tool use

Reward only on the final answer and learning crawls; shape intermediate tool calls and the model learns to spam SQL. Use outcome-grounded credit assignment, GRPO over a group of trajectories, and fine-tune a pre-aligned model so you're not teaching tool syntax from scratch.

Most candidates reach for a smaller model first. The staff answer builds an explicit per-stage latency budget, parallelizes independent tool calls, and spends the time budget where the user actually feels it.

This is the lethal trifecta in one sentence, and most candidates reach for a better system prompt. The answer that scores breaks the trifecta architecturally, because no amount of prompting stops indirect injection once all three capabilities are present.

Hard budgets stop the bleeding; they don't fix the cause. The real fix is progress tracking plus semantic loop detection plus a planning layer that commits to a plan instead of re-deciding every step, validated on a fixed trajectory set offline before it ships.

The pitch is a model that runs the loop. The design that survives production is a loop that code runs, with the model answering three narrow questions inside it: which tool, is this done, does this need a stronger model.

An agent with write access to a CRM, a chat tool, and an HR system is one bad tool call from emailing salaries to a channel. Safety is least-privilege scopes, a hard read/write split, human approval on destructive actions, and an audit log of everything.

Every control in the stack validates the shape of the action and none validates its target. A refund of the right amount, to a real customer, through a permitted tool, against the wrong account, is indistinguishable from success at every layer that is watching.