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The Founder’s Dilemma In The Age of AI: Working Toward Singularity
Editor’s note: This column is the final installment in a three-part series. Read part one here and part two here. By Mark Himmelsbach and Remy Pinson We like to think markets naturally align incentives over time. Maybe they will. But transitions always involve friction, and AI has accelerated the friction point between economic and human interests. AI didn’t create the tension between efficiency and decency, but it intensified and accelerated it. And even if AI doesn’t replace jobs wholesale, it will reshape them, compress them and fundamentally change the human-machine ratio inside companies. Mark Himmelsbach Which means leaders must answer a new question: How do we build a culture that keeps humans valued and motivated while leveraging machines fully? A hybrid human-machine organization requires rethinking almost everything: norms, rituals, contributions, trust dynamics, leadership models and more. Culture has always been the stabilizer that holds companies together. Now it must evolve. Below are the cultural imperatives we believe will define organizations that navigate this transition well. Remy Pinson Five cultural imperatives for the human-machine era 1. Build a culture of hybrid identity. Not human-first or AI-first, but hybrid. Humans bring judgment, creativity, empathy, taste and leadership. AI brings speed, scale, memory and tireless iteration. A culture that values both reduces fear and increases clarity. 2. Establish trust norms between humans and machines. Teams need to know when to rely on AI, when to challenge it, and how to collaborate with it. Trust must be explicit and expressed — not assumed or hidden. 3. Redefine contribution and recognition. If AI plays a meaningful role in output, recognition must shift too. Don’t just reward production. Reward insight, direction, taste, judgment, strategy and creative authorship. 4. Preserve belonging as leverage increases. Smaller teams can still be human-centered — but only with transparency, clear purpose and rituals that reinforce connection. Humans’ need for belonging must be intentionally designed. 5. Build culture early. Cultural debt accumulates faster than technical debt. Leaders who design norms early — around language, expectations, rituals and trust — will avoid confusion and resentment. I think about this constantly. Our company is one small version of what’s happening across industries. Efficiency is accelerating, roles are evolving and culture is stretching into something new. But I’m optimistic. History suggests we eventually find equilibrium with transformational new technologies. Perhaps it will even be a version like the one Ray Kurzweil imagines as “the Singularity” — where humans and machines truly elevate one another. Until then, we’re committed to building a culture where the efficient thing and the decent thing can coexist. Where machines do what they’re best at, humans do the same, and the space between them becomes a new source of creativity and possibility. We believe it, we’re building for it, and we’ll stand by it until proven otherwise. Mark Himmelsbach is the co-founder of the world’s newest creative AI marketing tool, RYA. He’s also the co-founder of Episode Four, an advertising agency that leverages data to make hits for Visa, Invesco QQQ, Charles Schwab, AT&T and many other marquee brands. Over the past two decades he has led cross-functional teams and developed multidiscipline communications and creative strategies for both for-profit and nonprofit organizations. Himmelsbach is a MBA graduate from Northwestern University’s Kellogg School of Management. Remy Pinson is head of business development at WestComms. He strongly believes that high-quality communication will only continue to appreciate in value and supports clients working in AI, crypto and frontier technologies. Pinson still keeps a regular hand-written journal, loves wine and earned a degree in economics and philosophy at Claremont McKenna College in California.
