A few things I will be carrying with me from the dinner:

1/ On knowing when you’re wrong. Higgsfield burned $10M of a $16M seed on consumer before Alex admitted AI doesn’t fix consumer retention. The courage to change course when you’ve already spent the money is rare. He did it.

2/ On picking your hero. Instead of chasing OpenAI, he studied Canva — 20M paying users, $4B ARR, built quietly out of Australia. That choice of role model says a lot. Not every great company looks like the ones on the magazine covers.

3/ On staying close to the work. Alex still knows which model releases shipped this week and what his customers are paying. When the company has grown so fast, you cannot step away. He isn’t. That proximity is the company.

4/ On what actually wins. Six releases a week. Cash-flow breakeven. No marketing budget. “We had to believe the best product wins.” Not the biggest raise. The best product.

5/ On speed as a tool. The way Alex described it, speed wasn’t the strategy. It was the byproduct of a small, deeply aligned team that knew exactly what it was building and why. Velocity as a function of clarity, not chaos.

What stayed with me wasn’t a tactic. It was Alex himself. The clarity he brought to every question, about the wins, the missteps, the parts of the journey most founders dress up, was the most inspiring thing in the room.

Thank you, Alex. And thank you to everyone who came.

A separate thank you to Alma for sponsoring the dinner and to the Central Asian Innovation Hub for providing us the space to make this happen.

The bottleneck in enterprise AI is organizational, not technical: Enterprise buyers are defensive, uninformed, and incentivized to avoid risk rather than adopt tools. This creates structurally slow adoption regardless of how good the technology becomes.

If thinking becomes a commodity, the next bottleneck shifts to the real world: When intelligence and software get cheap, the constraint moves to physical experimentation and infrastructure. AI can’t commoditize the physical world because it requires real-world feedback loops.

First-principles thinking matters more than a polished pitch: When VCs ask about moats or competitors, they’re testing how deeply founders think, not what they answer. Oftentimes, the best response to “Why can’t Google do this?” is “They can.”

The best founders are defensive of their equity: They ask “Why do I need this money?” before “Should I take it?” Raising only makes sense when there are specific offensive levers to pull. Otherwise, founders dilute themselves for optionality.

Deedy, thank you for your thoughtful insights and exciting stories!

Thank you to Silkroad Innovation Hub and Alma for supporting the event.

Chris Larsen, co-founder and Executive Chairman of Ripple, has spent over 30 years building at the frontier of fintech - E-Loan, Prosper, Ripple. Each time, he built where banks didn't want him to exist. Each time, he felt that fear.

When I worked in fintech, we were constantly looking at Ripple. They were the market. Last week, I got to sit down with Chris for dinner with Icons. What I wanted to understand: how do you keep building for three decades when the system is designed to stop you?

A few insights from our conversation:
1. That fear never goes away, and sometimes it's right to be scared.
All three companies terrified him. But he's also been fired, nearly went bankrupt, and spent eight years at Prosper when he should have walked away after two. That "yeah" feeling doesn't mean you won't fail. It just means you're willing to find out.

2. Don't hang on too long.
Chris spent eight years at Prosper. His biggest regret isn't that it didn't work, it's that he didn't walk away sooner.

"Try to fail sooner, don't hang on too long. This is a very short life. You don't have any time to waste."

VCs can always recapitalize a company. You can't recapitalize your time. This one hit harder as we continue to navigate the fast-changing world.

3. Self-awareness matters as much as capability.
After four years as Ripple's CEO, Chris brought in Brad Garlinghouse. That was 11 years ago. The boundaries are ruthlessly clear: any email Chris sends to Ripple employees copies Brad. Nobody can come to him and undo Brad's decisions.

"The CEO has to be seen as the person making decisions."

Knowing what he's good at gave Chris his life back. He's 65, still building, but now he has time for what matters. He swims. He works on climate. He spends time with his kids.

He's good at chaos. Brad's good at scaling. That partnership works because the boundaries are clear.

4. Culture requires relentless repetition.
"Talk about your core values all the time, until you are blue in the face. You think people can't possibly want to hear this again. Nope, they want to hear it all the time."

Chris and Brad talk about core values in every meeting. They do celebrations. People get jackets with the values on them. It sounds corny, but the discipline is rare.

