Thomas Thornton Blog

Deploying a model endpoint in Microsoft Foundry or Azure OpenAI is easy enough. The harder part starts when several teams want to use it, with different applications, budgets, data boundaries, security requirements and opinions about which model they need. Without a shared platform pattern, direct integrations spread quickly. Identity gets handled differently between applicat...

AI-assisted engineering is easy to measure badly and the usual numbers appear first: active users, accepted completions, generated lines of code, tokens consumed, agent sessions and pull requests opened. They prove that something happened, but not that it helped. For platform teams, the useful question is: Is AI-assisted work producing worthwhile engineering outcomes at a sen...

I have created a broader Draw.io MCP Diagramming Agent Skill for generating clear, structured and editable diagrams across a range of use cases, including cloud architecture, network topology, CI/CD pipelines, Kubernetes platforms, event-driven systems, C4, UML and entity relationship diagrams. The skill applies the same diagramming method across each request: choose the righ...

Agent skills are a practical way to capture reusable engineering judgement for AI coding agents, whether that judgement relates to reviewing Terraform, creating architecture diagrams, writing API Management policies, checking pull requests or following a migration approach. A skill does not guarantee a correct answer, and it should not be treated as a shortcut around engineer...