Notes on software engineering, applied machine learning, and building reliable production systems. I write to document trade-offs, patterns, and lessons learned.
Published: 2026-01-19 · Tags: System Design, Architecture, Engineering Practice
A concise statement of the principles that guide how I design production systems: explicit trade-offs, contract-first thinking, failure-aware design, and evolutionary architectures.
Published: 2026-01-19 · Tags: Distributed Systems, Event-Driven Architecture, Reliability
A practical guide to designing and operating event-driven systems, covering contracts, idempotency, ordering guarantees, failure handling, and observability.
Published: 2026-01-19 · Tags: Production ML, Reliability, Systems
Training a model is usually the easy part. This article covers the production fundamentals that keep ML systems reliable after deployment: data contracts, deployment discipline, observability, failure handling, and iteration loops.
This list is still in flux. It may change to "blog-like" format later (RSS feed, pagination, tag pages).
Event-driven architectures, scaling considerations, failure modes, and pragmatic trade-offs.
Model lifecycle, data quality, monitoring, evaluation loops, and operational patterns.
Tooling, automation, CI/CD, and practices that keep delivery fast and reliable.
My other publications, which I authored or co-authored elsewhere.