When Speed Stops Being the Bottleneck

by Jeff Humble

Dear Reader,

Quick question: What happens when the thing that used to take 12 weeks now takes 4 days?

I've been watching this play out across the industry, and it's wild.

Lots of companies aren't sharing their new speeds, but a few are:

Code and Theory (an agency that works with Microsoft and Amazon) is building dashboards in 40 minutes that used to take a week. They report cutting time-to-prototype by 75%.

Coinbase reports a 2-5x increase in engineering velocity. They talk about a single engineer building features in a day that would have taken weeks to prototype.

IDEO shortened its time to first prototype from weeks to days using AI tools.

Execution time is collapsing, especially in AI-powered prototyping. And most design teams are responding by… executing more.

More feature requests. Tighter deadlines. Same busy feeling.

But here's the thing: being 4x faster at saying yes to other people's ideas isn't strategic growth. It's just a faster reaction.

The IBM Watson Problem

Remember Watson winning Jeopardy in 2011?

The system was basically ChatGPT for Jeopardy, and it was way ahead of its time.

IBM moved FAST after that.

$5 billion spent. 7,000 employees. Rapid expansion into healthcare.

They built Watson for Oncology. It was an AI that would recommend cancer treatments to doctors.

The technology worked. The speed was incredible. The execution was flawless.

But it failed.

The strategy was completely wrong.

Doctors didn't want an "answer machine." They needed decision support.

Watson gave definitive recommendations when medicine requires nuanced judgment. It recommended drugs that would worsen bleeding for patients who were already bleeding.

IBM eventually sold Watson Health for $1 billion after spending over $5 billion.

This wasn't an AI failure. This was a strategy failure.

Speed without strategic clarity doesn't just waste time...it compounds mistakes at scale.

What Changes When AI Does the Making

When execution is no longer the bottleneck, the constraint shifts to:

Should we really design this thing?

That's where strategy comes in. And it's different from what most designers are trained to do.

It's about:

Framing problems before jumping to solutions
Influencing roadmaps instead of reacting to them
Aligning team actions toward bigger goals
Shifting your mindset from "the person who makes things" to "the person who ensures we're making the right thing."

When AI commodifies execution, strategy becomes your competitive advantage.