Future Ventures: Scaling with Clarity

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John Cowan was about to do what he'd done a hundred times before — make the calls, set the meetings, walk a young founder into the venture capital fundraising process. In a split second, he backed out. He couldn't morally send another kid into a system he knew was rigged against him: four cycles of dilution, ratchets, protective provisions, career death. Six or seven months of thinking later, he came back with an essay called The Theory of Venture Reciprocity, a new investment instrument called the SAFER, and a firm — Nextwave Partners — built to do venture differently. 

This conversation is for founders who've ever felt like they were just performing instead of truly pitching when talking to a VC. John explains how the industry has shifted from focusing on funding new ideas to prioritizing the size of the fund, what founder-friendly capital really looks like in real life, and where he's placing his bets for the next ten years. If you're raising money, advising, or managing investments with $3 million to $50 million in revenue, this hour will be one of the most honest and helpful you'll have this week. 

What we covered 

1. The structural collapse of venture capital. Why the 2009 shift to fee-driven economics turned VCs into venture banks — and what that did to founders. 
2. The SAFER instrument. John's alternative to the SAFE — re-centering the founder-investor relationship around revenue instead of equity. 
3. Killing the Unicorn cult. Why power-law thinking went from observation to ideology, and how Nextwave applies long-tail economics to startup investing instead. 
4. The machine economy thesis. Why John believes we're at the start of a long arc of innovation on par with electrification, and where the real money will be made. 
5. Geographic alpha and coalition funds. How distributed talent is reshaping where capital should flow — and the fund structure John thinks replaces the traditional GP model. 

Three insights worth sitting with 

• Revenue is the clearest indicator of early progress. If a customer is willing to pay for your product, that message is stronger than any pitch deck — and it aligns the goals of founders and investors instead of creating a zero-sum battle over ownership. 
• The Titans of rail didn't get rich on rail technology. They got rich on the economies that formed around it — towns, real estate, industry. The same logic applies to the machine economy: own the infrastructure, not just the software. 
• The next generation of transformative companies will not come out of Silicon Valley. Underserved regions — Florida, the Nordics, Latin America — are producing technical talent that the traditional VC hubs are structurally incapable of touching. 

Links and resources 

• Next Wave Partners: https://nextwave.partners/ 
• John on LinkedIn: https://www.linkedin.com/in/johncowan1 
• Future Ventures Corp: https://ca.linkedin.com/company/future-ventures-corp 

About the guest 

John Cowan is the General Partner at Nextwave Partners, a venture studio and investment firm focused on the era of autonomy and the machine economy. He's a 25-year founder, CEO, and strategist who has raised millions in venture capital across his career and become one of the more vocal critics of the traditional VC model. He's the author of Venture Capital 2.0: Building, Financing and Scaling Startups in the Post Power Law Era, with a second book on financing the machine economy due out shortly. 

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Sam Hasty, partner at Active Impact Investments — Canada's top climate tech seed fund — has supported early entrepreneurs in energy, logistics, farming, materials, and resilience over eight years. He started as a Memphis math teacher, helped launch a nonprofit accelerator funded by the Steve Jobs family, and studied rural entrepreneurship in Poland with a Fulbright before his first angel investment. 

This conversation is important because the climate tech scene has shifted in two years — Series B funding declined, and generalist investors' interest waned. However, Sam argues the situation is nuanced. Active Impact recently closed a $110M Fund III, their best, with five founders achieving nine-figure exits. The discussion covers how they evaluate founders, why many climate failures aren't tech-related, and where the next decacorns might emerge. 

These are some highlights of the talk: 

• Sam's path from seventh-grade math to venture capital. How a seventh-grade math classroom in Memphis, a Fulbright year in Poland, and writing angel checks alongside the family offices that backed his nonprofit landed him in a partner seat eight years later. 
• The economics of fund sizing. Why Active Impact thinks $110M is the right number — and why most GPs should be asking themselves whether they want to be greedy with carry or with management fees. 
• The 2x2 matrix every founder gets put through. Intelligence and accountability are weighted equally, and the creative questioning techniques that prevent smart founders from gaming the diligence process. 
• The valley of death and the project finance gap. Why the 2021-2022 cohort of climate founders had the wrong skill set — and what RotaTherm's CEO had that most climate founders don't. 

