The traditional venture capital model was designed for a different era. Write a cheque, take a board seat, wait for liquidity. The assumption baked into that model is that the founder has everything they need to build — they just need capital to do it.
That assumption was never entirely true. Today, it's fundamentally broken.
What Founders Actually Need
Capital is the easiest thing to provide. The genuinely scarce resources in company building are: engineering depth, product intuition, AI infrastructure, go-to-market architecture, operational systems, and the pattern recognition that comes from having done it before.
A VC writing a cheque provides none of those things. A board seat provides advice — which is different from execution, and often worse than silence when the company needs action rather than counsel.
The venture studio model is built on a different premise: that the studio itself should provide the capabilities that are genuinely scarce, and that the co-founder relationship — not the investor relationship — is the right model for the earliest stages of company building.
Why AI Makes This More True, Not Less
The AI revolution has raised the floor on what it takes to build a defensible company. A startup competing in any meaningful market now needs:
An AI infrastructure team that can build, fine-tune, and deploy models against real business problems — not just call the OpenAI API and hope for the best.
Data architecture designed from day one to generate proprietary training data, not just operational records.
Product intuition about where AI creates genuine leverage versus where it creates complexity without value — a skill that takes years to develop and is in genuinely short supply.
No early-stage founder can reasonably be expected to have all of these capabilities. The studio model solves this by embedding them at the point of inception, rather than trying to hire them in after the fact.
The TEN Labs Model
At TEN Labs, we define our role carefully: we are a co-founder, not a service provider and not an investor. The distinction matters because it determines how we behave when things get hard.
A service provider optimises for delivery. An investor optimises for returns. A co-founder optimises for the company — because their interests are genuinely aligned with its success.
In practice, this means we bring AI engineering, product architecture, brand strategy, and operational systems to every venture we take on. We're not advising on these things. We're building them.
We also think carefully about the ventures we take on. Not every business is right for the studio model, and not every founder is right for a co-founder relationship. We look for founders who have genuine insight into a market, a willingness to move fast and adapt, and an understanding that building with AI requires a different kind of company than building without it.
The Capital Efficiency Argument
The economic case for the studio model is compelling. When the studio provides infrastructure that would otherwise require significant hiring — AI engineering, product, brand, operations — the early capital requirement drops dramatically. Companies can reach meaningful product-market fit milestones with a fraction of the capital they would need as a standalone startup.
This is not just good for the studio. It's good for founders. It means less dilution at the most expensive stage, more time to find the right fit before raising external capital, and access to a depth of capability that money alone can't buy.
We believe the venture studio is the right model for this moment. Not because it's fashionable, but because the skills required to build great AI-native companies are genuinely concentrated — and concentrating them in a studio that deploys them across multiple ventures is the most efficient way to use them.
That's why TEN Labs exists. And that's why we build.