What Makes a Company a Winner in the AI era

FUTURE

The Secrets of an AI Winner

I’ve been advocating for a future where AI enables you to “just do things”. But instead of me pontificating to you all, I’ve finally decided to be totally clear on what I think are the fundamentals of a great business in the AI era.

In particular, we will:

Discuss why the concerns around failures to implement AI are mostly skill issues with a research-driven analysis, including discussions of accuracy, notable recent improvements in the frontier (i.e., overconfidence correction), and the uncertainty mindshift required to be successful with AI.

How to approach product strategy, covering the key differences between SaaS (software 2.0) vs agent tooling (software 3.0), and management consulting (consulting 2.0) vs forward-deployed engineering (consulting 3.0), and more.

What will be the defining moat for companies in the AI era, as well as pricing strategies, discussing topics like statistical coverage, the absurdity of AI subscriptions, and so forth.

We will even use a fascinating application of statistics and cryptography theory, zero-knowledge proofs, to prove how AIs being unpredictable doesn’t have to be a bad thing, and how you’re probably overstating the concerns regarding the uncertainty of AI predictions.

This isn’t just about validating my ideas, but hopefully serving as a starting point for you to think about companies in the AI era and make better investment decisions. By the end, you should be able to determine whether a company will succeed or not in an instant.

Let’s dive in.

It’s a Skill Issue

With studies like the one we discussed on Thursday by MIT, which claimed 95% of AI implementations still fail, companies that are too comfortable for their own good and unwilling to confront the inevitable change have the perfect excuse to delay AI adoption just a little longer.

But if you read Thursday’s post, you already know it’s not an AI issue, it’s a skill issue. AI is already good enough to transform most companies completely, but such companies are mostly clueless.

I have my fair share of interactions with executives. You never get used to how poor, on average, their knowledge of AI is, despite being the key decision makers.

But let me prove to you how ready AIs really are.

The Writing on the Wall

You can’t be blamed for thinking AI isn’t up for the task in most cases. It’s believed to be error-prone and generally inferior to humans. Hallucinations, untrustworthiness due to non-determinism, and other buzzwords will be thrown at you, even at the slightest suggestion of using AI.

The truth is, most of that is just people parroting “known knowns” about AI without actually verifying whether they remain true. And kid you not, they are mostly not true anymore.

In a recent study in New Zealand, a group of state-of-the-art (at the time) models, like GPT-4o or DeepSeek R1, were tested against humans, non-lawyers and lawyers, both young and experienced, to see who was more accurate for the invoice reviewing process, a necessary verification as to…

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