My writings, opinions, and random thoughts.
A pragmatic retrospective on the transition from AI autocomplete to autonomous agents: where real engineering velocity was gained, what created hidden debt, and how the role of the senior engineer evolved.
Why the next phase of AI leadership is not about raw model speed, but about bounded autonomy, verifiable guardrails, and turning digital responsibility into a durable competitive advantage.
When AI coding agents modify multiple files across a repository, how do you verify downstream impacts? A deep dive into blast radius, call graphs, and architectural guardrails.
Why rushing to automate surface workflows with AI creates invisible tech debt and team burnout, and how technical leaders can build durable leverage through purpose and architecture.
Most AI code review tools only look at the PR diff, missing crucial architectural dependencies and callers. Here is why structural codebase graphs change the game.
A practical roadmap for AI-native iOS features in 2026: moving beyond chatbot wrappers to integrated workflows, context-aware drafting, App Intents, and resilient recovery UX.
How diving deep into stoicism, ego detachment, introversion, and physical self-regulation transformed my engineering leadership and technical execution.
How revisiting strategic classics like Good to Great, Start with Why, Range, and classic sci-fi sharpened my framework for technical leadership and AI product engineering.
How revisiting Yuval Noah Harari's Sapiens altered my mental model for designing AI-enabled software, building user trust, and navigating technical uncertainty.
A comprehensive evaluation framework for mobile AI features, moving from offline benchmarks to production telemetry, behavioral metrics, and automated rollback rules.
