In design · TRAIN

ML for Agent Builders

The TRAIN loop for narrow models your agents can depend on

Your agents call models all day. Time to own a few.

Agents lean on models constantly, but the decision to own one stays murky. ML for Agent Builders is a build loop for the narrow models agents depend on — clear calls on fine-tune versus RAG, labeling, and eval drift — so you win on cost, latency, and control instead of renting everything.

• The TRAIN protocol: Target metric, Represent data, Automate, Inspect, Narrow
• Decide fine-tune vs RAG, control labeling and eval drift
• Narrow models that win on cost, latency and control