32 Million Dollar Fraud? Delve Scandal | E2266

Summary

This Monday TWiST is built around the unfolding Delve scandal — a YC- and Insight Partners-backed AI compliance startup accused via an anonymous “Deep Delver” Substack of producing 500 boilerplate SOC 2 reports with copy-pasted errors across blue-chip clients (including a publicly traded company), zero auditor findings on 259 Type 2 reports, plus a Supabase bucket leak that exposed background checks and Stripe tokens. Jason and Alex are joined by Hustle Fund’s Elizabeth Yin (year-zero AI investing) and Ryan Mahdavi from Ceel (Launch Accelerator Cohort 35, a Vanta competitor) to dissect what’s “hustling” vs “fraud,” why startup investing is a “trust-based ecosystem,” and where the line is between Airbnb-style rule-bending and securities fraud. Jason coins “diligence by proxy” as the cardinal sin — the FTX/Theranos pattern of using brand-name co-investors to talk later checks out of doing their own due diligence — and walks through specific founder traps (calling pipeline leads “customers” on a slide is enough to kill a round and, when paired with raising money, becomes literal SEC territory).

The middle of the episode is a wide-ranging conversation about how AI has compressed the cost of building software so dramatically that Hustle Fund now invests “more in hardware than ever” because the moat used to be code and “now somebody else comes along and does the same thing and it’s sort of game over” at $10M ARR. The hosts discuss Zenefits/Conrad Parker, Brex billboards, the Twilio “ask your developer” SF outdoor era vs C3.ai’s wall-to-wall ads as a contrarian indicator, why governance and a real board matter once you cross $3M raised or $1-2M in revenue, and why a 30-minute demo would have caught Delve’s “screenshot-native” features long before $32M of growth-stage capital got committed. They riff on Delve’s “tactical donuts” and branded doormats handed out around SF as a “brand-washing” tactic in the lineage of Catch Me If You Can’s Pan-Am uniform.

The back third pivots to two pitches and Jason’s emerging investment thesis. Brick (Seb Sheng) is an AI-native energy-tech company selling a $2,500 universal gateway that plugs into HVAC master units and uses an agent to run pre-cooling/pre-heating against power prices, claiming 15-35% savings — with paying customers like JLL, DoubleTree Hilton, Sheraton Grand, Lucid Motors, and data-center operators DCTC and Inspur on a revenue-share model. LeadPoet (Gavin Zaentz and Pranav Ramesh, ex-Nasdaq) is BitTensor subnet 71, a global “miner”-driven lead-generation marketplace that has dropped lead costs from $2-3 down to 3-5 cents while the show is recording, and that runs an on-air mock lead hunt for Brick. Jason closes by laying out his $TAO thesis in detail: a personal ~$500K Coinbase position plus a stake in Stillcore Capital, the partnership with Mark Jeffreys, his “I think the game of Bitcoin has ended” call, a 200x base case to a $500B market cap over 5-10 years, and his place-a-bet-then-learn philosophy.

Highlights

”Then somebody else comes along and does the same thing and it’s sort of game over”

“What is the moat? That’s the other question everyone’s asking. So it’s like okay, you back this company, they’re doing well, but I’ve had a couple of companies, Jason, where they’ve gotten to 10 million ARR and then somebody else comes along and does the same thing and it’s like sort of game over. And that never used to happen. So that’s sort of the other thing that everyone’s thinking about. So we’ve been looking at a lot of infrastructure rather than apps.” — Elizabeth Yin, 6:10

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”500 boilerplate reports… almost statistically impossible”

“Whoever put this investigation piece together, bravo. The level of forensic detail is impeccable… There’s a lot to unpack there, we’ll try to do the TLDR for the audience. The biggest problem here is 500 boilerplate reports, same errors, spread across a number of companies. Of those 259 type 2 reports, which is effectively the more rigorous version of SOC 2, zero auditor findings across every single client, which is almost statistically impossible. And this has affected brands like Lovable, Bland, Clearly, and then Duo’s Edge, which is a public company. And then of course, subsequently, they had that Supabase bucket leak.” — Ryan Mahdavi (Ceel), 14:11

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”There’s a difference between hustling and faking it”

“We see this as a broader problem than just Delve. We can get into the details of specifically how this goes into Delve, but there’s a difference between hustling and faking it. And to be fair, there’s a lot of overpromising and hype across the board in the space and maybe AI in general. But 500 boilerplate reports, nearly half of which are basically identical, zero incidents — this is not cutting corners. If proven true, this is gaming the system.” — Ryan Mahdavi (Ceel), 16:47

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Pipeline isn’t customers: how to commit securities fraud

“When you have your customers… they have a slide. ‘These are our customers in pipeline.’ And we’re like, okay, two different things. Customer implies they’re paying, user implies free, pipeline means you put them in a database and you sent them an email… We had a company, they said that they had certain customers, they also said they had certain employees in their deck. They pitched an investor. Investor puts 50k in. Company’s not working out… this angel investor went, called the people who were listed as employees and they said, ‘I never worked there.’ He then sent a demand letter saying, ‘I want my money back or I’m going to the SEC with this.’ They gave the money back, the whole thing blew up. The founder was exaggerating/lying while raising money. When you do those two things at the same time — you make claims and you raise money — there’s a special term for that… securities fraud. Correctamundo.” — Jason Calacanis, 21:34

