Most AI tools answer one prompt and quit, leaving the actual follow-through on your plate.
Give it a goal. It won't stop until the work is done.
Autopilot Agent is a manager-led team that plans a task, does the work with real tools, and checks its own results in a loop. It keeps going until your goal condition is fully met, then hands you the finished output.
Read the goal and set the definition of done
Broke the task into 7 numbered steps
Completed steps 1 to 5 and logged output
Goal Checker confirmed yes, report delivered
one run · manager plans, specialists report, you get one answer
The job, before you had a team for it.
This is the work Autopilot Agent quietly takes off your plate.
You get one answer, then the real work is still yours to finish
Long tasks lose the thread halfway through
You babysit the tool and re-prompt it over and over
No clear signal for when the job is actually done
A team of agents, not one prompt.
A manager agent reads the goal and hands each part to a specialist built for it, then reconciles their work into one result.
Owns the goal, hands work to the specialists, and only stops when the goal check returns a clear yes
Turns your goal into a specific, numbered plan that any agent can execute without guessing.
Works through the plan step by step with real tools and produces tangible output each cycle.
Makes a strict yes or no call on whether the goal is met, with reasons and what is still missing.
Records every step and finding so you can see exactly what the agent did and why.
How it runs.
Fork it, point it at your inputs, and let the team work.
Describe the task and what a finished result looks like.
Give the agent access to your data, search, and apps.
The team plans, works, and self-checks until the goal is met.
Read the finished output plus a full log of every step.
Build a competitor landscape report.
"Research our top 5 competitors and give me a report on pricing, positioning, and gaps we can win."
- A numbered research plan covering all five competitors
- Pricing and positioning pulled for each one
- A gap analysis of where you can win
- A finished report with a full step-by-step log
Where teams put it to work.
Turns a rough brief into a finished research report while they focus on selling.
Cleans and interprets messy data sets without hand-checking every row.
Tracks competitors and drafts a positioning summary on a set schedule.
- A goal and a clear definition of done
- Access to your data, search, and connected apps
- An optional loop cap to control cost
- A numbered execution plan
- Real, tangible output for each step
- A yes or no goal check with reasons
- A full log of everything the agent did
What is an autonomous ai agent?
An autonomous ai agent is software that pursues a goal on its own. It plans steps, acts with real tools, and checks whether the goal is done before it stops.
Unlike a chatbot that answers one prompt, an agent runs a loop of plan, act, and evaluate. Autopilot Agent packages that loop as a ready-to-use team.
Why use a manager-led team instead of one model?
Splitting work across focused agents makes long tasks more reliable. A manager owns the goal while specialists plan, execute, and evaluate in their own lanes.
Anthropic found a lead-plus-worker setup beat a single top model by 90.2% on its research eval. Structure keeps a goal-driven ai agent on track from start to finish.
New to this? Read our guide on how to build a sales battlecard.
Questions, answered.
How is this different from a chatbot?
A chatbot answers one prompt and waits. This agent runs a loop: it plans, acts with real tools, and checks its own work until the goal is truly met.
How do I stop it from running forever?
You set a clear goal condition and an optional loop cap. The agent stops the moment the Goal Checker confirms the goal is met, or when the cap is reached.
Can I see what it actually did?
Yes. The Progress Logger records every step and finding, so you get the finished output plus a full, readable trail of the agent's decisions.
Fork Autopilot Agent and make it yours.
Start from a working team of agents, then swap the tools, tune the instructions, and run it in your own workflows.
Fork this template