Building better platforms with Azure, GitHub, Terraform and AI
An Azure AI Landing Zone should make the governed route the easiest route for delivery teams. This post covers how Azure API Management, Azure Policy, identity, networking, quotas, telemetry and clear ownership boundaries work together to control AI consumption without turning the platform team into an approval bottleneck.
The Draw.io MCP Diagramming Agent Skill provides a reusable working method for creating clear, editable diagrams with Draw.io MCP. It supports cloud architectures, network topologies, CI/CD pipelines, Kubernetes platforms, event-driven systems, C4, UML and more, while applying consistent guidance for layout, containment, connector routing, labels and validation.
Agent skills are only useful if the agent knows when to use them. A clear description acts as selection metadata, helping the agent load the right guidance, avoid noisy context, and produce more consistent results across repeated engineering tasks.
Agent skills, custom instructions, and MCP configuration are becoming part of the engineering trust boundary. This post walks through using NVIDIA SkillSpector in GitHub Actions to scan AI skill repositories, surface findings in SARIF or PR comments, and make risky agent behaviour visible during normal review.
AI-assisted engineering is moving beyond “can the agent do the task?” and into the same practical concerns platform teams already deal with: cost visibility, ownership, observability, governance, repeatable workflows, and sensible defaults.
This post looks at why AI engineering needs boring platform controls, from APIM policies and token visibility through to Agent Skills, MCP, Terraform modules, OpenTelemetry, and evaluation loops.
The future of Infrastructure as Code isn’t about writing more Terraform. It’s about teaching agents how your platform works, letting AI handle the repetitive parts, and spending more time reviewing intent instead of syntax. Here’s how agent skills, MCP servers, and natural language workflows are quietly reshaping IaC.
If you’ve been using GitHub Copilot Chat in Visual Studio Code, you already know how good it is at answering questions and generating code. But sometimes it feels a little too “one-size-fits-all.” That’s where Custom Chat Modes change the game. With this feature, you can define exactly how Copilot Chat behaves – from its tone … Read more
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