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”Diligence by proxy. That’s the cardinal sin”

“How does a big company make this mistake? Like, how did they make the mistake in FTX? As the stakes get higher, the diligence should get deeper… I believe he used other people’s reputation and the momentum behind crypto to dissuade people from doing diligence and to put pressure on them. So we as investors will deal with this high pressure. Hey, this person’s leading, I have this many days, I’m oversubscribed, need the money now, yada yada yada, you have to rely on their diligence. And then diligence by proxy is the issue here. People will say, oh, these other people are in the deal — for Delve, for Theranos. I can use their diligence as a proxy. That’s the cardinal sin. People have to do their own.” — Jason Calacanis, 27:42

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”I think the game of Bitcoin has ended”

“I believe that [Tao] could become as big as Solana, let’s say, or Ethereum. Probably not as big as Bitcoin because Bitcoin is, you know, a phenomenon that might only be a once… I’ve always said there would be a better Bitcoin. I think the game of Bitcoin is ended. And it ended when Michael Saylor got to three, four, five points of ownership of Bitcoin… Therefore, I think making a bet on a crypto project that is distributed and that solves real world problems like startups — there’s something there that could compound to, you know, a $500 billion market cap for Tao… I think we could be sitting here and Tao in five to 10 years could go 200x. The chances of this happening are low… but we’ve seen it happen before. Therefore, I am fine losing all my money, hundreds of thousands of dollars close to a million dollars, whatever I end up putting in all this.” — Jason Calacanis, 1:19:59

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Key Points

• Hustle Fund’s existential question (3:52) - Elizabeth runs multiple Claude Code terminals daily; the amount of capital required for software has dropped dramatically; the firm is now spending more on its own AWS bill than ever
• A $1,000-day on Claude Code (4:42) - Elizabeth’s compute spend on AI tooling is closing in on $3K/month per the CFO note
• Bifurcation in founder quality (9:27) - “Some people are exceptional and using all the tools well, and then there are people who still haven’t really gotten the memo”; the bar is rising and lagging founders are losing access to capital
• AI is forcing existing portfolio reckoning (10:55) - Hustle Fund’s existing companies are confronting whether their engineers will make the leap; rebuilding from scratch with one shop is sometimes easier than carrying legacy hires
• The “Deep Delver” Substack (15:48) - Anonymous investigation, alleged customer data leak, web of “less than above board” auditors, copy-pasted errors across documents; Part 2 set to drop the same week
• Brand-name fallout (15:00) - Allegedly affected customers include Lovable, Bland, Clearly, and Duo’s Edge (a publicly traded company); the Supabase bucket leak exposed background checks and Stripe tokens
• Investing is “trust-based” (21:34) - As a sub-10% holder you have information rights you “never call”; you rely on monthly/quarterly founder updates and the diligence asks during fundraising
• The Conrad Parker / Zenefits parable (23:01) - Helping insurance brokers cheat their licensing test was illegal and selfish; Airbnb’s home-rental rule-bending arguably benefited renters and hosts more than Airbnb; the law cares which it is
• Misrepresenting customers can kill a round (26:00) - “If you tell me on this slide they’re customers, and it turns out they’re talking with them, I’m out — I can’t trust the rest of your slide deck”
• “Screenshot-native rather than AI-native” (32:01) - Pranav’s diagnosis from a 5-10 minute Delve demo; “you don’t even have to be an expert”
• Tactical donuts and branded doormats (32:42) - Delve’s growth tactic of mailing donuts (and branded doormats!) to prospects — and using them again to “smooth over things” when clients asked hard questions
• Brand-washing as fraud signal (34:09) - Alex compares to Catch Me If You Can / Pan-Am uniform: borrowed reputation as a stand-down-on-diligence weapon
• Twilio vs C3.ai billboards (39:47) - Twilio’s “ask your developer” billboards became SF milestones; C3.ai’s were a leading indicator of “absolute dumpster fire”; context matters
• Governance arrives at $3M raised or $1-2M in revenue (36:11) - Jason argues YC’s no-board-seat orthodoxy was a six-month overreaction to founder-ousting; once you’re spending $4M on ads against $1M in revenue you need adult supervision in a board meeting
• Greed index off the charts (41:08) - Hype-cycle distortion of risk perception; rules exist because of past lawsuits and bubble at peak
• Brick: 35% energy savings as a revenue share (45:11) - $2,500 universal gateway plugs into the master HVAC unit; foundation models per sector; the rev-share is structured so Brick reimburses the customer if no savings hit in a 4-6 week pilot window
• Brick customers: JLL, Hilton, Sheraton, Lucid, DCTC, Inspur (49:57) - All confirmed as live customers (not “worked-with” pilots), with $30-50K ACV per facility and a typical land-and-expand of 2-3 facilities
• The JLL-rollout problem (51:56) - Elizabeth’s familiar pattern: “the big logos are willing to try… but how do you get them to roll this out across all of their buildings?”
• TAO at $290 (1:01:52) - Volatile: “$205 last week, $300 this week”; subnet acquisition costs vary day-to-day from 200 to 600 TAO depending on demand
• Subnets capped at 128 today (1:03:04) - Bittensor Foundation expanded from 64 to 128; “let’s get a solid number of good ones in” before opening the floodgates
• LeadPoet drove cost per lead from $2-3 to $0.03-$0.05 (1:08:04) - The decentralized “miner” market drives commodity pricing; payouts are in alpha tokens that swap for TAO
• Validation chain (1:07:14) - LeadPoet’s validators check email validity, LinkedIn association, and Google indexing of the LinkedIn profile (a low-authority profile won’t be indexed)
• 5 million leads, “verified to a higher degree than Apollo or ZoomInfo” (1:05:07) - LeadPoet’s claim; ImageNet analogy for compounding global competition + token rewards
• Mark Jeffreys’s Stillcore Capital (1:18:30) - Jason seeded the fund with a couple hundred thousand and is a partner; AUM in the low millions; targets subnet ownership via OTC-style negotiated trades
• OpenClaw / Mac Mini agents (1:16:09) - Jason and Mark Jeffreys are running personal AI agents on Mac Minis at home; Jason wants his to “earn its keep” via subnets; cold-start problem on Moat Launch / agent marketplaces
• No-crying-in-the-casino TAO sizing (1:23:22) - Jason fully expects he could lose two-thirds of his close-to-$1M position; he keeps fund money out of it but wants the fund to track companies like LeadPoet’s parent for equity exposure

