Quantum is early. It’s also closer than most people think.

In February I spent a day in Santa Fe at a quantum investor roundtable co-hosted by Los Alamos and Sandia National Labs. The room was full of brilliant builders, researchers, and professors, marrying the missions of pushing the fundamental science forward and figuring out what it actually looks like to bring their work to a commercial market.

Hearing from all sides of the ecosystem has been super helpful for my own thinking and how I’m viewing quantum innovation across hardware, software, and applications.

On the hardware

We’re moving faster than predicted. A Harvard-led collaboration with MIT, QuEra, and others put out a paper in Nature this past January – a neutral-atom system that ran below-threshold error correction and encoded up to 96 logical qubits on a universal fault-tolerant architecture. That’s up from the 48 the same core group showed in 2023. In 2024, Google’s Willow hit its own below-threshold milestone on superconducting. Different paradigms leading on different axes, but both are step-function results. That’s real progress. 

That said, academic estimates for the full-blown sci-fi version of quantum computing we often think about still sit in the thousands of logical qubits. We still have a ways to go, and it’s happening faster than ever. Nobody knows which paradigm gets us there either. Groups are working across different hardware regimes – trapped ions, neutral atoms, superconducting, photonic, and they’re all still in play. I believe that uncertainty is a feature, not a bug, and it’s pushing a lot of innovation we’re seeing in the space.

On the software layer

What does routing look like across hardware paradigms with different strengths and weaknesses? What does the middleware for a pharma team, a finance team, or a materials scientist actually look like when they want to run on the hardware that serves them best? A handful of startups I’ve met recently are already deployed commercially, doing algorithm compression and payload optimization for real customers. The comparison I keep coming back to is the Cambrian explosion happening right now in enterprise infrastructure and middleware for AI and agents. Whether it’s at the same scale and distribution is very tbd, but something similar will likely play out in quantum, and the early versions are already shipping. 

An area worth mentioning within software is security. We’re already in harvest-now-decrypt-later territory, and timelines for when quantum can meaningfully challenge modern cryptography keep moving up. Securing proprietary information against that is a real problem waiting for real product.

On the applications of quantum understanding

Applications of quantum physics, mechanics, chemistry, etc. are where we’re seeing real products make it to customer deployments. A lot of people trained as quantum physicists are applying what they know to problems that don’t require a quantum computer at all. Quantum sensing, quantum-enabled navigation, and quantum radar, and it only compounds when applied to AI. 

There’s a growing wave of foundation models encoding the fundamentals of quantum mechanics, physics, and chemistry, then pointing that understanding at materials, organic chemistry, drug discovery, biology, the whole nine. The more AI can actually reason about how electrons move and what bonds form, the more interesting this gets. The downstream outcome is new drugs, new medicine, new materials, and a better grip on how the world actually works.

On the people

It’s still early days, and the pool of people who are most suited to do it is small. A lot of them are coming out of the national lab system like Los Alamos and Sandia, out of academic hubs at UNM, Berkeley, Maryland, and Zurich, and the early market players like IBM, Quantinuum, Google, and others. The winding path from physics PhD to founder is non-obvious, which is part of what makes this interesting. The ones making that jump right now are early, and early is the right time to be building here.

How True invests in emerging technology

All of these dimensions of the quantum stack, and applications, have their own timelines, and no one is sure when they will converge into the “quantum moment.” This doesn’t scare us, and in fact, it’s exciting.

At True, we like to be the first to believe in founders who are uniquely suited to take on their market, and support them for the entire journey. Timing is a feature of how we invest, not a risk to mitigate. The application layer, the software stack, and the quantum-AI intersection get rewarded well before the hardware winners get decided. That’s where I’m spending a lot of my time.

If you’re building in any of those layers, whether in quantum sensing, applications, software and devtools, or the quantum-AI intersection, I’d love to hear from you.

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