Building a $200M Bootstrapped Chess Empire with Chess.com CEO Erik Allebest

Summary

• Chess.com will do “a little over 200 million” in revenue this year with ~10M DAU, 40–50M MAU and 250M+ registered members—built without primary capital from a domain Allebest says they bought out of bankruptcy for $56K in 2005. Sand Hill Road called it “uninvestable”; Allebest grew “at the speed of cash,” charging memberships within ~18 months of the 2007 launch, and only in 2024 concluded this was a big business. The new ambition: “a billion people should be playing chess.”
• The demand came in waves that kept resetting the baseline higher—the growth compounded. Pre-COVID the site had ~1M DAU; the COVID/Queen’s Gambit spike he feared was “a flash in the pan, like treadmills and sourdough bread,” but a second 2023 wave—short-form content, the Mittens bot, the cheating scandal, and kids playing in schools—left the business on a much higher baseline by 2024.
• The recent CVC deal is secondary only; General Atlantic reinvested, and the investments described did not infuse primary capital. Against the PE trope, Allebest says both firms are “in the weeds on the product and the community” and helped drive operational maturity—while he “really did not enjoy” most other PE suitors, who were “focused on the wrong things.”
• Allebest’s answer to the machines-beat-humans question is that humans want to do human stuff—and AI can make chess more exciting. Stockfish’s perfection briefly made elite chess “pretty boring”; neural-net Leela Chess Zero then beat Stockfish with aggressive, unconventional play that “pushed the game forward,” and AI now powers coaching, game review and personalized puzzles.
• New product: Gambit (gambit.com) brings the chess rating playbook to poker—a skill rating rather than chips alone as the scoreboard. “How good are you really? Not just can you buy the most chips”; he predicts players will “care about it as much as money,” confessing “losing 100 rating points on my poker rating just really bothers me.”
• His founder advice is contrarian by lived example: he did the exact opposite of the 2005 playbook—hired a friend from San Jose State, worked remotely, raised nothing, paid nothing for acquisition, and picked a tiny market. “Stop listening to people just giving you advice on what to do. Just go do it.”
• On superhuman intelligence and AGI/ASI, he believes superhuman intelligence will move at a faster and faster pace, is “more optimistic than pessimistic,” but frames the risk as cultural, not technical. “The people who should probably not be in charge of the world are in charge”—while Guo reads chess’s growth as evidence that human skill stays relevant under superhuman AI, calling the contrary idea “nonsense.”

Deep dive

1. From a $56K bankruptcy-auction domain to $200M revenue, at the speed of cash

• The scale, in Allebest’s own surprised telling: ~10M daily actives, 40–50M monthly, 250M+ registered members, “a little over 200 million” in revenue expected this year, and a 650-person fully remote team—“more revenue than I thought we would end up with as a chess company.”
• The origin: he and a friend bought the chess.com domain for $56,000 in a 2005 bankruptcy auction, aiming to “be like MySpace” for chess. At Stanford Business School with Sand Hill Road next door, “basically most of them said this is uninvestable. You should get a real job.” Classmates passed too; he put in his own money and borrowed a little from his friend’s mom.
• The operating model: launched 2007, memberships for online chess learning within ~18 months, quickly profitable, hiring one person at a time as revenue allowed. They kept vowing “we’re never going to have more than 50 people… then 100”—until they stopped saying it. Now he asks: if 250M people have said they want to play chess at some point on Chess.com, “why don’t we have 50 million daily active users? A billion people should be playing chess.”

2. The growth arrived in waves—and only in 2024 did he believe it

• Before COVID they had ~1M DAU and were shocked at that. COVID plus Queen’s Gambit spiked usage, but “we’re like, oh, this might just be a flash in the pan, like treadmills and sourdough bread.” The base held below the 2022 peak—then 2023 brought another wave from short-form content, the Mittens bot, and the cheating scandal, with kids playing in schools. “When we came down again, we were so much higher and we maintained this baseline.”
• His candor on growth psychology: shrinking is scary, flat is scary, growing is scary—“it’s been pretty white knuckle” on scalability, and only the last 12 months have been calm, with the team in place and growth predictable.
• The cultural shift he says Chess.com was partly responsible for: chess was “almost like a secret hobby” he hid as a skater-snowboarder; now his kids’ friends all play, “the jocks play chess and the nerds play chess,” Louis Vuitton centers a whole fashion shoot on it, and Lewis Hamilton plays on his private jet. Chess.com’s contribution was redefining what it meant to be a chess player: previously “you weren’t really a chess player until you were 2,000 or above”—now “we celebrate your mistakes and when you hang your queen… if you’re rated 500, that’s fine. You’re still a chess player.”

