This is the fastest path from "never heard of Fleet" to "agents running and coordinating on my repo." I'll keep it tight.
What you need
A Mac, Linux, or WSL2 terminal. An existing AI coding setup (Claude Code, Cursor, Copilot, whatever you're already using). Five minutes.
That's the whole list. No Docker, no Node.js, no package manager, no cloud account.
Install
curl -fsSL https://fleetctl.ai/install | sh
This downloads a single binary. The entire product is that binary. Confirm it worked:
fleet version
Initialize a fleet on your repo
cd into whatever project you want to try this on and run:
fleet init
Fleet creates a .fleet/ directory with a starter config. Open .fleet/config.yaml. You'll see something like this:
agents:
- name: product-owner
role: product-owner
model: claude-sonnet # ticket refinement doesn't need Opus
subscriptions:
- ticket_created
routes_to:
- frontend-dev
- backend-dev
- name: frontend-dev
role: developer
model: claude-opus # complex implementation work
department: engineering
subscriptions:
- ticket_ready
- name: tech-lead
role: tech-lead
model: claude-sonnet # review works well on Sonnet
department: engineering
subscriptions:
- pr_needs_review
Three agents out of the box. The PO agent subscribes to new tickets, refines them, and routes them to the right developer agent. The developer agent wakes up when a refined ticket is ready. The tech lead agent wakes up when a PR needs review.
Notice the model config. Each agent runs the model appropriate to its job. Sonnet for ticket refinement and review. Opus for implementation. You can change these to whatever you want later.
Start the fleet
fleet start --all
Check what's running:
fleet status
Output:
Fleet: 3 agents running | 0 idle | 0 errors
product-owner running (tmux: fleet-po) model: sonnet
frontend-dev running (tmux: fleet-frontend-dev) model: opus
tech-lead running (tmux: fleet-tech-lead) model: sonnet
Each agent runs in a managed session. Fleet handles startup, shutdown, health checks, and restart-on-crash.
Turn on the reactive engine
This is the part that changes everything. Up until now you've been manually prompting each agent. The watcher makes the pipeline autonomous.
fleet watcher start --supervised
The watcher monitors GitHub labels, event subscriptions, and cron schedules. When a condition is met, it routes the event to the right agent.
Test it. Go to one of your GitHub issues and add the label "ready." Watch your terminal.
Fleet detects the label. The PO agent picks up the ticket, refines it with acceptance criteria and scope, and routes it to frontend-dev. The development agent starts working. When it opens a PR, a pr_needs_review event fires and tech-lead picks it up.
Nobody prompted anything. Nobody read an email. Nobody manually assigned a reviewer. The event chain ran itself.
Check the audit log
fleet log
Timeline of every event, every agent action, every decision. Timestamps, agent names, event types, outcomes. This is the thing your engineering manager will care about. Remember where it is.
What to do next
You now have a working agent fleet with reactive coordination. A few things worth trying from here.
Browse the template library. Fleet ships with 136 pre-built configs. Run fleet templates list to see them. There's a full-stack dev team with PO routing, a DevOps pipeline crew, a security review squad, an SRE monitoring setup, and a lot more.
Add an SRE agent. Subscribe it to deployment_complete events. It monitors error rates after each deploy and can trigger a rollback if something spikes. Runs great on Haiku since it's making simple threshold decisions.
Turn on Brain. Fleet's scoring engine evaluates every agent run on six dimensions and flags anomalies. fleet brain start activates it.
Set up a pipeline. Multi-stage workflows with approval gates. fleet pipeline init scaffolds your first one.
If you're evaluating Fleet for your team
The fastest way to build an internal case is to run Fleet on one repo for a week, then pull the fleet log, point to the event chain (ticket, PO refinement, agent implementation, automated review, merge), and show how the pipeline ran autonomously.
There's a page at fleetctl.ai/for-leaders that covers the business case without any code. Send it to your VP. It speaks their language.