Week 4 of 6
A single agent is powerful. But ask it to do something genuinely complex — research a topic, write a report, verify all the facts, format it, and deliver it — and you quickly hit limits. It loses track of earlier steps. Contradicts itself. Runs out of context window.
The most powerful AI systems in production are not single agents. They are teams of agents, each with a specific role, working together on a shared goal.
You would not ask one person to simultaneously be researcher, writer, editor, fact-checker, and publisher for a major report. You build a team. Multi-agent systems apply the same logic to AI.
| Orchestrator Agent | Worker / Specialist Agent |
|---|---|
| Breaks the goal into subtasks | Executes one specific subtask |
| Assigns tasks to the right workers | Focused on one skill or domain |
| Tracks progress, reassigns on failure | Returns a result to the orchestrator |
| Makes the final output decision | Does not need to know the big picture |
| Like a project manager | Like a specialist consultant |
A handoff is when one agent passes its output to another. The quality of handoffs determines the quality of the whole system. A bad handoff — wrong format, incomplete information, ambiguous instructions — causes errors that compound through every subsequent step.
The biggest risk in multi-agent systems is error propagation. If the research agent gets something wrong, the writer builds on that error, the fact-checker may miss it, and the user receives confidently wrong output. One bad step poisons everything downstream.
Put a human checkpoint before any irreversible action — sending an email, making a purchase, publishing content, executing code in production. Everything before that can be autonomous. Everything after needs a human approval step.
Good agent teams decide where a human approves before they’re built — not after something goes wrong. After you draw your pipeline below, mark a 🛑 everywhere a human must approve before the agent continues. The rule of thumb: a checkpoint is required before any action that is irreversible or affects someone else — sending an email, spending money, publishing, submitting a form, sharing personal data. Litmus test: “If the agent gets this step wrong, can you undo it?” If no, a human belongs in the loop there.
Choose a scenario and design the full pipeline. Be specific — name each agent, describe what it receives, what it produces, and where handoffs happen.
Go Deeper — Optional
Run in Google Colab — no setup, no install. Interactive Python exercises that reinforce every concept from this lesson.
Coming up — Week 5
Build Your First Agent
Project week. Build, test, and demo a real working AI agent using free no-code tools.