A million qubits? This quantum advisor isn’t buying it.

When Anastasia Marchenkova hears a founder claim they’re building a million-qubit quantum computer, she doesn’t roll her eyes or dismiss the claim outright. Instead, she runs through a series of questions: “What needs to be true for that to happen? Is it a physics problem? Or a manufacturing one?” Her no-nonsense “bullshit” test has made her a trusted advisor to venture capitalists and founders alike. 

Right now, Marchenkova’s pragmatism feels especially prescient. After several years of contracting funding, quantum technology is entering a renewed wave of investment. Funding in Q1 of 2025 for quantum companies reached $1.25 billion, roughly double that of the year before, and according to McKinsey, the total quantum market is predicted to be worth about $198 billion by 2040. In cities as far-flung as Tel Aviv and Tokyo, investors are making a bet that quantum tech will move out of the lab at last. 

But the challenge of convincing investors to fund quantum research persists. “Scientists have great ideas,” Marchenkova tells me. “[And] great technology.” But it can be difficult to translate that knowledge into a timely pitch, which is why she’s built her career helping quantum founders communicate the impact of their work. 

How to vet a quantum tech startup 

Today’s investors want to understand the technology behind the startups they back. As a result, they’re starting to ask more probing questions before writing a check. “It used to be you could dazzle people with the word ‘quantum,’” Marchenkova explains. “You don’t really want to do that anymore.” Yet it requires deep technical knowledge to vet a quantum startup. For most people, she recognized, quantum remained “beautiful, intricate, and … completely inaccessible.” So she started working with VCs as a technical expert.

First comes a comprehensive vetting process. Once a deck crosses her desk, Marchenkova looks for a few signs that the startup can scale. Her criteria vary depending on the startup’s stage, but her quick test is based on three factors: the quality of the team, the scale of the market, and most importantly, the logic behind the bold claims the team intends to make. In essence: “For this to be true, what problems need to be solved?”

This test, she explains, makes the logic clearer and the challenge more explicit to investors. 

If a startup claims to be building a million-qubit computer, for example, she breaks down the larger problem into its individual assumptions. For A to happen, we need B. Minor manufacturing troubles are one thing; an intricate and unsolved physics problem is another.  (The latter might make commercial applications pretty far off.) She lists off different assumptions, then pauses. It’s one thing to have a supply chain problem. On the other hand: “Do we need a Nobel Prize?” 

Bridging storytelling and science 

These communications challenges are why Marchenkova founded One Quark Media, a firm that helps founders talk to potential investors about quantum technology. Built on her work with Bleximo, the Lawrence Berkeley National Laboratory, and Georgia Tech’s Quantum Optics and Quantum Telecommunications Lab, One Quark isn’t your typical comms agency. Focused on education, its mission is to make quantum technology more widely understood among venture capitalists. “I just want to make sure that this technology doesn’t die in the lab,” she says. 

After all, quantum companies face more funding challenges than your average startup. They don’t fit into conventional exit timelines, with research often stretching up to 20 years before the startup sees true commercial payoff. That is why they’re often backed by corporate investment arms or established investors with a higher risk tolerance. They’re typically more niche, which makes them difficult to pitch to general investors. And they don’t always serve a large market. (Unless you’re serving Google, Marchenkova adds. Then even 1% market share means “you’re a billion-dollar company.”) 

But the funding landscape may be shifting, partly thanks to the changing role of VCs. With AI tools like Cursor Pro available for $20 a month, Marchenkova explains, a non-technical builder can easily build an app and sell it without traditional forms of investment. As the field sees more scrappy founders spin up consumer apps and software platforms in a matter of months — without big teams or hefty checks — investing in quantum companies could grow more attractive to investors. 

Many newer software startups, in this model, won’t necessarily have to seek funding, Marchenkova points out. But with deep tech startups, you can’t really get away with not understanding the underlying technology. Quantum startups take deep human expertise and funding. “AI can vibe code,” she quips. “Can it build a new chip?” 

Evaluating the gaps 

This brings us to one of the questions looming over quantum. How much will it cost? Some argue that quantum computers require billions of dollars and that few buyers will be in the market. Marchenkova disagrees. “Some problems are billion-dollar problems,” she counters. Running climate simulations, optimizing renewable energy networks, and streamlining the discovery of rare diseases, for instance. “But also,” she adds, “this is assuming that none of the infrastructure gets [10x] cheaper.”

In this hypothetical, reducing the cost of cryogenics and control electronics would suddenly open the door to developing commercial applications of quantum compute at a dramatically lower cost. In fact, Marchenkova points out, finding and fixing supply chain and infrastructure gaps is currently one of the most pressing problems holding quantum back. This might look like manufacturing specialized materials at scale, building new quantum foundries, expanding the talent pipeline, advancing cooling technology, and mass-producing cryogenic equipment and materials with superconductive properties. 

And supply chains aren’t the only challenge. As the technology matures, there’s also the challenge of benchmarking different forms of compute. “It’s the same problem as with AI,” Marchenkova points out. “Which model is better?” Most importantly: “How do you test it without spending millions of dollars?” 

What’s next? 

Marchenkova isn’t one to be easily swayed by industry predictions without a solid framework attached. As Vice Chair of the IEEE Quantum Computing Standards Project, she’s involved in setting global frameworks and analyzing the strengths and weaknesses of new applications for groundbreaking technology. The bold claims crossing her desk would be enough to make many people a bit jaded. She’s not. 

Instead, she’s focused on possible breakthroughs. She rattles off a quick list of companies she’s watching, from Q-CTRL and SandboxAQ to Infleqtion and Quantum Brilliance. Quantum computing gets “a lot of the hype,” she notes, but there’s more to quantum than just compute. Quantum sensing, often considered one of the earliest “true applications” of quantum technology, could reshape fields ranging from navigation to robotics, while advances in post-quantum security could protect everything from cryptocurrencies to classified intelligence.

Most importantly, quantum will continue to evolve with the world around it. As AI drives a rising cost of compute, she theorizes, the problems the next generation of graduates face will be more strategic. Rather than being taught to code, they’ll be tasked with deciding which challenges are worth the cost of quantum compute. “It’s more mathematical thinking now,” she adds. “Which problems are solved on which type of compute?” 

But no matter what, Marchenkova is pragmatic. After all, someone has to keep the hype in check. “People are like, ‘We have a million qubits,’” she concludes. “Cool, they don’t work. I’d rather have a hundred good ones.”