Claude Cowork — LinkedIn Multi-Agent GTM System
12 autonomous agents running an entire LinkedIn growth + outbound motion
A fully autonomous LinkedIn go-to-market system: 12 Python agents orchestrated through the Claude API that discover trending AI topics, draft and publish posts in the founder’s voice, score inbound and outbound leads on a 100-point ICP model, run a 7-day warmup, and send personalized DMs — with zero manual input.
The pain this had to solve
Founder-led GTM on LinkedIn works, but it eats hours every day: finding what to post about, writing in a consistent voice, identifying who is worth reaching out to, warming them up, and following through on DMs. None of it scales with a single person’s time.
The goal was an autonomous system that runs the whole loop end-to-end while keeping the output on-brand and the targeting tight enough that outreach stays credible, not spammy.
What I built — the architecture
Agents scan 22 sources daily to surface trending AI topics worth posting about.
A writing agent drafts and publishes ~2 posts/day matched to the founder’s tone and prior posts.
A scoring model ranks prospects on title, intent, company fit, and recent activity so outreach targets the right people.
A 7-day per-prospect warmup precedes personalized DM outreach, all sequenced by the orchestrator.
12 agents coordinated via the Claude API with shared state, integrating Apify, Chrome automation, and Google Sheets.
What it delivered
In its first 28 days the system lifted LinkedIn impressions by 5,735% (to 3,676), reached 1,156 members, and put 31 qualified leads into the pipeline — all on autopilot, with zero manual steps in the daily loop. It turned a founder’s scattered, hours-a-day LinkedIn effort into a hands-off GTM engine.
Want results like this for your team?
Tell me what you want to automate. On a free 30-minute call I’ll tell you straight whether it’s worth building, roughly what it costs, and how I’d approach it — no pitch, no obligation.
Book my free 30-min AI scoping call →