Two Truths About AI Success: Simplicity and Focus

Two truths keep hitting me as I reflect on Claude Code's success.

1️⃣ Simplicity scales.

Simple is repeatable. Simple is predictable. Simple is reliable.

Simple systems fail loudly → you fix them fast. Complex systems fail silently → you burn hours chasing ghosts.

Key takeaway: Break workflows into tiny steps → apply AI → measure impact → tweak.

2️⃣ Focus = capability.

Versatility ≠ capability. Builders don't use Swiss-army knives. They use screwdrivers.

Clear roles and specialization work for humans. They work for AI models too.

If I deploy an AI model in a hospital, I don't want it dabbling in astrophysics. I want it hallucinating less. Costing less. Connecting faster. Staying predictable.

And that's achieved by keeping it lean and focused.

Key takeaway: Use the smallest model possible to get your job done.

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My bet is that the future isn't one bloated generalist. It's a toolbox of sharp micro-models. Each built to do one thing exceptionally well.