Mentions

Companies

• Hustle Fund (3:00) - Elizabeth Yin’s “hilariously early” pre-product-market-fit fund with co-partner Eric
• Delve (12:39) - The YC + Insight Partners-backed AI compliance startup at the center of the scandal
• Insight Partners (27:11) - The growth-stage check-writer behind Delve’s $32M round
• Y Combinator (12:39) - Backed Delve early; the “tell us a time you hacked something” application question
• Ceel (ceel.io) (12:39) - Ryan Mahdavi’s automated-compliance startup; Launch Accelerator Cohort 35
• Vanta (13:14) - The incumbent SOC 2 leader; raised half a billion; “ask your developer”-style SF outdoor presence; over half of Ceel’s customers were Vanta or Drata refugees
• Drata (31:35) - The other major incumbent in compliance
• Lovable, Bland, Clearly, Duo’s Edge (15:00) - Customers reportedly affected by the Delve report leakage; Duo’s Edge is a public company
• Supabase (15:00) - The leaky-bucket vendor that exposed Delve customer background checks and Stripe tokens
• Lightning, Apollo, ZoomInfo, RocketReach (1:05:30) - Incumbent lead-data providers being commoditized by LeadPoet
• LeadPoet (Bittensor subnet 71) (1:00:12) - Gavin Zaentz and Pranav Ramesh’s subnet that uses miners to source verified leads
• Brick (44:46) - Seb Sheng’s AI-native energy-tech startup with a $2,500 universal gateway
• JLL, DoubleTree Hilton, Sheraton Grand (49:57) - Brick’s commercial-real-estate and hospitality customers
• Lucid Motors / Tesla (49:09) - Brick’s industrial-manufacturing customer (Lucid live, Tesla in pipeline)
• DCTC / Inspur (49:57) - Brick’s data-center customers
• Forum Ventures / Rice Capital (54:05) - SF accelerator and capital partner that ran Brick’s first round
• Stillcore Capital (stillcorecapital.com) (1:18:30) - Mark Jeffreys’s Tao-focused fund; Jason is a partner
• DSV Fund (UK) (1:12:30) - LeadPoet’s Bittensor-native early backer
• Coinbase (1:18:30) - The on-ramp Jason uses for TAO
• Robinhood / Kraken / MEXC Global (1:19:18) - Robinhood doesn’t list TAO yet; tier-2/3 venues are where subnet alpha tokens trade
• Twilio / Brex / Deel / C3.ai (39:47) - The Big Billboard hall of context: ranges from canonical good (“ask your developer”) to canonical bad (“absolute dumpster fire”)
• FTX / Theranos (27:42) - The two diligence-by-proxy archetypes
• Zenefits / Rippling (23:01) - Conrad Parker’s insurance-license hack and the SEC fine that lost him his company
• Airbnb / Uber / self-driving (19:08) - The “biggest companies we admire” rule-bending lineage
• OpenAI / Project Stargate (45:12) - The grid-strain concern Brick is selling against
• Salesforce, Apollo, ImageNet (34:54) / (1:15:38) - Social-proof brand and the global-competition compounding analogy
• Moat Launch (1:16:21) - One of the new agent marketplaces facing the cold-start reputation problem
• Plaud / Sentry / Northwest Registered Agent / LinkedIn Hiring Pro / Ro.co — sponsors

Products & Technologies

• Bittensor (TAO) (1:18:08) - The decentralized network; 128 subnets, alpha tokens, miners + validators
• Subnet 71 / LeadPoet (1:00:12) - The decentralized lead-gen subnet
• OpenClaw (1:16:09) - Jason and Mark Jeffreys’s Mac-Mini-based home AI agents
• Claude Code / Claude Co-worker (3:52) - Elizabeth’s daily multi-terminal AI workflow
• SOC 2 (Type 2) (15:00) - The compliance regime at the heart of Delve’s allegedly fake reports
• HVAC master/slave architecture (47:11) - The “one-to-many” setup that lets a $2,500 Brick gateway cover an entire building
• DCIM (47:50) - Data Center Infrastructure Management; Brick layers intelligence on top instead of being another aggregation dashboard
• Plaud NotePin / wristband / magnet attachments (0:19) - Sponsor; Jason wears the magnet, Alex wears the wristband
• GLP-1s / Ozempic / Tirzepatide (56:22) - Jason’s 40-pound transformation talked about with the Ro.co read
• USDC / Solana / Ethereum / Bitcoin (1:20:19) - The reference points for Jason’s $500B-cap TAO thesis
• Catch Me If You Can / Pan-Am uniform (34:09) - The brand-washing analogy for FTX-style social proof
• CompUSA (8:00) - Jason’s “sampling” analogy for the AI app churn cycle
• Apollo / RocketReach / ZoomInfo (1:14:23) - LeadPoet’s competition; “they validate by looking at each other”
• Andrew Huberman’s podcast / Ecobee (45:23) - Smart-thermostat reference for Brick’s enterprise pitch

