Beyond the Qubit

Transduction is “everybody’s problem and nobody’s problem.”

That line from Vijoy Pandey, SVP/GM of Outshift by Cisco, stayed with me after Part 2 of my Beyond the Qubit interview because it points to one of the most important value layers in quantum.

In this episode, I explore why connecting quantum computers may become just as important as building them. In classical networking, information can be inspected, routed, and forwarded. Quantum information is different. If you inspect the quantum state, you risk destroying the information you are trying to preserve.

This episode is for investors, founders, and anyone trying to understand the infrastructure that quantum computing will need to scale. The challenge is not only building better qubits. It is creating the interfaces, switches, and protocols that allow different quantum systems to communicate.

That is where transduction becomes strategically important. It is the translation layer between quantum computers and quantum networks. Without it, the industry risks creating isolated compute islands where every system speaks its own language.

Cisco’s approach is interesting because it is not built around betting on one winning quantum modality. Instead, the focus is on building a network layer that can connect different architectures. If quantum becomes a distributed computing platform, the companies controlling the interfaces and connectivity layers could become important control points.

💡 In this episode, we cover:
Why quantum networks cannot copy classical internet architecture

Why transduction is the interface problem between quantum computers and networks

How quantum switches differ from classical switches

Why different quantum modalities create a connectivity challenge

How Cisco’s universal quantum switch approaches translation between encodings

Why ecosystem collaboration matters for quantum networking

Why the network layer could become a valuable control point

What investors should watch as quantum infrastructure develops

Chapters
00:00 Why transduction matters in quantum networking
01:35 Why quantum needs a network layer
02:39 The NIC card analogy for quantum
03:24 Why transduction is harder than classical networking
04:51 Why quantum networks cannot inspect information
07:05 Building a universal quantum switch
08:45 Translating different quantum encodings
10:48 Why ecosystem collaboration matters
12:47 Keeping the network simple and complexity at the edge
14:48 Why transduction could become a strategic control point

Share this episode with someone investing in or building in quantum, and subscribe or follow Beyond the Qubit for more conversations on quantum technology, markets, and investing.

📌 Disclaimer:This is not investment advice.This post is shared on a personal basis and I do not represent any company.

The internet was built by reading packet headers.

Quantum networks cannot do that.

In this episode, I explore my biggest takeaways from Part 1 of my Beyond the Qubit interview with Vijoy Pandey, head of Outshift at Cisco. The key difference is simple but profound: classical networks scale by inspecting and forwarding information, while quantum networks have to preserve information they cannot directly inspect.

This episode is for investors, founders, and anyone trying to understand what infrastructure quantum computing will need beyond the QPU itself. If quantum systems are going to scale beyond isolated machines, they will need a network layer that can connect processors, sensors, and resources while preserving fragile quantum states.

Cisco’s approach is interesting because the company is not trying to build the quantum computer itself. It is exploring the networking layer around quantum systems, using photonics, telecom frequencies, room-temperature components, and existing fiber infrastructure. The goal is not to recreate the classical internet, but to build the architecture needed for quantum scale.

The strategic question is not only who builds the best qubits.

It is also:
Who builds the network that connects them?

💡 In this episode, we cover:
Why quantum networks cannot simply copy classical internet architecture

Why quantum information cannot be inspected like classical packets

How quantum switches and entanglement sources could enable scaling

Why networking between QPUs may become a major bottleneck

Why Cisco is focusing on the infrastructure layer around quantum computers

How photonics and existing fiber infrastructure could improve deployability

Why quantum networks may also connect sensors and shared resources

What investors should watch in the quantum networking stack

Chapters
00:00 Why Cisco is exploring quantum networking
00:50 Why quantum needs a network layer
03:22 Quantum clusters and the need for connectivity
04:47 What quantum networking actually means
05:23 The quantum switch challenge
08:01 Why classical networking cannot be copied
10:03 Why quantum networks cannot inspect information
12:29 Building networks without destroying quantum states
14:42 Why Cisco focuses on photonics and fiber
17:39 Connecting quantum computers and sensors
27:14 The current state of quantum networking

Share this episode with someone investing in or building in quantum, and subscribe or follow Beyond the Qubit for more conversations on quantum technology, markets, and investing.

📌 Disclaimer: This is not investment advice. This post is shared on a personal basis and I do not represent any company.

Quantum will not scale by optimizing hardware, software, and testing independently.

The winners will have to make the entire system work.

In this episode, I continue my conversation with Adriaan van Rol from OrangeQS to explore why quantum testing may become one of the most important infrastructure layers in the industry. OrangeQS looks like a hardware company at first. Its OrangeQS MAX platform combines cryogenics, electronics, cabling, control systems, and data acquisition to test quantum chips.

But one of the more interesting parts of the system is the software layer underneath: OrangeQS Juice. What started as the software environment around OrangeQS MAX evolved into a broader platform for multi-user workflows, instrument control, structured data, and scalable test operations.

This episode is for investors, founders, and anyone trying to understand what it takes for quantum to move from research toward manufacturing. At scale, testing is not just about measuring a chip. It is about turning measurements into diagnosis, validated insights, and better manufacturing decisions.