Sector Snapshot: Insurtech Funding Is Way Down, But AI Is Still Driving Some Big Deals
For obvious reasons, insurance-related technology isn’t exactly one of the sexiest investment areas for VCs, which might explain why funding and deal count are both down this year, per a review of Crunchbase data. But insurance impacts everyone in one way or another, and the sector is also one of the areas that shows great promise for artificial intelligence. Indeed, many of the venture deals that have gone into the sector this year have been around AI and automation. Funded insurtech startups are using AI for functions such as streamlining underwriting, automating claims processing, improving risk assessment, and reducing manual work. The broad trend: Even before the pandemic-fueled funding peaks, insurtech startups received more than double the amount of venture funding in 2019 than they have in more recent years. While investors haven’t given up on insurtech, funding to startups in the space is down in 2025 and deal count is at a multiyear record low. The numbers: So far in 2025, global insurance-related startups have pulled in about $3.9 billion in seed-through growth-stage financing, per Crunchbase data — almost less than one-fourth of the 2021 peak dollars raised — with deal counts also on the decline. The lower deal count signals both potentially decreased investor interest in the space, as well as larger round sizes. Noteworthy recent rounds Several large megadeals took place this year, many of them in this final quarter. Unsurprisingly, one of the largest recipients of venture capital often cited AI as an area of focus. In October, San Francisco-based CyberCube raised $180 million in a venture round led by Spectrum Equity. Founded in 2015, the company noted at the time of its fundraise that deeper adoption of AI technology has been a part of its strategy since its inception. “CyberCube has continued to harness the power of its proprietary AI toolset and internet-scale large language models to drive insights from complex data to solve clients’ biggest problem – to meaningfully quantify cyber risk to maintain profitability and sustainability,” the company said in a news release. And, in recent weeks, Austin-based Curative raised $150 million in a Series B financing that valued the startup at $1.275 billion. Founded in 2020, Curative created and launched an employer-based health insurance plan that focuses on preventative care and a pledge of $0 out-of-pocket costs. The startup uses AI to power its member experience in combination with human support. Investors include DCVC, Refactor, Duquesne Family Office, Jam Fund and Upside Vision Fund. On Dec. 3, Angle Health raised $134 million in a Series B financing to grow its own AI-driven healthcare benefits offering. Portage Ventures led the 6-year-old San Francisco startup’s raise, which also included participation from Y Combinator, Wing Venture Capital and others. And in January, Boston-based Openly brought in $123 million in a growth financing led by Eden Global Partners. Founded in 2017, the company offers home, auto and life insurance services using AI to generate quotes. Early-stage insurtech funding There were smaller insurtech raises as well, for companies working on a variety of insurance-related issues, many of them centered around automating aspects of the claims process. While funding is undoubtedly down from the peak, it’s also clear that insurtech isn’t dead. The industry’s newest winners just look a little different than the straight D2C plays we’ve seen in the past, as they are more focused on infrastructure and workflows. If that’ll make it easier and cheaper to get insurance, that’s not a bad thing. Related Crunchbase query: Related reading: Illustration: Dom Guzman
SpaceX IPO At $1.5T Valuation Would Be 10x Larger Than Biggest VC-Backed Listing Of All Time
SpaceX is forging ahead with plans for an initial public offering to raise “significantly” more than $30 billion, sources told Bloomberg. The Elon Musk-led company is reportedly targeting a valuation of $1.5 trillion. If that indeed happens, the transaction would be by far the biggest stock-market listing of all time, Crunchbase data shows. A SpaceX IPO could take place as early as mid- to late-2026, or possibly in 2027, Bloomberg reported. Until October, Hawthorne, California-based SpaceX was the world’s most valuable private, venture-backed company. It was reportedly valued at $400 billion after a secondary share sale this summer. OpenAI took over the top spot when it conducted its own secondary share sale at a valuation of $500 billion. Founded in 2002, SpaceX has raised nearly $12 billion in its lifetime, according to Crunchbase. Investors include Andreessen Horowitz, Sequoia Capital, Craft Ventures, Valor Equity Partners and Founders Fund, among others. Record IPOs A stock-market listing at its reported target valuation would dwarf the initial valuations of any other venture-backed startups on record. The largest to date remains Facebook’s IPO in 2012 that valued