Like everybody else, I straddle the line of agentic coding psychosis – excited about moving faster than ever, but deeply concerned about losing the thread and producing something incomprehensible and hard to evolve.

This has been a problem before – underspecified projects, specifications going out of sync with the first line of code. We've just amplified it now.

A lot of people (myself included) have tried to maintain good specifications in markdown to give LLMs and humans maximal context. But this is still walls of text that poison anyone's context, regardless of their artificiality.

So I built a way to model knowledge as a graph that both people and LLMs can consume progressively – by navigating the graph or searching for specific connectivity patterns rather than ingesting everything at once.

At its core it's an open specification for layers that add progressively more semantic value: starting with prose, growing into terminology, tasks, concepts, API surfaces, and structured plans.

The most critical component is a layer that maps artifacts (such as code) to the knowledge model with good enough precision to track drift and coverage automatically.