Google VP warns that two types of AI startups may not survive

The generative AI boom created a startup every minute. But as the dust begins to settle, two once-popular business models look more like cautionary tales: LLM wrappers and AI aggregators.

Darren Mowry, who leads Google’s global startup organization in Cloud, DeepMind and Alphabet, says these hooks are where startups turn on their “check engine light.”

LLM wrappers are essentially startups that wrap existing major language models, such as Claude, GPT or Gemini, with a product or UX layer to solve a specific problem. An example would be a startup uses AI to help students study.

“If you really just rely on the back-end model to do all the work and you almost white-label that model, the industry doesn’t have much patience for that anymore,” Mowry said on this week’s episode of Equity.

The fact that there is “very thin intellectual property around Gemini or GPT-5” indicates that you are not differentiating yourself, Mowry says.

“You have to have deep, wide moats that are either horizontally differentiated or something very specific to a vertical market” for a startup to “progress and grow,” he said. Examples of the deep moat LLM wrapper type are Cursor, a GPT-powered coding assistant, or Harvey AI, a legal AI assistant.

In other words, startups can no longer expect to layer a UI on top of a GPT and gain traction over their product, as they might have done in mid-2024 when OpenAI launched its ChatGPT store. The challenge now is to build sustainable product value.

AI aggregators are a subset of wrappers: they are startups that aggregate multiple LLMs into a single interface or API layer to route queries between models and give users access to multiple models. These companies typically provide an orchestration layer that includes monitoring, governance, or evaluation tools. Consider: AI search startup Perplexity or developer platform OpenRouter, which provides access to multiple AI models via one API.

While many of these platforms have gained traction, Mowry’s words are clear for new startups: “Stay out of the aggregator world.”

In general, aggregators aren’t seeing much growth or progress these days because, he says, users want to “build in a bit of intellectual property” to ensure they’re guided to the right model at the right time based on their needs — and not because of behind-the-scenes computing or access restrictions.

Mowry has been in the cloud space for decades, cutting his teeth at AWS and Microsoft before settling on Google Cloud, and he’s seen how this plays out. He said the current situation reflects the early days of cloud computing in the late 2000s/early 2010s, when Amazon’s cloud business took off.

At that time, a slew of startups emerged that resold AWS infrastructure and marketed themselves as simpler entry points offering tooling, billing consolidation, and support. But as Amazon built its own business tools and taught customers to manage cloud services directly, most of those startups were squeezed out. The only survivors were those who added real services such as security, migration or DevOps consulting.

AI aggregators today face similar margin pressure as model providers themselves expand into enterprise functions, potentially cutting out middlemen.

For his part, Mowry is bullish on vibe coding and developer platforms, which had a record year in 2025 with startups like Replit, Lovable and Cursor (all Google Cloud customers, according to Mowry) attracting major investment and customer traction.

Mowry also expects strong growth in direct-to-consumer technology, with companies putting some of these powerful AI tools into the hands of customers. He pointed to the opportunity for film and TV students to use Google’s AI video generator Veo to bring stories to life.

Beyond AI, Mowry also thinks biotech and climate tech are having a moment — both in terms of venture investments in the two industries and in the “incredible amounts of data” that startups can access to create real value “in ways we never would have been able to do before.”