Practical writing on AI agents, SDLC documentation automation, full-stack architecture, and product validation.
29 results
Google Workspace's agentic expansion and NVIDIA's BlueField-4 STX point to the same shift: AI is becoming an operations-architecture problem. This post reframes AI workloads through a control-plane lens.
Model quality matters, but execution structure matters more. This post lays out a practical framework for designing agentic workflows around decomposition, routing, state, and observability.
Agent systems usually fail in orchestration before they fail in model quality. This post breaks down workflow design, tool permissions, fallback, and evaluation as architecture problems.
AI coding agents are moving from code completion toward pipeline automation across reviews, test generation, and CI recovery.
How AI is moving beyond code completion into pull request review, security fix suggestions, test generation, and CI recovery workflows.
Why vector-only RAG breaks in production, when GraphRAG is worth the complexity, and how to run a reliable evaluation loop across retrieval, generation, latency, and cost.