Writing
Thoughts on AI, Engineering & Leadership
Essays for the people who build and run software at scale.
The great AI lockdown has begun
Strava, Garmin and Reddit are closing the free doors. SAP, Salesforce and ServiceNow are metering theirs. AI broke the open-API bargain. Access is repricing.
AI is either as good as it gets, or the worst it'll ever be
The AI debate fixates on capability. The variable that decides whether AI earns its place in what you build is cost, and falling cost is the base case.
Enterprise support was built for a clock speed that no longer exists
AI sped up exploits, vendor releases and agent workflows at once. The support model built for annual upgrades cannot keep up. A wake-up call for app leaders.
AI isn't killing content, it's exploding it
Surely AI should mean fewer documents, apps, and sites. Like email and the paperless office before it, it is multiplying them instead.
Vibe Coding in the Enterprise: Why Citizen Developers Are the Real Opportunity
How CIOs should think about vibe coding for citizen developers. Governed prototyping on a sanctioned platform, with a clear graduation path to engineering.
95% of companies get no ROI from AI. Here is what separates the 5%
The MIT and McKinsey data on AI underperformance points to a consistent pattern. The gap is not about tooling.
Building an MCP server for persistent workout memory in Pelaris
How I built a production MCP server to give Claude and ChatGPT persistent workout memory, and what broke along the way.
I built an AI-powered CI/CD pipeline that manages itself
From user feedback to deployed code. Here's the architecture, the tools, and what building AI at enterprise scale taught me about doing it for Pelaris.
The interface is the product - AI revolution is a UI/UX revolution
AI capability has outpaced human ability to use it. The bottleneck in 2026 is no longer the model, it's the interaction layer.
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