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Practitioner field guides for AI-augmented engineers.

Five tracks. Mastery series, how-tos, field notes and dispatches from production. Republished here with the original LinkedIn social proof, indexed for search and translation.

Tracks

Latest articles

  • Jun 5, 2026 · ai-business-roi

    5 Ways Claude Saves Your Business $100k a Year

    A line-by-line ROI breakdown: where Claude and Claude Code quietly cut six figures of cost — and how to measure it.

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  • Jun 5, 2026 · ai-business-roi

    5 Ways Claude Helps Your Business Earn $100k a Year

    The other half of the ROI story: not cost you cut, but revenue you unlock — with the math for each lever.

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  • May 21, 2026 · ai-systems-architecture-mastery

    The Reference Architecture in Production

    Topology, orchestration, memory, eval, cost, latency and reliability — composed into one blueprint for an AI system that survives real users.

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  • May 21, 2026 · rag-engineering-mastery

    The Production RAG Reference Architecture

    Every piece, assembled: ingestion, hybrid retrieval, re-ranking, grounded generation, guardrails, eval and caching — the blueprint you can ship.

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  • May 19, 2026 · ai-systems-architecture-mastery

    Reliability — Retries, Fallbacks, Guardrails

    Models return malformed output, providers go down, and outputs drift. A reliable AI system expects all three and keeps working anyway.

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  • May 19, 2026 · rag-engineering-mastery

    Cost & Latency Discipline

    A RAG query touches embeddings, a vector DB, a re-ranker and an LLM. Each adds milliseconds and cents. At scale, discipline here is the difference between a margin and a bonfire.

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