Contrary Research Rundown #132
Building in the physical world is going to require a new capital stack; plus new memos on Rippling, Writer, and more
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Research Rundown
This piece was originally published in Venture Desktop by Brett Bivens and William Godfrey.
The structure of the global financial architecture is set in stone – until suddenly it isn't. Financial history is marked by the redrawing of asset class boundaries by breakthrough companies, creative financiers, and macroeconomic shifts. This often happens at a shocking speed.
In these moments of transition, institutional capital often convinces itself that it's still operating in a previous paradigm long after that moment has passed. Today, the paradigm around which much of the asset management industry is oriented – the era of globalization and unobstructed capital flows – is rapidly giving way to what Russell Napier calls "National Capitalism," where state priorities around energy security, industrial capacity, and technological sovereignty reshape capital allocation.
Over the last few years, venture capital has had its guard up about the threat of AI enabling the proverbial “one-person, billion-dollar company” – small teams leveraging AI to create massive value without the need for massive amounts of venture funding.
Slightly more behind the scenes, another fundamental force is reshaping how technology scales in this new economic paradigm, putting pressure on the traditional venture capital model: debt.
From transport fleets (Zenobē) to digital infrastructure (CoreWeave) to energy storage (Base) to manufacturing (Hadrian) to clean fuels (Twelve) to aerospace (ISAR) – debt is playing an increasingly key role in the capital stacks of the most promising emerging companies. For companies deploying valuable hard assets – batteries, modular robotics, CNC machines – asset-based lending is emerging as the wedge to unlock scalable project and equipment-level finance, allowing these companies to grow at venture speed while consuming far less equity capital.
These hard asset businesses are increasingly built and valued on bundles of cash flows rather than revenue multiples, requiring an entirely different approach to capital formation across the company lifecycle. And while several early movers have begun to break through, the holistic financing models best suited to systematically support and scale this model remain fragmented and underdeveloped.
The most valuable financial innovations that grow out of this era will mirror the significance of this macro wave and the ambitions of the companies riding it, not merely creating efficiencies or engineering marginal returns, but fundamentally realigning incentives and reducing friction in capital formation to address these new structural realities.
The $68 Trillion Opportunity
As Larry Fink highlighted in his recent Chairman’s Letter, we are approaching an infrastructure investment boom of staggering proportions.
“Today, we're standing at the edge of an opportunity so vast it's almost hard to grasp. By 2040, the global demand for new infrastructure investment is $68 trillion. To put that price tag in perspective, it’s roughly the equivalent of building the entire Interstate Highway System and the Transcontinental Railroad, start to finish, every six weeks – for the next 15 years.”
Along with these figures, he posed a crucial question: "Who will own it?"
The obvious answer might be the world’s mega-credit funds, today sitting on hundreds of billions of dollars of dry powder and seeking to move up the risk curve as margin in established categories is competed away.
They recognize that deploying $68 trillion to drive true economic growth and renewal will require investment in new infrastructure categories – next-generation energy systems like modular nuclear and grid-scale storage, advanced manufacturing facilities for critical components, novel materials production, and autonomous logistics networks, among others.
The challenge isn't one of capital demand. It is a supply-side bottleneck. Simply, there are not enough investment-ready companies, assets, and projects with institutional-grade scale and risk profiles in these new segments.
While credit funds want to move earlier in the technology lifecycle and into new categories, they lack the agility and capacity to unlock this bottleneck. Their investment mandates, governance structures, and operational processes are fully optimized around mature assets with established cash flows, not emerging technologies at the point of commercialization.
Similarly, the venture capital ecosystem, where most of these emerging hard asset categories get their start, has thus far proven unprepared and undertooled for the debt-dominated, project-centric scaling model required of the physical technology companies that will define the coming hard asset supercycle.
As such, the greatest opportunity in this supercycle exists for an emerging class of "Production Capitalists."
That is, firms with a mix of venture and credit DNA that can i) identify and back emerging companies turning breakthrough technology and novel business models into the critical infrastructure powering energy transition, reindustrialization, and security initiatives, and ii) play an active role in helping those companies build the financial foundation – construct their capital stack – to unlock efficient scale.
These firms manufacture their own alpha by building the connective tissue between early-stage innovation and the mainstream credit, infrastructure, and strategic industrial capital that can scale it. They are purpose-built to coordinate efficient capital-intensive deployment on behalf of their companies in the emerging National Capitalism paradigm.
They operate less as investors and more as builders. Their “product”, which they co-develop alongside the technology companies they back, is a scalable bundle of infrastructure-ready projects and physical assets.
To read the full essay, check it out here at Venture Desktop.