Three insights worth sitting with: 

1. High-intelligence, low-accountability founders are the most dangerous bet a VC can make. They are the most sophisticated at telling diligence teams what they want to hear, which is why Active Impact relies more on reference calls than on direct conversations with the founder — ten references reveal more than ten meetings with the same person. 
2. The CEO's fluency in non-dilutive capital is now a screening criterion at seed. If the founder cannot speak the language of a debt provider, the company will get crushed on dilution at Series B, and that hurts the seed investor more than almost anything else. 
3. The bottleneck on more climate capital flowing in is not technology or revenue speed — it is exit evidence. Investors need to watch peers make exceptional returns before they reallocate, and Fervo's IPO at roughly $7B is the kind of proof point that unlocks the next wave. 

Links 

• Active Impact Investments: https://www.activeimpactinvestments.com/ 
• Sam Hasty on LinkedIn: https://ca.linkedin.com/in/sam-hasty-a7530143 
• Future Ventures: https://ca.linkedin.com/company/future-ventures-corp 

About Sam Hasty 

Sam Hasty is a Partner at Active Impact Investments, Canada's largest climate tech seed fund, where he focuses on infrastructure and carbon solutions innovation. He is a Fulbright Scholar with eight years of venture capital experience and a portfolio spanning energy, logistics, agriculture, advanced materials, and climate resilience. Before venture, he taught seventh-grade math in Memphis and co-founded a nonprofit accelerator backed by major foundations and the Steve Jobs family office. 

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Joyce Shin, founder of The Human Edge and ex-head of design operations at Dropbox, helped scale teams and systems there. Trained in neuroscience and raised across Texas, Ohio, Seoul, and Tokyo, she studied resilience and effectiveness, first after a traumatic brain injury and later professionally in tech. She left Dropbox to ask: in AI everywhere, what makes us human? She created the PEARLS framework—six skills in thinking, creativity, ethics, and leadership—areas AI can't replicate. 

This is her first public sharing of PEARLS. Many see AI as just a tool, not a way to rethink business. For startup founders building better teams, this chapter offers valuable insights. 

What we covered 

1. The PEARLS framework, fully unpacked — Presence, Edge, Authority, Roots, Legacy, and Signal as the six dimensions of human and organizational differentiation in the AI era. 
2. Why leading indicators beat lagging ones — The signals that tell you a team is cognitively decaying before engagement scores and turnover catch up. 
3. What acquisitions actually break inside a scaling company — Lessons from Dropbox on cultural integration, tooling, and the human work most M&A playbooks skip. 
4. The shift from linear careers to horizontal experience — Why disparate cross-functional exposure now beats two-years-and-promote, and what that means for how you design growth paths. 
5. The CEO's job in an AI-native organization — Why senior leaders should stop trying to dictate AI workflows and start building the container their teams operate inside. 

Three insights worth keeping 

• AI commoditizes the average, so the moat moves to what AI can't do. Partnerships, community building, and the communication of vision and story all become more valuable, not less, as automation eats the middle of the skill curve. 
• Resilient organizations are based on their identity, not just their processes. Companies that understand who they are and make steady decisions build trust with customers, employees, and partners—trust that rivals using the same tools can't easily copy. 
• Authenticity outperforms polish. The quirks, imperfections, and real-life mistakes of leadership build more trust than highly produced corporate messaging — and that gap will widen as AI-generated content floods every channel. 

Links 

• The Human Edge: https://humanedge.studio/ 
• Joyce Shin on LinkedIn: https://www.linkedin.com/in/joyceshin 
• Future Ventures: https://ca.linkedin.com/company/future-ventures-corp 

About Joyce Shin 

Joyce Shin is the founder of The Human Edge, an advisory practice that helps founders, CEOs, and organizations build the capacities AI cannot replicate. Before founding The Human Edge, she was head of design operations at Dropbox, where she scaled teams and systems through IPO growth, acquisitions, and the shift to remote work. She holds a degree in neuroscience and brings a uniquely cross-disciplinary lens to leadership, organizational design, and the future of human work. 

