GinkgoQTechnical writing on AI systems, domain intelligence, speech AI, RAG, agents, datasets, models, and production AI infrastructure.https://ginkgoq.github.io/ASHA Hyperparameter Tuning: A Practical Tutorial for Engineershttps://ginkgoq.github.io/blog/asha_tutorial/https://ginkgoq.github.io/blog/asha_tutorial/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.Thu, 04 Jun 2026 00:00:00 GMTDesigning Evaluation Frameworks for Production AI Systemshttps://ginkgoq.github.io/blog/designing-evaluation-frameworks-for-production-ai-systems/https://ginkgoq.github.io/blog/designing-evaluation-frameworks-for-production-ai-systems/How to build AI evaluation frameworks that test routing, retrieval, tool use, grounding, workflow behavior, cost, latency, and production regressions.Thu, 04 Jun 2026 00:00:00 GMTAgentic AI Architecture, Part 1: How to Design Reliable AI Agentshttps://ginkgoq.github.io/blog/guide-to-agentic-ai-architecture-part-1/https://ginkgoq.github.io/blog/guide-to-agentic-ai-architecture-part-1/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.Thu, 04 Jun 2026 00:00:00 GMTAgentic AI Architecture, Part 2: Building Production AI Agent Systemshttps://ginkgoq.github.io/blog/guide-to-agentic-ai-architecture-part-2/https://ginkgoq.github.io/blog/guide-to-agentic-ai-architecture-part-2/A production playbook for agentic AI systems: orchestration patterns, multi-agent design, retrieval repair, observability, evaluation, cost control, and implementation structure.Thu, 04 Jun 2026 00:00:00 GMTProduction RAG Architecture Beyond Vector Searchhttps://ginkgoq.github.io/blog/production-rag-retrieval-architecture-beyond-vector-search/https://ginkgoq.github.io/blog/production-rag-retrieval-architecture-beyond-vector-search/How to design production retrieval systems with evidence targets, hybrid search, source-fit scoring, context packing, retrieval repair, and grounding checks.Thu, 04 Jun 2026 00:00:00 GMTWhy Model Performance Does Not Determine System Reliabilityhttps://ginkgoq.github.io/research-notes/why-real-world-ai-systems-need-more-than-models/https://ginkgoq.github.io/research-notes/why-real-world-ai-systems-need-more-than-models/Benchmarks are useful, but production AI reliability depends on retrieval quality, validation, observability, fallback behavior, and evaluation across the full system.Tue, 12 May 2026 00:00:00 GMTBuilding Reliable Extraction Pipelines for Document Understandinghttps://ginkgoq.github.io/blog/building-reliable-ai-pipelines-for-document-understanding/https://ginkgoq.github.io/blog/building-reliable-ai-pipelines-for-document-understanding/A practical guide to designing document AI pipelines with structured extraction, validation, confidence scoring, provenance, human review, and production observability.Fri, 08 May 2026 00:00:00 GMTFrom RAG to Domain Intelligencehttps://ginkgoq.github.io/research-notes/from-rag-to-domain-intelligence/https://ginkgoq.github.io/research-notes/from-rag-to-domain-intelligence/Why retrieval-augmented generation is only the first layer of production AI, and how extraction, validation, provenance, and domain reasoning turn retrieved text into usable intelligence.Mon, 04 May 2026 00:00:00 GMT