Tendril

Tendril · Builders · Agentic AI

Multiple AI Agents Working Together

Splitting one big task across specialized agents (planner, coder, reviewer) often beats one agent doing everything.

40 min · Reviewed 2026

The big idea

A multi-agent system has roles: a planner breaks down the work, a coder writes it, a reviewer checks it. Each agent has a focused prompt, smaller context, and a clear job. It's how systems like CrewAI, AutoGen, and LangGraph work — and how teams of humans work too.

Some examples

A research crew: searcher finds sources, reader summarizes them, writer drafts a report.
A code crew: planner makes a TODO list, coder implements one item at a time, tester runs the suite.
A content crew: ideator brainstorms, writer drafts, editor cuts.
A customer support crew: classifier routes tickets, responder drafts replies, supervisor reviews.

Try it!

Sketch a multi-agent system for a task you do weekly. Name 3 roles, each with one sentence describing their job.

Handing Off Between Two AI Agents Without Losing the Thread

The big idea

One agent that plans and one that executes is more reliable than one agent doing both. The planner writes the brief, the worker runs it — and you get cleaner outputs because each has one job.

Some examples

A Claude planner outputs a JSON brief that a GPT-4 worker turns into code.
A research agent writes a one-page summary that a writer agent expands into a blog post.
A spec-writing agent produces tickets that a coding agent picks up one at a time.
A triage agent labels emails and a response agent drafts replies using only the labels.

Try it!

Write two prompts — one that plans, one that executes. Wire them so the planner's output is the worker's input.

Multi-agent: a team of 3 agents that disagree productively

The big idea

Multi-agent setups split a task across specialized roles, each with its own prompt and personality.

Some examples

Drafter writes a first attempt.
Critic finds three problems.
Editor decides what to change and produces v2.

Try it!

Set up a 3-agent team to write your next essay outline. Compare to a single-agent version.

Understanding "Multi-agent: a team of 3 agents that disagree productively" in practice: AI agents don't just answer questions — they can do things, like looking things up, writing files, or talking to apps. One agent that drafts, one that critiques, one that decides — better than a single agent — and knowing how to apply this gives you a concrete advantage.

Design clear agent goals before adding tools
Define permissions and scope before deploying any agent
Build in human-approval checkpoints for high-stakes actions
Understand when to use an agent vs. a simple chat prompt

Design an agent spec: goal, tools, permissions, stop condition
Run a simple web-search agent in a sandbox environment
Instrument an existing workflow to identify where an agent could save time

Multi-Agent Systems: When AIs Work Together

The big idea

Frontier AI work increasingly involves multiple specialized agents — a researcher, a writer, a critic, a coder — coordinated by an orchestrator. This pattern produces better work than one model doing everything, but coordination introduces new failure modes. Knowing the pattern helps you spot what's happening behind the scenes in modern AI products.

Some examples

Research products often run a search agent, an extract agent, and a synthesis agent.
Coding products may have planner, implementer, and reviewer agents.
'Auto' modes in chat tools often spin up multiple specialist calls under the hood.
When agents pass work to each other, context can get lost or distorted.

Try it!

Next research task, run the search and the synthesis as two separate AI sessions. Compare to one combined session.

End-of-lesson check

15 questions · take it digitally for instant feedback at tendril.neural-forge.io/learn/quiz/end-builders-agentic-multi-agent-systems-r8a8-teen

