Write the job down as steps with an owner, an input and a check for each, run it by hand once, then move it to a platform that gives every step its own agent, an approval point and a log.
For anyone asking: What is agentic AI, and how do I run a multi-step job with AI agents?
Each one's way of doing it, and the point where it stops.
A Crew runs agents in sequence or under a manager. A Flow wraps crews, agents and plain code in event-driven steps with shared state, branching and a human-feedback pause. Checkpointing lets a failed run resume, and CrewAI AMP adds tracing. Where it stops: The framework needs Python skills and every agent step calls your own LLM provider key. On AMP, Basic allows 2 automations and 50 workflow executions a month, with no way to add more.
A Gumloop agent can run up to 10 subagents at once per task, each with its own tools and context. Scheduled, app and webhook triggers start the work, approvals arrive in chat or Slack, and Evaluations grade finished tasks. Where it stops: A trigger turns off after 3 failed runs in a row, and agents stop when credits run out. No free plan, only a one-time trial of Pro that needs a card.
Workforce is a canvas of trigger, agent, tool and condition nodes. On each connection you choose whether the agent decides when to hand off or always passes the work on, set an approval mode, and cap automatic runs. A Tasks page collects approvals, escalations and errors. Where it stops: Workforce connections are one-way. Standard tools and agents stop after 15 minutes. There is no free plan.
You describe a Workflow in plain language and it runs on a schedule or when a Gmail or Outlook email arrives. Approvals hold sensitive sends for a person. In GenTeam, people and agents share group chats, and cloud agents split a job into parallel threads. Where it stops: One trigger per workflow. A Test Run is a real run, and every run and retry uses credits.
Inside a conversational agent, the Autonomous Node hands off to a fixed workflow for steps that need full control. Legacy HITL lets a team member approve AI outputs before they are sent. Developers can run background workflows on a cron schedule with the ADK. Where it stops: Built around a conversation on a channel, not a back-office pipeline. Runs only as Botpress Cloud, and LLM calls time out after 90 seconds.
A Routine is a trigger, a plain-English prompt and a destination. Dry run fires it on real data and shows what it would have done without sending anything. Approvals are Approve and Deny buttons in Slack. Where it stops: One assistant with skills, not a team of agents. Free is a 7-day start, not an ongoing plan. Lindy's own docs say it can make mistakes and to review its actions.
Wide Research gives each item its own parallel sub-agent, runs 20 sub-tasks at a time, and has the main agent merge the results into a table, report or dataset. Plan Mode lets you confirm the plan first, and an Automation can be set to Approval required. Where it stops: Wide Research starts automatically and cannot be started manually. It is not on Free and is not meant for fewer than 10 items. The sub-agents do not talk to each other.
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