the social media company (now named Meta) at $104 billion. More mega IPOs could be on tap Notably, SpaceX’s potential IPO, while the largest, is not the only massive listing that may be in the works. The largest two generative AI startups, OpenAI and Anthropic, are also reportedly mulling public listings that would value them in the hundreds of millions of dollars, or more. OpenAI is reportedly eyeing an initial public valuation of up to $1 trillion if it goes public as soon as next year, while Anthropic is currently said to be pursuing fresh funding at a private valuation of more than $300 billion. So it would presumably seek an even higher market cap in a public offering, although it’s yet unclear how high. Related Crunchbase queries: Related reading: Illustration: Dom Guzman
Jeff Bezos’ Project Prometheus Joins The Unicorn Board Alongside 18 Other Startups In November
November brought another strong showing for The Crunchbase Unicorn Board with 19 companies joining the ranks of billion-dollar startups. The largest round went to Jeff Bezos’ Project Prometheus, which has reportedly raised billions of dollars out of the gate with the intent to develop AI for manufacturing in aerospace, automobiles and computers. Among the sectors for new unicorn creation last month, AI led once again. The largest number of companies hailed from the data and model side as well as workflow applications. At least 13 of the 19 new unicorns have AI at the center of what they do. Other sectors with two or more new unicorns were healthcare and defense. Fourteen of November’s new unicorns are U.S.-based. The remaining five companies were each from China, India, Hong Kong, Canada and Denmark. In the U.S., Palo Alto rivaled San Francisco and Austin with three companies from the Silicon Valley city, compared to two each from the other cities. New unicorns Here are November’s 19 newly minted unicorns. AI data and models AI workflow applications Healthcare Defense Media and entertainment Financial services Web3 Transportation Insurance Govtech And here’s one we missed from the end of October. Commercial space station developer Vast raised a $150 million Series A led by IQT, a fund affiliated with U.S. national security. The 4-year-old Long Beach, California-based company was valued at $1.9 billion. Related Crunchbase unicorn lists: Related reading: Methodology The Crunchbase Unicorn Board is a curated list that includes private unicorn companies with post-money valuations of $1 billion or more and is based on Crunchbase data. New companies are added to the Unicorn Board as they reach the $1 billion valuation mark as part of a funding round. The unicorn board does not reflect internal company valuations — such as those set via a 409a process for employee stock options — as these differ from, and are more likely to be lower than, a priced funding round. We also do not adjust valuations based on investor writedowns, which change quarterly, as different investors will not value the same company consistently within the same quarter. Funding to unicorn companies includes all private financings to companies that are tagged as unicorns, as well as those that have since graduated to The Exited Unicorn Board. Exits analyzed here only include the first time a company exits. Please note that all funding values are given in U.S. dollars unless otherwise noted. Crunchbase converts foreign currencies to U.S. dollars at the prevailing spot rate from the date funding rounds, acquisitions, IPOs and other financial events are reported. Even if those events were added to Crunchbase long after the event was announced, foreign currency transactions are converted at the historic spot price. Illustration: Dom Guzman
Exclusive: Founded By Husband And Wife Team, Zed Raises $16.5M To Give Young Professionals In Asia Access to Credit
Zed, a Philippines-based startup building credit products for young professionals across the Asia-Pacific region, has raised $16.5 million in a Series A funding round, it tells Crunchbase News exclusively. Palo Alto, California-based Accel led the financing, which brings Zed’s total funding raised to $22.5 million. The startup’s latest round comes amid a robust period for fintech investment overall: Global venture funding to financial technology startups in 2025 has, as of Dec. 8, reached $48.7 billion across 3,498 deals, per Crunchbase data. That’s a 29.5% increase in dollars raised compared to the $37.6 billion raised across 4,588 deals during the same time period in 2024. An ‘aha’ momentSteve Abraham and Danielle Cojuangco Abraham. Courtesy photo. Founded in 2021 by husband and wife serial entrepreneurs Steve Abraham and Danielle Cojuangco Abraham, Zed’s initial market has been the Philippines. The pair stumbled upon the idea for Zed after selling their previous company, Symple, a B2B mobile payments network, to Feather in 2020. When traveling to the Philippines, where Danielle is originally from, the couple describes having an “aha experience.” After landing at the airport, they were going to meet