All three of Chris's companies were built where banks didn't want him to exist. The pattern: find where the system is broken, build the alternative, fight the incumbents.

Success wasn't just about the technology or the strategy. It was about having the conviction to build where everyone said you couldn’t.

Thank you to Chris for the time and the honesty he shared with us. Thank you to everyone who joined us.

Democratization of education

Technology has a long track record of democratizing access, and today’s LLM capabilities can provide students with something that used to be scarce: a personalized tutor and an individualized on-demand curriculum. That can widen opportunities by making education cheaper and more broadly accessible. At the same time, classes and universities still matter because they still serve an important social role as places where people meet and learn together.

Contrarian approach to Lean Startup for deep-tech companies

For deep-tech startups, shipping early can backfire: users cannot validate what is not technically viable yet. They will ask for better “horses,” not a car. Until the technology can deliver a real end-to-end experience (as with Waymo), early releases risk non-adoption and misrepresent the true potential.

Obsession with a problem

One of the most frequent mistakes founders make is giving up too early. Sometimes they are actually working on a meaningful problem, but after a few attempts they quit because their initial solution does not work. A better approach is to be obsessed with the problem, not a specific solution or technology. That mindset keeps you adapting, and staying focused on what you are ultimately trying to solve.

No shortage of inventions

Most of the technologies we rely on in our daily lives were invented within the last 150 years, which is a reminder of how early we still are relative to the age of humanity. The vast majority of useful inventions are still ahead of us, so there is no shortage of meaningful things left to build.

We are grateful to Sebastian for taking the time and providing valuable learnings with the Icons community!

Thanks to Silkroad Innovation Hub and CMT Digital for supporting the event.

Here are a few insights from the dinner:

1. Stablecoins are becoming a new form of money.
Stablecoins are no longer a niche crypto instrument. They are becoming embedded in the global financial system as programmable, internet-native money. Visa’s role is not to displace banks, but to act as connective tissue between banks, PSPs, and new on-chain payment rails.

2. Stablecoins are additive to Visa’s business, not disruptive.
Rather than cannibalizing card networks, stablecoins expand Visa’s surface area. They unlock new revenue opportunities in cross-border settlement, treasury management, and B2B payments where instant finality, lower costs, and 24/7 availability matter more than interchange economics.

3. PSP → merchant settlement in stablecoins will scale by orders of magnitude.
Merchant settlement in stablecoins is still early, but the direction is clear. Stablecoins offer faster settlement, fewer intermediaries, improved liquidity control, and global reach without correspondent banking friction. Once merchants experience this, it becomes hard to go back.

4. Crypto cards are early and will scale 100x.
Crypto cards today are where cards themselves once were: functional but underdeveloped. This is one of the few categories where startups can launch globally from day one, onboard users across geographies instantly, and compete with banks on speed, UX, and programmability.

5. Privacy is one of the biggest unsolved problems in crypto payments.
Privacy is not a “nice to have.” It is a prerequisite for enterprise and merchant adoption. Multiple models are emerging: on-chain privacy, off-chain abstraction, selective disclosure, and ZK-based approaches. Which architecture wins is still an open question, but some form of privacy must exist.

6. Banks adopting stablecoins will benefit long-term.
Bank resistance to stablecoins is softening. Allowing customers to instantly deposit stablecoins and use them for spending or transfers is low-hanging fruit. Over time, stablecoins strengthen banks’ product offerings rather than weakening them.

7. On-chain credit and programmable loans are a massive upcoming market.
Fully on-chain credit, programmable lending, and stablecoin-based financial strategies are poised to scale significantly. Every major bank will need a coherent stablecoin and on-chain strategy.

8. The “vibe-coding” market is real and accelerating.
The cost of building financial products is collapsing. AI-assisted development enables many more builders to ship wallets, payments, and settlement products faster than incumbents can respond.
Crypto retains defensibility today due to audits and the high cost of mistakes, but tooling will continue to close the gap.

9. Agentic commerce will shift from speculation to utility in 2026.
In 2025, protocols like x402 saw ~95% of volume tied to memecoins. Cuy expects that in 2026, this changes. Wallets will act as universal API keys, enabling pay-per-use access to tools inside agentic IDEs. He expects major tech companies to deploy an x402 server and push agentic commerce into real-world use.

