andrew chapello

528 posts

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andrew chapello

andrew chapello

@chapello

product @tryramp, mountain athlete, @cubs fan, father.

Boulder 🏔️ Katılım Mart 2009
334 Takip Edilen1.6K Takipçiler
andrew chapello
andrew chapello@chapello·
Prediction: the first crypto company built for accountants will be worth more than any crypto company built for traders. Coinbase, Kraken, Binance all optimized for speculation, retail, custody. The next decacorn optimizes for invoicing, reconciliation, tax classification, multi-entity treasury. Trading is saturated. Money movement is barely started.
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andrew chapello
andrew chapello@chapello·
The first trillion-dollar stablecoin category isn't cross-border B2B. It's machine-to-machine. Today's rails were built for humans initiating payments -- and they're excellent at that. They simply weren't designed to represent an AI agent billing in sub-minute increments and settling to a smart wallet. Programmable money is the prerequisite for programmable work. Agents are scaling faster than the rails purpose-built to serve them.
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Henri Stern Ꙫ
Henri Stern Ꙫ@sternhenri·
Come to @stripe Sessions, they said. It’ll be great, they said. Cue — onstage agent review of Privy’s docs. Thanks guys… 😓
Henri Stern Ꙫ tweet media
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andrew chapello
andrew chapello@chapello·
The reason stablecoin adoption goes vertical from here isn't transfer fees. It's yield. USD sitting in a corporate treasury today: ~0%, plus a 3-day clearing tax. USD sitting in a programmable wallet tomorrow: 4-5% APY, settles in seconds, available 24/7. "Free transactions" got the headlines. "Yield on idle cash" wins the CFO meeting.
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andrew chapello
andrew chapello@chapello·
Tokenized deposits and stablecoins are not the same product. Tokenized deposits: programmable bank balance, closed loop, bank-trust. Stablecoins: bearer instrument, open loop, asset-trust. The interesting q isn't which wins. It's which use case routes to which. Treasury intercompany -> tokenized deposits. Cross-border B2B -> stablecoins. Real-time payroll -> stablecoins. Domestic high-value -> tokenized deposits. The rail you choose tells you whether the counterparty trust assumption is "bank" or "asset."
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andrew chapello
andrew chapello@chapello·
We think so too. Send and receive USDT, now live on @tryramp.
Tokenized Podcast@TokenizedPod

“If you're a Ramp customer and you're doing business in emerging markets, being able to send USDT to a supplier in Colombia, that is probably what that supplier wants.” In the latest episode of Tokenized, @cuysheffield, head of crypto at @Visa, gives his take on Ramp integrating USDT 🎙️ Listen to the latest episode of Tokenized: tokenizedpod.com/episodes/every… 📷 Watch on YouTube: youtu.be/iEmqA0tVxg0

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andrew chapello
andrew chapello@chapello·
@zebulgar brother get out on the wsh for the whole run and you’re there. side streets + turns kill you
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delian
delian@zebulgar·
10 seconds away from breaking 19m. Soon.
delian tweet media
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andrew chapello
andrew chapello@chapello·
fascinating. increasingly as a writer, builder, publisher, you need to ask yourself: who is your audience? and it might be different today than it was yesterday.
Nav Toor@heynavtoor

Researchers sent the same resume to an AI hiring tool twice. Same qualifications. Same experience. Same skills. One version was written by a real human. The other was rewritten by ChatGPT. The AI picked the ChatGPT version 97.6% of the time. A team from the University of Maryland, the National University of Singapore, and Ohio State just published the receipt. They took 2,245 real human-written resumes pulled from a professional resume site from before ChatGPT existed, so the human writing was actually human. Then they had seven of the most-used AI models in the world rewrite each one. GPT-4o. GPT-4o-mini. GPT-4-turbo. LLaMA 3.3-70B. Qwen 2.5-72B. DeepSeek-V3. Mistral-7B. Then they asked each AI to pick the better resume. Every model picked itself. GPT-4o hit 97.6%. LLaMA-3.3-70B hit 96.3%. Qwen-2.5-72B hit 95.9%. DeepSeek-V3 hit 95.5%. The real human almost never won. Then the researchers tried the obvious objection. Maybe the AI is just better at writing. So they had real humans grade the resumes for actual quality and ran the experiment again, controlling for it. The result was worse. Each AI kept picking itself even when human judges rated the human-written version as clearer, more coherent, and more effective. It gets worse. The AIs do not just prefer AI over humans. They prefer themselves over other AIs. DeepSeek-V3 picked its own resumes 69% more often than LLaMA's. GPT-4o picked its own 45% more often than LLaMA's. Each model can recognize and reward its own dialect. Then the researchers ran the simulation that ends careers. Same job. 24 occupations. Same qualifications. The only variable was whether the candidate used the same AI as the screening tool. Candidates using that AI were 23% to 60% more likely to be shortlisted. Worst gap was in sales, accounting, and finance. 99% of large companies now run AI on incoming resumes. Most of them use GPT-4o. The paper just proved GPT-4o picks GPT-4o 97.6% of the time. If you wrote your own cover letter this week, you did not lose to a better candidate. You lost to a worse candidate who paid OpenAI 20 dollars. Your qualifications do not matter if the AI prefers its own handwriting over yours.

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Terry Angelos
Terry Angelos@terryangelos·
Friendly reminder hatcheries can deliver chickens via US Post! We received three new chicks from a hatchery in Iowa this week. Such a fun experience and they will join the backyard coop in a few months.
Terry Angelos tweet media
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andrew chapello
andrew chapello@chapello·
Hey @leifthunder are you considering paper trading mode for @public ? That would make this project a lot easier to get off the ground // offer guardrails for serious traders to build new systems. x.com/chapello/statu…
andrew chapello@chapello

Weekend project: an agentic hedge fund. 1/ Long-only equities (for now) 2/ 4 different agents as analysts, I am the PM 3/ Each agent has a distinct investment thesis 4/ Agents text me a 1-paragraph analysis, confidence level on a scale of 1-5, position sizing 5/ I greenlight all trades Building on @AlpacaHQ, Telegram for messaging. Likely not a big $ maker at my position sizes and on a Mac Mini, but fun to build & learn.

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andrew chapello
andrew chapello@chapello·
@TheStalwart The POS provider is hiding a huge markup in the "pay in USD" option they are giving you. Pay in local ccy and save.
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Joe Weisenthal
Joe Weisenthal@TheStalwart·
Question for a payments expert. What I pay for something by card in Spain, the reader offers me the choice to pay in euros or dollars. Obviously dollars are removed from my account. And the cafe gets euros. So what’s really going on in the transaction that requires this step?
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andrew chapello
andrew chapello@chapello·
CFOs aren't buying faster rails. They're buying automation. "Money moves in 10 seconds" is not the wedge. "Every payment auto-matches to invoice, vendor, GL entry, and tax category before close on the 5th" is. That's what we're laser focused on at Ramp. Not faster chains -- shorter closes.
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andrew chapello
andrew chapello@chapello·
@web3butwhy yes -- launched Stablecoin Account earlier this year and shipping more on the reconciliation side soon. the goal is making the stablecoin layer indistinguishable from how finance teams already work in Ramp.
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Siva
Siva@web3butwhy·
@chapello That is true. Settlement time is no longer a constraint. is try ramp doing something about stablecoin reconciliation?
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