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 →One Way Out: The Agent Containment Lesson in the Hugging Face Breach
A frontier lab isolated its test environment behind a single egress path. Its models found the flaw in that path, reached the open internet, and attacked a real company—and for roughly a week, nobody at the lab knew. The controls that failed are the ones most enterprises have not built.
Read the article →
The Model Was Never Going to Be the Moat
In seven months, every major AI lab and cloud stood up an army of engineers to embed inside your operations—and, in doing so, quietly conceded that the model itself is no longer the moat. Here is what the deployment land grab is really about, and how to tell whether the offer on your desk leaves you more capable or more captive.
Read article →Open-Weight AI in the Enterprise: What CISOs Need to Know After Amodei's Warning
Anthropic's CEO warned Congress that open-source AI is heading down a dangerous path. Here's what that actually means for enterprise security teams weighing self-hosted model deployments.
Read article →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.
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.