Rerun lets you build an entire AI workforce with a single prompt
Rerun now automatically spins up specialized AI teams—complete with managers, researchers, and copywriters—just by reading a plain-language business goal. Each agent gets its own memory, browser environment, and automated task-handoff rules. The big shift here is putting AI in charge of managing AI, leaving humans to simply set goals and approve results.
Setting up multi-agent workflows usually feels like building a complex flowchart by hand: you wire the tools, manage the context windows, and manually connect each step. Rerun wants to automate that management layer entirely.
Instead of designing nodes, you describe your business objective in plain English. Ask it to build a marketing team that monitors competitors, hunts for leads, and drafts social content, and Rerun automatically spins up a virtual crew—assigning an AI Foreman alongside dedicated research, sales, and copywriting agents.
Digital workers with their own desks
Every coworker comes with defined responsibilities, persistent memory, dedicated skills, and its own browser sandbox. You can monitor their screens in real time and take over the controls whenever an agent gets stuck.
What makes this genuinely useful is autonomous handoffs. Tasks can run on schedules or trigger based on events, and agents pass work directly to one another under the Foreman's coordination. That eliminates the tedious manual relaying of data between different bots.
Why it matters
Rerun shifts the multi-agent paradigm from rigid task pipelines to role-based organizations.
Instead of acting like a pipeline engineer constantly debugging context handoffs, you step into an executive role: setting high-level targets, assigning permissions, and reviewing final drafts before they go live.
Still, autonomous agent delegation remains notoriously delicate. If the Foreman misinterprets a goal or context drops during a handoff, errors can snowball across the entire chain. Giving AI the keys to middle management is promising, but keeping a human in the loop is still very much required.