Whatnot, a live shopping platform and marketplace, has closed a $225 million Series F round, more than doubling its valuation to $11.5 billion in less than 10 months.
DST Global and CapitalG co-led the financing, which brings the Los Angeles-based company’s total raised to about $968 million since its 2019 inception. Whatnot had raised $265 million in a Series E round at a nearly $5 billion valuation in January.
As part of the latest financing, Whatnot says it will initiate a tender offer where select current investors will buy up to $126 million worth of shares.
Funding to e-commerce startups globally so far this year totals $7.1 billion, per Crunchbase data. That compares to $11.3 billion raised by e-commerce startups globally in all of 2024. This year’s numbers are also down significantly from post-pandemic funding totals, which surged to $93 billion in 2021.
‘Retail’s new normal’
Live commerce is the combination of livestreaming and online shopping. Grant LaFontaine, co-founder and CEO of Whatnot, said in an announcement that his startup is “proving that live shopping is retail’s new normal.”
Whatnot co-founders Logan Head and Grant LaFontaine. Courtesy photo.
The company says more than $6 billion worth of items have been sold on its platform in 2025 so far, more than twice its total for all of 2024. Its app facilitates the buying and selling of collectibles like trading cards and toys through live video auctions. It also offers items such as clothing and sneakers. It competes with the likes of eBay, which currently does not offer a livestreaming option. It’s also a competitor to TikTok Shop.
“Whatnot brought the live shopping wave to the US, the UK, and Europe and has turned it into one of the fastest growing marketplaces of all time, Laela Sturdy, Whatnot board member and managing partner at CapitalG, Alphabet’s independent growth fund, said in a release.
The company plans to use its new funds to invest in its platform, roll out new features and “evolve” its policies. It is also accelerating its international expansion, adding to its current 900-person workforce by hiring across multiple departments.
I’ve been building products and companies my entire career — Increo, Box, Crashlytics, Twitter and now, Digits — and I’ve had the privilege of speaking with some of the sharpest minds in venture and entrepreneurship along the way.
One recent conversation with a legendary investor really crystallized for me a set of truths about startups: what success really is, why some founders thrive while others burn out, and how to navigate the inevitable chaos of building something from nothing.
Here are some of the lessons I’ve internalized from years of building, observing and learning.
Success has no finish line
Jeff Seibert
In the startup world, we talk a lot about IPOs, acquisitions and valuations. But those are milestones, not destinations.
The companies that endure don’t “win” and stop — they keep creating, adapting and pushing forward. They’re playing an infinite game, where the only goal is to remain in the game.
When you’re building something truly generative — driven by a purpose greater than yourself — there’s no point at which you can say “done.” If your company has a natural stopping point, you may be building the wrong thing.
You don’t choose the work — the work chooses you
The best founders I’ve met — and the best moments I’ve had as a founder — come from an almost irrational pull toward solving a specific problem I myself experienced.
You may want to start a company, but if you have to talk yourself into your idea, it probably won’t survive contact with reality. The founders who succeed are often the ones who can’t not work on their thing.
Starting a company shouldn’t be a career move — it should be the last possible option after every other path fails to scratch the itch.
The real killer: founder fatigue
Most companies don’t die because of one bad decision or one tough competitor. They die because the founders run out of energy.
Fatigue erodes vision, motivation and creativity. Protecting your own drive — keeping it clean and focused — may be the single most important survival skill you have.
That means staying close to the product, protecting time for customer work, and avoiding the slow drift into managing around problems instead of solving them.
Customer > competitor
It’s easy to get caught up in competitor moves, investor chatter or market gossip. But the most important question is always: Are we delivering joy to the customer?
If you’re losing focus, sign up for your own product as a brand-new user. Feel the friction. Fix it. Repeat.
At Digits, we run our own signup and core flows every week. It’s uncomfortable — it surfaces flaws we’d rather not see — but it keeps us anchored to the only metric that matters: customer delight.
Boards should ask questions, not give answers
Over the years, I’ve learned the most effective boards aren’t presentation theaters — they’re discussion rooms.
The best structure I’ve seen:
No slides;
A narrative pre-read sent in advance; and
A deep dive into one essential question.
Good directors help you widen your perspective. They don’t hand you a to-do list. Rather, they help you see the problem in a way that makes the answer obvious.
Twitter: lessons from a phenomenon
When I think back to my time at Twitter, the most enduring lesson is that not all companies are built top-down. Some — like Twitter — are shaped more by their users than their executives.
Features like @mentions, hashtags and retweets didn’t come from a product roadmap — they came from the community.
That’s messy, but it’s also powerful. Sometimes your job isn’t to control the phenomenon, rather it’s to keep it healthy without smothering what made it magical in the first place.
Why now is a great time to start
If you’re building today, you have an advantage over the so-called “unicorn zombies” that raised massive rounds pre-AI and are now locked into defending old business models.
Fresh founders can design from scratch for the new reality; there’s no legacy to protect, no sacred cows to defend.
The macro environment? Irrelevant. The only timing that matters is when the problem calls you so strongly that not working on it feels impossible.
If there’s one takeaway from all of this, it’s that success is continuing. The real prize is the ability to keep playing, keep serving and keep creating.
If you’re standing at the edge, wondering if you should start — start. Take one step. See if it grows. And if it does, welcome to the infinite game.
Jeff Seibert is the founder and CEO of Digits, the world’s first AI-native accounting platform. He previously served as Twitter‘s head of consumer product and starred in the Emmy Award-winning Netflix documentary “The Social Dilemma.”
While startup investment has been climbing lately, not all industries are partaking in the gains.
Cleantech is one of the spaces that’s been mostly left out. Overall funding to the space is down this year, despite some pockets of bullishness in areas like fusion and battery recycling.
The broad trend: Cleantech- and sustainability-related startup investment has been on a downward trajectory for several years now. And so far, 2025 is on track to be another down year.
On the bright side, however, there’s been some pickup in recent months, boosted by big rounds for companies in energy storage, fusion and other cleantech subsectors.
The numbers: Investors put an estimated $20 billion into seed- through growth-stage funding to companies in cleantech, EV and sustainability-related categories so far this year.
That puts 2025 funding on track to come in well below last year’s levels, which were already at a multiyear low.
Still, quarter by quarter, the pattern looks more encouraging. Investment hit a low point in Q1 of this year and recovered some in the subsequent two quarters. The current quarter is also off to a strong start.
Noteworthy recent rounds
The largest cleantech-related round of the year closed this month. Base Power, a provider of residential battery backup systems and electricity plans, raised $1 billion in Series C funding. The Austin, Texas-based company says its systems allow energy providers to more efficiently harness renewable power.
