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For decades, every product decision lived inside the same constraint: fast, cheap, or good — pick two. That tradeoff shaped roadmaps, budgets, hiring plans, and launch timelines.

AI collapsed two sides of that triangle. Fast and cheap are now available simultaneously, to everyone, at negligible marginal cost. The constraint is gone.

And that should be good news — except most organizations responded by doing the same thing faster and cheaper, without ever asking whether the thing was worth doing well.

When everyone has the same accelerant, fast and cheap stop being advantages — they become the floor. And that floor keeps dropping. The instinct, when a constraint disappears, isn’t to pause and ask what to do with the freed capacity. It’s to move faster in the direction you were already going: more output, more quickly, at lower cost.

The pattern is well documented. Writing in Harvard Business Review, analysts from Bain and OpenAI call it the “micro-productivity trap” — companies optimizing individual tasks without rethinking the workflows or the value creation around them, and never translating those isolated gains into real business results. The technology mostly works. The deployment choices don’t.

If any of this sounds like a question worth answering, our new ebook, Work Intelligently, is the place to start.