This DePIN Roundtable episode unpacks the evolving strategies for building sustainable decentralized infrastructure, revealing critical lessons on tokenomics, product-market fit, and capital coordination directly applicable to the burgeoning Crypto AI landscape.
Episode Introduction: Navigating the DePIN Landscape
- Connor Lovely, the host, kicks off the first DePIN Roundtable, introducing co-host Mahesh Ramakrishnan (Co-founder and Investor at EV3) and guests Jason Badeaux (from energy DePIN, Daylight) and Santiago "Santi" Santos (from Inversion Capital, a cryptonative PE firm leveraging DePIN).
- The discussion aims to bring diverse perspectives from seasoned DePIN participants to explore its current state and future potential, especially focusing on revenue generation and sustainable models.
Santi Santos: Non-Crypto Natives' Excitement and DePIN's Untapped Potential
- Santi Santos, sharing insights from the Token conference in Dubai, notes a significant trend: non-crypto natives (like Stripe and BlackRock) are increasingly excited about crypto's transformative potential, particularly stablecoins, for their businesses. This contrasts with a more skeptical sentiment among crypto natives due to stagnant prices.
- Stablecoins: Digital currencies pegged to stable assets like fiat money, offering price stability.
- Inversion Capital, Santi's firm, is focused on a core question: "Why don't we have like 10x or 100x more users on chain?" He believes DePIN is a key technology to drive this adoption by making capex-heavy industries more economically viable.
- Capex (Capital Expenditure): Funds used by a company to acquire, upgrade, and maintain physical assets.
- Opex (Operating Expenditure): Ongoing costs for running a product, business, or system.
- Santi emphasizes the importance of pressure-testing DePIN concepts with traditional industry experts, acknowledging their skepticism but also highlighting crypto's strength in coordination. He states, "We truly believe that DePIN is a technology that facilitates reduces like the transfer of capex to opex... that like really changes the game of infra capex heavy industries."
- Strategic Implication for AI: The challenge of user adoption and the need for robust infrastructure are mirrored in AI. DePIN models that successfully reduce capex for physical infrastructure could offer blueprints for deploying decentralized AI compute and data networks more economically.
Mahesh Ramakrishnan: Crypto Fundraising Doldrums and Emerging Collegiality
- Mahesh Ramakrishnan discusses the current challenging fundraising environment for crypto venture funds, describing it as being in "a little bit of a doldrums."
- Despite the difficulties, he observes a silver lining: a more collegial atmosphere among fund managers, who are now more collaborative due to shared struggles in hitting fundraising targets. Many funds, including EV3's new fund, have secured a first close but face a tough path to their ultimate goals.
- Mahesh touches upon the DePIN Summit in Africa, signaling a focus on emerging markets for decentralized infrastructure.
- Relevance for AI Researchers: The funding climate impacts all crypto sectors. AI researchers seeking grants or investment should be aware of these broader market conditions and the potential for increased collaboration.
Santi Santos: Inversion Capital's Vision – From Convincing to Acquiring
- Santi elaborates on Inversion Capital's successful, oversubscribed fundraise, attributing it to asking fundamental questions like why crypto hasn't reached a billion users despite "killer products" like stablecoins and DePIN.
- A key part of Inversion's strategy is shifting from trying to convince existing businesses to use crypto to directly acquiring them and integrating crypto solutions for efficiency. He cites Stripe's acquisition of Bridge as an example of established fintech recognizing the need to adopt crypto rails.
- Crypto Rails: The underlying blockchain infrastructure and protocols that enable crypto transactions and applications.
- Santi believes the industry is ready for mass adoption, stating, "Memecoins were a really good proof point... We're very much ready to go to a billion users."
- Actionable Insight for AI: For AI applications needing real-world integration, Inversion's model of acquiring and retrofitting traditional businesses with crypto tech could be a powerful go-to-market strategy, especially for decentralized AI solutions.
Mahesh Ramakrishnan: The Power of Conviction and Founder Collaboration
- Mahesh praises Santi's articulate vision and conviction, suggesting that such clarity is often missing among fund managers not directly involved in building.
- He highlights the importance of collaboration, noting how founders like Jason Badeaux have been instrumental in EV3's own fundraising efforts. "Amazing founders are kind of the lifeblood of the industry at the end of the day."
