Programs led by expert operators

The board wants an AI strategy, the CEO wants efficiency, and your team wants to know their jobs are safe. AI fluency has moved from “nice to have” to the capability boards now screen senior People leaders for. This peer advisory program gives you the AI systems — and the standing — to answer all three.

A team of two to five people can already supervise fifty to a hundred specialised agents running an end-to-end process. The org design frameworks most CXOs know — Team Topologies, squad models, OKRs — do not account for that third dimension: what work is human, what is agent-operated, and how you design the interface between them. This program is the upgrade.

Most early-stage ventures hit the same wall: growing brand awareness economically, finding lead generation channels that actually repeat, and building sales systems that scale. This program hands you a field-tested go-to-market gameplan and a growth engine run by AI-native agents, built with a founder who has done it five times.

Your best knowledge is already written down. Build a private knowledge layer Claude can query in plain language, and get answers from what you actually know.

AI made building cheap. Not knowing your customer is what gets expensive. Six weeks to map your customer across 19 dimensions, run real interviews, lock an ICP you can defend, and leave with decision briefs instead of assumptions.

Go from qualified to in market in four weeks. Build the assets, open all four channels, and leave with a 90-day plan to keep the work coming.

In 3 weeks, go from “never sold to the government” to registered, certified (where eligible), armed with a capability statement and a live opportunity pipeline, with your first bid submitted.

Build the system that ships your work: agents running for hours, securely, without you pressing enter. Everyone teaching agentic development teaches the middle — prompting, context, tools. It goes wrong at the edges.

The ticket increasingly writes itself. What doesn’t get automated is judgment: which problem is worth solving, whether the solution fits the user, and how to defend a trade-off in a room full of stakeholders.