In Part 1 of this series about the hard parts of building a venture studio, we explored how to recruit world-class venture builders. In Part 2, we learned what to do when the venture doesn’t have a CTO. Today, I want to talk about the challenge of venture capital expectations.
One of the most quietly demoralizing moments in an R&D venture studio goes something like this:
“We’ve explored dozens of technologies, but none of them look like venture-scale unicorn startups.”
If you’ve felt this, you’re not alone. Many studios — especially in their early years — assume that success means producing a steady pipeline of billion-dollar startup opportunities. When that doesn’t materialize, it can feel like the program itself is failing.
In reality, this is often a sign that you’re looking at the opportunity set through too narrow a lens.
The venture capital model is optimized for very specific kinds of outcomes: massive markets ($10B+), huge upside that would let any single investment return the whole fund, and the possibility of dominating a large value chain.
Some technologies clearly fit this profile. Many do not.
That doesn’t make them bad opportunities. It just means they might create impact and value in different ways.
As we argue in the R&D Venture Studio Playbook, the strategic objective of an R&D Venture Studio is only to generate unicorn startups. It’s also to:
Advance real-world deployment of breakthrough technologies
Strengthen partnerships with industry
Generate licensing revenue
Seed entirely new technical fields
Build credibility and momentum in priority sectors
etc.
Seen through that lens, the question is not so much:
“Can this become a unicorn?”
but rather:
“What could this realistically become if it succeeds?”
At MIT Proto Ventures, we’ve found it useful to give Venture Builders a simple framework for classifying opportunities based on their potential outcome.
We use a deliberately informal taxonomy because it makes conversations faster, clearer, and more honest.
Promising ideas that could eventually become huge, but require several more years of fundamental R&D before venture building can meaningfully begin.
Example: Magnetohydrodynamic generators to improve power plant efficiency.
These opportunities are worth tracking, supporting academically, and revisiting later. But forcing them into a startup exploration too early can waste time and credibility.
Technologies that improve an existing process or product category.
They often represent excellent licensing or partnership opportunities, even if they’re unlikely to support a standalone venture-scale company.
Example: Fouling-resistant coatings for heat transfer surfaces.
These wins can be strategically significant, especially for organizations seeking industry relevance and near-term impact.
Opportunities with a meaningful but bounded market — perhaps a ~$100M total addressable market.
These ventures may be ideal for strategic investors, specialized funds, or corporate venture arms, rather than traditional early-stage VCs.
Example: MIT Proto Ventures portfolio company American Fusion Instruments, which provides specialized diagnostic solutions for fusion energy companies.
They can become durable, highly respected technical businesses — even if they never make headlines.
The classic venture-scale opportunity: large markets, strong differentiation, and the potential to capture a significant share of the value chain.
These ventures are well positioned to raise institutional venture capital and scale rapidly.
Example: PV portfolio company Vertical Semiconductor, developing power supply systems for AI data centers built on vertical GaN technology.
Every studio hopes to find these. The mistake is assuming they should be the majority.
A taxonomy like this does more than organize your pipeline. It reshapes behavior.
It helps Venture Builders:
Avoid spending months forcing a “Tuna” into a “Moby Dick” narrative
Stay patient with high-potential “Tadpoles” instead of prematurely discarding them
Engage the right funding sources for each type of opportunity
Communicate more clearly with leadership about expected outcomes
It also reduces a subtle but dangerous bias: the tendency to judge ideas primarily by how investable they look today, rather than how much strategic impact they could create over time.
Every organization should develop its own version of this framework.
Your taxonomy might reflect:
Your studio’s sector focus (e.g., defense, healthcare, climate)
Your funding ecosystem
Your tolerance for long technical timelines
Your institutional goals
What matters is not the specific labels — it’s the discipline of asking, early and often:
What kind of outcome are we actually building toward?
Because once you’re honest about that, you can allocate time, talent, and capital far more effectively.
In the next post, we’ll tackle another deeply familiar frustration:
“Many of our most promising technologies need another 12–24 months of research before they’re ready for commercialization.”
We’ll explore how venture studios can bridge this readiness gap without losing momentum — or losing their founders.
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