- Strategic Consideration for AI: Strong conviction in a project's core value proposition and collaborative networking are crucial for navigating the crypto space, particularly for capital-intensive AI infrastructure projects.
Santi Santos: Attracting Top Talent to Build the Future of DePIN
- Santi discusses his journey from investor to builder, emphasizing that a key role is to "inspire smarter people to come join you in the mission." Inversion Capital is actively hiring A+ talent across telco, stablecoins, fintech, and private equity.
- He observes that many of the smartest founders entering crypto are building in DePIN, often because they've identified crypto as the solution to long-standing problems in their respective industries (e.g., Neil from Andrena in telco, Jason Badeaux in energy).
- Relevance for AI: The DePIN sector's ability to attract top talent from traditional industries by offering novel solutions is a model for Crypto AI. AI projects that solve tangible problems using decentralized approaches can similarly draw in specialized expertise.
Jason Badeaux: Daylight's Energy Subscriptions and Scaling Physical DePINs
- Jason Badeaux provides an update on Daylight, an energy DePIN, which has tens of thousands of homes and energy devices connected in its beta phase.
- He reveals Daylight's upcoming "energy subscriptions" product, designed to replace traditional electric utilities. This addresses the high capital cost of energy DePINs, where home systems can cost $30,000.
- Jason explains, "If your business model relies on coordinating behavior changes among groups of people and also coordinating huge amounts of capital... then building it in onchain capital markets on crypto rails is really the only way to do that today."
- Daylight aims to tie DePIN's physical infrastructure growth into the DeFi capital stack, offering uncorrelated yield products.
- DeFi (Decentralized Finance): Financial applications built on blockchain technology that operate without central intermediaries.
- Uncorrelated Yield: Investment returns that do not move in tandem with broader market trends, often sought for diversification.
- The company has grown to 21 people, focusing on hiring A+ players.
- Actionable Insight for AI: Daylight's model of using DeFi to finance and scale capital-intensive physical infrastructure is highly relevant for decentralized AI compute networks, which also require significant hardware investment. The concept of "energy subscriptions" could inspire "compute subscriptions" or similar models in AI.
Jason Badeaux: Revenue-First Approach to Token Launches
- Jason outlines Daylight's customer pitch: homeowners get cheaper, more reliable power with backup, paying less for more.
- Regarding a potential token launch, he emphasizes the need for a "differentiated fundamental opportunity," suggesting a target of eight figures in revenue with rapid growth before considering a token. This cautious approach questions the common DePIN strategy of launching tokens early.
- Strategic Implication for AI: For AI projects considering tokenization, Jason's revenue-first philosophy suggests focusing on building a sustainable business model and achieving significant traction before introducing a token, ensuring the token has underlying value.
The Helium Case Study: DePIN Model Inversion and Product-Market Fit
- The discussion shifts to Helium, a DePIN for wireless connectivity, which is experiencing explosive growth in coverage, usage, and revenue, even as its token incentives are winding down.
- Jason Badeaux posits, "The initial version of DePIN may have been incorrect, which is launch the token, then get to PMF [Product-Market Fit], and then you have utility." Helium's current success is attributed to its strong product and market fit, not just early token incentives.
- Product-Market Fit (PMF): The degree to which a product satisfies strong market demand.
- Santi Santos likens DePIN to "SaaS for infrastructure," as it shifts capex to opex, similar to how Software-as-a-Service transformed software deployment. He notes Helium's early reliance on enthusiasts buying hotspots.
- The panel agrees there's more to learn from Helium's recent phase (focus on product and demand) than its initial token-led bootstrapping phase. Andrena's Dawn protocol is cited as another example of using a token to supercharge growth *after* establishing a real business.
- Actionable Insight for AI: The Helium example strongly suggests that Crypto AI projects should prioritize achieving product-market fit and demonstrating real-world utility before relying heavily on token incentives for growth. A token can then supercharge an already working model.
Mahesh Ramakrishnan: Helium's Complexity and Equity vs. Token Dynamics
- Mahesh Ramakrishnan highlights that Helium's potential $50M+ revenue is substantial, but its biggest challenge is the "perception of complexity," particularly regarding how revenue accrues to token holders versus equity holders. This confusion leads to VC sell-offs.
