The loop hype is real! 📈 Curious what loops everyone here is running. Do you think it’s the latest overblown feature or has it truly changed the game for you? 📊 Poll: short and sweet, do you use loops❓

Like a lot of people here, I started with Jake's paper. ICM made immediate sense to me, the filesystem as the orchestration, folders as stages, an agent that navigates instead of being fed. So I built with it. And somewhere along the way I realized my main workspace was never a pipeline like ICM describes. So I made a workspace builder skill off the paper, and started my first true pipeline workspace and the contrast became apparent. My original workspace has been running for months now, agent-maintained, prose-dense, and the thing I was tending wasn't a sequence of stages anymore. It was a body of knowledge. Decisions piling up, conventions hardening, old files going quietly stale, and the question I kept hitting wasn't "what runs next." It was "does the right knowledge still reach the right task." Then Google published OKF, and the pieces clicked. Markdown, YAML frontmatter, typed nodes, a semantic layer over what you know. My existing html frontmatter wasn’t sufficient enough. But OKF is a format, and it says so itself. Nothing in it governs what happens when the corpus grows for a year. The next realization came when I stopped thinking in layers and started thinking in nodes: a long-running development workspace isn't a stack, it's a graph, and it accretes. So I gave it a name. An Accretive Context Graph. What it is An ACG is a project workspace built as a growing knowledge graph of plain markdown files. Each file is a node holding one piece of what the project knows: a decision, a convention, a failure, a spec. Typed links join the nodes and state what governs what, what answers what, and what depends on what. An agent works inside the graph. It walks the links to gather the context each task needs, adds what each session learns, and regenerates the indexes, maps, and checks from the prose, so the structure stays accurate as it grows. A human directs from the edge, judging what the checks and the agent surface, deciding what stays, what supersedes, and what earns a closer look. And because the graph accretes rather than resets, maintenance is part of the work: staleness is tracked, contradictions get reconciled, growth is consolidated on a cadence.