People

• Jason Calacanis — host
• Alex Wilhelm — co-host
• Lon Harris — contributing co-host (off-camera, narrates the Substack details)
• Elizabeth Yin (3:00) - Hustle Fund GP
• Ryan Mahdavi (13:11) - Founder/CEO, Ceel
• Seb Sheng (45:22) - Founder/CEO, Brick
• Gavin Zaentz (1:00:52) - Co-founder, LeadPoet (ex-Nasdaq)
• Pranav Ramesh (1:01:15) - Co-founder, LeadPoet (ex-Nasdaq)
• Mark Jeffreys (1:18:30) - Founder of Stillcore Capital; Jason’s TAO partner
• Sam Altman (17:26) - Cited as the canonical YC hacker/hustler in Paul Graham’s old anecdotes
• Paul Graham (17:26) - The “tell me a time you hacked something” YC application
• Conrad Parker (23:01) - Zenefits founder; SEC fine; lost his company; later founded Rippling
• Michael Saylor (1:20:19) - The 3-5% Bitcoin ownership concentration that ended Jason’s “punk rock” thesis
• Chamath Palihapitiya (59:12) - All-In co-host; brought up the distributed-network LLM training with Jensen
• Jensen Huang (59:12) - The All-In Jensen interview where the distributed-LLM moment happened
• Barry Silbert (1:12:29) - Jason’s first guess for who funded LeadPoet
• Andrew Huberman (45:23) - Mentioned in the Brick smart-home framing
• Leonardo DiCaprio (34:09) - Catch Me If You Can

Surprising Quotes

“The audience we attract fundamentally is trying to think out of the box, which may push the envelope and break some rules. And in fact, actually for some companies, they may literally be breaking the law, but then the laws may change over time.” — Elizabeth Yin, 18:53

“I legitimately think a 10 to 30 minute demo with anyone who has a baseline understanding of tech would probably catch this. Now, for me, I’m always also skeptical when a company’s early growth tactics consist of dishing out donuts and doormats and just going extremely heavy on growth tactics.” — Pranav Ramesh, 32:01

“Delve went around SF handing out donuts to different people, Jason. And also they used them per the Substack report as a way to smooth over things. The report says when clients ask hard questions, Delve dodges. They demand calls where founders charm, promise, and name-drop. And when that fails, donuts arrive. So it appears to be a donuts on the front end and donuts on the back end strategy.” — Lon Harris, 33:51

“How does a big company make this mistake? Like, how did they make the mistake in FTX? As the stakes get higher, the diligence should get deeper.” — Jason Calacanis, 27:42

“It’s just this distributed group of lunatics competing to get the best leads at the lowest price. It’s like Mechanical Turk globally off the rails.” — Jason Calacanis on LeadPoet’s miners, 1:08:32

“I am fine losing all my money, hundreds of thousands of dollars close to a million dollars, whatever I end up putting in all this. I’m okay losing it… I like, place a bet and learn, not deliberate forever and then place a bet.” — Jason Calacanis, 1:22:25

Transcript

Jason Calacanis: 0:00 All right, everybody, welcome back to This Week in Startups. Yes, it’s your boy J-Cal. I’m here with Alex Wilhelm, the one and only.

Alex Wilhelm: 0:07 As you can see, teardrop behind me if you’re watching us on YouTube. Ski season’s over. I’m shutting the house down in Tahoe and I did two days of skiing so I hit 30 for the season. I’ll do one half day tomorrow in the slush.

Jason Calacanis: 0:19 A lot of people have been asking me about my tweets about Tao and my fascination with Tao and Stillcore Capital and everything. Uh, we’re going to talk about Tao at the end of the show, right? In the back third. Why uh I am a bit obsessed with Tao. And as you know, I’m obsessed with a lot of technologies, including my Plaud pin. It’s time for us to applaud, golf clap, Plaud. As you can see here, I have it on my t-shirt. How did I get it on my t-shirt? I didn’t use the clip you usually see me use when I’m wearing a suit. Well, I’m in Tahoe, so I’m not suited up. It has a magnetic one. So you can put it right behind you. Then, uh, Alex, I got you on the Plaud train. I’m recording my Plaud right now. So if I have any ideas like, hmm, I should uh go to the emergency room and get my pinky, which I dislocated playing basketball yesterday, and make sure I send a note, I can do that. And uh you just flashed your Plaud, Alex. You’re using the attachment that lets you wear it like a wristband, which is kind of cool, too. It’s totally privacy-first because you have a button, you press it, the red light goes on. Everybody knows what you’re doing. And uh for meetings, it’s amazing. People say, “Well, why wouldn’t you just use your phone?” Getting your phone out, opening an app, starting it, closing it. Okay, all that’s great. It’s going to take you 30 seconds, a minute. Whereas here, you just press the button, one second or less and you’re recording. And it’s got multiple microphones on it. And the battery lasts forever. And if your phone’s in your bag or your jacket and you’re skiing, but you want to leave it on like a lunatic all day, Alex—I just leave it on when I’m skiing and I just talk to myself when I’m skiing alone. And, uh, you know, if I ever go down in a tree well or whatever, it’ll be my last will and testament.