Hans has been on the Forbes Midas List 13 times and has backed generational companies including Airbnb, ByteDance, Affirm, Coinbase, Slack, Quince, and Anthropic. Two decades of investing across the US and Asia gives him a global lens that’s rare — and it showed throughout the conversation.

Here are the ideas that stayed with me:

The biggest outcomes tend to follow a few repeatable patterns

Hans described three “shapes” that show up again and again in category-defining companies:

1) They democratize access.
The biggest companies don’t just build something new — they expand the pie. They help people earn more, save more, or buy more for less by making something previously expensive, complex, or exclusive suddenly accessible at scale.

2) They’re built with cross-border advantage from day one.
The best founders don’t treat “global” as a later-stage expansion plan. They architect for it early: talent, distribution, supply chain, go-to-market — and they compound faster because they’re playing on a bigger surface area from the start.

3) In AI, developers come first.
Models improve because millions of developers are constantly poking them with real-world requests. The feedback loop isn’t theoretical — it’s production traffic. Developers are the growth engine of model intelligence.

The future of VC: barbell or bust

Hans was straightforward: venture is splitting into two camps.

• Mega-funds that can write billion-dollar checks and need truly massive outcomes to move the needle.

• A long tail of small, sharp funds built by operators from this AI wave — people with real product and distribution instincts.

Everyone in the middle will feel the squeeze.

One line that landed: if your fund is many billions, to deliver top-tier returns you basically need at least one “Anthropic-level” win in every fund.

Why some Chinese founders build more enduring companies

Hans pointed to two forces that create relentless intensity:

• Culture and work ethic (the 9-9-6 reality) creates speed, iteration, and stamina.

• Early secondary liquidity is rare, so founders stay hungry longer.

In the US, early liquidity can be a double-edged sword: it can reduce urgency to build something truly enduring.

His advice: treat liquidity as a milestone — not the finish line.

Vertical AI can now create $10B–$20B outcomes

Hans believes vertical AI products can now reach outcomes that were almost impossible before.

But the biggest winners will blend vertical depth (workflows, distribution, and real customer outcomes) with horizontal potential that lets them generalize into adjacent industries over time.

Hardware: it’s not subsidies, it’s culture

Asia’s advantage in hardware isn’t mainly subsidies — it’s culture, iteration speed, and problem-solving directly on the production line.

In the US, he’s most excited about hardware where Asia isn’t an option — especially defense.

AI apps vs models: where compounding value sits

Models get better every day because developers keep pushing them with real usage. Apps on top can be valuable — but the compounding value tends to sit in the model layer.

So if you’re building applications, the moat has to be real: go deep enough in workflow complexity, proprietary data, distribution, or measurable outcomes that a base model can’t easily replicate what you do.

Hosting Hans was a reminder of how powerful it is to learn from people who’ve built conviction through cycles — and across continents.

Thank you to everyone in the Icons community who joined, and a special thank you to Hans for sharing so openly.

Healthcare as enhancement, not just treatment

Peters challenges the fundamental definition of what healthcare should be. In the traditional paradigm, healthcare is a tool to get you from “sick to non-sick, or negative one to zero.” But Peters believes healthcare should be a tool to get you from “zero to 10”—to help you achieve enhanced vitality beyond your baseline. His insight is that the human brain is remarkably good at acclimating to its baseline state. Most people think they feel fine until they make meaningful changes to their mitochondrial capacity, gut health, or nutrient balance and suddenly realize how much better they can feel. It’s like being in a toxic relationship or a job you hate—you don’t realize how much it’s affecting you until you’re out of it. This reframing positions health optimization not as vanity, but as unlocking human potential that most people don’t even know they’re missing.

Disintermediate the system to get to physics-based pricing

Peters identifies a fundamental problem in healthcare economics: services are priced at “the laws of incentives” rather than “the laws of physics.” A vitamin D test might cost $300 through a hospital system, while Superpower charges $10 for the same test. The difference isn’t the actual cost—it’s the layers of complexity, bureaucracy, and middlemen embedded in insurance contracts. Peters draws a parallel to Mark Cuban’s Cost Plus Drugs, which revealed that a drug costing $1,000 through insurance only costs $7 to manufacture. By building a direct-to-consumer model outside traditional healthcare systems, Superpower can price at manufacturing cost plus a small markup. It’s the same strategy Coinbase used in financial services—rebuild the entire system from the ground up to eliminate rent-seeking intermediaries.

