Swift

Swift Academy Podcast · Series A mock-interview series with Artem Mirzabekian, Lead iOS Engineer. Real mobile system design problems, solved out loud the way a senior interview actually runs, with the roles swapping between episodes. Two episodes published. 🎧 Swift Academy Podcast · Series · 2 episodes · Requirements • APIs • Domain • Architecture “Most system design conversations stop at the box diagram. The interesting part starts after: what happens when the cursor is stale, the receipt URL has expired, and the user is on a train with no signal.” ...

Two refinements to the NeighborhoodCoherence judge from part two: pass the metric name straight to ModelJudgeEvaluator to drop the ScoreDimension boilerplate, and shape what the judge actually reads with evaluationTarget and reference.

Code-based evaluators can only measure what code can measure. This companion article goes deep on ModelJudgeEvaluator: choosing a scoring scale, writing scoring levels that actually work, and wiring a model-as-judge into the TripPlanner evaluation from part one.

How to test generative, non-deterministic features with Apple’s Evaluations framework, the five steps of an evaluation, datasets and the Loader protocol, synthetic sample generation, evaluators and metrics, and the compiler gotchas hit along the way.

Swift Academy Podcast, Episode 12, Season 2 Modern iOS Security: Attacks, Defenses & AI Dave Poirier and Deya Elkhawaldeh on iOS security as an engineering culture problem rather than a tooling one, and on what AI has already changed for the people attacking your app. May 31, 2026 🎧 Swift Academy Podcast · Episode 12, Season 2 · Mobile Security • Attacker Mindset • AI Watch the Episode Why This One Matters “Apple handles security for us” is, according to both guests, the single most expensive misconception in iOS development. The platform gives you good defaults. It does not give you a threat model. ...

Cloud APIs put a frontier model behind a single HTTPS call. That convenience is hard to beat, and for most production workloads it remains the right choice. But something has shifted over the last couple of years: the gap between “what a hosted model can do” and “what a model running on your laptop can do” has narrowed enough that local inference is no longer a curiosity. For developers, especially those of us building on Apple Silicon, it has become a serious option. ...

Swift Academy Podcast, Episode 11, Season 2 MLX Swift & On-Device AI Adrien Grondin, iOS developer at LM Studio and creator of Locally AI, on why Apple Silicon changes the economics of running language models locally, and where that stops being true. May 17, 2026 🎧 Swift Academy Podcast · Episode 11, Season 2 · MLX Swift • Local LLMs • Apple Silicon Watch the Episode Why This One Matters Most teams shipping AI features today send everything to a cloud API. That works until you look at the bill, the latency, or the privacy review. Meanwhile Apple has been quietly building the other path: a framework designed from the start for unified memory on Apple Silicon. ...

A walkthrough of Anthropic’s new Claude Agents (agent view) inside Claude Code on iOS: how to run a Clean Architecture refactor agent and a unit-testing agent in parallel on isolated Git worktrees, with the full lifecycle and synchronisation pitfalls.