What is the core idea behind "Multiple AI Agents Working Together"?
1. Splitting one big task across specialized agents (planner, coder, reviewer) often beats one agent doing everything.
2. 'Suggest 5 ambitious summer projects for a 12-year-old who loves coding.'
3. Eliminate rollout risk
4. Capture approver identity and reason
Which term best describes a foundational idea in "Multiple AI Agents Working Together"?
1. specialization
2. multi-agent
3. roles
4. orchestration
A learner studying Multiple AI Agents Working Together would need to understand which concept?
1. multi-agent
2. roles
3. specialization
4. orchestration
Which of these is directly relevant to Multiple AI Agents Working Together?
1. multi-agent
2. specialization
3. orchestration
4. roles
Which of the following is a key point about Multiple AI Agents Working Together?
1. A research crew: searcher finds sources, reader summarizes them, writer drafts a report.
2. A code crew: planner makes a TODO list, coder implements one item at a time, tester runs the suite.
3. A content crew: ideator brainstorms, writer drafts, editor cuts.
4. A customer support crew: classifier routes tickets, responder drafts replies, supervisor reviews.
Which of these does NOT belong in a discussion of Multiple AI Agents Working Together?
1. A research crew: searcher finds sources, reader summarizes them, writer drafts a report.
2. A content crew: ideator brainstorms, writer drafts, editor cuts.
3. A code crew: planner makes a TODO list, coder implements one item at a time, tester runs the suite.
4. 'Suggest 5 ambitious summer projects for a 12-year-old who loves coding.'
What is the key insight about "The rule" in the context of Multiple AI Agents Working Together?
1. 'Suggest 5 ambitious summer projects for a 12-year-old who loves coding.'
2. Eliminate rollout risk
3. Specialization beats generalization — short focused prompts outperform one giant prompt.
4. Capture approver identity and reason
Which statement accurately describes an aspect of Multiple AI Agents Working Together?
1. 'Suggest 5 ambitious summer projects for a 12-year-old who loves coding.'
2. Eliminate rollout risk
3. Capture approver identity and reason
4. A multi-agent system has roles: a planner breaks down the work, a coder writes it, a reviewer checks it.
What does working with Multiple AI Agents Working Together typically involve?
1. Sketch a multi-agent system for a task you do weekly. Name 3 roles, each with one sentence describing their job.
2. 'Suggest 5 ambitious summer projects for a 12-year-old who loves coding.'
3. Eliminate rollout risk
4. Capture approver identity and reason
Which best describes the scope of "Multiple AI Agents Working Together"?
1. It is unrelated to agentic workflows
2. It focuses on Splitting one big task across specialized agents (planner, coder, reviewer) often beats one agent do
3. It applies only to the opposite beginner tier
4. It was deprecated in 2024 and no longer relevant
Which section heading best belongs in a lesson about Multiple AI Agents Working Together?
1. 'Suggest 5 ambitious summer projects for a 12-year-old who loves coding.'
2. Eliminate rollout risk
3. Some examples
4. Capture approver identity and reason
Which section heading best belongs in a lesson about Multiple AI Agents Working Together?
1. 'Suggest 5 ambitious summer projects for a 12-year-old who loves coding.'
2. Eliminate rollout risk
3. Capture approver identity and reason
4. Try it!
Which of the following is a concept covered in Multiple AI Agents Working Together?
1. multi-agent
2. specialization
3. roles
4. orchestration
Which of the following is a concept covered in Multiple AI Agents Working Together?
1. multi-agent
2. specialization
3. roles
4. orchestration
Which of the following is a concept covered in Multiple AI Agents Working Together?
1. multi-agent
2. specialization
3. roles
4. orchestration

← Back to interactive lesson

Tendril · Builders · Agentic AI

Multiple AI Agents Working Together

Splitting one big task across specialized agents (planner, coder, reviewer) often beats one agent doing everything.

40 min · Reviewed 2026

The big idea

Some examples

A research crew: searcher finds sources, reader summarizes them, writer drafts a report.
A code crew: planner makes a TODO list, coder implements one item at a time, tester runs the suite.
A content crew: ideator brainstorms, writer drafts, editor cuts.
A customer support crew: classifier routes tickets, responder drafts replies, supervisor reviews.

Try it!

Sketch a multi-agent system for a task you do weekly. Name 3 roles, each with one sentence describing their job.

Handing Off Between Two AI Agents Without Losing the Thread

The big idea

One agent that plans and one that executes is more reliable than one agent doing both. The planner writes the brief, the worker runs it — and you get cleaner outputs because each has one job.

Some examples

A Claude planner outputs a JSON brief that a GPT-4 worker turns into code.
A research agent writes a one-page summary that a writer agent expands into a blog post.
A spec-writing agent produces tickets that a coding agent picks up one at a time.
A triage agent labels emails and a response agent drafts replies using only the labels.

Try it!

Write two prompts — one that plans, one that executes. Wire them so the planner's output is the worker's input.

Multi-agent: a team of 3 agents that disagree productively

The big idea

Multi-agent setups split a task across specialized roles, each with its own prompt and personality.

Some examples

Drafter writes a first attempt.
Critic finds three problems.
Editor decides what to change and produces v2.

Try it!

Set up a 3-agent team to write your next essay outline. Compare to a single-agent version.

