Welcome to the 121st edition of Deep Tech Catalyst, the educational channel from The Scenarionist where science meets venture!
This week, I sat down with Haig Farris, Co-Founder of D-Wave, to unpack what it takes to build a successful Deep Tech startup in quantum computing when the technology is ahead of the market, the product path is uncertain, and the commercial outcome may take decades to fully emerge.
Founded in 1999, D-Wave reached the public markets in 2022. Today, we’ll explore how the company began as a startup at the frontier of quantum technology and took its first steps toward commercialization through technical progress, strategic pivots, patient capital, and excellent teamwork.
Key takeaways from the episode:
🧠 Deep Tech Starts With People Before Product
In a field as early as quantum computing was in 1999, the first investment decision was not only about the technology. It was about backing people who could translate deep physics into a vision others could understand, believe in, and support.
📜 IP Can Become a Critical Asset Before the Product Is Ready
Intellectual property became part of the company’s financing story, giving the founders a way to sustain the project, raise capital, and keep building value before the commercial opportunity was fully mature.
🔁 In Deep Tech, the First Commercial Thesis May Be Wrong
The company initially expected that demonstrating linked qubits would attract major technology players. That did not happen. But the company survived because it kept improving the technology, the team, and the defensibility of the business.
🧩 Commercialization Requires a Full Stack
The breakthrough was not only the quantum chip. It required reducing noise, improving connectivity, linking more qubits, and building software that allowed users to work smoothly with optimization problems.
⏳ Long-Horizon Companies Are Built Through Talent and Persistence
D-Wave’s story is not only about quantum computing. It is about what it takes to keep a company alive while the market catches up: technical progress, patient capital, stronger leadership, accumulated IP, and an organization capable of carrying the vision forward.
BEYOND THE CONVERSATION — STRATEGIC INSIGHTS FROM THE EPISODE
Starting a Quantum Company Before the Market Was Ready
Framing the story of D-Wave requires starting from a point that differs from the usual founder narrative around frontier science.
It did not begin with a market that was already waiting for a quantum computer. And it certainly did not begin with a clean, obvious path from scientific insight to commercial product.
It began with people.
That distinction matters because in the earliest stages of Deep Tech, especially in a field as new and difficult as quantum computing was in 1999, investors often are not underwriting a market-ready product. They are underwriting exceptional people who may be able to make the technology real.
That was the case in this story.
The company began with people before it began with a product
As we discuss every week, in Deep Tech, the ability to translate complexity is not a soft skill. It is part of the company’s commercial infrastructure.
If a founder cannot explain the core idea to investors, early employees, strategic partners, and eventually customers, the science remains trapped inside the lab.
From the beginning, D-Wave was not built only around deep physics. It was built around people who could make that physics understandable, credible, and commercially meaningful.
What stood out was the combination of deep physics and commercial vision: the ability to see not only a scientific breakthrough, or the possibility of one, but why it might matter outside academia.
At that stage, there was no mature quantum computing market waiting for a product.
What existed first was the ability to make a complex idea compelling enough for others to believe it could one day become economically important.
That is the first lesson here.
The scientist-entrepreneur has to be capable of translating the impossible into stages of progress. And the company has to keep accumulating value before the final commercial outcome is clear.
The longer the commercialization path, the more the team must be unusually smart, unusually driven, and unusually capable of bringing others into a difficult vision.
The founders must show that they can keep learning, keep attracting talent, and keep making progress even when the market is not yet ready.
In that sense, D-Wave did not start because the market was ready. It started because the people were unusual enough to make the market worth waiting for.
IP became an asset before the product became obvious
Another key aspect of this journey is that the intellectual property D-Wave accumulated in its early years became one of the company’s most important assets.
In a science-intensive company, IP can become part of the financing story before the product is commercially mature. That becomes especially important when the time to market is measured in years.
For D-Wave, the patent portfolio helped investors believe that even if the company did not reach the commercial outcome everyone hoped for, there was still real underlying value.
The company had built something defensible. It had accumulated ownership around a field that could become important. It had a position that might retain value even in a downside case.
That was especially important because the early product thesis was still uncertain.
Quantum computing was not a market with established demand. There were no standard customers buying quantum machines in the ordinary way. The company was still trying to make progress on the science and engineering, while also convincing investors that the value of the company was increasing.
