Harvey, the legal AI platform, has integrated GPT-6 Astra to generate structured, context-aware legal documents. The system processes case-specific inputs and produces drafts that reflect procedural nuance, reducing the time lawyers spend on initial document preparation.
The shift matters because legal drafting is not generic writing. Contracts, briefs, and motions require precise clause hierarchies and jurisdiction-sensitive language. GPT-6 Astra's extended context window and improved instruction-following appear to close the gap between raw generation and court-ready output, at least at the draft stage.
The full piece is worth reading for how Harvey structures its prompting pipeline and what GPT-6 Astra gets right that prior models missed. The open question, which the article only partially addresses, is where the model still fails and what human review actually catches.
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