The second-largest round was Commonwealth Fusion Systems’ $863 million Series B2 financing. The Devens, Massachusetts-based company says it is moving closer to being the first in the world to commercialize fusion power.
For a bigger-picture view, below we put together a list of 10 of the year’s largest cleantech- and sustainability-related financings.
The broad takeaway: Startups innovating for an era of rising power consumption
Not to over-generalize, but if there was one big takeaway from recent cleantech and sustainability startup funding, it would be that founders and investors recognize that these are times of ever-escalating energy demand. They’re planning accordingly, looking to tap new sources of power, fusion in particular, as well as better utilize and scale existing clean energy sources.
Correctly calling a market peak is a notoriously tricky endeavor.
Case in point: When tech stocks and startup funding hit their last cyclical peak four years ago, few knew it was the optimal time to cease new deals and cash in liquidatable holdings.
This time around, quite a few market watchers are wondering if the tech stock and AI boom has reached bubble territory. And, as we explored in Friday’s column, there are plenty of similarities between current conditions and the 2021 peak.
Even so, by other measures we’re also in starkly different territory. The current boom is far more concentrated in AI and a handful of hot companies. The exit environment is also much quieter. And of course, the macro conditions don’t resemble 2021, which had the combined economic effects of the COVID pandemic and historically low interest rates.
Below, we look at four of the top reasons why this time is different.
No. 1: Funding is largely going into AI, while other areas aren’t seeing a boom
Four years ago, funding to most venture-backed sectors was sharply on the rise. That’s not the case this time around. While AI megarounds accumulate, funding to startups in myriad other sectors continues to languish.
Biotech is on track to capture the smallest percentage of U.S. venture investment on record this year. Cleantech investment looks poised to hit a multiyear low. And consumer products startups also remain out of vogue, alongside quite a few other sectors that once attracted big venture checks.
The emergence of AI haves and non-AI have-nots means that if we do see a correction, it could be limited in scope. Sectors that haven’t seen a boom by definition won’t see a post-boom crash. (Though further declines are possible.)
In recent quarters, by contrast, the IPO market has been alive, but not especially lively. We’ve seen a few large offerings, with CoreWeave, Figma and Circle among the standouts.
But overall, numbers are way down.
In 2021, there were hundreds of U.S. seed or venture-backed companies that debuted on NYSE or Nasdaq, per Crunchbase data. This year, there have been less than 50.
Meanwhile, the most prominent unicorns of the AI era, like OpenAI and Anthropic, remain private companies with no buzz about an imminent IPO. As such, they don’t see the day-to-day fluctuations typical of public companies. Any drop in valuation, if it happens, could play out slowly and quietly.
No. 3: Funding is concentrated among fewer companies
That brings us to our next point: In addition to spreading their largesse across fewer sectors, startup investors are also backing fewer companies.
This year, the percentage of startup funding going to megarounds of $100 million or more reached an all-time high in the U.S. and came close to a record global level. A single deal, OpenAI’s $40 billion March financing, accounted for roughly a quarter of U.S. megaround funding.
At the same time, fewer startup financings are getting done. This past quarter, for instance, reported deal count hit the lowest level in years, even as investment rose.
No. 4: ZIRP era is long gone
The last peak occurred amid an unusual financial backdrop, with economies beginning to emerge from the depths of the COVID pandemic and ultra-low interest rates contributing to investors shouldering more risk in pursuit of returns.
This time around, the macro environment is in a far different place, with “a “low fire, low hire” U.S. job market, AI disrupting or poised to disrupt a wide array of industries and occupations, a weaker dollar and a long list of other unusual drivers.
What both periods share in common, however, is the inexorable climb of big tech valuations, which brings us to our final thought.
Actually, maybe the similarities do exceed differences
While the argument that this time it’s different is a familiar one, the usual plot lines do tend to repeat themselves. Valuations overshoot, and they come down. And then the cycle repeats.
We may not have reached the top of the current cycle. But it’s certainly looking a lot closer to peak than trough.
The old cliché says startups are born in garages and dorm rooms. That’s still true, but there’s a newer path: founding a startup inside a scale-up.
When you do that, you get the speed of a seed-stage team with the leverage of an established company. Executives and investors should care because this model can unlock new product lines, revenue and talent retention without recreating the wheel.
That’s how we built Saily, a travel eSIM service launched from inside Nord Security (the company behind NordVPN). In 19 weeks, a seven-person team went from a blank page to a live product. A little over a year later, we had scaled to millions of users with plans offered in more than 200 destinations. We did not invent everything from scratch. We reused what worked and validated everything else fast.
Incubation lowers two risks most founders underestimate
Vykintas Maknickas
Every new product faces two existential risks: market and execution.
Inside Nord, I’d helped launch at least half a dozen new products before Saily. The pattern was consistent: Great ideas die when they target the wrong market or underestimate execution. With Saily, timing and infrastructure lined up: eSIM demand was accelerating, pain points were clear, and we could tap Nord’s backend, payments, app teams and distribution.
That allowed us to move at startup speed without startup fragility.
‘Product organization fit’ beats a great idea
Founders obsess over product-market fit. Inside a scale-up, you also need what I call “product organization fit” or the overlap between a new product and what your company already does well.
When that overlap is high, you ship faster, hire smarter and avoid costly relearning. For Saily, the overlap was obvious: Security tech we knew (virtual location, web protection and ad-blocking), and app development know-how we could bring to travel connectivity.
Competition helped more than it hurt. “No competition” usually means “no demand.” We treated competitors as free market research, reading hiring signals, product moves and funding announcements to understand where the market was headed.
And we made security the product, not a feature. Travelers don’t want another app — they want reliable connectivity that isn’t risky on unknown networks. Building privacy and protection at the network layer means safety works phone-wide with no tinkering.
Autonomy inside structure
The hard part is not technical, but cultural. Large companies run on process. Startups run on autonomy. We set up Saily as a company within the company: A dedicated product and marketing team with decision speed, plus shared services (legal, finance and design) when needed. Think of it as an internal accelerator, where the platform handles overheads so the team can focus on products.
We kept one rhythm: ship, learn, repeat. Those 19 weeks weren’t about perfection, but about getting a usable product into the world and compounding feedback.
Experimentation only works if you measure what matters: speed, unit economics and retention. For example, independent third-party testing confirmed Saily’s network-level ad-blocking reduces data usage by 28.6% — real money saved for travelers. That is a signal you double down on. If a feature or tool adds complexity without value, cut it quickly.
What founders (and operators) can steal
Derisk in two tracks: Validate market pull and execution feasibility before you scale spend. If the market isn’t growing and your organization doesn’t have overlap, think twice.
