What I'm working on

I'm running the go-to-market engine through the fourth quarter while the 2027 plan takes shape. Inside revenue operations we're building on Teradata's own newest products, including the Autonomous Knowledge Platform, so the analysis and agents we build work from governed context and customer data rather than from whatever someone pasted into a prompt.

In December I'm on a panel at the Revenue Operations Summit in London on breaking down silos. My view is that most go-to-market silos are a question of who owns the number, and they only look like strategy problems. In September I spoke at the Sales Enablement Leaders Conference on why enablement and revenue strategy should own the context layer for AI.

Two long-form projects are underway. The first is a co-authored practitioner book on go-to-market strategy to planning, written as a field manual for companies from their first sales team to a global enterprise. The second is the operating-model section of a Growth Institute paper on how an AI-native go-to-market organisation works, including how work divides between creating, reviewing and executing once agents work alongside sellers. On this site, two new frameworks are in progress: one on the future shape of RevOps, and one on how fast an organisation can absorb AI, which now sets the pace in go-to-market more than the technology does.

Outside software, I'm researching physical AI: robotics, autonomy, and AI in factories, warehouses and on the roads. The question I keep coming back to is how a company plans capacity and pricing when its product does work that people used to do.

I've just rebuilt this site. Each framework now has a short, self-drawing visual you can watch in full or a section at a time, and the frameworks sit on one map that shows how they fit together.