3. The CVC deal is secondary-only—and PE, against type, made them better

• The cap-table history as told: early investors who said “I’ll hold this forever” needed liquidity years later, forcing the company to seek larger investors. General Atlantic and Tenzing came in in 2020 or 2021; the investment bought secondary shares. Now CVC—which Allebest says brought “deep experience in gaming, in sports, in community businesses”—has bought out shares, with General Atlantic reinvesting. “We’re still a bootstrapped business… no capital needed to grow this business.”
• Guo flags the conventional wisdom about PE involvement; Allebest’s rebuttal is specific: it hasn’t been “give you money and then just say work harder.” GA and CVC are “in the weeds on the product and the community,” helping push forecasting and operational excellence that improved actual operations, not just reporting—though he concedes he “really did not enjoy” the broader PE process and most people he met were “focused on the wrong things” until GA and Tenzing backed the mission-first thesis.

4. Chess isn’t patentable, so product wins—and Lichess is “the Linux” of chess

• Twenty years ago the “industry” was FICS, ICC and Yahoo Chess; Chess.com won by building what they wanted as players—free to play, in the browser, “a wonderful experience.” With thousands of chess apps in the store, “really product is going to win out, and community and content.”
• On coexistence: Lichess “exists for a really important reason… it’s open source, it does what it does and we coexist”—Chess.com drives growth through investments its revenue enables. And on never raising: for pure software and content with “no major tech company bearing down on us,” the slower road built the culture; he grants that hardware, inventory, or speed-critical markets are different.

5. Superhuman engines made chess more exciting—and taught him how humans learn

• Asked about Deep Blue’s lesson 30 years on, Allebest says “fundamentally, humans want to do human stuff.” The arc had a dip—Stockfish’s perfection had players “grinding out these boring end games”—before neural nets arrived: Leela Chess Zero beat Stockfish in ways that were “aggressive and did unconventional things and really pushed the game forward.” Computers first made chess boring, then “so much more exciting,” and now power game review, on-demand coaching, and personalized puzzles.
• Guo asks what Chess.com’s dataset of millions of improving players reveals about expertise. “Fortunately and unfortunately, it’s quite an easy answer”—repetition of small building blocks, no shortcuts except in tooling. His compounding heuristic, verbatim: “take any given day in your life and multiply that by a thousand—that’s kind of what your life looks like.” Five puzzles a day becomes 5,000. AI is “walking into a professor’s office… but you get it in your pocket all the time”—hedged with worries about bias, ego-inflation, and research showing some AI users “do stop thinking.”
• On cheating—Guo frames it as a version of the wider problem of passing off superhuman machine output as human performance. Allebest won’t detail methods, but emphasizes the data behind detection: “we know what it’s like when humans play chess, we know what it’s like when computers play chess.” The system uses statistical and ML models, with two work streams: general detection versus prize-money events. “Cheating can’t be prevented… but we do a really good job at catching it.”

6. In a world of infinite AI-generated games, chess is the Beatles—and poker gets a rating

• Why a billion people should play chess when “you could give an AI a prompt and have 10,000 new board games tomorrow”: the same reason infinite music sends people back to “the Beatles and Led Zeppelin.” Chess has no loot boxes, no skins, no rule changes, full information, and no luck—“enough complexity that can just blow your mind, but enough simplicity that you can learn it.”
• The expansion: Gambit at gambit.com applies the chess playbook to poker with a rating based on opponents’ ratings, chips won, and hands played, rather than simply who can buy the most chips or use a bot. The rating algorithm is “still evolving,” but the question is “how good are you really? Not just can you buy the most chips… we’ve all played those games where you’re playing for M&M’s and someone’s just all-in all the time and they just rebuy more M&M’s.” His conviction: “losing a hundred bucks at a table… I don’t care that much. But losing 100 rating points on my poker rating, that just really bothers me.” Guo’s framing of why it’s equalizing: “is Erik better than I am, or does he just have more M&M’s and is he a bully?” More classic games are coming from a small team.

7. AI inside the company, contrarian founder advice, and a cultural read on AGI

• Internal AI: support automation alongside human agents, LLM-powered analytics, CTO Josh’s early-built “GNS” authentication-and-knowledge layer across the org, in-house martech, and agentic development compressing idea-to-shipped-code—“have an idea or see a problem, fix a problem.” Product-side: an AI coach in your pocket (“not a replacement for a human”), prototype chats reviewing the previous week’s games, and comparative advanced stats against players just above you.
• His advice for founders in “too small” markets: the 2005 playbook said hire a Stanford technical founder, raise money, get an office, chase a big market, and buy customers—“we literally just did all the opposite of that.” The closer: “stop listening to people just giving you advice on what to do. Just go do it.”
• On AGI/ASI, his explicit claim is that he believes in superhuman intelligence and that it will move at a faster and faster pace; he is “more optimistic than pessimistic,” but insists “this is less a technology problem and more a cultural problem”—like nuclear technology, guns, and economic systems, outcomes depend on how people use them, and “I don’t know how we got into a place where the people who should probably not be in charge of the world are in charge.” Guo’s optimistic counter-read—that chess is evidence people want to acquire and watch human skill even when machines outperform, hedged with “maybe you limit that to gaming” before landing: the idea that human skill is irrelevant simply because of superhuman AI “is nonsense.” Allebest agrees; the open complexity is guardrails and “distribution of the fruits.”