Enterprise AI, from go-to-market to governance.
I've spent four decades building software, architecting enterprise cloud, and leading teams. As Lead AI GTM Strategist at GitHub, I help organizations do far more than sell AI. I help them implement it, manage it, and govern it at enterprise scale.
Recent thinking
All articles →The Second Invoice: What AI-Generated Code Costs After the Meter Stops
The token bill is the cheap part. AI-generated code moves most of its real cost downstream—into review time, rework, failed builds, and the compute burned re-running pipelines. Here is how to find that cost before it finds your budget.
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The Multi-Model Mirage: Governance, Cost, and Accountability When Every Developer Picks Their Own AI
Enterprise AI coding environments now support a dozen model choices per developer. That flexibility is real. So is the governance vacuum it creates—and the cost exposure that accrues quietly under uncapped usage-based billing.
Read article →Benchmark Theater: The Leaderboard Is a Press Release
Frontier AI models arrive roughly every two days, each announced with curated benchmark scores. For enterprise teams making procurement decisions, the noise has become the problem. A framework for what actually predicts model performance in production.
Read article →The Atrophy Risk: What Happens to Developers When AI Goes Dark
Controlled trials, outage data, and cognitive science converge on a warning most teams haven't heard yet: the developer who can't function without AI is a liability, not an asset.
Read article →Bringing AI into your enterprise and need it to actually land?
Advisory for leaders who need AI strategy, adoption, and governance to move as one.