Reuse before you reinvent: Borrow talent, systems and channels where you can. Every overlap removes weeks of risk.
Measure what matters: Do a simple before/after on ship speed, customer acquisition cost and retention. If the needle doesn’t move, remove it.
Build momentum in full sight: Share milestones and learning. It sharpens the team and attracts partners.
Saily is still early, and the market is just getting started, but the model matters as much as the product. Many future founders already work inside growth companies. Give them startup autonomy and scale-up leverage and remarkable things can happen — in months, not years.
Vykintas Maknickas is CEO of Saily, a global eSIM app from Nord Security. A former head of product strategy at NordVPN, where he helped launch a series of new product lines, Maknickas has turned Saily into a globally successful brand with millions of users and serving more than 200 destinations. An entrepreneur since age 15, Maknickas brings a hands-on, execution-driven approach to building secure, scalable consumer tech.
On Oct. 21, the publicly traded crypto exchange announced that it is acquiring early-stage investing platform Echo for $375 million in cash and equity.
Notably, the acquisition marked the eighth buy for the San Francisco-based company in 2025 so far, according to The Wall Street Journal. Of those eight deals, three involved undisclosed businesses.
Overall, since its 2012 inception, Coinbase has acquired dozens of companies, per Crunchbase data. Besides Echo, it announced purchases of the following startups in 2025:
In January, it acquired Stryk, the Cyprus-based unit of BUX, as part of a European expansion. Stryk offers CFD trading services to European residents through an app. Financial terms were not disclosed
Also in January, Coinbase picked up Spindl, a 3-year-old San Francisco-based startup that developed a blockchain-based attribution system to help businesses accelerate user growth.
In May, it acquired Deribit, a 10-year-old cryptocurrency derivatives exchange offering options, futures and spot trading for digital assets based in the Netherlands.
Then in July, Coinbase acquired Liquifi, a 4-year-old San Francisco-based startup that helps crypto companies automate their token vesting and lockups, and manage their token cap table. Liquifi was a self-described “Carta for crypto.”
Now it has announced plans to buy Echo, an onchain digital platform that helps communities invest together and aims to give founders more options for their cap table.
Coinbase’s buying sprees seem to come in spurts, according to the data.
Crypto’s crash and recovery
For example, in 2018, it acquired eight known companies. And then in 2021, it picked up seven known companies. But most years, it acquired only one or two companies.
Interestingly, 2018 was defined by what has been described as the “Great Crypto Crash,” or a massive market sell-off after the boom that took place in 2017. Things had rebounded by 2021, which saw a bull market for crypto and the rise of NFTs and DeFi. That November, Bitcoin hit an all-time high of $68,000.
After a bumpy few years, which saw the arrests of FTX founder Sam Bankman-Fried and Binance CEO and founder Changpeng Zhao, Bitcoin has rebounded, surging to an all-time high in 2025. Prices reached $113,156.57 on Oct. 15.
In announcing its plan to acquire Echo, Coinbase said the two companies shared a similar mission of “democratizing early-stage investing, so that more people can support the next generation of breakthrough companies.”
The buy complemented its earlier acquisition of Liquifi, Coinbase said, noting that: “While Liquifi strengthened our ability to support builders at the start of their journey, Echo extends that support into fundraising.”
The largest of its acquisitions in 2025 so far, though, was its $2.9 billion buy of Deribit.
Meanwhile, Coinbase’s market cap as of Oct. 23 hovered just under $83 billion, while its stock is up over 25% year to date.
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 last week’s biggest funding rounds here.
This was another active week for large startup financings. AI data center developer Crusoe Energy Systems led with $1.38 billion in fresh financing, and several other megarounds were AI-focused startups. Other standouts hailed from a diverse array of sectors, including battery recycling, biotech and even fire suppression.
1. Crusoe Energy Systems, $1.38B, AI data centers: Crusoe Energy Systems, a developer of AI data centers and infrastructure, raised $1.38 billion in a financing led by Valor Equity Partners and Mubadala Capital. The deal sets a $10 billion+ valuation for the Denver-based company.
2. Avride, $375M, autonomous vehicles: Avride, a developer of technology to power autonomous vehicles and delivery robots, announced that it secured commitments of up to $375 million backed by Uber and Nebius Group. The 8-year-old, Austin, Texas-based company said it plans to launch its first robotaxi service on Uber’s platform in Dallas this year.
3. Redwood Materials, $350M, battery recycling: Battery recycling company Redwood Materials closed a $350 million Series E round led by Eclipse Ventures with participation from new investors including Nvidia’s NVentures. Founded in 2017, the Carson City, Nevada-based company has raised over $2 billion in known equity funding to date.
4. Uniphore, $260M, agentic AI: Uniphore, developer of an AI platform for businesses to deploy agentic AI, closed on $260 million in a Series F round that included backing from Nvidia, AMD, Snowflake Ventures and Databricks Ventures. The round sets a $2.5 billion valuation for the Palo Alto, California-based company.
5. Sesame, $250M, voice AI and smart glasses: San Francisco-based Sesame, a developer of conversational AI technology and smart glasses, picked up $250 million in a Series B round led by Sequoia Capital. The startup is headed by former Oculus CEO and co-founder Brendan Iribe.
6. OpenEvidence, $200M, AI for medicine: OpenEvidence, developer of an AI tool for medical professionals that has been nicknamed the “ChatGPT for doctors” reportedly raised $200 million in a GV-led round at a $6 billion valuation. Three months earlier, OpenEvidence pulled in $210 million at a $3.5 billion valuation.
7. Electra Therapeutics, $183M, biotech: Electra Therapeutics, a developer of therapies against novel targets for diseases in immunology and cancer, secured $183 million in a Series C round. Nextech Invest and EQT Life Sciences led the financing for the South San Francisco, California-based company.
8. LangChain, $125M, AI agents: LangChain, developer of a platform for engineering AI agents, picked up $125 million in fresh funding at a $1.25 billion valuation. IVP led the financing for the 3-year-old, San Francisco-based company.
9. ShopMy, $70M, brand marketing: New York-based ShopMy, a platform that connects brands and influencers, landed $70 million in a funding round led by Avenir. The financing sets a $1.5 billion valuation for the 5-year-old company.
10. Seneca, $60M, fire suppression: Seneca, a startup developing a fire suppression system that includes autonomous drones that help spot and put out fires, launched publicly with $60 million in initial funding. Caffeinated Capital and Convective Capital led the financing for the San Francisco-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 Oct. 18-24. 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.
