Every consumer company runs growth. Very few run it well.<\/p>\n
The reason is almost never strategy. It\u2019s plumbing. Behind every growth team sits a tangle of data schemas, event taxonomies, attribution tables, and warehouse logic that must be correct before anyone can run a meaningful experiment, optimize a campaign, or even answer the question \u201cdid that even work?\u201d The people who build and maintain this layer \u2013 the ones who truly understand how the data connects \u2013 are the hardest to hire, the most expensive to retain, and the first bottleneck in every growth organization we\u2019ve ever seen.<\/p>\n
We know this because we\u2019ve lived it. Between us, we\u2019ve led and built growth functions at companies like Snap and Uber, and we\u2019ve interviewed hundreds of candidates for growth roles over the years. The pattern is always the same: companies can find creative talent, they can find media buyers, but finding the person who can architect the data foundation underneath \u2013 the \u201cplumber\u201d \u2013 is excruciatingly difficult. And without that plumber, everything downstream is guesswork.<\/p>\n
This is not a new problem, but it is a newly solvable one. We\u2019re entering the era of what Andrej Karpathy calls Software 3.0 \u2013 agents that don\u2019t just answer questions but autonomously do the work, maintain their own knowledge bases, and get smarter with every cycle. Applied to growth, that means an AI system that can learn a company\u2019s data schema, structure and label it, and then keep maintaining that foundation as the business evolves \u2013 recursively compounding its understanding over time. What used to be a six-month, multi-headcount project can now be deployed in weeks. And the right data foundation doesn\u2019t just save money on headcount. It makes every growth dollar smarter, every experiment more trustworthy, and every analyst more dangerous.<\/p>\n
That\u2019s why we\u2019re excited to announce our investment in Hilbert.<\/p>\n
Hilbert is building AI growth agents for consumer companies. They start where it matters most \u2013 structuring and labeling the data that growth teams need to operate at scale. Once that foundation is in place, Hilbert layers on analytics, operations, and \u2013 increasingly \u2013 execution, allowing teams to co-create growth strategies on top of clean, reliable data. TLDR: Hilbert lays the plumbing, automates the trading, and continuously brings forth high-value opportunities for teams to act on \u2013 bringing best in class growth practices to every company that needs them.<\/p>\n
What\u2019s been remarkable to watch is the range of companies pulling Hilbert in. They\u2019re working with some of the biggest retailers in the world and winning against legacy marketing clouds with billion-dollar sales orgs. At the same time, some of the fastest-growing AI-native companies are choosing Hilbert. And once Hilbert maps a customer\u2019s data schema and deploys agents on top of it, they become deeply embedded in how a company runs its growth function \u2013 the kind of infrastructure that, once it\u2019s working, nobody wants to replace.<\/p>\n
At the heart of all of this are Naz and Ceyda. Naz built Getir\u2019s entire growth function from scratch and scaled it across nine countries \u2013 she\u2019s the person who was on call for every metric, in every market, obsessive about the data in a way that made her team the analytical backbone of a multi-billion-dollar business. Ceyda is the operational backbone \u2013 the person who injects urgency into everything and makes sure the machine actually runs. Together with co-founders Ozgur and Cenk, they\u2019ve been the growth team, the data team, and the ops team at a company that scaled at breakneck speed. They\u2019ve felt every pain point they\u2019re now solving.<\/p>\n
We\u2019ve spent a lot of time with this team, and honestly, they\u2019re the reason we\u2019re writing this post. We\u2019ve seen what separates growth orgs that compound from ones that churn \u2013 and Hilbert is encoding that kind of visceral knowledge into a product. We\u2019re thrilled to be along for the ride.<\/p>\n