What makes a company truly AI-native?

A company is truly AI-native when the product collapses without the AI model, the team operates at radically smaller ratios (such as 3 people doing the work of 30), and growth is driven by media and audience building rather than traditional outbound SaaS sales.

Is code still a competitive moat for startups?

Code is no longer a strong competitive moat because AI-native founders can rapidly spin up applications and integrate complex APIs, turning what was once a valuable proprietary asset into a cheap commodity that can be replicated over a weekend.

What assets create durable value for AI-native companies?

Durable value comes from unique proprietary datasets that competitors cannot access, intellectual property and patents that create structural barriers to entry, and loyal user bases built on attention, trust, and brand.

Why isn't adding ChatGPT or Cursor enough to make a company AI-native?

Adding AI tools like ChatGPT subscriptions or Cursor seats to a traditional company only layers AI as an add-on feature, whereas being AI-native requires AI to be the load-bearing foundation of the product, team structure, and distribution strategy.

What are VCs looking for in AI-native startups?

VCs are rigorously filtering for genuine AI-native traits in product, team, and distribution, while still evaluating real underlying assets such as proprietary data, intellectual property, and loyal user bases that provide leverage and long-term defensibility.

Beyond AI-Native: The Real Assets That Hold Value

Ali Mackani, a leader at Growth Factory Ventures, recently published a piece in The Memo breaking down what an "AI-native" founder looks like. He argues that slapping a ChatGPT subscription and a Cursor seat onto a traditional company doesn't make it AI-native.

To recap his core framework, Ali uses three tests to identify the real deal:

The Product: Without the AI model, the product must completely collapse. It cannot just be an add-on feature; it has to be the load-bearing foundation of the business.
The Team: The ratios are fundamentally different. A 3-person team doing the work of 30 is the new standard, drastically changing how companies scale and allocate equity.
The Distribution: Growth looks more like media and audience building than traditional outbound SaaS sales.

Ali’s insights highlight what investors are looking for, and it is clear that VCs are now rigorously filtering for these traits. But reading his piece sparked a tangential thought about how we evaluate companies once the initial novelty wears off.

Avoiding the "Soup of the Day" Myopia

No, don't get me wrong, AI-Native is the new normal. Being AI-native is a clear advantage, but founders and investors alike have to be careful not to get myopic. When a paradigm shifts this violently, the new tech becomes the "soup of the day." It is easy to get tunnel vision and focus entirely on the new shiny tech, in this case, AI-native architecture, while forgetting the broader picture.

While VCs are hunting for genuine AI-native structures, they are still evaluating real assets. AI provides unprecedented leverage, but leverage still needs an underlying foundation to move the needle. To build a valuable company today, maintain a clear view of the breadth of assets that actually create value:

Unique Data Sets: While models are becoming commoditized, the proprietary data you gather is not. A company building a dataset that no one else has access to is building a competitive advantage that others cannot easily replicate.
Intellectual Property & Patents: Hard IP and patents still command a premium, creating structural barriers to entry that an LLM cannot bypass.
Loyal User Bases: Attention, trust, and building a strong brand are incredibly hard to replicate. Cultivating an engaged audience, which ties directly into Ali's point about media-style distribution, is an asset that compounds over time.

The Depreciating Asset: Code

There is one traditional asset missing from that list, and it used to be one of the most important: Code.

Historically, complex, proprietary codebases formed deep competitive moats. That is no longer true. Because we can now spin up applications and integrate complex APIs so rapidly, the raw value of code is plummeting. It is shifting from a valuable asset to a cheap commodity. If your company's only competitive advantage is that you wrote a lot of code, an AI-native founder may recreate your product over a weekend.

Building an AI-native company is the baseline for the next generation of startups. But surviving the long game means remembering that the tech is just the engine; your valuation will ultimately rely on the durable, hard-to-replicate assets you build around it.