- He suggests that if Helium were starting today, it might bootstrap differently, perhaps using stablecoins and partial equity incentives, given the current DeFi landscape. The path forward might involve combining its equity and token structures.
- Strategic Consideration for AI: AI projects navigating tokenization must clearly define value accrual mechanisms between equity and tokens to avoid investor confusion and ensure long-term alignment, especially if significant off-chain operations or services are involved.
Defining DePIN: Is Bitcoin a DePIN?
- A lively debate ensues on the definition of DePIN. Santi Santos provocatively asks, "What was the first DePIN network by the way? It was Bitcoin."
- Santi's rationale: Proof-of-work networks like Bitcoin involve deploying physical hardware (ASICs) and face constant sell pressure as miners recoup capex. Bitcoin achieved "escape velocity" through its powerful narrative.
- ASICs (Application-Specific Integrated Circuits): Specialized hardware designed for a particular task, such as Bitcoin mining.
- He explains Inversion Capital's strategy with Helium: by operating an MVNO (Mobile Virtual Network Operator) that uses the Helium network, Inversion becomes a major client, absorbing HNT supply and reducing sell pressure because their primary benefit is cheaper data, not HNT speculation.
- MVNO (Mobile Virtual Network Operator): A wireless communications services provider that does not own the wireless network infrastructure over which it provides services.
- Jason Badeaux questions why Inversion would need Helium if deploying its own infrastructure, but Santi clarifies the ROIC (Return on Invested Capital) is higher with Helium due to shared network effects, HNT emissions, and roaming revenue.
- Relevance for AI: The discussion on network participation and incentive alignment (e.g., Inversion using Helium) is crucial for designing sustainable decentralized AI networks. Understanding how large players can contribute to and benefit from the network beyond pure speculation is key.
Jason Badeaux: Innovative Tokenomics and Supply Sinks
- Jason Badeaux discusses the need for innovative tokenomics, especially for retail miners who often sell tokens to cover costs.
- He proposes designing DePIN economies where tokens can be used productively within the ecosystem, such as burning tokens to pay for the services the network provides (e.g., mobile plans, energy bills). "Imagine if you could burn your tokens to pay your energy bills."
- This creates a "closed economy" model, where service payments (e.g., in stablecoins) could fund a treasury, and users could burn network tokens at an exchange rate for these stablecoins to pay for services, directly reducing circulating supply.
- Actionable Insight for AI: For decentralized AI services (e.g., inference, model access), designing tokenomics where users can pay for services with the native token, potentially through a burn mechanism, can create strong utility and reduce sell pressure, fostering a more robust economic loop.
Connor Lovely & Panel: Refining the DePIN Definition
- Connor Lovely suggests it might be time to narrow the scope of the DePIN definition, which has become a broad catch-all. One proposed definition: "machines that are distributed around the world that are together that are providing a service that is not blockchain consensus."
- Mahesh Ramakrishnan agrees, admitting that a previous EV3/Messari report inadvertently broadened the definition, causing confusion. He advocates bringing DePIN back to "the incentivization of physical devices that largely have a hardware element... to build out some sort of resource network or service." He views "DePIN as an asset class."
- Jason Badeaux criticizes "DePIN" as a poor term and argues that lumping diverse projects (e.g., energy, wireless, mapping) under one umbrella leads to flawed comparisons and reasoning by analogy. He urges evaluating projects on their own fundamental merits.
- Santi Santos concurs, comparing the "DePIN" label to the outdated "internet business" generalization. He sees crypto more broadly as a "cost-cutting technology" or an "operating standard" that improves coordination and removes friction across various industries.
- Strategic Implication for AI: As Crypto AI matures, it will likely face similar definitional challenges. The key is to focus on the specific value proposition and underlying technology of each AI project rather than relying on broad categorizations. The principles of DePIN (incentivizing distributed resources) can be applied to AI compute, data, or model networks, but each will have unique characteristics.
Conclusion: DePIN's Evolution Offers Key Lessons for Crypto AI
This roundtable underscores a shift in DePIN towards product-led growth and sustainable tokenomics. For Crypto AI investors and researchers, the core takeaway is the critical need for tangible utility and robust economic models before scaling with token incentives, ensuring decentralized AI infrastructure delivers real-world value.