Danielle’s brother at a bar three miles away. “It really should have taken only 15 minutes. But it ended up taking a full hour, because we realized it was payday Friday, where everyone’s rushing to the ATMs after work,” Danielle recalls. “They’re pulling out their entire paychecks and spending them all night because they’ve been waiting to shop with that cash that they’ve gotten that day.” When they got to the bar, the couple noticed that Danielle’s brother paid for refreshments in cash. They were confused why the young man — a lawyer at a prestigious firm — didn’t use a credit card. His response when asked? “I tried. I’ve gone to three banks, and they’ve all rejected me. I can’t get a credit card.” “That was the moment that Steve and I realized that we just had to dig into this, and learn more about this opportunity,” Danielle said. And so Zed was born. Regulation and risk management The co-founders/co-CEOs spent the first three years of Zed’s life acquiring the startup’s financial institution license from the Central Bank of the Philippines. They then launched Zed’s first product — a “modern” credit card that focuses on features for travel, online shopping and peer-to-peer payments — in mid-2024. “To get our license, we had to set up a compliance org and operations org and essentially pass all of the application checks that any bank would have to pass,” Steve told Crunchbase News in an interview. “That took a while — it was a beast of an effort. … In order to do this, we’ve had to reinvent the primitives that banks are built on.” Traditional banks, he said, rely exclusively on credit scores, which are based on factors that depend heavily on age — such as how long a person has had their accounts or how many credit lines they’ve ever opened. “So young people, like recent college graduates, with growing incomes, stable jobs and no negative marks in their files still can’t get credit cards because of low scores that are only a reflection of their age,” he added. “This leaves a huge segment of potentially prime customers unserved.” Zed uses foundational models to profile and underwrite the risk of customers based on transaction data, financial documents, and other structured and unstructured data sources. That way, the pair said, Zed can serve young professionals with signals of low risk across data sources such as stable cash flows, responsible spending and saving patterns, and other factors. “This approach unlocks massive opportunity across a region where less than 50% of the population is under 30 and where current credit card penetration is sub-15%, excluding China and Singapore,” Danielle said. Targeting a younger customer base Zed’s biggest competitors are long-established, incumbent banks that are more focused on older and wealthier customers, the pair said. They’ve intentionally designed Zed’s credit card to have features that are geared toward the young professional, including zero FX fees and zero FX markup; the ability to create single-use or 24-hour cards that automatically close themselves, and the ability to send each other money “as easily as using Venmo but with the flexibility of settling when their card statement is due.” For now, Zed is still in the invite-only launch period. Its waitlist has attracted nearly 200,000 sign-ups “strictly through word of mouth.” The company says its customer base has grown by 10x, and its monthly gross merchandise value (monthly spend) has grown by about 500% since the beginning of 2025. The startup generates revenue from interchange fees and interest on purchases made by customers using its credit card. “The vast majority of our waitlist has yet to be invited,” Steve said. Presently, Zed has 13 employees across San Francisco and Manila. Operations are headquartered in Manila, while product and design employees work out of San Francisco. The startup in March 2021 raised $6 million in a seed round that was led by Valar Ventures and included participation from Mercury CEO and founder Immad Akhund, along with Dalton Caldwell, Kunal Shah and other angels. Looking ahead, Zed wants to expand throughout the APAC region, including markets such as Vietnam, Indonesia, Malaysia and India. “Eventually, our plan is to expand globally and connect young people who share a common lifestyle and financial goals, wherever they may be, from Asia to North America,” Danielle said. Accel Partner Nafis Jamal, who previously worked as head of consumer payments at fintech giant Circle, told Crunchbase News via email that he believes Zed has potential because “very few people” have access to credit despite the fact that the Philippines is one of the youngest, fastest-growing markets in the region. The firm was also drawn to the co-founding team’s experience. “Danielle and Steve bring serious technical talent and a deep understanding of the local customer and regulatory landscape,” he said. “Second, they execute with unusual discipline: smart underwriting paired with a product that feels incredibly intuitive to use.” Related Crunchbase query: Related reading: Illustration: Dom Guzman
