My AI Predictions for 2026

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THEWHITEBOX

TLDR;

New Year, new predictions. As with previous years, I’ve collected my thoughts and the progress we’ve made in 2025 to see how we did on our past predictions and how that can inform this year’s prognostications.

We’ll cover technology, markets, and products, leaving no stone unturned, from the first big AI IPO coming in 2026, my personal bets for companies that will do great in 2026, the next big trade, what’s next after LLMs, my fears of what might go wrong with AI, and finally, things that won’t happen in 2026.

Let’s dive in.

How Did I Do in 2025?

Let’s start by taking a brief look at how I did in my ‘predictions for 2025’ piece back on December 30th, 2024. A humbling way to see what real progress we’ve made this year.

Release of True "LLM + Search" Models

My first prediction was that future reasoning models would use search algorithms to search the solution space. I’ll give me half of the points on this one. Not because I was wrong about the essence, but I was wrong about the structure.

Human intelligence is a combination of three things: intuition, search, and feedback. Our experiences and knowledge build intuition, which is essentially pattern recognition that suggests how to approach a problem.

But intuition only takes us so far. With complex problems, we need time to think. This introduces the idea of intuition-guided search. Using our intuition of what might be good ways to solve a problem, we search for the optimal solution.

But human intelligence has one last feature: the ability to adapt to feedback, something AIs do not yet have, because it’s a very problematic procedure that usually leads to performance decreases (known as catastrophic forgetting).

Humans continuously experience the consequences of their actions, shaping their beliefs and thus priming them for better predictions in the future. AIs do not encode or hold beliefs (at least not explicitly), nor do they adapt to new data in real-time (for now).

Knowing all this, the prediction was that, in 2025, we would see AI conquering steps 1 and 2; an LLM serving as the intuition machine, using explicit search over possible solutions at runtime.

At that time, most models behaved like an option second-to-the-left, just a straight line of thoughts. Instead, I predicted models would evolve into the thing on the right, where they would explicitly reevaluate their thoughts and decide which reasoning chains to pursue and which to “kill”, creating a “tree of thoughts”.

And do top models look like today? Well, not one, not the other, but the one in between, self-consistency models.

Today, most models behave the same way they did one year ago, but with two big chances:

An improved chain of thought, incorporating things like self-reflection that allow them to “change their mind” midway through a reasoning chain, and also, for the most expensive models, the ability to run the task many times in parallel.

Put another way, they…

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