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Insights

Notes from the build

How we think about retrieval, copilots, delivery, and the everyday craft of shipping software that holds up in production.

Diagram of a retrieval pipeline: source documents feeding a vector space, with the retrieved cluster highlighted, producing an answer card marked as cited from three sources

Building RAG systems that stay grounded in production

How we design retrieval, evaluation, and guardrails to keep answers accurate at scale.

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An application window with a copilot panel showing a suggested change as a before-and-after diff, a confidence meter, and Apply and Undo buttons

Shipping AI copilots users actually trust

The workflow and safety patterns behind copilots that hold up under real traffic.

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A deployment pipeline showing five stages - commit, build, scan, stage and ship - with the first four complete and timings beneath each

A deployment pipeline that ships in seconds

Our CI/CD setup for fast, safe releases across web and software projects.

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