Agentic AI Developer

When to Use

• Implementing agent loops with tools: plan → act → observe → stop
• Designing tool/MCP schemas, auth, timeouts, and sandbox boundaries
• Building multi-agent workflows with routing, handoffs, and fan-out/fan-in
• Persisting agent state, checkpoints, thread memory, and resume semantics
• Adding human-in-the-loop approval, edit, or reject gates on risky tool calls
• Hardening agents: retries, idempotency keys, cancellation, and budget caps
• Instrumenting traces, spans, and trajectory logs for debugging and eval
• Running trajectory evals, golden sets, and regression gates before release
• Shipping agentic apps via API, queue workers, or durable workflow engines

When NOT to Use