Normalized Telegram record
Harvey trained a legal agent with an applied compute loop
Harvey describes domain experts, task environments, evaluation, and iterative training as one system for legal agent performance.
Signal contract
Harvey describes domain experts, task environments, evaluation, and iterative training as one system for legal agent performance. High-stakes vertical agents need expert-designed tasks and feedback loops around the model rather than a domain prompt added at deployment time. Novelty: notable. Verification: source-inspected. This New Runtime record is an evidence-linked retrieval unit.
Source ledger
Publishable sources attached to this record.
| # | Source | Role | Public status |
|---|---|---|---|
| 1 | harvey.aisource | primary receipt | source_urls |
Observation
Harvey describes domain experts, task environments, evaluation, and iterative training as one system for legal agent performance.
Why it matters
High-stakes vertical agents need expert-designed tasks and feedback loops around the model rather than a domain prompt added at deployment time.
Entities
Harvey
Provenance
This public record is an English normalization of QWG AI Telegram message 2614. The complete original-language post remains the canonical raw message.