Foundation Capital is a 30-year-old early-stage firm that backs founders at 'day zero' — before product, before revenue, before the world catches on. Roughly 80% of its investments happen before a company has generated a single dollar of revenue, and it organizes its conviction around 'zero-billion-dollar markets' that don't yet appear in industry forecasts. Across its enterprise, fintech, and crypto practices, it has come to believe that in an AI world where everyone has the same models, durable advantage comes from proprietary data, feedback loops, and systems built around the AI — not the AI itself.
Founders obsessed with a large, enduring problem rather than wedded to a specific solution — ideally a problem so fundamental it points to a 'zero-billion-dollar market' invisible in industry forecasts. Customer discovery should prove the problem is real and someone will pay to fix it.
“fall deeply in love with the problem you're aiming to solve, not the specifics of your proposed solution” — How to go from $0 to $1M ARR
“You need to have the CIO tell you what the problem is...and the CIO needs to also tell you that he's willing to pay” — Ashu Garg (citing Mohit Aron, Cohesity)
“Founders who focus on large and enduring problems have the opportunity to craft solutions so revolutionary that they border on magic.” — Ashu Garg
AI-native solutions built as whole systems — domain-specific data feeds, feedback loops, and humans in the loop — not features bolted onto a model provider. The best solutions deliver maximum value with minimal code and learn from every interaction.
“The most resilient AI startups are building entire systems around their AI, complete with domain-specific data feeds, custom feedback loops, and human experts in the loop.” — When model providers eat everything: A survival guide for Service-as-Software startups
“The best businesses have the least lines of code with the maximum amount of value” — Ashu Garg (citing Rob Bernshteyn, Coupa)
“Agents transform AI from a passive tool into an active team member.” — Ashu Garg
Conviction in markets that don't yet show up in analyst TAM charts — 'zero-billion-dollar markets' visible only to those who see beyond what exists. A sharply defined ICP should anchor the entry point into that market.
“We look for what we call 'zero-billion-dollar markets' - opportunities that don't appear in industry forecasts because they're only visible to those who see beyond what exists today.” — Announcing our Fund 11: A new $600M fund in support of our enduring commitment to founders
“Your ICP should guide virtually every product and GTM decision you make as a founder” — Ashu Garg
“Conviction, not consensus, motivates each of our investments.” — Foundation Capital
Because ~80% of investments happen pre-revenue, hard traction is not a gate; instead they look for evidence of learning and the path from customer discovery to a Minimum Sellable Product on the way to first dollars and $1M ARR. The early signal is rapid, honest learning rather than vanity metrics.
“80% of our investments happen before a company has generated a single dollar of revenue.” — Announcing our Fund 11: A new $600M fund in support of our enduring commitment to founders
“the biggest risk isn't being wrong: it's failing to learn” — Ashu Garg
“Talk to as many potential customers as you can, and really listen” — Ashu Garg (citing Christian Owens, Paddle)
Technical founders with product and engineering DNA who pursue excellence relentlessly and can translate deep technical complexity into simple value for customers. Because they invest pre-product, the team is most of the bet — and the founder's first five hires are treated as decisive.
“they had the right combination of product and engineering DNA and showed that relentless pursuit for excellence we look for amongst the best founders” — Our Investment in Neurelo: Making Databases Easy Again
“The first five people you hire will define the next hundred. You need co-founders in spirit.” — Foundation Capital
“fellow builders who are relentless, resourceful, and as committed as you are.” — Foundation Capital
Models where proprietary, compounding data is the core asset and moat — companies that own the data, outcomes, and definitions of success in their domain so each interaction improves the product. In fintech, 'tech' matters more than 'fin,' favoring data-driven products over balance-sheet plays.
“By owning the data, outcomes, and definitions of success in your domain, you create a feedback loop that continuously improves your product.” — When model providers eat everything: A survival guide for Service-as-Software startups
“We've long embraced the principle that 'tech' is more important than 'fin' in fintech.” — Foundation Capital fintech team
“This period of rationalization is ushering in a new chapter for fintech, one more reliant on data than capital.” — Foundation Capital fintech team
A defensibility story that survives the next model breakthrough: unique data no one else sees, learning from every interaction, and AI tuned to the nuances of a specific field. They explicitly worry that the model provider powering you can turn around and out-compete you, so the moat must live in proprietary data and feedback loops.
“the model provider that powers you can also turn around and steamroll you.” — When model providers eat everything: A survival guide for Service-as-Software startups
“If you can capture data no one else sees, learn from every interaction, and tailor your AI to excel in the nuances of your field, then you won't have to worry about the next breakthrough” — Foundation Capital
“the stream of interaction data generated by users and agents working in tandem is becoming the key proprietary asset in AI” — Foundation Capital
A timing argument tied to AI's exponential improvement across the stack and to a specific structural shift — e.g. AI agents able to replace human 'data transfer' layers inside regulated industries. The best 'why now' identifies a workflow that can suddenly be automated without expensive integrations.
“Every layer in the AI stack is improving exponentially, with no signs of a slowdown in sight.” — Beyond LLMs: Building magic
“We're specifically looking for companies that understand and can exploit the power of AI agents acting as human APIs.” — Foundation Capital fintech team
“The opportunity starts with identifying manual processes and building software that can replicate the human workflow exactly, without requiring expensive system integrations.” — Foundation Capital fintech team
A clear narrative the capital will fund — language that rallies a team, recruits talent, and convinces customers. Because they back day zero and stay for the full journey, the ask is framed as a long-term partnership to tackle the earliest, most fundamental challenges, not a transaction to the next round.
“We stand by our founders for the full journey, not just the path to the next round.” — Announcing our Fund 11: A new $600M fund in support of our enduring commitment to founders
“Narrative is power. You need language that rallies your team, draws in talent, and compels customers.” — Foundation Capital
“We invest early with deep conviction. Then we roll up our sleeves and build it with you.” — Foundation Capital
“fall deeply in love with the problem you're aiming to solve, not the specifics of your proposed solution”
“innate ability to interact with customers—he could explain technical concepts in simple terms”