Why use Claude instead of ChatGPT for technical documentation work?
Three reasons working tech writers cite when they switch. First: Claude tends to preserve technical terms exactly as written — it will not silently rename `user_id` to `userId` or change `POST /v2/widgets` to `POST /widgets/v2` mid-paragraph, which is the failure mode that ships broken docs. Second: long context windows mean you can paste an entire OpenAPI spec, the existing reference section, and three competing style guides into a single prompt and get a consistent rewrite. Third: structured XML-style prompting (per Anthropic's own prompt engineering guide) maps cleanly onto the structural thinking documentation already requires.
The economics: Claude Pro (per Anthropic's pricing) handles the daily volume of a working tech writer comfortably. For docs teams running prompts at scale via the Anthropic API, per-token pricing varies by model tier. A docs team measured on time-to-publish for new SDK features recovers the cost in the first sprint they use the API-reference scaffolder.
What Claude is not good at: running your code, hitting the live API to verify a response payload, or guaranteeing that a sample request actually executes. Treat every code block it emits as a draft until a developer or your own test runner confirms it works.