The life-coach Agent Skill helps you examine hard decisions, map ambivalence, and test goals, and refuses to pretend it’s something it isn’t.

The Raleigh Agent Skill helps residents find useful answers about buses, permits, and parks without first learning where the city keeps everything.

Ponytail made my AI agent terser. Neckbeard makes it prove its work. Why I ditched the viral coding skill for one designed to catch mistakes, verify at the real boundary, and say what it couldn’t check. The architecture, authority gates, and evaluation suite inside.

A practical method for earning AI autonomy by finding workflow bottlenecks, strengthening adjacent capabilities, and expanding only with evidence.

Postmortems matter when their lessons survive the meeting and constrain the next release, without turning blameless learning into automated blame.

Andrej Karpathy predicted a small AI model that would trade encyclopedic knowledge for raw reasoning. Just over a year later, it is a product category, and it changes everything about how we should think about AI infrastructure.

Human organizations have a maximum perceivable rate of change. Above that threshold, they don’t accelerate their response. They slow down. They treat a category shift as a tool upgrade. The shift from deterministic to probabilistic computing has exceeded the threshold, and the three gaps we see everywhere are not failures of leadership. They’re symptoms of an organizational immune system working exactly as designed for a world that no longer exists.

Shannon Ryan’s talk at AgileRTP on why AI adoption fails when organizations fixate on tools instead of the human systems that use them.

As AI coding agents accelerate implementation, the bottleneck shifts upstream to spec creation. A practical walkthrough of how recorded stakeholder meetings, AI agent skills, and open-source profiles can break through the spec ceiling.

Taking on the genuinely hard problems: speaker diarization, meeting auto-detection, and what this fork actually proves about open-core and vibe coding.

Actually forking the MIT codebase: rebranding across 69 files, stripping 928 lines of telemetry, and having an AI coding agent implement a locked feature in a single pass.

A speculative roadmap for forking an open-core AI meeting assistant, with a worked example of how to use AI coding tools to implement it.