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Practical guides, explainers and analysis for people who build and evaluate AI systems. Every external claim links to its primary source.
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  1. Career

    Building a portfolio that proves AI engineering skill

    How to choose, evaluate, write up and package projects so that a reviewer can see you build systems that work and measure whether they do — plus how to scope freelance AI work and estimate it honestly.

    5 min readSkills & careers in AI, AI engineering, Evaluation

  2. Guide

    A practical checklist for shipping a RAG system

    What to have in place before a retrieval-augmented generation system meets real users: a retrieval evaluation set, structure-aware chunking, hybrid search, verifiable citations, permission-aware retrieval, a freshness plan and production monitoring.

    6 min readRetrieval (RAG), AI engineering, Evaluation

  3. Explainer

    What counts as an AI agent? A working definition for engineers

    A definition you can check against code: a model, a set of tools, a loop, state carried between steps and an explicit stop condition — plus how to tell when a fixed workflow is the better engineering choice.

    6 min readAgents, AI engineering, Large language models

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