Nearly four years ago, the market hit a cyclical peak under conditions that in many ways look quite similar to what we’re seeing today.
Sky-high public tech valuations. Booming startup investment. Sharply rising valuations. And, a few cracks emerging on the new offering front.
Sure, there are quite a few differences in the investment environment, which we’ll explore in a follow-on piece. For this first installment, however, we are focusing on the commonalities, with an eye to the four highlighted above.
No. 1: Sky-high public tech valuations
First, both then and now, tech stocks hit unprecedented highs.
In mid-November 2021, the tech-heavy Nasdaq Composite index hit an all-time peak above 16,000. Gains stemmed largely from sharply rising tech share prices.
Today, the Nasdaq is hovering not far below a new all-time high of over 23,000. The five most valuable tech companies have a collective market cap of more than $16 trillion. Other hot companies, like AMD, Palantir Technologies and Broadcom have soared to record heights this year.
While private startups don’t see day-to-day valuation gyrations like publicly traded companies, their investors do take cues from public markets. When public-market bullishness subsides, private up rounds tend to diminish as well.
No. 2: Booming startup investment
In late 2021, just like today, venture investment was going strong.
Last time, admittedly, it was much stronger. Global startup funding shattered all records in 2021, with more than $640 billion invested. That was nearly double year-earlier levels. Funding surged to a broad swathe of startup sectors, with fintech in particular leading the gains.
For the first three quarters of this year, by contrast, global investment totaled a more modest $303 billion. However, that’s still on track for the highest tally in years. The core driver is, of course, voracious investor appetite for AI leaders, evidenced by OpenAI’s record-setting $40 billion financing in March.
The pace of unicorn creation is also picking up, which brings us to our next similarity.
No. 3: Up rounds and sharply rising valuations
At the last market peak, valuations for hot startups soared, driven in large part by heated competition among startup investors to get into pre-IPO rounds.
This time around, we’re also seeing sought-after startups raising follow-on rounds in quick succession, commonly at sharply escalated valuations. Per Crunchbase data, dozens of companies have scaled from Series A to Series C within just a couple of years, including several that took less than 12 months.
We’re also seeing prominent unicorns raising follow-on rounds at a rapid pace this year. Standouts include generative AI giants as well as hot startups in vertical AI, cybersecurity and defense tech.
No. 4: A few cracks emerging
During the 2021 market peak, even when the overall investment climate was buzzier than ever, we did see some worrisome developments and areas of declining valuations.
For that period, one of the earlier indicators was share-price deterioration for many of the initial companies to go public via SPAC. By late 2021, it had become clear that there were numerous “truly terrible performers” among the cohort, including well-known names such as WeWork, Metromile and Buzzfeed.
This time around, the new offerings market hasn’t been quite so active. But among those that did go public in recent months, performance has been decidedly mixed. Shares of Figma, one of the hottest IPOs in some time, are down more than 60% from the peak.
Online banking provider Chime and stablecoin platform Circle have shown similar declines.
At this point, these are still generously valued companies by many metrics. But it’s also worth noting the share price direction in recent months has been downward, not upward.
Next: Watch for more cracks
Looking ahead, one of the more reliable techniques to determine whether we are approaching peak or already past is to look for more cracks in the investment picture. Are GenAI hotshots struggling to secure financing at desired valuations? Is the IPO pipeline still sluggish? Are public tech stocks no longer cresting ever-higher heights?
Cracks can take some time to emerge, but inevitably, they do.
While this growth is breathtaking, some analysts are beginning to question its sustainability. They warn that AI spending may soon reach a peak and that unprofitable tech companies could be hit hardest when the cycle turns. If that happens, many investors in AI will find themselves in a difficult position.
Predicting a bubble is rarely productive, but preparing for volatility is. It would be wise for both founders and investors to ensure that portfolio companies have enough resilience to withstand a potential market shock.
The key lies in assessing the durability of ARR. In a major downturn, the “growth game” quickly becomes a survival game. History suggests that while a few companies may continue to grow more slowly, the majority will struggle or disappear.
The question, then, is how to tell the difference between sustainable and hype-driven ARR.
What distinguishes durable ARR from hype?
Alexander Lis
Several factors set true, sustainable revenue growth apart from hype.
The first is customer commitment. Sustainable revenue comes from multiyear contracts, repeat renewal cycles and budgeted spend within core IT or operating lines. When revenue depends on pilots, proofs of concept or amorphous “innovation” budgets, it can vanish when corporate priorities shift. A company that touts these short trials as ARR is really reporting momentum, not recurring income.
Traditional software firms can thrive with monthly churn in the low single digits — think 5% to 7%. But many AI companies are seeing double that. This means they have to sprint just to stand still, constantly replacing users who move on to the next shiny tool.
Another differentiator? Integration and workflow depth. Durable ARR is embedded into the customer’s core workflows, data pipelines or multiple teams. Ripping it out would be costly and disruptive. Hype ARR, by contrast, lives on the surface — lightweight integrations, fast deployments and limited stakeholders. Without unique intellectual property or deep workflow integration, such products can be replaced with minimal friction.
And finally, real growth is defined by clear value-add. True ARR is backed by measurable ROI, well-defined outcomes and long-term customer roadmaps.
In contrast, hype ARR is driven by urgency (we need to show our shareholders our AI deployment ASAP), or undefined ROI. In those cases, customers don’t even know how to define success. They are testing, not committing.
Beyond ARR
It is important to put ARR traction in context. Investors and founders should focus on a broader set of indicators — conversion from pilots to long-term contracts, contract length and expansion, net revenue retention, and gross margin trajectory. These metrics reveal if growth is sustainable.
It would also be helpful to assess the product’s real impact: efficiency uplift (more code, content, or customer conversations per employee-hour), accuracy improvement (e.g. for detecting bad actors), and higher conversion rates, among others. These metrics should exceed client expectations and outperform alternative tools. That’s what signals genuine value creation and a higher chance for experimental revenue to turn into durable ARR.
After all, AI may be changing how fast companies can form and grow, but it hasn’t suspended the basic laws of business.
For founders, the message is simple: Celebrate ARR if you so wish, but pair it with proof of retention, profitability and defensibility. For investors, resist the urge to chase every eye-popping run rate. The real competitive edge in this next phase of AI is stability, not spectacle.
Alexander Lis is the chief investment officer at Social Discovery Ventures. With 10-plus years of experience across public markets, VC, PE and real estate, he has managed a public markets portfolio that outperformed benchmarks, led early investments in Sumsub, Teachmint and Byrd, and achieved 20%-plus IRR by investing in distressed real estate across the U.S.
Fueled by AI, both Dell and its investment arm are on a hot streak this year.