The clinical model is the IP, not the technology

When asked about competition from wearables companies like Oura and Whoop, or tech giants like OpenAI, Peters made a critical distinction: the intellectual property in healthcare isn’t the technology—it’s the clinical model. Why would someone go to a renowned clinic over their local hospital for a serious diagnosis? It’s not just brand recognition. It’s the accumulated protocols, best practices, and decision-making frameworks embedded in how Mayo Clinic doctors approach patient care. Peters argues that ChatGPT and other general AI models lack this clinical expertise. Wearable companies have proprietary data streams but no care delivery model. Superpower’s bet is that having an opinionated clinical model from day one—actually delivering healthcare, not just data—will be the sustainable competitive advantage as the market consolidates toward one or two dominant players.

The market will consolidate to two major players

Peters predicts the AI doctor market will follow the pattern of most venture-funded categories: it will consolidate to two major players who capture the lion’s share. Think Uber and Lyft, Ancestry.com and 23andMe, Apple Music and Spotify. While there may be room for a winning super app that does many things moderately well like chatGPT, there will also always be room for vertical players like Superpower where one thing is all they do and they do it better. Peters isn’t worried about OpenAI entering the space because Superpower’s entire brand identity is frontier medicine—that’s all they’ve stood for since day one. The name itself communicates the value proposition: you should feel super-powered, like Iron Man, with the energy and vitality that comes from optimized health. This singular focus, combined with their clinical model and early market position, positions them to be one of the few winners when the market matures.

Build culture around the mission

Their foremost cultural principle is “super-prioritize health”—put your health first as the foundation for everything. Their second principle is “mission obsession,” which they screen for aggressively in hiring. Three teammates have Superpower tattoos. Peters reflects on his own evolution across three companies, distinguishing between “clean fuel versus dirty fuel” or “motorboat versus sailboat.” Superpower runs on passion and love for the mission. When people genuinely care about the problem they’re solving, putting in long hours doesn’t feel like work—it feels like contributing to something greater than yourself and sailing effortlessly.

Every decision is a health decision, including your career

Peters offers a provocative framework for thinking about health: treat every decision as a health decision, because everything you do is either positively or negatively impacting your epigenome. Even being in a room with certain people for 15 minutes can change your nervous system and epigenetic expression. A team and culture can create epigenetic convergence and nervous system coherence. The thought exercise: if we had a quantum computer that could model every particle in the universe, we could perfectly predict everyone’s health trajectory. If that’s true, then every decision—what you eat, where you work, who you spend time with—is genuinely a health decision. Peters takes this further with a generational perspective: the epigenetic damage you accumulate will directly affect your future offspring, and their offspring, and their offspring. The health decisions we make today have repercussions for an infinite number of generations. This isn’t guilt—it’s recognizing the profound responsibility and agency we have over not just our own wellbeing, but the biological inheritance of all humans who will ever live from our lineage.

Conclusion

Peters’ journey from nearly losing his life to building Superpower illustrates a founder archetype increasingly common in healthcare: the patient-turned-entrepreneur who experienced the system’s failures firsthand and decided to fix it. His approach combines Silicon Valley’s playbook for category creation with a genuine mission to democratize access to frontier medicine. Whether measuring success by the number of Americans subscribed to Superpower or by clinical outcomes like his parents discovering early-stage conditions that would have become cancer, Peters has built something that transcends typical startup metrics.

The most striking aspect of Peters’ vision isn’t the technology or business model—it’s the philosophical reframing of what healthcare should be. By positioning health as a tool for human enhancement rather than just disease treatment, and by arguing that every decision we make carries both personal and generational health consequences, he’s not just building a company. He’s advocating for a fundamental shift in how we think about our bodies, our choices, and our responsibility to future generations.