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Shahin Nabavian, a computer scientist turned venture builder, has worked across operations, infrastructure, and transformation for the past decade. His experience includes a London-based financial startup, venture-building at Shell's maritime division, work at The Economist Group, and founding edtech startup Super Savvy Education. Now, he leads Team CMV (CentricMind Ventures), focusing on emerging technologies like infrastructure enabling companies to use LLMs effectively. Their main venture, Go-User, applies this to people services. 

The conversation is important because much of what is called' AI adoption' is actually just deployment without ROI. Shahin has observed companies of all sizes misusing chatbots, wasting tokens, and ending up with chaos. He can also explain why this happens in simple language. If your company earns $ 3m-$50 M and you're exploring AI's ROI, this episode is for you. 

Topics Covered 

• Why company culture beats company size in AI adoption. Why The Economist Group made more progress than expected, and why Shell's scale became a hindrance, not an advantage. 
• The real reason AI ROI is missing. It's not the models. It's not the agents. It's the infrastructure layer beneath them — and most companies haven't built it. 
• Every company needs a brain. What Shahin means by "AI brain," why generic RAG implementations fail, and what a librarian-style routing layer actually looks like in practice. 
• The evolving role of the founder and CEO. What AI takes off the executive plate, what stays uniquely human, and why "purple unicorns" — operators fluent in both business and tech — become the default hire. 
• Why Kodak and Blockbuster aren't technology stories. Shahin's view on Board dynamics, shareholder pressure, and the kind of CEO incumbents actually need to bring in to survive a platform shift. 

Key Insights 

1. The bottleneck isn't intelligence — it's plumbing. The models and tools are well-developed, but most organizations still need a way to understand how their business actually operates. This way, the AI can direct questions to the right source instead of randomly searching through every connected system. 
2. Engineering-led AI initiatives consistently underdeliver. Starting a transformation by focusing on tools instead of clear service goals can cause a lot of manual work, higher costs, and confusion for users. It's better to start by understanding what the business wants to achieve and then plan the system around that. 
3. Transformation is a challenge for the Board before it becomes a tech issue. Most CEOs don’t stumble because the technology is too complex; instead, they often face pressure from shareholders demanding faster results than are realistically achievable. To help overcome these hurdles, companies might consider bringing in a CEO from outside the industry, pairing them with a COO who understands the current business well, and giving them the freedom to learn from mistakes along the way. 

Links 

• Shahin Nabavian on LinkedIn: https://www.linkedin.com/in/nabavian/ 
• Future Ventures: https://ca.linkedin.com/company/future-ventures-corp 
• Future Ventures Forum: futureventures.ca/community 

About the Guest 

Shahin Nabavian is the Founder of Go-User and a co-founder of Team CMV (CentricMind Ventures), where he builds AI-native systems for fast-growing companies. He holds a PhD in computer science and has spent over a decade building and supporting ventures across financial services, energy, publishing, and education — including work with Shell and The Economist Group. His current focus is on the infrastructure layer that turns organizational data into something AI can actually reason over. 

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Dr. Sylvain Charlebois, the "Food Professor," is the Senior Director of Dalhousie’s Agri-Food Analytics Lab, lead author of Canada's Food Price Report, and a prominent researcher in food supply chain management. He’s the go-to expert for food inflation stories and provides data that guides grocery executives. With 20 years studying Canada's rising food costs, he argues that debates wrongly blame big corporations or stores, overlooking factors like trade barriers, slow regulations, retail crime, and recycling policies that lack proper cost analysis. Sylvain’s data helps differentiate between factors influencing prices and those making headlines, offering valuable insights for food producers, agtech investors, and sector analysts to better interpret news. 

Topics Covered 

1. Grocery theft as a $10 billion problem — The rise of organized retail crime, the urban food deserts it creates, and who ultimately pays. 
2. Why Canadian food companies sell in the US, not Canada — How weeks-versus-months approval timelines are quietly redirecting capital and product south. 
3. Canada's branding problem — "Boston lobster from Canada" and why a country with great products can't seem to build great food brands. 
4. AI in the food system — Where it's already working (precision agriculture, soil science, animal feed), where it's lagging (manufacturing), and where it gets ethically uncomfortable (surveillance pricing for households). 