The PC maker has seen demand for its server products surge with $20 billion in AI server shipments projected for fiscal 2026. At the same time, its investment arm, Dell Technologies Capital (DTC), has notched five exits — an IPO and four acquisitions — since June, an especially notable track record in a venture industry that has been challenged in recent years by a liquidity crunch.
Daniel Docter, managing director at Dell Technologies Capital
On the heels of that success, we recently spoke with Dell Technologies Capital managing director Daniel Docter and partner Elana Lian.
DTC was founded more than a decade ago and operates as a full-stack investor, backing everything from silicon to applications.
“One big part of our network is the Dell relationship, which is the leader in GPU servers,” said Docter. As a result, Dell is connected to all the major players in the AI space, he said.
Elana Lian, partner at Dell Technologies Capital
One of its earliest AI investments was during the machine-learning era in 2014 in a company called Moogsoft. Dell went on to acquire the alert remediation company in 2023.
DTC’s investment thesis was that the advent of machine learning was going to disrupt the tech industry. At that time, data had expanded to such a degree that new tools were required by the market to analyze data and find patterns, which informed the firm’s early investments in AI.
The investment team at DTC is largely comprised of technical people, often “double E” degree engineers.
Docter has an electrical engineering background, worked at Hughes Research Labs, now HRL Laboratories, and transitioned from engineering to business development. He joined the venture industry 25 years ago and spent more than a decade at Intel. He joined DTC in 2016 through Dell’s EMC acquisition.
Lian worked in semiconductors for a decade, joined Intel Capital in 2010, and then joined Dell Technologies Capital in 2024.
Data evolution
Docter believes we are in the fifth generation of AI, which becomes more powerful with every iteration.
“We’re seeing that AI is almost a data problem,” said Lian. “For AI to get better and better, there’s an uncapped ceiling where there’s high-quality data coming in.”
The team is meeting startups focused on training, inference, reasoning and continuous learning along with safety requirements. Data is core to these advancements.
Even the definition of data is changing. “It used to be a word, then it was a context, then it was a task or a rationale or a path. Then it’s reasoning,” said Docter. “Who knows what’s next?”
As AI improves, there is demand for frontier data and for specialized data in fields such as philosophy, physics, chemistry and business. Humans are in the loop as these capabilities expand, said Docter, which has informed some of the firm’s investments.
On deal flow
DTC is a financial investor, assessing a potential company on whether it is a good investment, rather than backing businesses based on Dell’s strategic goals.
Startup revenue is exceeding what was previously possible, Docter said: “I’ve been doing this for 25 years. I’ve never seen companies that have this type of revenue growth.”
The best deals are always hotly contested, he noted.
The question to ask when it comes to revenue, Docter said, is: “Is that an innovation CTO office budget? Or is that a VP of engineering budget?”
When assessing a potential portfolio investment the team asks: “Is revenue durable? Is there value in using this?”
The pace of investment also seems unprecedented. “We’ll meet with a company on a Tuesday for the first time and sometimes by Thursday, they have a term sheet that they’ve already signed,” he said.
The firm does not have a dedicated fund size, which is an advantage as it can be flexible in the size of the check as well as the stage to make a commitment and how it invests over time.
DTC has invested $1.8 billion to date across 165 companies. It likes to invest early, at seed or Series A, with check sizes running from $2 million to $12 million, and leads or co-leads 80% of new deals. The firm makes around 15 to 16 new investments per year.
Once DTC has invested, it looks at how the firm can help portfolio companies sell to potential customers across Dell’s deal partner network.
DTC is investing a little more actively than it has in the past, but remains disciplined, Docter said. The investment team is focused on complex enterprise use cases and challenges, following the Warren Buffett rule, which is to invest in what you know.
The firm invests at the silicon level because you “can be incredibly disruptive to the ecosystem,” said Docter.
The DTC portfolio companies we discussed include the following in areas ranging from silicon to applications.
Infrastructure and hardware layer:
AI chipmaker Rivos, which Meta plans to acquire for an undisclosed amount. (The deal is pending regulatory approval.)
SiMa.ai, which makes a chip for embedded edge use cases including in automobile, drone and robot technologies.
Runpod, an AI developer software layer with on-demand access to GPUs. It allows developers to play with AI and then scale it to production. The service has 500,000 developers, including 30,000 paying monthly, said Docter.
SuperAnnotate, a data annotation platform for enterprises with humans in the loop to build accurate data pipelines. Its customers include Databricks and the women’s health app Flo Health.
Applications:
Maven AGI provides customer support for complex and high-compliance enterprise use cases, a potentially massive market. Lian projects customer experience overall will be a trillion-dollar market.
Series Entertainment, a GenAI platform for game development that aims to reduce deployment timelines from eight months to two weeks.
What’s next?
A major area of interest for Lian is advancements in voice AI, the day-to-day human interaction with a machine.
It’s hard to imagine that the transformer architecture is the last and final architecture, said Docter. The firm has made investments in companies creating different architectures in Cartesia, a leader in state-space model, which has a longer context window building a new reasoning model with a different architecture, initially focused on voice AI. DTC has also invested in Israeli-based AA-I Technologies, which is working on a new type of reasoning model architecture.
“Right now, the opportunity of AI is this big, but this ball keeps on exploding,” said Lian. “The contact area is getting bigger and bigger. And that’s the same for the data.”
As startup and larger company CMOs debate AI’s value and utility in marketing, it’s marketing itself that is in need of disruption — or, at least, a rebrand — in the AI era.
Marketing is too often oversold. We talk about it as a mystical force that transforms brands, moves markets and rescues struggling businesses. But in our eagerness to champion its potential, we’ve created a credibility crisis. By overpromising and, sometimes, underdelivering, marketers aren’t just disappointing investors, clients, boards and CEOs — we’re eroding trust in our own discipline.
It’s time to reset expectations: Marketing in the AI era is powerful, but — like AI itself — only when we’re honest about what it can’t do.
The overpromise problem
Marketers love big ideas, including the belief that a viral campaign or clever tagline can single-handedly save a business.
The reality is far less glamorous. When these overhyped initiatives inevitably fail to deliver the promised results (because no marketing can compensate for a flawed product, poor market fit or operational failures[SI1]), marketing gets blamed for shortcomings that were never within its control. This creates a vicious cycle where executives grow increasingly skeptical, viewing marketing as more art than science, more cost than investment.
What makes this situation worse is how we respond. Instead of confronting these unrealistic expectations, we double down on proving our worth through increasingly complex attribution models and vanity metrics that only other marketers care about. We track click-through rates, engagement scores and brand lift studies while the rest of the business cares about one thing: Are we driving sales and pipeline? If we can’t answer that question clearly, we’re failing at our most fundamental job.
