In-depth architectural notes, lessons from building production data systems, and pragmatic perspectives on Agentic AI, reproducible MLOps, and real-time model monitoring.
Why early-stage AI teams do not need multi-node Kubernetes clusters or $3,000/month cloud bills. An in-depth engineering breakdown of MLite: unifying DVC, MinIO, MLflow, FastAPI container serving, Evidently AI drift monitoring, and 1-command rollback on a single VPS.
Part 1 of the Role Architecture series. Why one monolithic prompt fails and bloated multi-agent swarms are overkill. How to engineer a single autonomous agent that sequentially embodies multiple specialized roles (Researcher, Analyst, Critic, Synthesizer) with five-clause contracts, role-isolated contexts, and a bounded self-critique loop in LangGraph.
Part 2 of the Role Architecture series. When static agent teams meet tasks nobody planned for, they improvise, badly. A deep engineering guide to Dynamic-Role Agents: task entropy scoring, governed role synthesis, just-in-time tool binding, adaptive persona morphing, a LangGraph implementation, and the guardrails that keep autonomy safe.