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Practical writing on agentic AI architecture, document understanding, retrieval, validation, observability, and the system design work that makes AI useful in production.
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A practical guide to the Asynchronous Successive Halving Algorithm for hyperparameter tuning, with rung schedules, promotion logic, worker behavior, failure modes, and production implementation patterns.
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A practical guide to the Asynchronous Successive Halving Algorithm for hyperparameter tuning, with rung schedules, promotion logic, worker behavior, failure modes, and production implementation patterns.
How to build AI evaluation frameworks that test routing, retrieval, tool use, grounding, workflow behavior, cost, latency, and production regressions.
A practical guide to agentic AI architecture: what AI agents are, where LLMs fit, and how to design reliable agent systems with state, tools, retrieval, guardrails, and evaluation.
A production playbook for agentic AI systems: orchestration patterns, multi-agent design, retrieval repair, observability, evaluation, cost control, and implementation structure.
How to design production retrieval systems with evidence targets, hybrid search, source-fit scoring, context packing, retrieval repair, and grounding checks.
A practical guide to designing document AI pipelines with structured extraction, validation, confidence scoring, provenance, human review, and production observability.
