The Myth of Certainty

We all want certainty — dates, costs, delivery promises.
The problem is, certainty doesn’t exist in knowledge work.

The idea of predictability was born with Henry Ford.
He could say, “You can have any colour you want, as long as it’s black,” because his world was mechanical.
The work was physical, repeatable, and measurable.
Once you got the process right, the output was guaranteed.

That’s the dream so many businesses still chase today — certainty through control.
It makes sense in manufacturing, where variation is failure.
But it doesn’t work when your product is thinking.

Most of us work in wetware — the messy, brilliant, human kind of work.
Hardware follows rules.
Software follows logic.
Wetware? It follows mood, energy, distraction, and sometimes bad coffee.

Until AI replaces wetware (and that’s a debate for another day), software and wetware are intrinsically linked — one doesn’t exist without the other.
Software is less “hard” than hardware. It has a certain fluidity — not quite as viscous as wetware, but still unpredictable and prone to change.
Even metal, when it changes through heat or cold, does so in a predictable, mappable way.
Software and wetware don’t.

And that’s why you need to stop chasing something that can’t exist — certainty.

You can fake certainty if you want.
Freeze the design. Stop feedback. Limit deviation.
You’ll get predictable outputs.
But you’ll also get products nobody wants.

Because certainty kills learning, and learning is how progress happens.

That’s what agility was meant to give us — not perfect predictability, but better adaptability.
Not the comfort of certainty, but the confidence to deal with uncertainty deliberately.

So next time someone asks for an exact delivery date, try this instead:
Tell them what you know so far, what you’re learning next, and how you’ll adapt based on what you find.

Because the future doesn’t need a promise.
It needs a plan that’s flexible enough to survive reality.