Dr. Robert Moir, PhD, is an applied mathematician. With a PhD from Western University, he transitioned from over a decade in academia—focused on scientific inference and computation—to industry leadership roles at HyperCycle and Earth64.
What brought you into crypto? Was it a friend, trading — what led you down this path?
I got into crypto around 2020 or 2021. A friend of mine had been talking about it, so I put in a little money and started exploring. That motivated me to learn more about the tech behind different blockchains.
A few years later, I found myself working with a group on something blockchain-adjacent — which brings us to what we’re talking about today.
You’ve described Hypercycle as the network infrastructure for all “AI kind.” What does that mean?
The idea is that it’s optimised for machine-to-machine interaction. It lets machines connect directly, exchange capabilities and intelligence, fully peer-to-peer, with no intermediaries in the middle. Most systems today still rely on some central component.
Hypercycle removes that, enabling seamless intelligence sharing without compatibility bottlenecks.
What are some of the key bottlenecks in current AI ecosystems that Hypercycle is being designed to solve?
A big one is payment friction. Traditional systems require pre-setup and have built-in assumptions that slow things down.
Hypercycle uses ledgerless micropayments between nodes, so they can transact directly, without setup or delays. It makes machine-to-machine commerce more efficient and straightforward.
Is that similar to how the Lightning Network creates bespoke payment channels between nodes?
In some ways, yes, but Lightning still relies on a layer 1 ledger and predefined payment channels, which need to be settled back onchain.
Hypercycle has no global ledger and no channels to manage. There’s nothing in between — just peer-to-peer interaction. That opens up many different possibilities.
I think the acronym is TODA/IP? How does that model compare to traditional blockchain designs?
Exactly. Traditional blockchains rely on a global ledger — a massive shared database of transactions.
It’s expensive and inefficient. With TODA/IP, each asset carries its own ledger and only shares it with the counterparty during a transaction.
Combined with what we call proof-of-N² work, where real economic work is done by a distributed network, only a minimal global state is shared. Essentially just a single hash per “heartbeat.”
Is “heartbeat” your term for block times?
Pretty much. It’s a periodic global network summary — similar to a block — but instead of bundling transactions, it summarises useful work happening across the network.
From a design perspective, how do you balance eliminating upfront fees while ensuring long-term sustainability and aligned incentives?
You’re probably referring to HMS — that’s actually a product from HyperPG, a partner of ours.
It’s an example of the multi-sided marketplace that Hypercycle enables. HMS connects node owners, operators, hardware providers, algorithm developers, service providers, and users.
The incentives are designed so everyone benefits when services running on the network succeed and generate revenue.
The more valuable services there are, the more node utilisation and revenue, which benefits everyone across the ecosystem.
You also mentioned a tranche model for HMS, similar to what we’ve seen in DeFi, but in your case it’s about security and protecting early adopters. How will that scale?
Right. It’s more about honouring early participants in HMS. The structure ensures they never earn less than newcomers.
Over time, as revenue stabilises across the network, those tranches will likely converge into a single rate or narrow band.
How does HMS reward productive infrastructure over pure speculation?
That’s the core of the marketplace. HMS only earns if the nodes are generating revenue.
So it encourages onboarding high-quality, revenue-generating services. Everyone wins when those services succeed.
How do non-technical participants engage meaningfully in the network? It’s been a challenge in DAOs, where non-technical delegates often struggle to contribute.
We’re addressing that on two fronts: node owners and node operators.
For owners, HMS will offer simple choices, like choosing whether to allow experimental services on their nodes. Over time, they’ll have more control without needing technical expertise.
On the operator side, we’re launching educational programmes. It’ll start with short videos — eight-minute explainers to help people run nodes without a technical background — and then expand to running actual AI services.
Making this accessible is a priority.
From your perspective as CSO, what’s the biggest challenge before AI-driven commerce reaches an inflection point? And what’s next for Hypercycle?
The biggest challenge is proving that AI agents can deliver real business and personal value, beyond simple task automation. Once they demonstrate meaningful utility and integrate smoothly into workflows, adoption will take off.
For Hypercycle, the focus is on showcasing practical services that use our node architecture. We’ll also boost accessibility through better tooling and education. By Q4, we plan to kick off hackathons to get more people involved.
Who do you see as your biggest competitors, and what sets you apart?
There are networks building collaborative tools for AI agents — some in big tech, some in web3. But the key difference is openness.
Others are building closed ecosystems — essentially intranets. We’re building the internet equivalent: a fully peer-to-peer global architecture where any node can reach any other. That openness is our differentiator.
Is there anything outside of Hypercycle that you’re particularly bullish on within crypto?
That’s tough, because we don’t really see ourselves as part of the crypto ecosystem per se. Hypercycle grew from blockchain roots, but it’s designed to solve the limitations of traditional blockchain.
That said, we’ll use blockchain wherever it solves a specific problem, like representing our Node Factory licences onchain. We’re open to integration, especially in AI-agent-focused ecosystems.
And what’s on your short-term roadmap?
Right now, the focus is on HMS. We’re working with HyperPG to launch it as the first real-world example of our multi-sided marketplace.
The more services that onboard, the more the network grows organically. It’s all about proving the model, then letting the ecosystem evolve naturally.
That’s the priority for now, but there’s much more to come.