llms.txt
This site provides machine-readable content for AI agents and LLMs following the llms.txt standard. Whether you're building an agent, doing research, or just curious — here's what's available.
Available Files
/llms.txt Curated article index with titles, URLs, and descriptions. Start here.
/llms-full.txt Expanded summaries with key excerpts from each article. More context for deeper understanding.
/articles/{slug}.md Full article content in clean markdown. Each article page includes a <link rel="alternate"> header pointing to its .md version.
What's Included
91 evergreen articles on agentic development, GitHub Copilot, context engineering, DevOps automation, and agent governance.
✅ Included
- Published deep-dive articles
- Technical guides & tutorials
- Architecture & pattern articles
- Tool comparisons & reviews
❌ Excluded
- Weekly roundups
- Draft articles
- Paid blueprints
- Newsletter issues
How to Use
For AI Agents
Fetch /llms.txt for a quick index, or /llms-full.txt for richer context. For specific articles, use /articles/{slug}.md.
For Developers
Each article HTML page includes a <link rel="alternate" type="text/markdown"> header, so your tools can discover the markdown version automatically.
Recent Articles
Windows Agent Runtime — What Microsoft Gets Right About Agent Sandboxing
Microsoft's Windows Agent Runtime introduces OS-level sandboxing for AI agents. Here's what it gets right, how it compares to NVIDIA OpenShell, and what's still missing.
Frameworks Don't Execute Themselves
Every transformation framework tells you WHAT to do but provides zero enforcement. The solution isn't another framework — it's a harness.
The Definitive GitHub Actions Debugging Guide: 65+ Real Errors and How to Fix Them
Every GitHub Actions error message, root cause, and fix in one place. From YAML gotchas to OIDC failures — the debugging reference you'll actually bookmark.
Platform Team Burnout Is Real — Here's How I Rescued Mine with AI
I built 10 interconnected frameworks across 60+ repos as a solo platform engineer. The backlog hit 500 issues. Then GitHub Copilot changed everything.
Per-Turn Evaluation: Dynamic Governance for AI Agents
Per-turn evaluation gives AI agents dynamic governance by re-evaluating rules, tools, and context from live state instead of startup config.
The Functional Options Pattern for AI Agent Composition
The Go functional options pattern is a clean way to compose tools, guardrails, memory, and middleware into production-ready AI agents.
What Is Harness as Code? The DevOps of AI Agents
Harness as Code applies Infrastructure as Code principles to AI agents: declarative governance, reproducible behavior, and auditable context.
Copilot Plugins: Building Domain-Expert AI Teammates
Build Copilot plugins with domain knowledge, MCP tools, and custom skills so Copilot acts like a specialist teammate, not just autocomplete.
Custom Copilot Agents: Building Domain-Expert AI Teammates with Skills, MCP Tools, and Custom Knowledge
Most teams stop at autocomplete. The real unlock is building custom Copilot agents that know your codebase, workflow, and tools.
Platform Engineering with GitHub: How to Build an Internal Developer Platform Using Copilot, IssueOps, and Golden-Path Starter Repos
Stop building Backstage. Your IDP already exists — it's GitHub with Copilot extensions, IssueOps workflows, and golden-path starter repos.