I wrote a book.
147 pages. 5 pillars. Everything I learned building AI agents that actually work in production.
Not theory. Real patterns from systems handling millions of requests.
Link: https://t.co/yhmTBcn1m7
On May 20, 2026, the NSA published its first formal cybersecurity advisory on MCP.
Fifteen pages. Cybersecurity Information Sheet U/OO/6030316-26.
The message is calm and clear: MCP adoption has raced ahead of MCP security.
Three vulnerabilities. One pattern. 🧵
The NSA is not asking anyone to stop with MCP.
The advisory is asking us to know where the trust boundaries actually live — and to enforce them ourselves.
Because the protocol will not do it for us.
Full walkthrough of the build here, with the working agent running live end to end:
https://t.co/ximYitqSnB
What was the first agent build that survived a real user on your team?
Most n8n AI agent tutorials look impressive in the demo and fall apart on real input.
I built a hotel discovery agent this week — real SerpAPI data, real Claude Sonnet 5 reasoning, real hotels with real prices.
Four architectural calls made it survive real input. 🧵
The tools are the easy part. Every team has n8n. Every team has an API key.
The four calls are what separate a real agent from a demo that only works on the one input the tutorial was built around.
Free to install. Search Depwire in VSCode Extensions.
Pro at $9.99/month → health breakdown, security scanner, dead code, What If simulation, temporal graph.
https://t.co/UFG8qkz0pO
Your AI coding agent doesn't have a map of your codebase.
It has a context window. Maybe some vector search.
Neither knows what breaks when you delete something.
I built the fix. 🧵
The workflow that changed how I use AI agents:
Agent suggests a change
Run impact analysis in Depwire
See exact blast radius
Give agent the full context
Agent executes correctly
Map before you mutate.