• API-first products.
• Multi-language SDK shops.

Common mistakes

• Shipping pure auto-generated docs without prose — feels like a vendor spec sheet.
• Skipping changelog narratives — users miss what changed.

FAQ

Related terms

• AI docs — AI docs is the documentation category where AI-native features (semantic search, Q&A chat, auto-summary, code-example generation) are first-class — Mintlify AI, ReadMe AskAI, GitBook AI, Algolia AI Search are 2026 leaders.
• SWE-bench — SWE-bench is the standard benchmark for autonomous coding agents — real GitHub issues from popular Python repos paired with the actual fix commit; the agent must produce a patch that passes the hidden test suite.

Last updated: 2026-06-01. Raw markdown: https://promtable.com/glossary/doc-generation.md.