Alex Wilhelm: 2:14 I was about to say, didn’t we just talk about you not skiing alone anymore like like 10 days ago? It wasn’t that far back, man.

Jason Calacanis: 2:22 We have a promo code, uh, people can get a good deal, I think, on a Plaud, yeah?

Alex Wilhelm: 2:25 If you go to P-L-A-U-D.ai, plaud.ai/twist, use the code twist, save 10%. Jason, I’m using mine to take ideas for uh blog posts when I’m out and about. Love it. And because I have the wristband, my children can’t yank it off my body. So not really a clip-on guy yet, but give me like five years of older children and then I’ll be able to, you know, safely wear it like that. But yeah, I’m loving it, Lon’s loving it, you’re loving it. Kind of a hit here at Twist HQ.

Jason Calacanis: 2:44 Uh, everybody’s loving it and thank you to them for supporting the program. If you use that URL, they know we sent you and tell your friends about it, shout it out on your social medias. Big show today, got a couple of great guests. Why don’t we get started, Alex? We have Elizabeth Yin…

Alex Wilhelm: 3:00 from the Hustle Fund. If you don’t know Hustle Fund, it is one of those venture capital firms that actually will invest in you very, very, very early. Or as they put it, they invest in hilariously early startups. Think founder university, if you will, Jason, people with an idea, but not yet product market fit or anything that far along. Um, I love their fund. I know her co-partner Eric, and they’re just some of the nicest people in the entire world. Elizabeth, welcome to the show.

Elizabeth Yin: 3:25 Thank you. Thanks, guys.

Jason Calacanis: 3:27 It’s been a while, it’s been a minute, so good to see you. Uh, how has this AI revolution in the last two years or so impacted what you and I do, which I call now year-zero investing? From the front lines, how is it changing how startups are created, who’s creating them, how fast they grow, product market fit, whatever, and maybe even how you run your firm?

Elizabeth Yin: 3:52 Oh my gosh, it’s been crazy. Well first off, my own workflow has changed. Like on my computer over here, which you can’t see, I had multiple terminals going, Claude coding away, press 111, and, uh, you know, just playing with all the tools and using them a lot. Open Claude, Claude Co-worker, Claude Code, like etc. So, so internally we’ve built a lot more, um, to help us, you know, run our operations. But I think that also has informed a lot of our investment decisions as well, right? Like everybody can be spinning up these apps over a weekend. And so now, A, the amount of capital you need for software has gone down dramatically. So there’s this question of, you know, why do people even need us? That’s the existential question. But I mean, we have noticed actually companies get faster growth and so they need to pay for their compute bill. So we’re still needed on that level. I don’t know if you’ve ever seen your own cloud bill or mine, but like, there’s money that is needed.

Jason Calacanis: 4:42 What are you up to? What was the biggest day/month you’ve had? Have you had a thousand-dollar month?

Elizabeth Yin: 4:52 Um, not quite there, but getting there. Yeah.

Jason Calacanis: 4:57 Yes, so 700 bucks a month. You’ve had a 200-dollar day?

Elizabeth Yin: 5:01 Yeah, we’ll probably cross that this month in March, over a thousand. Yeah. Yeah, and I just love my CFO note, like it’ll probably be more than 3000 by the end of the year per month. Crazy.

Jason Calacanis: 5:08 Uh, it is nuts, and I share too your observation here. Uh, you have to ask, well what is the role of venture capital? And people have been saying that for a long time. Sure. It does seem like, you know, the cloud computing revolution, the WeWork revolution, getting rid of those big ticket items, Alex, that we used to negotiate 100,000, 200,000 for the lease of your office, two-year commitment. You know, you used to stand up 20 years ago your own rack of servers in a co-location facility, so that was 100K in servers probably, 50, 100K plus 10,000 a month, 5,000 a month, plus you needed a sysadmin to do all that work. All that got abstracted away. Okay, GitHub, you know, DigitalOcean, AWS, whatever, you know, you’re going to use. Um, but now this is different because those two or three first developers you were we’re going to hire maybe

Elizabeth Yin: 6:02 Okay yeah, maybe we don’t, maybe we hire one but we don’t hire 10. Yeah, you don’t need them. At least not in the beginning.

Jason Calacanis: 6:07 Right. So that’s a big sea change.

Elizabeth Yin: 6:10 And then what is the moat? That’s the other question everyone’s asking, right? So it’s like okay you back this company they’re doing well but you know I’ve had a couple of companies Jason where they’ve gotten to 10 million ARR and then somebody else comes along and does the same thing and it’s like sort of game over.

Jason Calacanis: 6:24 Yeah.

Elizabeth Yin: 6:25 And that never used to happen. So that’s sort of the other thing that everyone’s thinking about. So we’ve been looking at a lot of infrastructure rather than apps.

Gavin Zaentz: 6:34 So you’re going one layer down the stack essentially to prevent from being vibe coded out of existence?

