* pinned a-network-mcp.md
A network MCP
An open-source, vendor-agnostic MCP service for AI-assisted network troubleshooting — starting read-only, with a roadmap toward gated write operations.
! Latest Articles
* pinned the-anatomy-of-an-ai-agent.md
LLM as CPU, agent as OS
AI agents are starting to look like operating systems. The LLM is the CPU, the agent is the OS, and skills and MCPs are the applications — here's why that analogy holds up.
yang-the-network-data-model.md
YANG: the schema behind every modern network API
A practical guide to YANG data models — the modeling language that defines what NETCONF, RESTCONF, and gNMI actually transport, and why it matters for network automation and AI agents.
! Recent Syslog
router# show logging | tail
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Dwarkesh Patel and Dylan Patel (SemiAnalysis) got an exclusive tour of Microsoft’s Fairwater 2 datacenter with Satya Nadella. Each Fairwater building has hundreds of thousands of GB200s & GB300s, with over 2 GW of total capacity across the interconnected sites — a single building already outscales any other AI datacenter that exists today.
The interview covers how Microsoft is preparing for AGI across the full stack: business models, the CAPEX explosion turning Microsoft into a capital-intensive industrial company, in-house chip development, the OpenAI partnership structure, and whether the world will trust US companies to lead AI. Worth the full watch.
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The Pragmatic Engineer interviewed Mitchell Hashimoto about his new way of writing code. The bit that stuck with me: always have an agent running in the background. Don’t wait for it to finish — kick off a task, context-switch to something else, come back when it’s done. Treat agents like background jobs, not pair programmers.
It’s a subtle shift but it changes how you structure your work. You stop thinking sequentially and start thinking in parallel — like managing async workers instead of typing code yourself.
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Worth watching: The 5 Levels of AI Coding. A solid framework for thinking about where you actually sit on the AI-assisted development spectrum — from basic autocomplete all the way to fully autonomous agents. Honest about what each level demands from the engineer and where the real productivity gains (and risks) live.
Most of us are somewhere in the middle and kidding ourselves about it. Good gut check.