Modernizing workflows to deliver the introductions that matter.
Talent searches. LP research. Advisor matching. Portfolio founder introductions. Each one runs on the same underlying work: research, outreach, brief, connection, and follow up.
Hand Axe takes that work and encodes it into AI workflows specific to your operations. Not a generic tool. A system built around your network, your thesis, and your knowledge. We help you construct the systems so specialist work can start at judgment, not drudge work.
You have a mandate to automate and nobody to do it
You're one person carrying talent, or fundraising, or platform. The firm bought the subscriptions. Nobody ever wrote down how your work actually gets done. You keep going back and forth in a chat and doing things manually.
That's the problem I work on. Not a tool you have to learn. One workflow, made repeatable, starting with what's due next.
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About
Tyson Bennett spent years inside the work software was supposed to automate. Executive recruiter. Head of talent at a VC firm. He has done the calls with founders, the partner searches, the LP coordination, and the platform mandates that land on one person's desk.
Hand Axe is the practice he built when he realized the tools to execute with better memory and automated tasks have arrived.
How It Works
Three steps to leverage AI for VC Operators, Platform, and Talent Leaders.
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Step 1 — Diagnostic call
One hour. $100. We map what you actually produce on a repeating basis and score it — what recurs, what has good past examples, what has a real deadline against it. You leave with one named workflow and a written recommendation within 24 hours. Nothing gets built on this call.
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Step 2 — First Rep
90 minutes on your live work against a real deadline. You walk me through why your good output is good. We write it down as a recipe, then run it once on the thing that's actually due. You leave with one file, on your machine, that you edited yourself. We find out how much time you save and define the ROI.
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Step 3 — Ongoing Sessions
Biweekly. Each one takes on the next workflow, or polishes at the last one. The files accumulate. Around the fourth or fifth session you have a knowledge base built out of work you actually do that can become your AI Operating System.