AI's State of the Union: Application and Service Layers

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Your Full Guide to AI Investing

Last week, we explored the sweeping changes coming to AI in 2025, focusing on hardware, infrastructure, and models. This week, we shift to the application and service layers—the ones poised to disrupt the status quo and challenge investors thanks to the emergence of ‘AI wrappers’.

These businesses, some of the fastest-growing companies in history, are the hot new form factor for start-ups, one that takes you from 0-to-1 (millions in revenue in days or weeks) much faster than at any time in history.

But most wrappers are actually death traps that won’t scale despite exceptional initial traction. They are, essentially, born to die (early).

They are zombie companies dressed as high-time 90s Hollywood producers. And the worst thing? Their own investors don’t even know that.

All in all, today, you’ll learn:

What are wrappers, and why you should be equally excited and scared about them

How to categorize AI start-ups according to their wrapper level

The unit economics of start-ups in an AI world

Why most AI start-ups won’t make it, and how to pick the winners & avoid the losers using my AI-adjusted Value Formula, a non-technical, simple-to-apply way of evaluating AI companies

And the Big Service Opportunity. Why are most investors looking in the wrong direction when identifying the most significant opportunity in AI.

Let’s dive in!

A Wrapped World

The vast majority of start-ups today, especially those that leverage AI (the majority, at least according to their pitches), are, in some shape or form, AI wrappers.

But what does that mean? And why is it such a crucial detail?

AI-Native, But at What Cost

Until further notice, the truth is that the most powerful AIs in the world are not public. Sure, DeepSeek-R1, the model we saw on Friday, gives everyone hope that these tools will continue to be commoditized and could be stored in the safety of your organization, but the rapid progress of the field will force you to readapt your AI stack every few weeks, months at best.

And even if you plan to use open-source models, you will still be required to run them outside your organization (at least physically) unless you own a multiple-million state-of-the-art GPU cluster in a data center site with at least 40 kW per-rack power capacity (if you aren’t knowledgeable in AI energy discussions, you can read this piece, but I’ll save you the hustle: your company most likely does not have such a data center or the capacity to build it).

Long story short, you’re using technology developed by third parties for most of your AI use cases. And, as open-source will require you to be a much more mature organization, most companies trying to become—or are born as—AI-native opt for a much simpler option: outsource the AI from private companies like OpenAI, Anthropic or Google, becoming what most people in the industry know as wrappers.

But what exactly makes you a wrapper?

To me, a company…

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