Key Insights 

• Bad policy is the blind spot nobody can see. Interprovincial trade barriers, industrial carbon pricing, and recycling laws all add real cost to running a food business — but because consumers can't point at them on a shelf, the political will to fix them never materializes. 
• The story of grocers versus consumers overlooks how the real incentives work. When cheaper options like GMO products or newly-made dairy substitutes appear on store shelves, stores with thin profit margins—around 2-3%—don't usually lower prices for shoppers. Instead, they often choose to increase their profit on familiar products. Until labeling requirements and competition rules change, having cheaper ingredients won't necessarily lead to lower grocery prices. 
• Greenfield innovation moves faster than retrofitting. Canada's food manufacturing industry is slow to adopt AI and automation because it's weighed down by old habits and investments in outdated equipment. The best way to move forward is to build new facilities, ideally working with universities, so there's no old baggage holding things back. 

Links 

• 📺 Watch the episode on YouTube: https://youtu.be/vLM1QKjrE40 
• 📊 Agri-Food Analytics Lab at Dalhousie: https://www.dal.ca/sites/agri-food.html 
• 🎧 The Food Professor Podcast: https://the-food-professor.simplecast.com/ 
• 🔗 Connect with Sylvain on LinkedIn: https://www.linkedin.com/in/thefoodprofessor/ 
• 🔗 Connect with Maxim on LinkedIn:  https://www.linkedin.com/in/maxim-atanassov 

About Dr. Sylvain Charlebois 

Dr. Sylvain Charlebois is a professor and Senior Director of the Agri-Food Analytics Lab at Dalhousie University, where he leads research on food supply chains, consumer behavior, and food economics. He is the lead author of Canada's Food Price Report, co-host of The Food Professor podcast, and one of the most-cited researchers globally in food supply chain management and traceability. His work bridges academia, industry, and policy — making him a go-to voice on the forces shaping the future of food, grocery, retail, restaurants, and agriculture.

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Tim Fung, Founder and CEO of Airtasker, leads one of the world's top local services marketplaces. Since launching in Sydney in 2012, it’s now a publicly listed company operating across Australia, the UK, and the US, facilitating over a billion dollars in jobs for flexible income. Tim is a prominent voice on the future of work and the gig economy. He experienced what most founders only theorize: raising $1.5M in 2012 when "startup" wasn't common in Sydney, and navigating many trials before success. He took Airtasker public and now, as a CEO, admits the company has fewer employees than four years ago, despite revenue growing five to six times. His insights are very relevant, especially for those building marketplaces, navigating IPOs, or integrating AI into non-software businesses. 

Key Topics Covered 

1. The origin story — How a friend with a truck and an apartment moved in 2012 turned into a marketplace that has now processed over a billion dollars in job opportunities. 
2. Solving the supply side first — Why Tim made the supply experience 10x better than Angie's, Thumbtack, and TaskRabbit, and how that one decision shaped everything that followed. 
3. Trust, payments, and the $20 fee — The escrow innovation that unlocked Series B, plus the small cancellation fee that cut cancellations by around 40%. 
4. Building rails, not blueprints — Why marketplace founders should stop trying to design every use case and start watching what users actually do — including the German bundtlet costume request. 
5. AI as enabler, not replacement — Tim's measured take on AI, the rise of the 10x employee, and why he thinks incentivizing token consumption is doing it backwards. 

Key Insights 

• The product is the network, not the app. A marketplace app with no users on it is genuinely useless. Liquidity comes first. Everything else — features, design, polish — only matters once the network exists. 
• Accountability needs both rewards and punishment. Most platforms only reward good behavior, and that's why they break. Free returns, no-cost cancellations, and frictionless agentic commerce all suffer from the same flaw: when there's no cost to bad behavior, the system fails. Tim's analogy — speed limits without fines change nothing. 
• AI's biggest impact on a non-software business is software velocity. Airtasker doesn't sell software, but it builds a lot of software to run the marketplace. AI has made that build cycle dramatically faster — which matters more than chasing AI features for their own sake. 