That is where the strategic opportunity becomes interesting. The potential moat is not only the hardware or the software individually. It is the integrated system: hardware + software + data + domain knowledge. Because in quantum manufacturing, the ability to create a faster feedback loop may become just as important as the ability to build the device itself.

💡 In this episode, we cover:
Why quantum testing needs to evolve beyond laboratory workflows

How OrangeQS MAX combines hardware infrastructure for quantum chip testing

Why OrangeQS built Juice instead of relying on simple lab scripts

How software enables repeatable, traceable, multi-user testing

Why testing becomes inseparable from manufacturing at scale

How measurement data can become manufacturing insight

Why integrated systems may create stronger moats than individual products

The importance of data governance in quantum manufacturing

Chapters
00:00 Why quantum testing needs a complete system
01:50 What OrangeQS is building for quantum chip testing
08:10 Why testing and manufacturing need feedback loops
14:40 Turning test data into manufacturing learning
29:33 Why OrangeQS Juice became a hidden gem
30:54 Moving from lab scripts to scalable workflows
35:00 Hardware, software, data and domain knowledge together
42:15 The future of quantum manufacturing infrastructure

Share this episode with someone investing in or building in quantum, and subscribe or follow Beyond the Qubit for more conversations on quantum technology, markets, and investing.

📌 Disclaimer:This is not investment advice.This post is shared on a personal basis and I do not represent any company.

Why is building a great deep-tech product only half the battle?

In this episode, I explore one of my biggest takeaways from my conversation with Adriaan Rol from OrangeQS. OrangeQS is building test solutions for quantum chips, but the challenge is not only technical. When a product costs millions, the company also has to solve a different problem: how customers actually buy.

This episode is for investors, founders, and anyone interested in deep-tech commercialization. Adriaan shares an honest lesson from OrangeQS’s journey: they underestimated not the physics or engineering, but the complexity of corporate decision-making, CapEx budgets, procurement processes, and internal risk.

A strong technical story is not enough. A great product is not enough. At some point, deep-tech companies need to make the buying decision easier. That means understanding the customer’s internal process, creating the right milestones, reducing risk step by step, and turning technical interest into a purchase order.

The lesson is bigger than quantum. In deep tech, product-market fit is only part of the equation. Companies also need procurement-market fit.

💡 In this episode, we cover:
Why deep-tech companies need more than product-market fit

Why expensive hardware requires a different sales approach

How OrangeQS learned to navigate CapEx decisions and procurement

Why technical validation does not automatically lead to purchases

How partnership programs can reduce customer risk

Why customers need a buying process they can defend internally

How deep-tech founders can turn interest into purchase orders

Why adoption is often as difficult as the technology itself

Chapters
00:00 Why deep tech needs procurement-market fit
08:34 Why million-euro hardware changes the buying process
17:32 Building a partnership program to reduce risk
22:19 The hidden challenge of CapEx decisions
40:29 Why procurement can make or break adoption

Share this episode with someone building or investing in deep tech, and subscribe or follow Beyond the Qubit for more conversations on quantum technology, markets, and investing.

📌 Disclaimer:This is not investment advice.This post is shared on a personal basis and I do not represent any company.

When quantum computers scale out, the algorithm has to know where the weak links are.

In this episode, I continue my conversation with Enrique Solano from Kipu Quantum to explore why modular quantum computing is not only a hardware challenge. Most people think modularity means more chips, more qubits, and more scale. But Enrique highlights a deeper issue: once quantum computers become distributed systems, the algorithm has to understand the physical reality of the machine.

This episode is for investors, founders, and anyone trying to understand where quantum software value may emerge. When computation moves across multiple chips, not every connection is equal. Some gates may have very high fidelity inside a chip, while connections between chips can introduce weaker operations. Small differences in fidelity can determine whether an algorithm survives long enough to become useful.

That is where Kipu’s hardware-aware approach becomes interesting. The software cannot treat every quantum backend as identical. It needs to understand connectivity, topology, fidelities, and the weak points of the architecture. In quantum, scaling hardware creates a new software problem. The winning software layer may be the one that understands the machine well enough to extract value from its imperfections.

💡 In this episode, we cover:
Why modular quantum computing changes the software challenge

Why more qubits do not automatically mean more useful computation

How inter-chip connections can create new fidelity bottlenecks

Why algorithms need to understand quantum hardware topology

Why hardware-aware software may matter more than hardware-agnostic approaches today

How Kipu thinks about extracting value from imperfect quantum systems

Why scaling quantum hardware creates new algorithmic challenges

What investors should watch in quantum software companies

Chapters
00:00 Why Kipu Quantum focuses on hardware-aware software
01:29 Why algorithms must adapt as hardware changes
03:26 Why architecture matters in quantum systems
06:46 Fidelity limits inside quantum architectures
08:03 Why modularity changes the algorithm
09:01 Building quantum systems beyond single chips
15:04 Why inter-chip connections create new challenges
15:21 Why small fidelity differences matter
16:30 Why algorithms must know the machine

Share this episode with someone investing in or building in quantum, and subscribe or follow Beyond the Qubit for more conversations on quantum technology, markets, and investing.

📌 Disclaimer:This is not investment advice.This post is shared on a personal basis and I do not represent any company.