Writing
Deep-dives on software architecture and the way source code is structured — written to be understood by beginners, yet useful to teams shipping at scale. Diagrams, real examples, no hand-waving.
A practical look at API gateway responsibilities: routing, authentication boundaries, rate limiting, request aggregation, backend-for-frontend trade-offs, failure modes, and the observability needed to keep the edge of a system understandable.
A beginner-friendly explanation of Retrieval-Augmented Generation: how documents are split into chunks, turned into embeddings, found with vector search, and used to ground AI answers with citations, evaluation, and clear failure checks.
A calm reflection on why stable, familiar technology often helps teams move with more confidence. The article looks at reliability, hiring, maintainability, shared knowledge, and the trade-offs behind choosing a tech stack that does not need to impress anyone.
A practical guide to applying Hexagonal Architecture to one small feature: drawing the boundary, naming ports in business language, keeping adapters at the edge, testing the core, and deciding when the extra structure is worth the cost.
A practical guide to writing acceptance criteria as shared evidence for done behavior: clear examples, important edge cases, reviewable scope, and a calmer handoff between product, engineering, QA, and stakeholders.
A calm comparison of Kanban and Scrum through the shape of real team work: how requests arrive, how much WIP the team can carry, what kind of predictability the business needs, and which operating rhythm fits the team's context.
A reflective essay on moving away from perfectionism in code and toward maintainable, understandable, reviewable work. The piece looks at why good code is not the most impressive version in isolation, but the version a team can safely understand, change, and carry forward.
A practical look at context window limits as one of the quiet bottlenecks in AI workflows. The article explains why long chats, big codebases, stale summaries, and missing working memory can make AI assistance drift, and how teams can work around the limit without turning every task into a document dump.
A calm look at high-output behavior that damages trust: why teams reward it, how feedback loops break, and how leaders can set boundaries while still offering a real repair path.