Nuclear Fission Shows Continuing Popularity (With VCs, At Least)
At first glance, nuclear fission power doesn’t seem like the most obvious area for U.S. venture capital to cluster. After all, the last big boom for building American nuclear power plants was in the 1970s. Not long after that, environmental and safety concerns, project cost and broader availability of other affordable power options, among other factors, effectively brought new installations to a halt. In VC portfolios and IPO pipelines, however, nuclear has been making a comeback. So far this year, investors have poured close to $2 billion into an assortment of companies across stages working on nuclear power offerings outside of the fusion space 1 curated using Crunchbase data. The funding influx coincides with public market offerings activity as well. Notable funding recipients For a sense of who’s getting funded, we put together a list of 16 good-sized rounds that closed this year for nuclear-focused startups. The largest round is also one of the most recent: a $700 million Series D in late November for X-energy, a developer of advanced nuclear reactor and fuel technology. Jane Street Capital led the financing for the Rockville, Maryland-based company, which is looking to build small modular reactors. For X-energy, it helps that the 16-year-old company has attracted some high-profile partners. Currently, it has projects mapped out with Dow Energy and Amazon. The startup says it plans to use some Series D funds toward beefing up its supply chain TerraPower, one of the most recognized names among nuclear startups, also landed a huge follow-on financing this year. The Bill Gates-founded startup picked up $650 million in fresh funding this summer, with Nvidia’s NVentures as a backer. The Bellevue, Washington-based company touts its Natrium technology, which it describes as an advanced nuclear reactor paired with gigawatt-scale energy storage. It began preparatory construction activities on the site of the first plant last year and says it expects regulatory approval for the nuclear reactor next year. We’re also seeing early-stage activity. Just this month, Antares, a 2-year-old startup focused on building compact nuclear microreactors for remote locations, announced that it closed on a $96 million Series B round. Valar Atomics, founded in 2023, has also been a fast serial fundraiser. The El Segundo, California, company, focused on building nuclear reactors for grid-independent projects, raised $130 million a month ago in a Series A led by Day One Ventures, Dream Ventures and Snowpoint Ventures and joined by backers including Anduril Industries founder Palmer Luckey. Valar is also known for being one of the parties suing the Nuclear Regulatory Commission over the licensing process for small reactor designs. Exits too Interestingly, nuclear is also an area where we are seeing both planned and actualized public-market debuts. In the actualized category, the standout is Oklo, which develops nuclear reactors and went public last year through a merger with a SPAC launched by Sam Altman. It’s a pre-revenue company and had a recent market cap around $16 billion. It’s a pretty big-number outcome, which might help explain why other SPAC deals have also popped up: The ’70s boom, redux? For those putting their money behind expectations of a nuclear power development renaissance, it helps that the political winds are turning in their direction. In May, President Trump signed executive orders intended to greatly increase domestic production of nuclear power in the next 25 years. The act aims to speed up approvals of new projects. These won’t mimic 1970s installations in form or purpose. They’ll likely be smaller, not always grid-connected, and conceived with an eye toward feeding the power demands of artificial intelligence. However, the hope among investors is that in terms of the quantity of power generated and new installations built, we will enter another boom era. Related Crunchbase query: Related reading: Illustration: Dom Guzman
Hollywood Legend Turned Startup Investor Jeffrey Katzenberg On Where He’s Placing His AI Bets
When Jeffrey Katzenberg sold DreamWorks Animation in 2016, he knew his next venture would be technology related. Soon after the sale, he teamed up with former Dropbox CFO Sujay Jaswa to found WndrCo, a holding company and venture capital firm “reimaginging how people live and work.” With $2.8 billion in assets under management, the firm has invested in companies including Writer AI, 1Password, Abridge, Airtable, Alembic, Aura, Cursor, Databricks, Figma, Point Wild and Super Unlimited. Film producer to tech investor may not seem like the most natural of evolutions. But for Katzenberg, it wasn’t a stretch. Before DreamWorks, he was chair of Walt Disney Studios, which during his tenure, produced films such as “Aladdin,” “The Lion King,” and “Beauty and the Beast.” He was also previously president of Paramount Pictures. Over the course of his illustrious and legendary career, Katzenberg