The Agent Is the Least Trustworthy Part of the System
Eight AI and agentic systems signals from October 15–21, 2026, and three practical experiments for safer harnesses, durable state, and verifiable outcomes.
16 publicaciones etiquetados con "mcp"
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Which AI Coding Harness? A Field Guide to AI in Your SDLC
The model is the engine, the harness is the car. We sort today's AI coding tools into six families, map them onto your software lifecycle, and share a practical way to choose.
Models Are Becoming Commodities, Orchestration Is the New Advantage
AI models are rapidly commoditizing. The real advantage now is AI orchestration: memory, verification, safety guardrails, and workflow design. Learn a practical framework to build reliable AI systems.
Tokenmaxxing: Why AI Token Consumption Is a Vanity Metric
Learn why optimizing for AI token consumption is a vanity metric, how friction drives token waste, and how teams can improve token efficiency with MCP, managed agents, and lower-friction AI infrastructure.
Turn Voice Notes Into Production-Ready Content with Local AI Transcription
Learn how to use a local AI transcription tool, to transform voice notes into clean production-ready content, technical documentation, blog posts, and operational knowledge.
GitHub’s MCP Registry
TL;DR: GitHub just launched the MCP Registry, a central hub to discover, trust, and install Model Context Protocol (MCP) servers. This isn’t just a developer convenience—it’s the f
ChatGPT Meets Custom MCPs
Imagine a world where ChatGPT doesn't just answer your questions—it talks directly to your systems. Your API. Your server. Your private data.
QBot: A CLI MCP Client to support DevOps
I wanted to give it a try with OpenAI Codex or Claude Code. I found this 1-dollar promo code for OpenAI, hence, I went with Codex.
OpenAPI + MCP + Arazzo = The Formula for AI Automation
What’s possible when you mix OpenAPI, the Model Context Protocol (MCP), and the Arazzo Specification?