The patent portfolio helped make that argument.
That is not the same as saying patents alone made the company investable. They created a layer of value that made the long journey more fundable.
This is an important distinction for Deep Tech founders.
When the Original Thesis Does Not Work as Planned
One of the most useful parts of the D-Wave story is that the original pitch did not work. It is central to understanding how long-horizon Deep Tech companies actually survive.
At the beginning, there was a belief that a certain kind of technical demonstration would be enough to create strategic pull.
If the company could demonstrate that it could link two qubits together and show how they functioned, the large technology companies would understand the importance of what had been built.
The expectation was that the field’s major players would beat a path to the company’s door.
That did not happen.
The team did the work. They linked the qubits. They published papers. They gave demonstrations. The milestone was real. But the market reaction was not what the company had expected.
No large incumbent arrived with the urgency the founders and investors had imagined. No strategic buyer treated the demonstration as the inevitable beginning of a large commercial opportunity.
So the company had to raise more money and take the next step.
That sentence captures a great deal of what frontier company-building feels like.
A technical milestone can be genuine and still not be enough. A scientific proof point can be important and still fail to unlock the next commercial chapter. The market can be impressed without being ready. Large companies can observe the future without feeling the need to own it immediately.
In a conventional startup, that mismatch might be fatal.
If the company is built around a short-term commercial assumption and the customer does not respond, the business may not have enough reason to continue.
But in a frontier technology company, the first commercialization thesis can be wrong while the underlying company still becomes more valuable.
That is what happened here. The company kept going because it kept becoming better.
The Strategic Pivot from Gate Model to Annealing
There is a moment in some Deep Tech companies when the original technical path does not disappear because it is wrong, but because it is too far away.
That distinction is important.
The early D-Wave journey began with an ambition around quantum computing that was enormous in scope. The company was working on a gate-model path, a broader approach to quantum computing than the annealing route it would later choose.
But after roughly five years, the practical reality became impossible to ignore. The gate-model approach was going to take too long.
The problem was that the technical obstacles made that path look too long for the company to keep pursuing as its main route. There were major issues around noise.
There were major issues around linking qubits in large numbers. The path might have been scientifically meaningful, but from a company-building perspective, it was too distant.
That was the strategic significance of D-Wave’s pivot to annealing.
Focus came from accepting what would take too long
Broad visions can become dangerous when the technical execution horizon is too long. A startup does not have infinite time. It does not have infinite money.
The annealing approach was described as a faster, more practical way of getting to a quantum computer that worked in a particular domain: optimization.
It was narrower. But it was reachable.
In brief, annealing offered a different logic: instead of continuing to pursue the broader gate-model route as the company’s main path, the company could concentrate on a class of problems where quantum effects could be applied more directly.
Optimization became the center of gravity.
That meant the company could focus its technology development and financing story around a more specific kind of value proposition.
That is one of the most difficult strategic moves in Deep Tech: knowing when to stop pursuing the original vision and start pursuing the version that can become a company, especially when there is no existing path to follow.
The company changed direction overnight
The pivot was decisive.
Once the company switched to the annealing path, it did not simply add annealing as another research direction. It changed the company.
The organization moved away from the earlier path because the team believed it already knew how to make the chips required for the annealing approach.
The decision also reshaped the financing story. After the pivot, the company began more serious attempts to raise capital and eventually found the right investors.
That financing did not happen in a vacuum. It came after the company had chosen a more focused technical path and could tell a clearer story about what it was trying to build.
In that sense, annealing was not merely a technical pivot. It also reshaped the business architecture of the company. It defined what kind of problems the company would focus on. It defined what kind of investor story could be told. And it allowed the company to move toward a more focused path for engineering and commercialization.
From Scientific Breakthrough to Commercialization
The technical journey of D-Wave was not only about making a quantum machine work for a specific class of problems.
It was about turning a deeply complex physical phenomenon into a system that could keep improving, solve increasingly difficult problems, and eventually be used by people who were not quantum physicists.
That distinction matters because in Deep Tech, the core breakthrough is rarely the whole product. It is the beginning of the product.
In the case of D-Wave, the technical obstacles can be understood through a few central problems:
Reducing the number of wires needed to link qubits together.
