AI Agents · Apr 14, 2026 · 10 min read
A blueprint for multi-agent systems in the enterprise
From single-shot prompts to autonomous agents that plan, call tools, and act across enterprise APIs.

A useful enterprise agent is a loop: perceive, plan, call a tool, observe, repeat. Claude's tool-use is the substrate; the engineering is in the orchestration, guardrails, and observability that make the loop safe to ship.
We design agents around explicit roles — a router, specialists, a critic, and a human-in-the-loop escalation path. Each role gets its own prompt, its own tool surface, and its own budget for tokens and tool calls.
Reliability comes from constraints: typed tool schemas, retry policies, max-step ceilings, and structured logs of every tool invocation. When an agent misbehaves you want to replay the trace, not guess.
Start narrow. A single agent that resolves one ticket category end-to-end will teach you more than a six-agent swarm that almost works.

