Has its own computer and browser
It does the legwork itself: finds the people, checks job changes, launches and funding news, reads the sources and fact-checks claims before anything ships.
Buyers in your ICP live where you do.
The agent has its own computer and browser, so it finds the people and the news itself. It drafts every comment, connection note and message, and you approve what goes out. Use it when:
The agent has its own computer and browser, so it does the legwork itself. Every skill is on for every play; these are the ones this play leans on.
It does the legwork itself: finds the people, checks job changes, launches and funding news, reads the sources and fact-checks claims before anything ships.
Comments, connection requests and messages on LinkedIn, aimed at the people your posts pull in who match your ICP.
Matches everyone who engages to your ICP and hands sales a worked list every week.
Drafts for the company page, founders, executives and employees from each person's best posts. Imagine AI started as the operating system for ghostwriting teams, so sounding like you is the core of the product.
Multi-image posts, infographics and visuals from your brand kit, made in its own sandbox, with the right people and companies tagged.
Plan launches, sequence posts, schedule comments and edit together. Approvals sit with each person or route through one owner.
Positioning, brand kit, decks, campaigns and compliance rules in one place it reads before every draft, remembered across threads.
Events, podcast episodes, videos, decks and call notes become a week of posts across the team.
Reads the public benchmark of 1,000+ B2B companies and tracks your competitors, so post types and formats follow your industry's data.
Connects to HubSpot or Salesforce and traces each closed deal back to its first content touch: post, person, deal stage moves.
Engager data over API and webhooks, and the benchmark over MCP for your own agents.
Watch it work on one of your people.
The playbook lives as a file the agent reads. Edit it once and every run follows it.
coffee-in-your-city.md
SaveStep 1 · Find local buyers
Step 2 · Connect locally
Step 3 · Ask with a time and place
Step 4 · Follow up after
Fig. 02: The playbook as a file in your workspace.
The outline, what to avoid and how to measure it, in the file the agent drafts from.
local-coffee.md
SaveOutline
Example from the run above
Avoid
Measure
Fig. 03: The outline, part by part.