Switch from CrewAI to Task Machine

CrewAI is an open-source Python framework, with a cloud control plane, for developers who build multi-agent "crews": roles, tasks, and tools you define and wire together in code. It is a toolkit you assemble, aimed at engineers. Task Machine is a packaged product for operators: playbooks and an inbox replace wiring agents in Python. The people who switch are usually the ones who wanted the outcome — leads qualified, reports sent, content shipped — and discovered they had signed up for a software project instead.

Why do people switch from CrewAI?

• The crew is code someone has to maintain. A framework means writing it, running it, and keeping it working as models and dependencies change. Task Machine ships the workflow as a product: pick a playbook from the catalog — 123 playbooks across 17 categories — or describe the job in chat.
• Building and operating are different jobs. A framework gives you building blocks, but it doesn't give you the day-to-day surfaces to run the work. Task Machine's three-surface workflow (chat, inbox, tasks) is that operating layer: direct from chat, approve from the inbox, dig into a task when it matters.
• Human review is a first-class step. Task Machine workflows have approval and question steps built into the graph, all landing in one shared inbox, so a person is part of the run rather than something you code around.
• Runs you can verify. Task Machine runs deterministic, verifiable workflows — explicit steps with verifier checks and step-level run history you can read after every run.

What maps to what?

What do you give up?

A framework gives developers unlimited flexibility: if you can code it, a crew can do it, in whatever shape your problem demands. Task Machine's workflows are structured — explicit graphs with agent, approval, question, and verifier steps — which is the point for operators, but a constraint for engineers with a genuinely custom architecture in mind. Teams with developers and an unusual problem shape often keep CrewAI for that work.

How does the switch work?

1. List the crews doing standard business work — outreach, research, reporting, content — versus the genuinely custom ones. The standard work is the migration candidate.
2. Join the Task Machine waitlist, connect the accounts those jobs touch, and pick the playbooks that match.
3. Recreate each candidate as a workflow: agent steps where the judgment lives, an approval step before anything consequential, a verifier step where output must meet a bar.
4. Run both for a cycle, compare results from the step-level run history, then retire the code you no longer want to maintain.

Common questions

Do I need to write any code?

No. Playbooks and chat replace the Python. You connect accounts, pick or describe workflows, and review from the inbox.

Does Task Machine replace CrewAI for developers?

Not always. If your team is engineers building genuinely custom multi-agent systems, a framework keeps its place. Task Machine takes the standard recurring business work that never needed custom code.

Do agents act without my approval?

Only where you allow it. Each agent has an autonomy level, the default routes consequential actions to your inbox, and token and money budgets alert you at 80% and 100%.