experienced firsthand how technology could impact the film industry — from Steven Spielberg building a big shark out of plastic and dragging it behind a motorboat as a “special effect” to the “transformative” power of animation. Jeffrey Katzenberg “I always saw tech as a competitive advantage in storytelling,” Katzenberg told Crunchbase News in an interview. The introduction of computer graphics and CGI didn’t evolve animation, he said, but “revolutionized” it. And that, he said, is somewhat analogous to what’s going on with AI today, and not just in media, but “writ large.” “It’s actually a fantastic, interesting use case of where you can see not only total and complete reinvention and disruption, but the ultimate outcome of something bigger and better,” Katzenberg said. “It displaced every job, but it did not eliminate jobs. And that’s where I actually have a slightly more optimistic point of view about what is coming our way [when it comes to AI].” Justin Wexler Today, Katzenberg and WndrCo general partner Justin Wexler lead the firm’s enterprise AI investing practice and work with portfolio companies to secure big customer wins, helping them land deals with brands like Nike, Delta, NBA and Disney. WndroCo Holdco, the firm’s company-building arm, has incubated eight companies with a total of a combined $1.25 billion in top-line revenue and $250 million in EBITDA. Through this strategy, WndrCo partners with founders and CEOs, often acquiring controlling stakes in “underappreciated” tech companies in an effort to turn them into category leaders. Crunchbase News conducted a video interview with the pair to get their thoughts on what’s next when it comes to enterprise AI and how storytelling can be a competitive advantage. The interview has been edited for clarity and brevity. Where are we exactly in the enterprise AI cycle? Katzenberg: We are of the school that the world is being revolutionized, not “evolutionized,” by the introduction of AI on the third anniversary of ChatGPT and all of the amazing things that have happened since then. There are many ways to look at AI. It’s such a giant umbrella … and it has so many verticals in it … and so many layers, some of which are out of our realm. We’re not in the hyperscaler business. We’re not in the LLM business. We’re not in the infrastructure side of it. … We are most excited about the simplest applications that actually change how people go about their lives, be it at work or at home in their professional lives or on the consumer side of it. The overarching category would be the consumerization of software. So we’re trying to stay very focused on this idea that if you actually just took what has already been created with these large language models, and where we are in January 2026, the value that can be built today with the tech that has already been created and is deployable, could be bigger than everything that has come before it. Wexler: We’re in a pretty unique role in this ecosystem that we have a lot of pride in. Jeffrey has built so many relationships over decades, and a lot of folks admire the transformation he had to go through in animation. So we just try to be a really close partner to a lot of Fortune 500 execs, as they’re thinking about, “There’s this totally game-changing technology with generative LM AI and agentic AI. How do I deploy it to transform my part of the organization?” …Getting deployments at scale that are successful is hard to do, and it’s hard for many reasons. There’s a lot of confusion in a lot of these organizations on how best to set up AI for a lot of success. It’s hard for a startup alone to try to be learning about an organization while selling and while competing with a lot of other noise in the market. … One thing that we spend a lot of time with the founders we work with is helping them navigate that … because if you can prove success, then you can really scale. It’s also a huge unlock for enterprise. But to date, there’s been a lot of deployments that, because you don’t have that alignment, it’s a lose-lose for everybody. We actually counted one company that did like 200 meetings with a startup, and it went nowhere because the alignment wasn’t there. The technology could have been very impactful to them, but they didn’t have that organizational alignment. So that ingredient is so important. We’ve tried to play that role. Katzenberg: I think that’s where our role is becoming more important and valuable, and that can be summed up in a simple word: trust. We’ve now been doing this long enough that we have built out a pretty extraordinary network of relationships with the Fortune 500 companies and the C-suites there, and we have brought multiple products to them over the past couple of years, each one of which has actually delivered on its promise. So today, I find that when we come in with a new product, a new offering, a new company, it’s easier; it’s not easy, but it’s easier. We are super sensitive around the issues of reliability, security, data protections and all of the things