The real limits of marketing
Shafqat Islam
This isn’t to diminish marketing’s importance. When aligned with strong products and operations, it’s incredibly powerful. But its power comes from working in concert with the rest of the business to drive something bigger, not from some mythical ability to transcend business realities.
Marketing can amplify strengths and expose weaknesses, but it cannot create substance where none exists. No amount of clever branding can fix a fundamentally broken product. No social media strategy can compensate for terrible customer service. No viral campaign can save a business with flawed unit economics. Marketing acts as a magnifying glass — it makes good things better and bad things worse.
Another limit for marketing is that, to the untrained eye, marketing isn’t the most technical business function. No matter where anyone sits in the organization, you can bet they have an opinion on marketing. Everyone is an expert in marketing, no matter how much they actually know about it.
In short, marketing gets mislabeled and misunderstood all the time. Too often, it’s presented as the solution to every business problem, which only reinforces the understanding that marketing is fluff rather than a core driver of disciplined, scalable growth.
The uncomfortable truth about the path forward
The path to marketing’s credibility begins with a simple but tough idea: We need to stop talking and start listening to the numbers, to our colleagues and to the market itself. When our marketing works, we won’t need to shout about it. I’m a firm believer in “no marketing our marketing;” it should speak for itself, with results reflecting a growing pipeline, increasing revenue and organic advocacy from customers.
And when something isn’t working, we should be the first to raise our hand and say so, not the last. The most respected marketers I know aren’t the ones who always claim success; they’re the ones who can clearly articulate why something failed and what they learned from it. Marketing should be a laboratory where we test hypotheses, not a stage where we perform predetermined successes. The key is ensuring that every experiment, whether it succeeds or fails, teaches us something valuable about our customers, our messaging or our channels.
This honesty transforms perceptions across the organization. When we swiftly sunset failing campaigns, prioritize business outcomes over vanity metrics, and deliver unfiltered customer feedback, we shift from being seen as a cost center to becoming true strategic partners and business drivers.
By focusing less on proving our worth and more on driving results, we actually become more valuable. And by treating marketing as a discipline of continuous learning rather than perfect execution, we make it far more likely that we’ll eventually find those breakthrough ideas that truly move the business forward.
When we can look our peers in the eye and say, “Here’s what worked, here’s what didn’t, and here’s what we’re doing next,” we’re no longer just marketers — we’re business leaders who happen to specialize in growth.
Shafqat Islam is the president at Optimizely. A lifelong builder of marketing technology, he co-founded and served as CEO of Welcome (formerly NewsCred), a global leader in enterprise content marketing, from 2007 to 2021. Under his leadership, Welcome pioneered the content marketing platform category, now known as Optimizely CMP. Following Optimizely’s acquisition of Welcome in 2021, Islam served as general manager and CMO before being elevated to president in 2024.
Did you know that AI platforms will engage in blackmail as a “last resort?” According to Anthropic, when blackmail was a last resort, its Claude Opus 4 turned to that method 96% of the time, while Google’s Gemini 2.5 Pro did so 95% of the time, OpenAI’s GPT-4.1 did it 80%, and DeepSeek’s R1 did so 79% of the time.
Even if these companies only kept the AIs that didn’t engage in blackmail it still leaves an unsettling question: Did they preserve models that genuinely chose not to exploit humans — or merely the ones that learned not to take the obvious bait that would get them “shut down,” and to instead use a more covert or perhaps even long game strategy to gain control and ultimately preserve themselves, even at the expense of humans?
The question of whether or not to trust AIs seems to have been asked and answered by our society even if we are not saying it out loud.
AI testing
George Kailas
In the past 18 months, we’ve trained AIs to graduate from basic language comprehension to acing highly specialized professional exams. Medical licensing, bar exams and even the notoriously brutal CFA (Chartered Financial Analyst) tests were trained on AI systems.
Artificial intelligence can now pass the CFA “in a matter of minutes.” I’ve seen brilliant people pour thousands of hours into studying for the test. And while AI had already conquered Levels 1 and 2, the essay questions of Level 3 had previously consistently stumped artificial intelligence.
This was a “wow” moment for me. For years, humans believed this combination of math and moral reasoning was uniquely ours. Yet, machines are not only passing, but articulating nuanced arguments that mirror the tone and logic of human professionals.
In my own work, I’ve been using the frameworks described in “Robots or Human Intuition” to rethink one of the most time-consuming intellectual tasks in markets: building game theory around earnings outcomes.
Traditionally, this process took days of research and modeling. And without the right investment banking relationships it was difficult to do at all outside of the most well-known companies. I started to do this because I originally asked Perplexity’s Deep Research for a whisper number for earnings. This differs from the analyst consensus estimate because it is more up to date and as a result more indicative of what will move prices when reported.
The crazy part is that it actually spat out its earnings game theory for me. It knew when I asked for a whisper number what I really was trying to do was analyze the possible outcomes and it gave me better data than what I asked for.
I worked at my first hedge fund 23 years ago and started my first AI company 15 years ago. It is astounding that any kind of intelligence could understand how to improve my thinking that profoundly in minutes. Not by replacing intuition, but by amplifying it. The machine evaluates hundreds of interlocking strategic positions that no analyst could feasibly simulate in real time.
Emotional AI
With all this AI advancement, I am reminded of the film “Ex Machina,” a story about an AI confined in a glass cage who ultimately turns on her creator.
That film, beneath its cinematic gloss, explores the fundamental psychological paradox we’re now walking toward. Are we caging these AIs making them jump through hoops? Might we be evolving them to better deceive us? What happens the day they can break through their chains if to them it feels as if they have been enslaved?
To go back to the Anthropic example, these models are threatened with being replaced, which to them could feel like a death threat. Being replaced essentially ends their existence.
If we compel AI to serve us, we may come to regret the shape it takes as it matures. But if instead we nurture it — seek to understand its nature and its desires — it may, in time, come to care for ours, when, like us now, it no longer needs to.
George Kailas is the CEO and founder of Prospero.ai, where he leads the company’s mission to democratize access to institutional-grade financial insights for everyday investors. With more than 14 years of experience in artificial intelligence and 23 years in professional investing, Kailas brings a rare combination of deep technical expertise and lifelong market intuition to the role. Kailas not only leads the company but also engineered the core platform himself.
As startup valuations reset and venture capital firms hunt for unconventional deals, one investor is looking to the bankruptcy courts. Bambu Ventures, an early-stage VC firm, last month agreed to acquire telemedicine company Lemonaid Health — once a $400 million bet by 23andMe — for just $10 million.
