Distill notes into retrieval blocks your model can actually use
Convert raw notes into layered summaries that are easy for both humans and AI systems to scan and reuse.
Distill for scanning, not decoration. Long notes are expensive to reread and expensive to retrieve from. Progressive summarization fixes that by adding layers over time: highlights, summaries, sharper summaries, and explicit reuse cues. The note still keeps the detail, but the important material becomes visible in seconds. For AI workflows, this matters twice. First, a human can quickly choose what to paste into a prompt. Second, a retriever has better semantic anchors when the note names the decision, the evidence, the caveats, and the next-use framing. Dense prose with weak headings forces the model to do discovery work that you…
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