Links 

• Airtasker: https://www.airtasker.com/ 
• Tim Fung on LinkedIn: https://au.linkedin.com/in/timjfung 
• Future Ventures: https://ca.linkedin.com/company/future-ventures-corp 

About Tim Fung 

Tim is the Founder and CEO of Airtasker. He started the company in Sydney in 2012 with his co-founder Jono Lui, after the two of them caught the startup bug while working on the founding team at Amaysim, a mobile SIM card business. The idea came from something pretty ordinary — Tim asked a friend with a truck to help him move apartments, and started wondering why people defaulted to friends and family for that kind of work when there were so many people out there who actually wanted to earn income. 

More than a decade later, Airtasker is publicly listed, operating across Australia, the UK, and the US, and has facilitated over a billion dollars in job opportunities. Tim is one of the more grounded voices on marketplaces, the gig economy, and the future of work — partly because he's been at it long enough to be skeptical of easy answers. 

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Mike Feinman is the Managing Partner at Texas Business Brokers, a top M&A advisory firm for the lower mid-market and main street. His career began at PepsiCo's Taco Bell division and includes leadership at Yum! Brands across 16 countries. He has facilitated millions in sales across manufacturing, restaurants, services, and tech. He entered brokerage unexpectedly—an ex-Pizza Hut colleague asked him at Starbucks in 2014 what he'd do with the four and a half days a week he wouldn't be running his three restaurants. Mike works where founder vision meets buyer reality, often telling founders the truth before the market does. Many overestimate their business’s value and transferability. His role is to narrow that gap years before a sale. If you're 3-5 years from an exit or building without planning for one, this episode is essential before your accountant. 

Four Key Topics Covered 

1. The Origin Story Behind Texas Business Brokers — How a chance Pizza Hut connection, a mentor lost to mesothelioma, and a passed torch turned into a multi-state M&A advisory practice. 
2. The Current State of the M&A Market — Why we are in a buyer's market, why sellers are holding back, and how tariffs, energy costs, and onshoring are quietly reshaping multiples by industry. 
3. The Strategic Planning Framework Every Founder Should Run — Mike's full process from SWOT through five-year SMART vision, reverse success planning, one-year milestones, and the enabling culture that wraps it all together. 
4. The Three Risks Every Acquirer Underwrites — Key person risk, customer concentration risk, and the absence of scalable, repeatable systems — plus the "develegating" approach Mike used to get one founder out of the weeds before a $20M sale. 

Three Key Insights 

• Founders find time to do things over far more often than they find time to do them right the first time. A failed business is almost always failed planning — eyes wide shut instead of eyes wide open. The discipline to step back, run the SWOT, and build the vision is the discipline that protects valuation years later. 
• Potential, in Mike's words, is just something that ain't been done yet. And the moment a founder starts negotiating on what the business could be instead of what it actually is, the back goes against the wall. Buyers don't pay for the story. They pay for what's already on the page. A premium on outlook only shows up when the engine underneath it is already running — and even then, the buyer is doing the math on what they can do with it, not what you say they can. 
• A deal is a piece of clay that gets shaped, broken, and reshaped multiple times before close. Buyers and sellers sing Kumbaya, fall apart at the LOI, fall apart again at due diligence, and need to be brought back together at every stage. The job of a real M&A advisor is keeping every stakeholder on the same island long enough for the deal to actually happen. 

Links 

• Mike Feinman on LinkedIn: https://www.linkedin.com/in/mikefeinman/ 
• Texas Business Brokers: https://texasbusinessbrokers.com/ 
• Connect with Maxim Atanassov: https://ca.linkedin.com/in/maxim-atanassov 

Guest Bio 

Mike Feinman is the Managing Partner at Texas Business Brokers, advising on lower-mid-market and Main Street deals across multiple states and industries. Previously, he held senior roles at PepsiCo and Yum! Brands, led restaurant operations, and built training and service organizations in 16 countries. He is a father of three, grandfather of four, active musician, and loves helping founders turn their businesses into their dreams. 

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Sarah Romanko, an investor at Geek Ventures, backs immigrant-founded AI and robotics startups. She entered venture without traditional credentials, relying on persistence like cold outreach, online events, and paying it forward. Her approach shapes how she evaluates and supports founders. This conversation reveals how an early-stage investor thinks—what prompts a "yes" or "no"—and how founders misprice opportunities. She questions the media narrative around fundraising, explains why some founders shouldn't raise venture capital, and discusses AI's new moat. 

