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.
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.