Match each multi-agent framework to its coordination model
CrewAI coordinates through role-based delegation, AutoGen through a moderated group chat, and LangGraph through an explicit state graph with conditional edges.
Imagine three ways to run a team project. In the first, you hand each person a job title and a task, and they pass work down the line. The researcher gathers facts, the writer drafts, the reviewer checks. That is CrewAI. In the second, everyone sits in one chat room and a facilitator decides who speaks next, so the work emerges from conversation. That is AutoGen. In the third, you draw a flowchart on the wall with arrows and decision diamonds, and the team follows the arrows, branching based on what they find at each box. That is LangGraph. All three get the same kind of work done, but the way control passes between people is completely different. The first leans on roles, the second on dialogue, and the third on an explicit map of who runs when.
Detailed answer & concept explanation~8 min readEverything you need to truly understand this topic: intuition, mechanics, step by step explanation, code, formulas, and worked example. Click to expand.
Everything you need to truly understand this topic: intuition, mechanics, step by step explanation, code, formulas, and worked example. Click to expand.
Everything you need to truly understand this topic: intuition, mechanics, step by step explanation, code, formulas, and worked example.
Everything important, quickly.
Name each framework's coordination model in one line, then contrast control flow visibility, show how each handles a new branch, and close by mapping each to the task shape it fits, with the graph model winning for audited branch-heavy work.
Real products, models, and research that use this idea.
- A research-report pipeline in CrewAI uses a Researcher agent to gather sources, a Writer to draft, and a Reviewer to fact-check, with tasks chained in sequence.
- AutoGen powers code-generation assistants where a coder agent, an executor agent, and a critic agent debate fixes in a GroupChat until tests pass.
- LangGraph backs LangChain's prebuilt ReAct and supervisor agents, modelling tool loops and multi-agent handoffs as conditional edges over typed state with checkpointing.
- Teams pairing Claude Opus 4.7 or GPT-5.5 with LangGraph get replayable traces and human in the loop interrupts for audited, branch-heavy enterprise workflows.
What an interviewer would ask next. Try answering before peeking at the approach.
QHow does adding a new conditional branch differ across CrewAI, AutoGen, and LangGraph?
QWhy do audited or compliance-heavy workflows tend to converge on the graph model?
Don't say thisRed flags and common mistakes that signal junior thinking. Click to expand.
Red flags and common mistakes that signal junior thinking. Click to expand.
Treating the three as interchangeable wrappers. They differ in their core coordination model, and that choice drives how you debug, branch, and control the workflow.
The night-before-the-interview bullets. Scan these on the way to the call.
Primary sources. Skim if you want the original framing.
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