A note of thanks

We’re grateful to Jacob Peters for sharing his time, insights, and personal health journey with Stanford students and alumni. His willingness to discuss both the strategic vision and intimate details of his own health challenges provides invaluable perspective for the next generation of healthcare entrepreneurs. Thank you, Jacob, for your candor and for the important work you’re doing to reimagine healthcare for all Americans.

These insights emerged from a dinner conversation between Jacob Peters and Stanford students & alumni in December 2025.

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Last week, we had a chance to host Max Hodak, founder of Science and Co-Founder of Neuralink. It was one of the most phenomenal conversations we’ve had at Icons, covering topics ranging from what is the future of brain-computer interfaces to learnings that Max had after co-founding company with Elon Musk.

Here are a few insights from the conversation:

• Max starts from a blunt premise: the current human condition is mediocre, and the whole point of brain–computer interfaces are not only to treat pathology, but to reengineer the human experience.

• He sees the next 10 years as a phase transition: with AI and BCIs compounding at today’s pace, our world will end up either absolutely beautiful or absolutely crazy, but definitely not a slightly different version of 2025.

• Max frames AI and BCIs as two distinct technological quests. If the end goal of artificial intelligence is superintelligence, the end goal of the BCI quest is a conscious machine. Classical BCIs are about reading and writing information to and from the brain—extracting motor representations to control a cursor or keyboard, or writing sensory information to restore vision, hearing, or proprioception. But he believes a non-classical form of BCI is on the horizon. Instead of reading or writing information, these systems would enable phenomenal binding over a network. That would be a fundamentally different kind of technology, and if it works, it wouldn’t just improve human capabilities – it would qualitatively transform the human condition.

• Reasoning is, in his view, the most important capability humans brains have — and widespread LLM use quietly erodes it, which is why he actively restricts LLMs at work and pushes people to keep doing hard, first-principles thinking themselves.

• Max co-founded Neuralink with Elon and speaks very highly of his management skills: when you put extreme urgency at the center of decision making among people with the highest level of critical thinking - impossible things become possible.

• One of the big observations that Max had is that the statement of risk is overrated. People can take way higher risks but they don’t have enough agency to think clearly about such risks. He shares the example of Silicon Valley founders - almost everyone can raise money and then if things don’t work - join a big tech firm. No risk is involved.

• Max describes a biohybrid approach to BCIs built from stem-cell–derived biological neurons. Instead of placing mechanical or electrical devices into the brain, the idea is to embed engineered neurons into a device and engraft it onto the brain’s surface. The question is whether those cells would grow in and form functional connections – and the answer is yes. Even a tiny graft, on the order of four millimeters by four millimeters, can integrate extensively. Because cells are small, such a device can contain on the order of a million neurons, forming billions of synapses. Max sees this as a genuinely new kind of system, and possibly the first plausible path to a whole-brain – or interhemispheric-bandwidth – neural interface.

• Consciousness is independent from intelligence. LLMs have intelligence but don’t have consciousness. Conversely, non-intelligent objects might have consciousness. One of the problems with consciousness is defining it, we all know it exists, but it always has a broad definition.

• Causing visual hallucinations via video is possible but the implications are very limited.

• During interviews, the most important quality that Max checks is agency. Agency in making all the decisions people made to get where they are or they just followed the flow?

• Max’s definition of success for someone is this: does this person have the life they wanted to have? And it doesn’t necessarily have to be rich or luxury life. Someone wants to have good work-life balance and hang out with friends - does this person have this?

• His long-term economic thesis is that powerful tech will drive us into a state of abundance, and once that happens, capital and opportunity can be distributed far more equally, making today’s rich-vs-poor discourse feel oddly outdated.

• Max thinks about neural engineering from the bottom up: his work is largely in low-level cognition and neural mechanics, even when he talks in terms of high-level concepts like consciousness and identity.

• One of the biggest problems to scale BCI is 10 bits-per-second bottleneck of human output. You can increase input, but how can you scale output? It might be possible biohybrid approaches using stem-cell-derived neurons that integrate into the brain, and breaking by directly serializing thought.

• He’s deeply interested in the “binding problem” of consciousness — how billions of neurons over space and time become a single unified “moment,” and why you only ever experience your bundle of sensory modes together rather than, say, your vision and someone else’s hearing.

