Ios

A practical roadmap for AI-native iOS features in 2026: assistant workflows, trust UX, and operational reliability.

A practical evaluation stack for mobile AI features, from offline rubrics to production telemetry and rollback rules.

How I would structure a practical AI unit inside a product engineering team: scope, roles, cadence, and quality gates.

What helped during Swift 6 concurrency readiness work: actor boundaries, Sendable cleanup, and safer async ownership.

A practical framework I use to decide when AI should run on-device, in the cloud, or in a hybrid architecture.

My practical takeaways from WWDC 2024 announcements around Apple Intelligence and what they imply for iOS product teams.

How I integrated AI coding assistants into Swift workflows while keeping architecture, tests, and review quality intact.

Notes from my Q1 2024 reading list and how these books influenced iOS product thinking, AI evaluation, and leadership decisions.

Practical reliability patterns I leaned on in 2024 to ship iOS features with fewer regressions and faster recovery.

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