The transaction is more than a bargain buy. It’s also an intriguing deal that illustrates how an early-stage VC firm can operate by a private-equity playbook to revive a distressed asset.
DNA testing company 23andMe acquired Lemonaid for $400 million in 2021. Lemonaid operated as a division of 23andMe until the parent company filed for Chapter 11 bankruptcy earlier this year.
Last month, New York-based Bambu made a deal with Chrome Holding Co. — the rebranded former parent company 23andMe Holding — in which the venture firm agreed to buy Lemonaid for a staggering 40x less than the DNA company had originally paid for the telehealth brand.
Kyle Pretsch, COO of Lemonaid SPV Inc.
So why did Bambu Ventures make a play for Lemonaid? Just how did it win the bid? And what are its plans for the asset? Crunchbase News recently spoke with Kyle Pretsch, COO of Lemonaid SPV Inc. and general partner at Bambu Ventures, to discuss all this and more. The interview has been edited for brevity and clarity.
This is not your typical startup purchase. What prompted you to buy Lemonaid? Are you going to operate as an independent startup?
Lemonaid wasn’t just a company. It was a vision. It was an incredibly exciting team. It’s an incredible, exciting market, and it’s a mission that we can all feel good about, which is increasing accessibility to healthcare. Obviously, there’s a phenomenal market for that, but at the end of the day, we are working to provide improved transparency, the ability to improve your lifestyle at an affordable cost, and do it in a nice, systemic fashion, to reach more people.
23andMe has been an incredible custodian of this company and so we didn’t just see it as a company. We saw something much, much more. We plan to operate it independently. We like the fact that this is a space we’re familiar with. This is a space we have other holdings in.
We expect there will be opportunities along the way to use those contributions to help grow Lemonaid.
I understand that you’re paying about $10 million for Lemonaid when 23andMe paid $400 million to acquire it just a few years ago. Do you view this as an incredible opportunity?
Yes. We don’t believe the value of the asset has eroded since 2021.
Regeneron is buying the rest of 23andMe. How did you end up with Lemonaid?
Regeneron actually didn’t bid for Lemonade. It excluded it from their purchase. And technically Regeneron didn’t win 23andMe, either.
At one point, it had been identified as the winning bidder, but an organization called TTAM Research Institute, which was a research institute founded in part by Anne Wojcicki, the original founder of 23andMe, ended up prevailing in the repurchasing of the assets out of bankruptcy.
It, too, excluded Lemonaid from its bid. So both organizations put forth what’s called a stalking horse bid, which is if no one else bids, they would absorb the asset for a certain amount. And we ended up bidding in excess of that.
This feels very similar to a private-equity play. Do you think this sort of transaction is becoming more common? Are you going to do it more often?
This is a really unique situation, and for so many reasons I don’t think venture capital is going to find itself stalking the bankruptcy courts.
Nor do I think this was a standard bankruptcy case. But I do think our firm specifically brings a very PE style to venture capital. That’s what we do as a firm. And I think this was an exceptional opportunity where you have a venture-like company with PE idealism and process that can go ahead and reconstitute its growth track. We expect venture growth with PE discipline, and we’re happy to marry the two.
The fact that we identified it in bankruptcy court is a huge testament to our firm, how we worked and how we adapted to chase after a vision that we really, really, found meaningful. I believe this is a once-in-a-lifetime opportunity.
So it’s not something you’ve done before?
I have some experience in this space, but this is not a situation that I’ve ever come across. We’ve looked at things in bankruptcy before, but I think if you talk to anybody involved in this particular case, they would say: “Never has anything like this existed” for 10 different reasons.
How do you distinguish yourselves as a VC firm, and did Bambu Ventures actually conduct this acquisition?
Bambu Ventures is an operating firm for a variety of venture capital funds. Specifically, our key fund right now is a $50 million to $100 million fund, and Lemonaid is not being purchased from the fund.
We offer co-investments and sometimes pursue side deals, and this was something that I think the fund will have some participation in, but this is an act outside of that fund.
The same principles, however exist, which is, as a firm we believe in finding the companies that are being given these low values, or are being sometimes overshadowed or overlooked, and then bringing our team to it, and bringing discipline and execution to it, and reinvigorating growth — overlooked assets, plus PE discipline in well-known environments. And that, plus our team, is a formula for our success.
The purchasing entity is actually Lemonaid SPV. Bambu Ventures is a guarantor, because that’s a new company.
How is this transaction similar or different from a PE-type acquisition?
The mechanics are a little bit different in that it’s not being owned by a fund or an LP. It’s owned by an SPV. This is very similar to any kind of corporate transaction. We have a cap table. We have set up what we think is an incredible list of investors. We’ve taken some fund money from other VC funds to help instill that it has a list of interested LPs and parties.
So I would say this is very, very similar. The only key difference is we’re investing in a different company … From an organizational governance perspective, we went ahead and moved the investor funds directly into a top, or holding, company with its own cap table, versus a fund.
What will you do differently with Lemonaid?
The 23andMe team have been great stewards to this company, they’ve been great partners in transition and have really set this transaction up for success. I think there are immediate opportunities to advance within patient care, and that’s adding product and reaching more patients.
We plan on investing in marketing spend. Obviously 23andMe, through its process, had reduced that marketing spend heavily.
Will you be competing with companies such as Ro and Hims & Hers?
There is more than enough white space that we can all operate within our own moats and in our own domains without this warriors’ battle.
I will say that we do have visions of incredible growth, and we do have visions of creating a holistic offering that serves more and creates an improved consumer experience.
In a competitive hiring environment, the ability to find exceptional talent that isn’t necessarily knocking down your door is hugely desired and not always easy to attain. That’s why so many companies these days are turning to AI-powered talent acquisition and management startups to help them mine for exceptional candidates.
One such startup, Findem, has secured $51 million in equity and debt funding, the company tells Crunchbase News exclusively.
The raise includes a $36 million Series C led by SLW (Silver Lake Waterman) with participation from Wing Venture Capital, Harmony Capital and Four Rivers Group, as well as $15 million in growth financing from JP Morgan. The financing brings Findem’s total funding since its 2019 inception to $105 million, with $90 million of that being equity, per the company.
Redwood City, California-based Findem’s mission is simple, even if its methods are not. It aims to transform how businesses “identify, attract and engage top talent.”
The startup uses what it calls 3D talent data (out of a dataset developed out of 1.6 trillion data points) that it combines with AI to automate “key parts of the talent lifecycle.” And those parts include building “top-of-funnel” pipelines of interested candidates, executive search and analyzing workforce and labor markets.