Reducing noise so the quantum state could be maintained.
Linking more qubits together so the machine could address large optimization problems.
To link qubits together, the company had to send wires down into the system. Reducing the number of wires needed to create those connections was a major step.
In a normal technology company, a wiring problem might sound secondary. In this context, it was central because the ability to connect qubits was part of the path toward making the machine capable of doing something powerful.
The second challenge was noise.
A quantum state is delicate. If the electronics create too much disturbance between the chips, the quantum state can be disrupted. If the quantum state is disturbed, the calculation is not accurate. That means noise is not only a performance issue. It directly affects whether the computation can be trusted. The machine has to protect the state well enough for the computation to matter.
The third challenge was scale and connectivity.
The company had to learn how to link more qubits together because that is where the computational power begins to matter.
Low noise, many qubits, and deep connectivity between them were the ingredients that could allow the system to process large optimization problems.
This is where the technical progress became inseparable from the business story.
The company was not simply making a better chip for the sake of making a better chip. It was improving the system so that the machine could solve more difficult problems.
That is the way technical progress becomes commercial progress in frontier hardware.
Another essential part of the system was software.
For the technology to become useful, users with optimization problems had to be able to work with the machine without first becoming quantum physicists.
That meant building software that could translate a real optimization problem into the quantum requirements of the system.
Building a Company That Can Outlast Its First Founders
One of the most interesting lessons from the D-Wave story is that a long-horizon Deep Tech company cannot depend forever on the same kind of talent that made it possible in the first place.
The earliest phase requires people who are willing to live at the frontier.
These are the people who are excited by uncertainty, who want to work on problems before the path is clear, and who can operate in a world where the difference between a technical enabler and a company strategy is still being worked out.
In D-Wave’s case, that kind of talent was essential at the start. Without it, there would have been no company to build.
But as the company moves forward, the work changes.
At some point, the problem is no longer only whether the science can be imagined. It becomes whether the technology can be engineered, financed, sold, supported, and managed over many years.
The company has to move from invention to execution. And that transition can require a different kind of organization, with different kinds of talent.
Long time-to-market companies need belief, adaptation, and luck
Another advice for founders building in a long time-to-market sector is both simple and difficult: keep at it, but only if the belief is grounded in real economic value.
That distinction is essential.
It is not enough to believe that the science is beautiful. It is not enough to believe that the technology is intellectually important. A company can only keep raising money, attracting talent, and surviving hard cycles if the founders and investors believe that the work has long-term economic significance.
The value has to be more than scientific.
In D-Wave’s case, the belief was that quantum computing could eventually matter economically because of the kinds of problems it could address.
Even when the original commercialization assumptions did not play out, the company could continue because investors believed the underlying asset was becoming more valuable.
The technology improved. The IP improved. The team improved. The company kept moving.
That is the foundation of persistence in Deep Tech.
Persistence is not simply refusing to quit. It is continuing to make the company more valuable while the world catches up to the technology.
But persistence alone is not enough.
The company also has to adjust to the times. It has to adjust to the people it has, the financing environment it faces, and the market it is trying to reach. The strategy cannot be frozen at the moment of founding.
The company has to keep understanding the market well enough to know how to pitch itself, what kind of people to recruit, and how to move the business forward.
That is where the board becomes important.
In a long-horizon Deep Tech company, the board is not just there for governance. It has to help the company survive transitions.
It has to help find the right leadership. It has to help the company recognize when the talent needed for the next phase is different from the talent that defined the first phase. It has to help assemble the team that can carry the company forward.
In the end, a long time-to-market company is not built by a single act of genius. It is built through repeated acts of continuation.
The company has to survive the period when the market is not ready, when the original pitch does not work, when the technical path changes, when founders move on, when investors need reassurance, and when the product is still becoming understandable to customers.
In that kind of company, belief is necessary, but belief has to be renewed through progress.
The company has to become more valuable every year. Not always through revenue at first, and not always through commercial validation, but through capability, defensibility, talent, and strategic relevance.
D-Wave’s story is therefore not only a quantum computing story. It is a story about what it takes to build a company in a field where the market may take decades to fully form.
The technology has to advance. The people have to evolve. And the organization has to become strong enough to carry the company forward, even if the original thesis has evolved.