that we already know we can anticipate where people are going to be anxious. You have said that you work closely with your companies and landing these big logos and clients. What separates a cool AI demo from a product that actually does become embedded in enterprise workflows? Wexler: We found that it’s hard to build for everybody all at once. There’s incredible AI and technology that serves SMB and mid-markets. But the founders we’ve seen that have the most success in enterprise, built for enterprise from day one. They didn’t try to move up, as they’re getting some traction with startups. They built with compliance from day one. That way, it’s much easier to get HIPAA compliant and GDPR versus trying to make changes along the product journey. … so you can scope a great initial proof of concept or pilot, but they’re betting just as much on this potentially being a new partner for them for the longer term. We’ve seen a one-year deal turn into a three-year deal, and actually a couple companies are starting to talk about four- or even five-year contracts, which we have not seen previously with AI startups. But it’s happening now, and just goes to show the level of comfort that enterprises are gaining, and the trust that they’re gaining with some of the most innovative early-stage companies that could be long-term partners for them. When you look at AI startups today, how do you decide whether something is actually an AI company or really just like a feature on top of somebody else’s model? Wexler: We have a portfolio of companies that we would categorize as AI, and they partner very well with the major LM companies, whether it’s OpenAI, Anthropic or Gemini. We also have companies like Writer, which have trained off of the models either from scratch or from working Llama models as well, where they really take an ownership in trying to build a best-of-breed model for their specific use case. There’s been success with both. Where do you expect most of the enterprise value to actually accrue? Would it be an infrastructure foundation? Models, application layer? Katzenberg: I think 100% at the application level, not 80% or 90%, but 100%, as best we are seeing. That’s where you can actually see incremental value. It is additive and it is not, rip and replace. Now, will this accelerate in coming years? Likely. But this idea that in the next five years, 80% of white-collar workers are going to be replaced, I think, is just way ahead. I’m not saying that might not actually be correct in the long run, but the transition to it is going to be, I think, significantly more than five years. Wexler: As application-tier companies build their case studies and prove examples, the rest of those industries pay close attention, see the success and want to follow. So then as application-tier companies scale, they’re actually the ones who choose the infrastructure that’s best for them, and that includes the LLMs as well. Really, what the end client, the Fortune 500 or the enterprise, is getting is kind of a package solution. A lot of people were trying to build CRMs and ERP before Salesforce 1 really built the bundled solution that became the industry standard. We’re going to see that for particular use cases. Look no further than Harvey or Bridge. Katzenberg: The big hyperscalers probably have the capability of doing it all. But they don’t have the capacity, and they don’t have the focus. And so that’s why, when you look at a Bridge, or you look at Harvey or Cursor, in these cases these are phenomenal entrepreneurs who are brilliant and singularly focused. They have this one idea, this vision if you will, for an exceptional application with a value. So can somebody come along and do what any of those three companies can? They can’t do it all, and they’re not going to do it with that same laser ambition and focus of a great entrepreneur. They might have the capabilities to do it, but I don’t think they have the focus. They can’t. When you try to be all things to all people, you end up not being anything. Looking ahead to 2026, what do you expect the biggest correction to be — whether in valuations, business models or assumptions founders and investors are making about enterprise AI today? Katzenberg: I have a bottomless well of optimism. I’m not looking for the clouds on the horizon. Where’s the concern? Where are the anxieties coming from? I’m not saying that it’s not there. It’s just in our lane, there’s too much opportunity I do feel we are well equipped to navigate. In AI specifically, what are some nonnegotiable qualities that you look for in a founder? Wexler: It’s a pretty high bar to be a great AI founder. There’s a lot of demands on you. You’re at the cutting edge of technology where things are constantly shifting faster than any other era. You have to stay on top of that and be on the bleeding edge. Because if not, it’s going to be hard. You have to be able to truly understand these pain points in a way that you can articulate how technology can solve them, and in a way that has not been