Larry Cheng

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Larry Cheng

Larry Cheng

@larryvc

Co-Founder/Managing Partner, Volition Capital. Journaling general business thoughts so I don't forget them. Christian. Harvard. Several private/public boards.

Boston, MA Katılım Mart 2009
1K Takip Edilen69.1K Takipçiler
Larry Cheng
Larry Cheng@larryvc·
I’m not predicting this but just saying it is conceivable to me that in the world of AI, a company could raise private capital at a $1 trillion valuation and that same company could go to zero.
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Larry Cheng
Larry Cheng@larryvc·
I was telling an LP today that over time, I've come to believe that if you have to have a market size slide to justify the size of the opportunity, then it's not a truly big market. Truly big markets are obvious. They said that's the same dynamic when evaluating GPs. If a VC pitching an LP has to have a slide that justifies the size of their geographic opportunity then it's not that big of an opportunity either.
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Larry Cheng
Larry Cheng@larryvc·
The case for founders to reverse vest their founder stock is to protect the co-founder who stays from having to carry a co-founder who leaves from a free ride. The concept of reverse vesting is often received by founders as a penalty since they already own their stock, but it should be received as protection by any founder who is committed to staying.
Larry Cheng tweet media
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Larry Cheng
Larry Cheng@larryvc·
Excited for the livestream tomorrow…
Larry Cheng tweet media
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Larry Cheng
Larry Cheng@larryvc·
I'm realizing that ~50% of my Claude projects could be stand-alone businesses if they were better tuned for the use case.
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Larry Cheng
Larry Cheng@larryvc·
I encourage a healthy level of humility and paranoia if you're leading a company dependent on: - 1 or 2 customers - 1 or 2 channel partners - 1 or 2 platforms - 1 or 2 acquisition channels I've seen some work and others get sideswiped. Nothing should be treated as guaranteed when that type of dependency exists.
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Larry Cheng
Larry Cheng@larryvc·
Next X Livestream: When: Tuesday, March 17 Time: 10:30am EST Special Guest: Nat Turner (@natsturner), CEO of Collectors, Inc. (Parent of PSA) No formal agenda or topics. Just hanging out talking about trading cards and other fun stuff. Mostly just taking your questions.
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Larry Cheng
Larry Cheng@larryvc·
Interesting, @WHOOP doesn't have a default activity setting for cross-training, but it does have: -circus arts -darts -dedicated parenting -firefighting -hot dog challenge -poker -thrill ride Hmmm, ok, to each their own I guess?
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Larry Cheng
Larry Cheng@larryvc·
You’re about to see a lot of software engineers laid off by technology companies because of AI, and you’ll see a lot of software engineers hired into traditional industries because of AI. Make no mistake, the amount of software being developed is going parabolic because of AI.
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Larry Cheng
Larry Cheng@larryvc·
Two years ago in PE/VC: Bad words: -hardware -services -consumer Today: Hot AI sectors: -hardware -services -consumer
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Larry Cheng
Larry Cheng@larryvc·
$15B of ARR on one non-technical growth marketer. Ha ha, that's remarkable - new game, new rules.
Ole Lehmann@itsolelehmann

i can't believe nobody caught this. Anthropic's entire growth marketing team was just ONE PERSON (for 10 months, confirmed) a single non-technical person ran paid search, paid social, app stores, email marketing, and SEO for the $380B company behind claude here's exactly how one human is doing the job of a full marketing team: it starts with a CSV. 1. he exports all his existing ads from his ad platforms along with their performance metrics (click-through rates, conversions, spend, etc) 2. feeds the whole file into claude code 3. and tells it to find what's underperforming. claude analyzes the data, flags the weak ads, and generates new copy variations on the spot this is where he gets clever: he then splits the work into 2 specialized sub-agents: 1. one that only writes headlines (capped at 30 characters) 2. and one that only writes descriptions (capped at 90 characters). each agent is tuned to its specific constraint so the quality is way higher than cramming both into a single prompt so now he's got hundreds of fresh headlines and descriptions. but that's just the text. he still needs the actual visual ad creative, the images and banners that go on facebook, google, etc. so he built a figma plugin that: 1. takes all those new headlines and descriptions 2. finds the ad templates in his figma files 3. and automatically swaps the copy into each one. up to 100 ready-to-publish ad variations generated at half a second per batch. what used to take hours of duplicating frames and copy-pasting text by hand so now the ads are live. the next question is which ones are actually working. for that he built an MCP server (basically a custom integration that lets claude talk directly to external tools) connected to the meta ads API. so he can ask claude things like: • "which ads had the best conversion rate this week" • or "where am i wasting spend" and get real answers from live campaign data without ever opening the meta ads dashboard and the part that ties it all together and closes the loop: he set up a memory system that logs every hypothesis and experiment result across ad iterations. so when he goes back to step one and generates the next batch of variations... claude automatically pulls in what worked and what didn't from all previous rounds. the system literally gets smarter every cycle. that kind of systematic experimentation across hundreds of ads would normally need a dedicated analytics person just to track the numbers from the doc: ad creation went from 2 hours to 15 minutes. 10x more creative output. and he's now testing more variations across more channels than most full marketing teams a $380 billion company. and their entire growth marketing operation (not GTM) = just one person and claude code lol truly unbelievable

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Larry Cheng
Larry Cheng@larryvc·
Some people’s thinking is constrained by what’s been done before and others are not. It’s pretty much that simple.
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Larry Cheng
Larry Cheng@larryvc·
Using compensation studies from 2024-2025 to calibrate organizational salary scales in 2026 will look very misplaced come 2027-2028. AI is changing org structures and with that compensation structures will similarly be reset.
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