TECHThe Smallest Agent That Works, Part 3: The Three Agents With StateTECHThe Smallest Agent That Works, Part 2: The Three Reach-Out AgentsTECHThe Smallest Agent That Works, Part 1: The Three Cheap AgentsTECHWhat MLX Got to Throw Away (That PyTorch Can't)TECHThe Unified-Memory Bet: Why On-Device Inference Stopped Being a ToyTECHEvery Useful Skill Is One of Five ShapesTECHMCP Gives You the Kitchen. Skills Are the Recipe.TECHThe Three-Level Skill, and Why Yours Is Probably One Level Too ManyTECHThe Smallest Agent That Works, Part 3: The Three Agents With StateTECHThe Smallest Agent That Works, Part 2: The Three Reach-Out AgentsTECHThe Smallest Agent That Works, Part 1: The Three Cheap AgentsTECHWhat MLX Got to Throw Away (That PyTorch Can't)TECHThe Unified-Memory Bet: Why On-Device Inference Stopped Being a ToyTECHEvery Useful Skill Is One of Five ShapesTECHMCP Gives You the Kitchen. Skills Are the Recipe.TECHThe Three-Level Skill, and Why Yours Is Probably One Level Too Many
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Tech· 2026-05-15· 5min

What MLX Got to Throw Away (That PyTorch Can't)

Every mature framework is a museum of decisions you can't take back. MLX is interesting mostly because it started after the decisions that matter for Apple Silicon were already mistakes — and the things it threw away are the things that were quietly costing the rest of us the most.

#ai-engineering#apple-silicon#mlx#ml-frameworks