How the next iconic data infrastructure company will be born in the AI era

“Infrastructure inspires applications” but “applications inspire infrastructure” as well — reflections on how these interconnected innovation loops may play out during the AI revolution

The emergence of generational data infrastructure companies often aligns with major platform or paradigm shifts. This is intuitive since such technological sea changes can serve as a catalyst to unlock R&D breakthroughs, leading to the birth of category-defining powerhouses. Snowflake, a ~$62Bn market cap public company, is one such example. Fueled by the rise of cloud, Snowflake’s founders built a cloud-native data warehouse from scratch with groundbreaking architecture that separated storage and compute. Databricks (with a Series J valuation of $62Bn) is another illustration of this phenomenon; this data behemoth was incepted during the “Big Data” movement.

Notably, both Snowflake and Databricks did not originate from existing companies — Snowflake was incubated by Sutter Hill Ventures (and remains one of the biggest success stories of the venture studio model) while Databricks has academic roots, built on the foundations of Spark which was conceived at UC Berkeley.

In the early days of a technological revolution, activity at the infrastructure layer tends to be very dynamic and attracts significant attention, driven by the belief that technical innovations in this layer must develop first before downstream applications can bloom. The “infrastructure inspires applications” concept makes sense sequentially — just think of all the applications that are built on top of Snowflake and Databricks today — but this relationship is not merely a one-way street. Infrastructure and application development are in fact deeply intertwined and much more bi-directional than one would expect, evolving in closely-linked responsive cycles:

Source: Union Square Ventures, “The Myth of The Infrastructure Phase” (10/1/18)

Building on this point, there are numerous case studies of transformative infrastructure innovations that were developed internally (and often inadvertently) by builders within app companies. Apache Druid, ClickHouse, Hudi, Iceberg, Presto, and Temporal, are just a few recent examples that come to mind. The origin stories of such technologies demonstrate how “applications inspire infrastructure”, since feedback from the application layer can often drive innovation at the infrastructure layer. Several project creators have even gone on to found iconic infrastructure companies based on their original inventions. For instance, Confluent (~$12Bn market cap) was initially co-founded by Jay Kreps, Neha Narkhede, and Jun Rao, to commercialize Kafka, a project that they developed at LinkedIn and subsequently open-sourced .

So why am I bringing up the notions of “infrastructure inspires applications” and “applications inspire infrastructure” right now? Turning to today, the AI infrastructure landscape has been extremely vibrant throughout the early innings of the current AI paradigm shift. Numerous new AI tooling innovations, with many having a research or academic provenance (chart below), are being developed at high velocity, forming a strong foundation for downstream AI-native applications to build upon. This dynamic has led to the birth of new AI infrastructure giants, especially within the foundation model category.

Source: Bessemer Venture Partners, “Roadmap: AI Infrastructure” (6/11/24)

While a large amount of venture focus and funding has already flowed into the AI infrastructure layer (chart below), we may just be at the first wave of innovation during an “infrastructure inspires applications” phase. As I highlighted in a VC Wednesday segment with LinkedIn News, we are entering an “applications inspire infrastructure” phase. Here, I’m not just referring to radical AI infrastructure technologies such as Pytorch and TensorFlow that have already emerged from applied teams at large corporations. Rather, I anticipate that some of the most exciting infra innovations are likely to come from the new generation of AI-native application startups, since eng and product teams at these startups are pioneering novel infrastructure approaches as they build real-world, applied offerings at the frontlines of the AI revolution.

Source: S&P Global, “GenAI funding on track to set new record in 2024” (10/21/24)

I’m excited to witness the birth of more iconic AI infrastructure companies as this second wave of innovation fully materializes in the coming years. The best is yet to come!

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