Multi-Agent Orchestration

6 Interactive Sessions

Short, interactive sessions — watch it work, steer it, then build it yourself. Go deeper anytime with the full code walkthrough.

1. 1

   The Team — four specialists beat one generalist

   The competitor-memo task needs four different skills — search, analysis, drafting, compute. One agent juggling all four does each poorly. A team of specialists, each with its own tools and system prompt, wins.

2. 2

   The Conductor — decompose, route, assemble

   Four specialists don't coordinate themselves. The supervisor reads the goal, breaks it into subtasks with dependencies, routes each to the right agent, and assembles the result. It never does the work — it conducts.

3. 3

   Shared Brain — write once, read everywhere

   The Writer needs what the Researcher found. Without a shared memory each agent re-does the work or makes the facts up. Three tiers — working, short-term with TTL, and long-term — let findings flow, with provenance, and stay bounded.

4. 4

   Agree & Hand Off — vote, gate, transfer safely

   The Researcher says 24.5% market share; the Analyst's model says 19.3%. Who's right? A quality gate and a vote settle it before the memo ships a contradiction — and an idempotent handoff moves the work without doing it twice.

5. 5

   Watch Them Work — make the run visible

   A multi-agent run is a black box unless you can see it. The app turns it into a picture: the task goes in, agents work in visible lanes, handoffs flow on a timeline, and the memo assembles — so you can tell who's working, what passed, and where it's stuck.

6. 6

   Run It in Production — metrics, breakers, budgets

   Day 2, an agent gets stuck in a retry loop or two agents ping-pong forever, and the bill climbs. Multi-agent systems fail in new ways. Per-agent metrics, circuit breakers, and cost caps are the guardrails that catch them.

What you walk away with