solved before. How does great storytelling, in your opinion, actually change outcomes? Katzenberg: One of the things that was the siren drawing me to Silicon Valley and company building is I realized very, very early on how foundational storytelling is to every single chapter of every single company’s journey in that the better you can tell your story, the more successful you are. Telling your story in every phase of company building is more than essential, it’s existential. The way in which you get other people to join you and pursue your idea as an entrepreneur, you’ve got to be able to share your dream in a way that others can get excited about, and recognize your vision, your ambition, your dream. You have to be able to tell it to get other people to come on the journey with you. You need to tell it to investors in order to be able to raise money. You need to be able to tell it to customers when you go to market, and virtually every step along the way in company building and company running. Related reading: Illustration: Dom Guzman
The Week’s 10 Biggest Funding Rounds: Investors Get Back To Writing Large Checks
Want to keep track of the largest startup funding deals in 2025 with our curated list of $100 million-plus venture deals to U.S.-based companies? Check out The Crunchbase Megadeals Board. This is a weekly feature that runs down the week’s top 10 announced funding rounds in the U.S. Check out our last biggest funding deal roundup here. We took a break from covering the largest U.S. startup investments over Thanksgiving week, which was just as well, given that it was a predictably slow period for big deal announcements. Now, with just a few weeks left in 2025, things are picking up again. Predictions market Kalshi led the list after confirming its already widely reported $1 billion fresh financing. Other big rounds came from sectors including defense tech, AI infrastructure, cybersecurity and biotech. 1. Kalshi, $1B, predictions market: A couple weeks ago, we included Kalshi in our Top 10 after the company reportedly secured $1 billion in fresh funding. Well, now it’s official, with confirmation from the fast-growing New York-based predictions marketplace. Crypto-focused investor Paradigm led the financing, with participation from a long list of venture firms. 2. Castelion, $350M, defense tech: Castelion, a developer of hypersonic munitions, says it raised $350 million in Series B financing led by Altimeter Capital and Lightspeed Venture Partners. The Torrance, California-based company was founded by SpaceX alum in 2022. 3. Eon, $300M, cloud data: New York-based Eon, a provider of cloud data backup technology for enterprise AI, landed $300 million in a Series D led by Elad Gil of Gil Capital. The round brings Eon’s total funding to $500 million since its founding less than two years ago and increases its valuation to $4 billion. 4. Curative, $150M, health insurance: Curative, a startup that markets a free out-of-pocket health plan, picked up $150 million in a Series B round led by Upside Vision Fund. The financing values the Austin-based company at $1.27 billion. 5. Angle Health, $134M, health insurance: San Francisco-based Angle Health, an AI platform for healthcare benefits, closed on $134 million in Series B funding led by Portage Ventures. The round included a combination of debt and equity, bringing total funding to nearly $200 million, according to the company. 6. (tied) 7AI, $130M, cybersecurity: 7AI, a developer of tools for scaling AI agents to do security work, pulled in $130 million in a Series A led by Index Ventures. The funding round comes just 10 months after the Boston-based company launched out of stealth mode. 6. (tied) Protego Biopharma, $130M, biotech: Protego Biopharma, a startup therapeutics that aims to reprogram protein folding to address multiple diseases and disorders, raised $130 million in Series B funding. Novartis Venture Fund and Forbion led the financing for the San Diego-based company. 8. Triana Biomedicines, $120M, biotech: Lexington, Massachusetts-based Triana Biomedicines, developer of a molecular glue discovery platform, secured $120 million in Series B financing. Ascenta Capital and Bessemer Venture Partners co-led the round. 9. Antithesis, $105M, simulation testing: Antithesis, a developer of simulation testing tools for software systems, raised $105 million in Series A funding. Jane Street Capital led the financing for the Tysons Corner, Virginia-based startup. 10. Axiado, $100M, AI server chips: Axiado, developer of a chip designed to save space and power in artificial intelligence servers, secured $100 million in a Series C+ round. Maverick Silicon led the investment for the San Jose, California-based company. Methodology We tracked the largest announced rounds in the Crunchbase database that were raised by U.S.-based companies for the period of Nov. 28-Dec. 5. Although most announced rounds are represented in the database, there could be a small time lag as some rounds are reported late in the week. Illustration: Dom Guzman