For founders considering fundraising or rethinking it, this episode offers a tactical, straightforward guide from someone who reviews pitch decks daily and invests early. 

Topics Covered 

• Breaking into venture without the traditional background. Sarah talks through how she got in: cold outbound, online events at 10 pm her time, and showing up consistently when nobody was paying attention yet. 
• The Geek Ventures thesis — Why the firm backs immigrant founders building AI and robotics companies at pre-seed and seed, and how being hands-on at a small fund changes what value looks like. 
• The three things that win deals at pre-seed — Founder-market fit, founders who know how to sell, and a credible "why now" that grounds vision in the present. 
• When founders should not raise venture capital — The wrong reasons people chase a round, why a fundraise does not equal success, and how taking the wrong money can quietly kill a company. 
• Cold outreach, follow-ups, and the new moat — What makes an inbound message memorable, why Sarah responds to cold emails without warm intros, and why the go-to-market moat now matters as much as technical differentiation. 

Key Insights 

1. Time-to-value is the operating principle of a VC relationship. Founders who build durable investor relationships deliver value first — an introduction, an event assist, a useful insight — before they ever ask for a check. Reverse that order, and the conversation is already on the back foot. 
2. The biggest mispricing in early-stage fundraising is not valuation — it is misunderstanding the LP model. Founders price rounds against market comps without considering whether the math actually works for the fund. A round that is too high for the underlying business not only creates future down-round risk; it also removes investors from the table before the conversation even begins. 
3. The new moat in the AI era is go-to-market, not just technology. Technical defensibility still matters, but with AI lowering the cost to build, the durable edge is increasingly trust, distribution, and the ability to win and retain customers. Founders who can articulate a fact-based, evidence-backed differentiation — not opinion-based positioning — stand out immediately. 

Connect with Sarah 

• LinkedIn: https://www.linkedin.com/in/sarahromanko/ 
• Pitch Geek Ventures: geek.vc/pitch 
• Geek Ventures website: https://geek.vc/ 

About the Guest 

Sarah Romanko invests at Geek Ventures, focused on pre-seed and seed AI and robotics companies founded by immigrants to the US. Her path into venture was unusual — no traditional banking or consulting background — and she credits sheer persistence, cold outbound, and a habit of paying it forward for getting her in the door. She speaks regularly at industry events, mentors founders through programs like Startup Grind and Founder Institute, and writes openly about democratizing access to capital.

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Nikola Borisov is CEO and co-founder of DeepInfra, offering open-source models like DeepSeek, Llama, Kimi, GLM, and GPT-OSS via APIs. He previously scaled IMO Messenger to over 200 million users, handling up to a million new users daily with cheaper self-built infrastructure. A Northwestern CS grad and Bulgarian programming veteran, he learned that distributed systems succeed at the margins. This conversation is crucial because AI inference—execution—is the silent battleground of the AI economy, yet few discuss the compute layer, which now limits access outside big labs. Nikola applies his hyperscale infrastructure knowledge to compute-intensive workloads. For those in AI, understanding this layer is vital. 

Topics Covered 

• From Sofia to scale — How Nikola progressed from Bulgarian programming contests to scaling IMO Messenger's backend to 200M+ monthly users, teaching him about doing more with less. 
• Why the bet is on open source — The strategic and structural case for hosting open-source models, why a startup like DeepInfra had no realistic alternative, and why the US has an open-source gap worth worrying about 
• The supply crunch nobody is pricing in — Demand for AI compute has roughly 4x'd in the last four months, driven mostly by coding agents finally crossing the line from "useful sometimes" to "useful always." Nikola explains why this is a GPU shortage now, not a demand problem. 
• How Nikola actually thinks about optimization — Cache token pricing is the key cost lever most teams overlook, especially on agentic workloads. We discuss why inference hardware is diverging from training hardware and Nikola's habit of the build-then-measure loop since IMO days. 

