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Build an AI agent team, not just one agent

You've built a single agent before. Now build a small team — one Supervisor that plans, and up to four Specialists that carry out the work — and watch it plan, run, pause for your approval, hit a snag, and recover. Still no code. Still nothing saved or sent anywhere.

Three colleagues in a dusk-lit meeting room gather around a curved monitor showing a glowing orange network diagram, representing a team reviewing how their AI agents are coordinating

Listen to this briefing

Building Resilient, Autonomous AI Teams

0:00

Getting Started

New to AI agents?

This tool builds on Build Your Own AI Agent, the beginner tool. If you haven't built a single agent before, start there first — it takes 5–10 minutes and explains the basics this tool assumes you already know: goals, tools, and rules.

What's different here

Beginner tool

One agent. One goal. A flat, simulated reasoning trace. A single "ask first" rule.

This tool

A Supervisor + Specialist team. A visible plan before it runs. A live run with an approval checkpoint. A simulated failure and recovery. A team-wide governance record.

What you will do — 5 steps

1Start. Load a starter team, or build one from blank.
2Build your team. Name your Supervisor, then add Specialists with jobs and tools.
3Give it a task. Write a task, then see the plan your team makes before anything runs.
4Watch it run. Approve a checkpoint if one comes up. Watch it recover if a tool fails.
5Get your team's record. A full governance report for the whole team, ready to print or save as a PDF.

Start Building a Team →

StartTeamTaskRunRecord

Step 1 of 5: Choose a starting point

Choose a starting point

Pick a starter team that matches a real scenario, or start blank and build your own. You can rename and rewire everything after.

Why this step matters

Every real deployment starts from a known-good shape. These three templates are simplified versions of patterns used by real multi-agent platforms — a Supervisor that plans, and Specialists that each do one job well.

Build your team

Every team has one Supervisor and up to four Specialists. The Supervisor never does the work itself — it plans, assigns, and checks.

Supervisor's name

🧭

Supervisor

Your Supervisor

Plans the task, assigns each step to a Specialist, and merges the results.

Why this step matters

A team splits one big job into smaller jobs different agents are good at. Marking a Specialist as needing approval creates a checkpoint the plan can never skip — this is how real teams keep a person in the loop on risky actions.

Give it a task

Your team so far

Write the task below. Your Supervisor will read it and build a plan — nothing runs until you approve the plan.

This is a practice tool that teaches the ideas behind multi-agent AI using simple, built-in rules. It does not call a real AI model. Everything you type stays in your browser.

Why this step matters

Seeing the plan before it runs is the single biggest upgrade from a single agent. You can catch a wrong assignment or a missing checkpoint before anything happens, not after.

Watch your team work

Each step lights up as it runs. If a checkpoint comes up, the team pauses for you.

Why this step matters

Real teams fail — a tool times out, an approval takes a moment. This step shows the whole loop: plan, act, check, and (when needed) recover, live.

Your team's governance record

The same idea as the beginner tool's record — scaled up to a whole team, and to the extra risks a team brings.

This record is simplified for learning. It cites real, published design patterns from theAgentic AI Pattern Catalogue — 61 patterns for autonomous agents, mapped to real regulatory standards including Singapore's IMDA Model Governance Framework and the OWASP Top 10 for Agentic Applications. Finishing this tool does not mean a real agent team is certified or compliant. For a real organisation, use the fullISO 42001 AIMS Readiness Checklist andTRACE Agent Evaluation tools.

Where to go next

The five checks above are 5 of 61 patterns in theAgentic AI Pattern Catalogue — explore the rest to see what a production-grade agent team adds on top of the one you just built and ran. Ready to go further? Try theExpert AI Agent Builder — turn on production guardrails for this team, then red-team it with 5 real attack techniques to see whether those guardrails actually hold.

Before you start

Four ideas this tool adds

You already know goal, tools, rules, and prompt from the beginner tool. A team adds four more ideas.

Supervisor

The agent that plans and assigns, but never does the work itself. It keeps the team on track.

Plan

The list of steps the Supervisor makes before anything runs, so you can check it first.

Checkpoint

A step marked to always pause for a person's approval before it runs.

Recovery

What the Supervisor does when a tool or step fails, instead of just stopping.

Build an AI agent team, not just one agent

New to AI agents?

What's different here

What you will do — 5 steps

Customer Refund Approval Chain

Market Research Crew

Contract Review Crew

Start from blank

Your Supervisor

Four ideas this tool adds

Supervisor

Plan

Checkpoint

Recovery