WhatA system where AI agents automatically produce structured documentation — architecture decision records, dependency maps, API contracts — that other AI agents can consume, creating a self-reinforcing context loop.
SignalThe post identifies that agents consuming context need agents producing it, and that most organizations have never created the written substrate that agents need — this is a chicken-and-egg problem begging for automation.
Why NowMulti-agent workflows are going from research demos to production in 2026, but there is no standard way for agents to leave structured breadcrumbs for other agents operating on the same codebase.
MarketEnterprise engineering teams running multi-agent pipelines; $100K+/year contracts; adjacent to Sourcegraph and LinearB but focused on agent-to-agent communication rather than human developer experience.
MoatThe schema and format for agent-readable context becomes a de facto standard — network effects kick in as more tools produce and consume your format.
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