Learn the controls and knobs

Primary knobs for fine-tuning vs RAG: retrieval freshness SLA, tune data mix, LoRA rank, eval for style vs fact, abstain policy.

Write a sheet for the legal research assistant with columns: control, current value, predicted benefit, predicted cost, rollback trigger. Fill it using this topic’s real tension: Tuning can lock tone and is slow/expensive to refresh for facts. RAG cites sources and fails when retrieval misses. Doing both raises complexity.

Change one fine-tuning vs RAG family at a time. If you move two knobs and the legal research assistant improves, you learned a cocktail, not a cause—and you cannot roll back surgically.

End users of the legal research assistant should see only safe dials related to fine-tuning vs RAG. Infrastructure limits, private prompts, and policy thresholds stay server-owned. A user-facing control that bypasses those limits is a vulnerability dressed as UX for fine-tuning vs RAG.

Publish the fine-tuning vs RAG control sheet next to the legal research assistant runbook. On-call should see which knob moved in the last deploy without reading chat archaeology. Unknown fine-tuning vs RAG knobs are unowned knobs.

Also pin one numeric memory from this fine-tuning vs RAG chapter: If regulations change weekly, a 2-week fine-tune cadence cannot beat an index refreshed hourly on citation freshness. That number is not decoration; it is a template for how claims about fine-tuning vs RAG on the legal research assistant should look in design docs. Scoped specifically to fine-tuning vs RAG / legal research assistant / controls-and-knobs.

People confuse fine-tuning vs RAG with neighboring buzzwords when debugging the legal research assistant. Before changing prompts, ask whether the broken stage was evidence gathering, the fine-tuning vs RAG judgment itself, validation, or the product action. Fixing the wrong stage creates folklore (“we tried fine-tuning vs RAG and it failed”) that blocks the next team on the legal research assistant. Scoped specifically to fine-tuning vs RAG / legal research assistant / controls-and-knobs.

Write a five-line artifact for this page: goal, inputs, check, owner, stop rule. Invent one fluent failure that the check would catch. Keep details specific to fine tuning vs rag rather than generic AI advice.

Write a five-line artifact for this page: goal, inputs, check, owner, stop rule. Invent one fluent failure that the check would catch. Keep details specific to fine tuning vs rag rather than generic AI advice.