Ai

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 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.

Why isolated AI research labs fail, and how to structure a high-leverage embedded AI enablement pod inside your mobile product engineering organization.

A pragmatic architecture framework for evaluating on-device Core ML models versus cloud LLMs, balancing latency, privacy, thermal budgets, and unit economics.

A pragmatic analysis of WWDC 2024 Apple Intelligence announcements, App Intents integration, Private Cloud Compute, and what they mean for iOS product architecture.

How to integrate AI coding assistants into your daily iOS workflow to accelerate repetitive tasks while strictly protecting architecture, concurrency safety, and code review standards.

How diving into systemic risk, cognitive flexibility, first-principles survival engineering, and Alan Watts transformed my perspective on software architecture and engineering decisions.

Notes from my Nov-Dec 2023 reading sprint and how those books changed my approach to iOS reliability, AI product thinking, and team execution.