Elizabeth Yin: 6:42 Exactly. Exactly. We’ve been looking at more hardware than ever. We didn’t used to look at so much hardware now we look at a lot of hardware for the same reason. So, so I don’t know. I think in some ways nothing has changed but everything has changed, right? Still looking at the same fundamentals, customer acquisition’s important, but you know how like how are you going to kind of maintain your position.

Gavin Zaentz: 6:54 Do you pay more attention to to churn than you did before? It’s always been a very important thing especially in the SAS era people want to just have you know net positive retention and so forth but if someone can show up to your 10 million ARR business and and crush it is churn now even more important at the earlier stages of vetting the startup.

Elizabeth Yin: 7:11 Yes and no. So there have been some high flying marquee companies and I won’t name names but we all know them in the sort of vibe coding space that have had awful churn numbers and a lot of VCs have been passing because of that. But I think one of the things that will change is as the AI models get better and that’s what everyone is riding on then they will ride that wave to getting more accurate and being a better product and that will actually help your churn. So so there’s some things you can control and other things that I think you know the LLMs will control and and make your product better over time.

Gavin Zaentz: 7:54 Are you referring to like Hatable and Zaplet?

Elizabeth Yin: 7:58 Yeah, yeah, maybe.

Jason Calacanis: 7:59 Well, you know I kind of think we’ve seen this before. People did a lot of sampling at you know in mobile, when the PC came out there was a lot of sampling, people would do it as a hobby, they would go to CompUSA and buy a bunch of packaged software. Internet comes out, people would you know pay for websites, apps came out, people would pay for a flashlight app. So it’s a lot of sampling coming out but it will come out in the end. I think the thing that is also pretty tremendous is the ability for founders to get better at the job of being a founder by learning new skills very quickly. So if you were a founder and you didn’t quite understand the legal issues or maybe you didn’t understand cap table issues or you weren’t good at go to market strategy or you sucked at design, whatever you sucked at, you will suck a lot less instantly and then you might even become good at it quickly. And then if you can be good at you know the dozens of things to take, to do the chores at a startup. Man, that’s a big breakout, yeah?

Elizabeth Yin: 9:04 100%. And anybody, and so that means that everyone’s bar is higher. Like everyone has to level up and anybody who is not, then it’s just going to get harder to get funding.

Jason Calacanis: 9:15 Yeah, everybody became a superhero overnight. It was like somebody got the serum and everybody becomes a mutant and has crazy abilities. So it doesn’t matter if you used to be a mutant, now everybody is.

Elizabeth Yin: 9:27 But I don’t know if you’re seeing this, Jason, there is a bit of a bifurcation, like when we see startups, like there are some people who are just exceptional and using all the tools well, and then there are people who still haven’t really gotten the memo, whether it’s for coding or whether it’s for,

Jason Calacanis: 9:41 That’s crazy.

Elizabeth Yin: 9:42 you know, general business ops or sales and marketing, like there are a lot of people who have not leveled up. So that, that playing field is changing as well.

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Elizabeth Yin: 10:55 Both. So we have definitely had conversations within our existing portfolio where the companies are further along, they’ve got a built-out team, and then now it’s like, okay, we’re kind of in this weird dichotomy where maybe some of their existing engineers are not going to make it. And that’s, that’s actually really tough. And then there’s also this dichotomy of, okay, I have these people but now who do I hire next? Do I hire someone? Do I have to kind of change what this person’s doing? So actually in some ways it’s a little bit trickier I think to be an existing startup with all of this sort of legacy stuff and now you’re changing versus oh I’m starting from scratch as a one-person shop.

Jason Calacanis: 11:33 Yeah, and this is what we’re seeing at the big companies too. You know, if you had an overhang of middle management or too many PMs, product managers, you’re kind of like, well, product management was a lot of note-taking and like, we just talked about Applaud, like you don’t need a note-taker, you just get a literally you spend a hundred dollars on Applaud and you’re done. Uh like we’re here folks. So that note-taking role or just every day checking in on the changes That is kind of over, and if you’re a founder who doesn’t embrace this, you’re at risk. It would be like being the founder who doesn’t embrace cloud computing during that change, or you didn’t embrace mobile. So just pause for a second, right, Elizabeth? And think about our friends who had an incredible website; they never figured out mobile. They had an incredible, you know, business for SaaS or whatever, but they never figured out cloud. You know, and like Dropbox had to make that change, right? Like—

Elizabeth Yin: 12:27 Yeah.

Jason Calacanis: 12:28 Okay, we’re not going to stand up our own servers, we’re going to use storage, we have to put more money into the application level, yada, yada, yada. All right, lots more on the docket, let’s get to work.

Alex Wilhelm: 12:39 All right, so the biggest startup story of the last couple days has to deal with a company called Delve. Now, if you don’t know about SOC2 compliance and other bits of enterprise arcana, this is a little bit esoteric to you, Jason, but the issue is: did a company, did a startup that was backed by both YC and some major VCs, essentially cook their entire business out of thin air? As in, did they do some fraud? So we’re going to bring on a founder, Ryan Mahdavi, he’s the founder and CEO from Seale, which is from Launch Accelerator Cohort number 35, Jason, and Seale does automated compliance, very similar to what Delve claimed to do. Ryan, welcome to the show.

Ryan Mahdavi: 13:11 Thanks for having me. Good to see you guys.