• His working hypothesis is that consciousness is tied to physically realized information and thermodynamics: whenever a system burns energy to stabilize a representation against entropy, you get qualia — an idea he’s honest about holding with medium-low epistemic confidence but sees as concrete enough for a real research program.

• On ethics and regulation, he argues that concerns around “neural privacy” are often overstated, and that overly restrictive rules around pooling brain data are slowing down progress on exactly the science that could make BCIs safe, useful, and eventually life-changing.

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A few takeaways that really stuck with me:

💭 1. “You don’t decide to start a company — you get infected by an idea.”
Ali described entrepreneurship as something irrational. You try to talk yourself out of it, poke holes in it, and move on, but if you still can’t shake it off, that’s when you know it’s worth building. “It’s like a disease you can’t cure,” he said. This obsession helps carry you through the chaos.

⚡ 2. Fear is the quiet killer of startups.
His biggest regret was trying to hedge his risks. “Every time you act out of fear, you lower both risk and reward.”
Ali talked about how one company failed because they diversified prematurely by adding new products to “de-risk.” However, all it did was just diluted focus. Startups are about choosing which risk you want to live with.

🧲 3. “I ask one question before I invest: if this person started something, how many of their smartest friends would want to join?”
He said he’s drawn to founders who are magnetic, people others want to follow because they radiate conviction and drive. The kind of person who makes you raise your own bar just by being around them. This line says everything about leadership, culture, and momentum.

👩‍💻 4. Computer science teaches more than coding.
Ali’s belief: “CS is a great predictor of future founders”, because coding trains your brain to break big, intimidating problems into smaller solvable parts, which is the same mindset you need to scale a team or a product.

🔥 5. “De-risking doesn’t mean avoiding risk. It means taking it — and learning fast.”
Conviction is rarely about having perfect or complete data, it’s about having enough courage to decide with 70% of it and building intuition through reps. It means taking the risk and learning from it fast.

Grateful to everyone who joined the conversation, and to the Silkroad Innovation Hub for helping us bring these dialogues to life.

Karan’s journey began with something deeply personal — a family crisis that exposed how invisible mental health struggles can be. That moment set him on a path to build Ginger, one of the earliest digital mental-…

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Here are a few insights from the conversation:

-World rests on three core assumptions: most future internet traffic will be driven by AI, the value of the network increases exponentially as more people join, and a token can effectively bootstrap and sustain that network from day one;

- The revenue thesis follows from those assumptions: the cost per verified human will be significant, creating strong demand for services like social networks, while belief in the token itself becomes a powerful driver of value and participation;

- From the outset the idea sounded outright crazy to nearly everyone, which Alex argues is exactly what you should expect when you are working on something truly transformative;

- The iris scan is the single piece of biometric data that remains uniquely unspoofable, making it the critical element that ensures the system cannot be tricked or duplicated while allowing individuals to remain completely anonymous in the network;

- If World succeeds at scale, it has the potential to become the dominant global human coordination layer of the internet, a foundational infrastructure for how humans and AI interact online;

- Alex is the co-founder of The Merge, the research labs that is aimed to advanced human brain via non-invasive brain-computer integration. He mentioned that one of the bottlenecks of Neuralink’s current methods is their invasive approach that destroys more neurons than it saves, which he sees as fundamentally unsustainable for long-term brain–computer integration;

- Alex illustrated how “ridiculous” ideas, when grounded in first-principle reasoning, can scale to something massive. Professors openly mocked both AGI and crypto after the bubble burst, but he spent weeks in deep isolation reasoning through why it could work, and that conviction ultimately produced World now serving nearly 40 million users;

- He believes that small, deliberate choices by people like us can redirect technological progress in outsized ways, so he completely shut down his personal life and dedicated every waking hour to the mission, convinced this is the most consequential moment to be building in reality;

- Getting rejected by YC120 became a pivotal turning point: a VC happened to notice an auto-liked Instagram post, Alex followed up, and that unexpected chain connected him to Sam Altman. He was even ready to fly to San Francisco just to tell YC they were wrong, showing how setbacks can fuel something far bigger;

- One of the most surprising lessons he learned from Sam Altman was the power of radical simplicity. He now asks himself whether an idea could be as simple as Sam suggests, realizing that every truly genius concept can and should be distilled into one crystal-clear sentence.