Doss is targeting this shift with a modular ERP platform that provides low-code infrastructure, readable by both humans and AI, combining inventory, order, and fulfillment management in one system. To learn more, read our full memo here and check out some open roles below:
Full-stack Engineer - San Francisco, CA
GTM Engineer - San Francisco, CA
Writer is a generative AI platform that helps businesses use LLMs to generate accurate and compliant content and deploy generative AI applications across different departments, including operations, products, sales, and marketing. To learn more, read our full memo here and check out some open roles below:
Site reliability engineer - San Francisco, CA (hybrid)
AI Engineer - New York, NY (hybrid)
Rippling was built to consolidate functions by creating a comprehensive platform for HR, IT, and payroll processes at a global scale. To learn more, read our full memo here and check out some open roles below:
Full Stack Engineer II (Backend) - Time Products - New York, NY
Senior Forward Deployed Engineer - New York, NY
Check out some standout roles from this week.
Persona | San Francisco, CA, New York, NY or Remote - Product Designer, Senior Software Engineer, Software Engineer, Security, Software Engineer, Product, Software Engineer, iOS / Android
Sourcegraph | San Francisco, CA or Remote - Forward Deployed Engineer, ML Engineer, Software Engineer (Search Platform), Software Engineer (Cody Core)
Semgrep | San Francisco CA, New York NY, Boston MA, Denver CO, or Remote - Senior Software Engineer (Backend Code Team), Senior Software Engineer (Infrastructure/Data Platforms), Senior Software Engineer (Managed Scanning), Software Engineer (Supply Chain), Sr. Engineering Manager Code and Secrets
Meta pitched a “Llama Consortium” to Microsoft, Amazon and others seeking cash or compute to offset training costs for its open‑source LLM. But potential partners balked at funding a model they’d still receive free, underscoring strain even as Meta plans $60‑65 billion in AI capex this year.
OpenAI is negotiating its largest-ever acquisition with Windsurf (formerly Codeium), an AI-powered coding assistant last valued at $1.25 billion. The potential deal positions OpenAI to challenge GitHub and Anthropic in the competitive coding-assistant market, reflecting increased merger activity amid growing investor interest in AI tools.
In other OpenAI news, the company is exploring an X-like social network prototype, currently centered on ChatGPT’s image-generation capabilities. Though still in early stages, the project could escalate competition with Elon Musk’s X and Meta’s forthcoming AI-driven social app. Altman reportedly seeks to leverage social interactions to train AI models and possibly match the viral integration Musk achieved with Grok on X.
To round off OpenAI’s week, Sam Altman shared that courteous ChatGPT prompts (“please,” “thank you”) rack up “tens of millions of dollars” in extra compute each year; a Future PLC survey found roughly 70% of users are polite to AI, spotlighting the trade‑off between etiquette and energy use.
Precision Neuroscience, a startup co‑founded by a former Neuralink surgeon, has won FDA 510(k) clearance for its “Layer 7” cortical interface, a stamp‑size, 1,024‑electrode film that can be slipped through a sub‑millimeter incision to rest on the brain’s surface, capturing and stimulating neural signals for up to 30 days and advancing a less‑invasive route to commercial brain‑computer interfaces.
VCs are increasingly bracing for a new “funding winter”: Firms like Flybridge urged portfolio companies to close rounds “ASAP,” one Bay Area firm froze high‑multiple deals, and LPs are stalling commitments—reviving déjà‑vu fears of capital drying up just as AI exuberance had revived deal flow.
A new essay argued that tech leaders may be misreading their sci‑fi heroes—Musk (Banks, Asimov), Zuckerberg (Snow Crash), Thiel (Tolkien)—turning cautionary cyberpunk into business plans for Mars colonies, metaverses and seasteads, and in doing so risk engineering the very dystopias those novels warned about.
Strava, the social network loved by runners but notably lacking robust training plans, has acquired Runna, a popular AI-powered running coach. While initial changes will be minimal, the move addresses a key gap in Strava's offering and taps into Runna’s rapidly growing user base spanning 180 countries.
Figma has filed IPO paperwork, signaling a strategic pivot 16 months after regulators scuttled its $20 billion acquisition by Adobe. Last valued at $12.5 billion, the IPO move highlights corporate boldness amidst a largely frozen IPO market—though it remains uncertain when or if the company will proceed further.
Google unveiled DolphinGemma, an AI model trained on decades of dolphin vocalizations collected by the Wild Dolphin Project, in partnership with Georgia Tech. Using advanced audio processing and deep learning, DolphinGemma identifies patterns in dolphin "language," potentially enabling researchers to understand—and even interact with—wild dolphins through synthetic sounds.
The Rippling <> Deel drama continues! Rippling's major lawsuit against Deel CEO Alex Bouaziz hit a snag as Bouaziz relocated to Dubai, complicating legal proceedings due to the UAE's reputation as a haven from extradition. Rippling accuses Bouaziz of bribing a Rippling employee in Ireland.
Interviews with Rodney Brooks, David Eagleman, and Yann LeCun reveal a coherent vision for AI’s path forward, highlighting common pitfalls like "magical thinking" about AI’s capabilities and emphasizing the need for AI systems that combine intuitive (fast) and analytical (slow) thought processes.
Apple is developing two successors to its struggling $3.5K Vision Pro headset: one lighter and cheaper, and another designed for ultra-low-latency Mac connectivity, targeting enterprise users. CEO Tim Cook remains focused on creating lightweight, consumer-friendly AR glasses, but the technology could still be years away.
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