Building in the unknown

For months I have had the same conversation with executives and architects about systems that nobody has built before. The pattern repeats every time. The initial idea sounds impossible, unfounded, and not worth the time. The pushback then steers everything toward deterministic outcomes the business already knows how to solve. After two years of deep work with AI, that instinct looks shortsighted to me, because plenty of standard engineering practice seemed impossible six months ago.

These new models keep moving the line between what they can do and where a human still holds the wheel. Inside organizations, the resistance to letting go of twenty-year-old habits is enormous.

The bottom of the mountain

I have climbed half a dozen of the tallest peaks in the lower 48, and building in the unknown produces a feeling I know from every one of them. At the bottom, the mountain looks insurmountable. You drive up, you watch the summit grow through the windshield, and no path to the top is visible. You think repeatedly about turning around and doing something else with your day.

Part of the flow is dropping off a ledge. You know there is ground below you, and you do not know exactly how you will land. Or you leap from one boulder to the next with hundreds of feet of exposed rock underneath, where one slip means you are dead or leaving in a helicopter. A friend of mine lived the second version last year on the Siphon Draw trail at Lost Dutchman State Park. One slip snapped his humerus in half, and we had him airlifted out.

At the bottom, the mountain looks insurmountable.

Is this even real?

We are replacing major pieces of how engineering work gets done, and that exposure feeling shows up constantly. You swing between absolute confidence that this is the way and extreme uncertainty about everything ahead. Is this even real? Are the models convincing me this is good when it is actually bad? How do I quantify the business impact of something that changes how an entire organization works?

Quantifying a new feature, a more efficient architecture, or a faster process is a known problem with established patterns. Reasoning about changes that rewrite the mental model behind every item on that list is not.

Resistance as the feature

After watching an interview with Dario Amodei, the pattern seems clear to me: keep pushing the vision forward, and use the resistance as a feature. I wrote about this before at the learning layer, as deliberate friction between me and the models. This time it happens at the organizational layer, where whole industries are asked to change their mental models at once. Resistance at that layer is extreme, and it is also valid. Many things remain unknown, and many scenarios will not work easily, or ever, with nondeterministic next-word predictors. Yet.

For the first time in my life, the machines have caught up to how my brain works.

The machines caught up

This has been the hardest part for me personally. I swing through what feel like manic episodes of disbelief and elation. New ideas arrive suddenly, ideas that would change how entire industries operate. That frightens me, and at the same time I have never felt so certain of anything in my life. My ideas sound crazy at first. Then, one or two months later, the people who resisted hardest come back and tell me the thing changed their lives, inside and outside of work. That loop is satisfying and intellectually stimulating in equal measure. I am probably on some sort of spectrum, but for the first time in my life the machines have caught up to how my brain works.

No stretch of my career compares to this one: a major shift in capability and reach arriving all at once. I am dictating this article by voice from a mountain just outside Phoenix, the same way I shipped a post from a trail in March. Before I reach the car, an agent on a computer in the cloud will clean this up, generate the audio version, and stage it for review, all autonomously.

Charge forward

Keep pushing against the force that wants you to stop climbing, the one that says this is impossible and the models are not as good as you think. On this particular Friday, the models are the least capable they will ever be. That thought inspires and scares in the same breath. Lean into the fear and uncertainty, the way Pema Chödrön teaches in Comfortable with Uncertainty, and let the resistance push you to think deeply about what is not currently possible. Dario bet on scaling compute while serious people in the field disagreed violently. A few years later, the result is so obvious we forget it was ever contested.

On this particular Friday, the models are the least capable they will ever be.

Fable 5 from Anthropic is a significant shift in model capability. People are realizing it now, and it is another moment like last November with Opus. Headlines will shout absurd claims and fear in both directions. Underneath the noise, this is another slingshot for the human race, for our ability to work alongside machines as a superpower. Charge forward, optimistically skeptical.