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Notes

A few longer reads

Start with the thesis if you want the full argument. These are shorter cuts into data, eval, and deploy.

Data

Sessions beat docs as training data

A wiki says what should happen. A session shows what someone did when the ticket was incomplete.

Evaluation

Grade the tool path, not only the answer

Correct finals can hide bad process. For operational work, the path is part of the product.

Systems

From laptop sessions to a model you can ship

Capture, clean, train, measure, deploy. The artifact is weights, not a forever API hop.

Midbar

M_workload = distill(τ_team)

Small models trained on how your team already works.

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