Key Insights 

1. AI's bottleneck is supply, not demand. Coding agents alone — Claude Code, Cursor, the rest — have driven token usage up roughly 4x in the last four months. There aren't enough GPUs to go around, and the big labs are eating most of the available capacity. Smaller buyers are getting priced out of the market entirely. 
2. Cache token pricing is the cost lever most teams overlook. Agentic workflows reuse massive amounts of context across tool-calling loops. Pricing — and architecting around — cached tokens separately is what separates teams that can afford to scale agents from those that can't. 
3. Open source vs. closed source won't end 100-to-zero. Nikola thinks we land at roughly 80/20 — the question is just which side gets the 80. His reasoning: information leaks, engineers move between labs, and the Anthropic GitHub commit that exposed model details earlier this year is exactly the kind of thing that's going to keep happening. You can't really isolate a model from the outside world for long.  

Links 

• DeepInfra: https://deepinfra.com/ 
• Nikola Borisov on LinkedIn: https://www.linkedin.com/in/nikola-borisov 
• Future Ventures Corp: https://ca.linkedin.com/company/future-ventures-corp 
• Maxim Atanassov on LinkedIn: https://ca.linkedin.com/in/maxim-atanassov 

About the Guest 

Nikola Borisov is the CEO and co-founder of DeepInfra, an inference-only AI cloud that hosts open-source models like DeepSeek, Llama, and GPT-OSS for developers and enterprises. Before DeepInfra, he led backend infrastructure at IMO Messenger, scaling the platform past 200 million monthly users on infrastructure his team built and ran themselves — at a fraction of what comparable cloud-native competitors were spending. He's a computer science graduate of Northwestern University with over a decade of experience building distributed systems at scale. 

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Grant Blaisdell, CEO of Copernic Space, is developing space's financial infrastructure by tokenizing payloads, satellite data, computing, and lunar rights, turning space into a liquid market. A serial entrepreneur and blockchain pioneer, he cofounded Coinfirm, the first AML platform for crypto, and created the first AML solution for ERC tokens during the ICO era. His grandfather, a space pioneer, helped Poland reach space. The space economy exceeds $600 billion, mostly driven by private activity, yet many lack understanding of how value is created. 

Maxim and Grant discuss building standards, marketplaces, and liquidity for this future asset class. If space seemed outside your reach, this episode offers a reset. 

Key Topics Covered

1. The blockchain-meets-space thesis — Why this is the first asset class that can be built on-chain from day one, without decades of legacy infrastructure to overcome. 
2. Who actually owns space — The emerging standards for verified ownership of orbital assets, lunar infrastructure, and mining rights, and why the US-China dynamic is reshaping the race. 
3. Tokenization and fractional ownership in practice — How Copernic Space tokenizes payload capacity, external "billboard" surfaces, satellite data, and compute, with real examples from Moon Mission One and a top-10 European rocket company. 
4. The Copernic business model — Smart contract-embedded transaction fees, strategic acquisitions and fractionalization, and the future SAI ("Space Asset Intelligence") layer — an AI-powered Bloomberg terminal for space. 
5. The hidden Musk strategy — Why SpaceX, xAI, Tesla, and Boring Company aren't separate bets — they're components of a fully integrated space stack. 

Three Key Insights 

• Space isn't an escape — it's an upgrade for Earth. The most valuable applications aren't lunar colonies or Mars cities; they're pharmaceuticals, energy, data, compute, and agriculture (think satellite imagery for wildfire prevention) that solve problems on this planet. 
• Standards beat speed. Whoever defines what "verified ownership" means for space assets — payloads, data, compute, lunar rights — captures the long-term value, just as the Dutch East India Company captured the first era of exploration. 
• The private market is already leading regulators. The US still hasn't fully clarified the securities treatment of tokenized real-world assets. Still, private players are setting de facto standards that governments will eventually have to ratify, not the other way around. 

Links

• Copernic Space: https://www.copernicspace.com/ 
• Grant Blaisdell on LinkedIn: https://www.linkedin.com/in/grantblaisdell 
• Future Ventures: https://www.linkedin.com/company/future-ventures-corp/  

About the Guest 

Grant Blaisdell is the Co-founder and CEO of Copernic Space, building the financial infrastructure and marketplace for the space economy. Previously, he cofounded Coinfirm, a leading analytics and compliance platform that pioneered AML for crypto and was the first to enable AML for ICO-era ERC tokens. A third-generation space entrepreneur and blockchain pioneer, Grant operates at the intersection of capital markets, digital assets, and one of the largest emerging asset classes of this century.