Design clear agent goals before adding tools
Define permissions and scope before deploying any agent
Build in human-approval checkpoints for high-stakes actions
Understand when to use an agent vs. a simple chat prompt

Design an agent spec: goal, tools, permissions, stop condition
Run a simple web-search agent in a sandbox environment
Instrument an existing workflow to identify where an agent could save time

Multi-Agent Systems: When AIs Work Together

The big idea

Some examples

Research products often run a search agent, an extract agent, and a synthesis agent.
Coding products may have planner, implementer, and reviewer agents.
'Auto' modes in chat tools often spin up multiple specialist calls under the hood.
When agents pass work to each other, context can get lost or distorted.

Try it!

Next research task, run the search and the synthesis as two separate AI sessions. Compare to one combined session.

End-of-lesson check

15 questions · take it digitally for instant feedback at tendril.neural-forge.io/learn/quiz/end-builders-agentic-multi-agent-systems-r8a8-teen

What is the core idea behind "Multiple AI Agents Working Together"?
1. Splitting one big task across specialized agents (planner, coder, reviewer) often beats one agent doing everything.
2. 'Suggest 5 ambitious summer projects for a 12-year-old who loves coding.'
3. Eliminate rollout risk
4. Capture approver identity and reason
Which term best describes a foundational idea in "Multiple AI Agents Working Together"?
1. specialization
2. multi-agent
3. roles
4. orchestration
A learner studying Multiple AI Agents Working Together would need to understand which concept?
1. multi-agent
2. roles
3. specialization
4. orchestration
Which of these is directly relevant to Multiple AI Agents Working Together?
1. multi-agent
2. specialization
3. orchestration
4. roles
Which of the following is a key point about Multiple AI Agents Working Together?
1. A research crew: searcher finds sources, reader summarizes them, writer drafts a report.
2. A code crew: planner makes a TODO list, coder implements one item at a time, tester runs the suite.
3. A content crew: ideator brainstorms, writer drafts, editor cuts.
4. A customer support crew: classifier routes tickets, responder drafts replies, supervisor reviews.
Which of these does NOT belong in a discussion of Multiple AI Agents Working Together?
1. A research crew: searcher finds sources, reader summarizes them, writer drafts a report.
2. A content crew: ideator brainstorms, writer drafts, editor cuts.
3. A code crew: planner makes a TODO list, coder implements one item at a time, tester runs the suite.
4. 'Suggest 5 ambitious summer projects for a 12-year-old who loves coding.'
What is the key insight about "The rule" in the context of Multiple AI Agents Working Together?
1. 'Suggest 5 ambitious summer projects for a 12-year-old who loves coding.'
2. Eliminate rollout risk
3. Specialization beats generalization — short focused prompts outperform one giant prompt.
4. Capture approver identity and reason
Which statement accurately describes an aspect of Multiple AI Agents Working Together?
1. 'Suggest 5 ambitious summer projects for a 12-year-old who loves coding.'
2. Eliminate rollout risk
3. Capture approver identity and reason
4. A multi-agent system has roles: a planner breaks down the work, a coder writes it, a reviewer checks it.
What does working with Multiple AI Agents Working Together typically involve?
1. Sketch a multi-agent system for a task you do weekly. Name 3 roles, each with one sentence describing their job.
2. 'Suggest 5 ambitious summer projects for a 12-year-old who loves coding.'
3. Eliminate rollout risk
4. Capture approver identity and reason
Which best describes the scope of "Multiple AI Agents Working Together"?
1. It is unrelated to agentic workflows
2. It focuses on Splitting one big task across specialized agents (planner, coder, reviewer) often beats one agent do
3. It applies only to the opposite beginner tier
4. It was deprecated in 2024 and no longer relevant
Which section heading best belongs in a lesson about Multiple AI Agents Working Together?
1. 'Suggest 5 ambitious summer projects for a 12-year-old who loves coding.'
2. Eliminate rollout risk
3. Some examples
4. Capture approver identity and reason
Which section heading best belongs in a lesson about Multiple AI Agents Working Together?
1. 'Suggest 5 ambitious summer projects for a 12-year-old who loves coding.'
2. Eliminate rollout risk
3. Capture approver identity and reason
4. Try it!
Which of the following is a concept covered in Multiple AI Agents Working Together?
1. multi-agent
2. specialization
3. roles
4. orchestration
Which of the following is a concept covered in Multiple AI Agents Working Together?
1. multi-agent
2. specialization
3. roles
4. orchestration
Which of the following is a concept covered in Multiple AI Agents Working Together?
1. multi-agent
2. specialization
3. roles
4. orchestration

← Back to interactive lesson