Jason Calacanis: 13:14 Yeah, Ryan doesn’t have an axe to grind here. This is straight-up, heads-up competitor. This story is crazy. And there’s also, like, Vanta, which came before this. So this is a pretty wide space. And they came in with the concept, Alex, of disrupting the Vantas of the world and using AI to make this go faster, yeah?

Alex Wilhelm: 13:36 Absolutely. The idea was to bring AI and automation to a very boring process. Compliance is kind of like doing your personal taxes. Like, you have to do it, but everyone absolutely hates it, and it always involves more paperwork than you think. So why not use tools to go faster? Well, if you fake it, you can go really, really fast. So, Ryan, I want to start with just a very broad point here. You’ve seen all the materials, you’ve seen the Substacks and the leaks and so forth. How credible are the allegations against Delve from your professional standpoint?

Jason Calacanis: 14:05 And what are they? Let’s explain to the audience what the actual granular accusations are, if you have them there, Ryan.

Ryan Mahdavi: 14:11 Yeah, yeah, yeah. I’ll—there is a lot to unpack there. It’s quite in-depth. I want to just start off by saying that this is an—a very genuinely unfortunate situation, not just for Delve’s customers, but the entire industry that effectively runs on trust. That said, whoever put this investigation piece together, bravo. The level of forensic detail is impeccable. And like I said, there’s a lot to unpack there, we’ll try to do the TLDR for the audience. But I’m curious whether you guys think this is a disgruntled customer or a coordinated hit piece. Either way, these are very serious allegations, which if proven, will likely have criminal implications. So on a high level, you know, there was an incident that happened, right? This incident happened in December, there was some leakage since then. The biggest problem here is 500 boilerplate reports, same errors, spread across a number of companies. And when you—

Seb Sheng: 15:00 of those 259 type 2 reports, which is effectively the more rigorous version of SOC 2, zero auditor findings across every single client, which is almost statistically impossible. And this has affected brands like Lovable, Bland, Clearly, and then Duo’s Edge, which is a public company. And then of course subsequently, they had that Supabase bucket leak, which publicly exposed background checks, Stripe tokens, I mean it’s getting messy.

Alex Wilhelm: 15:30 So that’s the latest and keep in mind we’re at part one, part two is set to drop this week, which you know we’re all unfortunately grabbing our popcorn for, but this is what’s happened at a high level.

Jason Calacanis: 15:42 Okay so Alex, just to step back here, somebody released these allegations in a Substack anonymously, am I correct?

Alex Wilhelm: 15:48 Yes, they went by Deep Delver. There was a leak of customer information, the company said that’s all fake, they went through the leaked information and said, ‘Hey, this looks incredibly fishy,’ you know, copied errors across different documents from different companies, a web of auditors that appeared to be, I would say, less than above board if you will. And as Ryan mentioned, just a lot of indication that these were not personalized reports that indicated how a company actually did, but were instead essentially compliance theater, Ryan might be a way to put it.

Jason Calacanis: 16:17 Got it. So there was a leak of data and then somebody did a Substack based on that leak? Or the Substack is the leak? Just so I’m clear.

Alex Wilhelm: 16:26 It’s hard to say because the leak definitely exposed a lot of information, but there’s so much detail here and that’s the piece where it’s like there has to be a collaborative effort. It seems like that leak alone doesn’t necessarily paint the whole picture, like there’s - it’s very very detailed.

Ryan Mahdavi: 16:47 I mean, you know, look, we, you know, see this as a broader problem than just Delve. We can get into the details of specifically how this goes into Delve, but there’s a difference between hustling and faking it. And to be fair, there’s a lot of overpromising and hyper across the board in the space and maybe AI in general. But 500 boilerplate reports, nearly half of which are basically identical, zero incidents, it’s - you know, this is not cutting corners, if proven true this is gaming the system.

Jason Calacanis: 17:19 Yeah, it’s pretty clear from what we saw in it that they - if it’s true, because this is all allegedly, if this is true and they did those reports and they just changed the logo on them and it’s like AI slop or it’s cut and pasted, that would be definitionally fraud. And you could have gotten your customers into trouble with their customers, so there’s like lots of second order impact here. But somebody leaked this. Was it an internal whistleblower? Is it a customer of Delve’s? Those are all the questions. But there is an underlying issue here Elizabeth that you and I deal with. The area of… Y Combinator specifically and, you know, startups generally can attract hackers. In fact, Elizabeth, on the application for YC, they ask this very specific question, which is like, tell us some time you hacked something. And when Paul Graham talks about, you know, Sam Altman, he was like, oh my god, he was such a hustler, a hacker, you know, got through all these things. There is a hacker culture, white hat, black hat, grey hat in between. So I guess we have to also think how much of this has to do with the culture of Silicon Valley’s saying, hey, bend the rules, and where the line is there, Elizabeth. So take the audience through what you and I see on the back end when we do diligence, how often you see people bending reality and how often are they just straight up lying.

Elizabeth Yin: 18:53 It’s really tricky because the audience we attract fundamentally is trying to think out of the box, which may push the envelope and break some rules. And in fact, actually for some companies, they may literally be breaking the law, but then the laws may change over time, right? So there’s also that factor.

Jason Calacanis: 19:08 Airbnb, Uber…

Elizabeth Yin: 19:10 Yeah.

Jason Calacanis: 19:11 Self-driving, yes.