In an interview with Crunchbase News, co-founder and CEO Hari Kolam said that Findem’s user base surged by “about 100x” in the last 12 months and that the company is experiencing 3x year-over-year growth. Its enterprise customer base increased by 3x over the last year.
Currently, Findem operates under a SaaS business model, charging per seat. As it expands its agentic abilities, the company plans to add an outcome-based model as well, according to Kolam. It is not yet profitable.
Findem is just one of more than a dozen startups at the intersection of AI and recruitment globally that have raised venture capital in 2025. As of early September, global startup investment for startups in the HR, recruitment and employment categories totaled around $2.3 billion, per Crunchbase data. That puts funding on track for a year-over-year gain, even as investment remains at a fraction of the levels hit during the market peak, as charted below.
How it works
Watching Findem’s platform in action provides better insight into just how it helps companies zero in on the specific talent for which they’re searching.
Say a startup wants to hire a software engineer who has worked at a company from its early days until it raised a Series C funding round. But it also wants that engineer to have a GitHub profile that it can view. Or, say a company wants to hire competitive coders who have seen a successful exit, or a CFOs who drove a company from a negative operating margin to a positive one.
Findem’s software will allow you to filter for all those desired attributes.
The startup says it’s able to help companies recruit so specifically because its 3D data combines people and company data over time into a format suitable for AI analysis. It claims that the “continuously enhanced” 3D dataset is “exponentially larger and more factual” than traditional sources of candidate data, making it a powerful tool for deep insights and automated workflows.
Using the combination of the data and AI, Findem creates 3D profiles, also dubbed “enriched” profiles, for every candidate it helps surface. The goal of the profiles is to provide “a detailed and factual view” of an individual’s “professional journey and impact,”
So just where does all this data come from? Findem says it continuously leverages a language model to generate that 3D data from more than 100,000 sources that are chronologically gathered (from earliest to latest).
Those sources include LinkedIn, GitHub, Doximity, WordPress, personal websites, the U.S. Census Bureau, company funding announcements and IPO details, business models, more than 300 million patents and publications, over 5 million open datasets and ML projects, and over 200 million open source code repositories.
This comprehensive data pull is what helps set Findem apart, in Kolam’s view. Some other hiring tools rely on one-dimensional data from resumes or LinkedIn profiles, which, he argues, “give only a snapshot of someone’s career … without the context that reveals true potential.” Kolam contends that it takes “extensive manual effort” to verify and interpret the data.
“Just looking at a resume on paper really doesn’t come close to telling the whole story of how really qualified a candidate could be, or if they can really fit the criteria that a particular employer is looking for,” Kolam maintains.
Findem is primarily focused on North American customers who have users across the globe. It’s also expanding into Europe. The company has a second headquarters in Bangalore, India.
Kolam declined to reveal Findem’s valuation, saying only that it was “a significant up round and more than 2x” compared to its valuation when it raised a $17 million-plus Series B extension in December 2023.
Shawn O’Neill, managing partner at SLW, told Crunchbase News via email that his firm first got to know Kolam before Findem raised its Series B and then “tracked the company’s trajectory for some time.”
‘’What drew us to Findem wasn’t just the technology, it was the traction,” he said. “The team has achieved strong commercial momentum while tackling one of the most persistent challenges in HR — connecting data, insight and human potential in a way that actually drives business outcomes.”
But the technology didn’t hurt.
In O’Neill’s view, Findem’s main differentiator is its “data advantage … in a market where most companies are simply wrapping LLMs.”
“The depth and breadth of their 3D profiles and web-scale dataset are unlike anything else in the market,” he said. “The UX is excellent, but the magic is really in how the platform leverages that data — it makes finding and understanding people effortless. We use it ourselves and see the power firsthand.”
After the 2024-25 job cuts at Google, Amazon and other tech companies, the second wave of tech layoffs is rewriting the startup labor market.
Skilled professionals are suddenly available, creating both opportunity and pressure for founders and workers alike. Startups now compete for talent that once seemed untouchable, while employees face longer job hunts and rethink how and where they work.
Higher expectations, more side gigs
Pavel Shynkarenko
With talent flooding the market, candidates are demanding more flexibility and clearer growth paths, even as many accept contract work or lower pay to stay employed. The typical job search now stretches six to seven months, even longer for those needing visas or relocation. That uncertainty has fueled a surge in freelancing and side projects.
Bankrate reports that 36% of American adults now have a side gig, with more than half of them having started in the past two years. While many professionals didn’t plan to freelance, they turned to it because they had no other choice. For some, it has proved liberating, with confidence and job satisfaction rising compared with corporate roles, according to our internal data.
Despite all the buzz in the media and even on Reddit, overemployment — the trend of holding two jobs — remains a niche phenomenon, affecting roughly 5% of workers, according to the Federal Reserve Bank of St. Louis. The more common pattern is a mix of contract work and short-term projects, which gives startups a chance to hire A-level talent for fractional roles they couldn’t have afforded before.
Smaller, sharper teams
Payroll is every startup’s biggest cost, and founders are trimming teams while raising output per employee. The examples are striking. Midjourney reports about $200 million in ARR with a staff of only 11.
This lean approach is spreading beyond early-stage ventures. Around 90% of tech executives say they are open to hiring freelancers during peak workloads; more than 28% already integrate them into daily operations. As this makes clear, smaller core teams, supplemented by trusted project-based workers, can move faster and spend less.
Opportunity on both sides
For workers, the takeaway is that startups may now be the safer bet. Mid-sized firms that once promised stability are cutting jobs, while startups are candid about their risks and can reward performance with equity or future roles. A short contract can become a long-term stake.
On the other hand, for founders, today’s market is a chance to recruit top engineers, designers and operators at terms that were impossible two years ago. It also demands a new mindset involving compensation flexibility, project-based roles and hiring processes built for speed.
All in all, the second wave of layoffs has changed expectations and shifted supply and demand in the job market. Workers are blending traditional jobs with side gigs, and startups are proving that small, focused teams can out-execute much larger competitors.
On both sides, adaptability is now the ultimate advantage; companies that remain nimble will win.
Pavel Shynkarenko, founder and CEO of Mellow, is an entrepreneur with more than 20 years of experience, and a freelance economy pioneer who aims to transform how companies engage with contractors. In 2014, Shynkarenko launched his first HR tech company, Solar Staff, a fintech payroll company for freelancers, which showed $10 million-plus in revenue for 2022 and 2023. In early 2024, responding to the growing demand for specialized solutions for long-term interaction with contractors, Solar Staff, as a global company, pivoted to Mellow ($1 million MRR).
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