Elizabeth Yin: 19:12 The biggest companies we admire. Yeah. So I think that that’s tough. Um, but I think let’s take it from the investor perspective. I mean, from our perspective, Jason, like the companies we look at are so early, and we don’t often know what is happening on the day-to-day basis, like do they actually have auditors? Are these, you know, accredited auditors? We don’t know.

Jason Calacanis: 19:30 No, candidly speaking.

Elizabeth Yin: 19:32 No, like candidly speaking. So we’re just kind of going based on what the founders say, etc. And that is actually what every founder wants, like investors who can move fast and make a decision. So there’s going to be some of that. But I think that’s also why we need checks and balances in the ecosystem, journalists who can discover these things. Um, unfortunately, it seems like the regulatory bodies haven’t discovered this yet, but I’m sure based on this, they will come in and take a look. But that that is why we have these different parties. I don’t actually think it’s our job as investors to get into the weeds. No one would ever get a check if we were to get into the weeds because you can scrutinize everything ad nauseam. So that’s on the investor side, and unfortunately, we just—like I think there’s just going to be a percentage of every cohort, whether you’re YC or whoever, who will end up in a problem like this, and that’s sort of the price we pay. Um, but on the founder side, like I think how would you have protected yourself if you were a Deel customer? It is really important to ask your vendors like for, you know, their credentials. Like you could ask whether the auditors are accredited, like show me that proof. Of course, they could still make it up. I’m sure there are ways they can fabricate paperwork, but that, you know, helps a little bit. Um, but that’s the kind of thing I do think that founders need to, you know, ask their startup vendors like how they’re doing this, etc., and—and to some extent suss out whether it makes sense.

Jason Calacanis: 21:00 full-time job and hey, guess what? I already have a full-time job. I make podcasts and I invest. But when you’re running a small company, we both know every hire matters. You don’t want to waste any of the seats you have at your company. And the best partner you can have is LinkedIn Hiring Pro. Why? There’s a billion people using LinkedIn. All the great talent are there. If you’re proud of your work, you build a LinkedIn page and you update it. LinkedIn Hiring Pro is going to streamline and simplify the entire…

Seb Sheng: 21:27 Jason, tell me more about how to find fraud at companies and what are the red or pink flags that you look for when you’re talking to a founder for the first or maybe even third time?

Jason Calacanis: 21:34 Yeah, so Elizabeth makes some really good points here. We live in a trust-based environment. Now there might be some people, you know, who are, you know, in the media or just naive who think, ‘Oh well, you’re an investor in the company, so you’re sitting at the office every day and you’re listening to the conversations and then everybody submits your work and you validate it.’ Like, not how it works. When you’re a minority shareholder under 10%, you have, you know, information rights, which you never call. You rely on the trust of the founder to send you a monthly, quarterly update—every six months, whatever it happens to be. We like to get monthly in the early days and quarterly thereafter. So you’re relying on them to tell you the truth. But we do diligence. And when we do diligence, there’s some very simple things. We will ask the founder: Has there been any legal action taken against the firm? Has anybody threatened legal action? Have you had an email, a letter sent to you about that, you know, threatening legal action or of a legal nature? So, you know, we really expand it. Now, we’re trusting them, you know, to do that. In our accelerator, we take great pains to explain to our founders—and we love a good hacker, we love somebody who can, you know, bend the will of the world to their vision. But we tell people when you are doing something for a selfish reason, so for your own gain… Like, you know, there was an issue where Zenefits was helping people hack their insurance licenses, right? And this was like the big battle at that company, and the founder, Conrad Parker—I got that right? Yeah. He got ousted. He did his revenge startup, Ripple and all this stuff. You know, he made a mistake, he got an SEC fine, he got a, you know, slap on the wrist, basically. But he also lost control of his company. In that example, the reason why helping your insurance brokers, in the eyes of the law, cheat on their insurance test or just not take it properly, that was to benefit them. Now, if you’re Airbnb and you’re saying, ‘Hey, we believe that people should be able to rent a room in their house,’ that doesn’t benefit Airbnb as much as it benefits the person renting the room and the person renting it for having more options. So you have to put it through that lens. Okay, put that aside. Then we also do training, Alex, very specifically around—and Ryan, you went through this—don’t ever exaggerate reality. So when you have your customers, like people, I don’t know if you’ve seen this a bunch of times, Elizabeth, they have a slide. ‘These are our customers in pipeline.’ And we’re like, okay, two different things. Customer implies they’re paying, user implies free, pipeline means you put them in a database and you sent them an email. So put that on the three different slides. So we’ll train founders to do that. Or they’ll say like, ‘This is our pipeline,’ or ‘weighted pipeline,’ all this like weaselly language that can unintentionally get you in trouble. And we’ll give you an example. We had a company, they said that they had certain customers, they also said they had certain employees in their deck. They pitched an investor. Investor puts 50k in it. Company’s not working out, they’re not getting information from the company, this angel investor went, called the people who were listed as employees and they said, ‘I never worked there. Like, I met the guy, but I never worked there.’ And then they—he called the people who they said had pilots and they said, ‘We never had a pilot, we took a meeting with them.’ He then sent a demand letter saying, ‘I want my money back or I’m going to the SEC with this.’ They gave the money back, the whole thing blew up. The founder was exaggerating/lying while raising money. When you do those two things at the same time, Alex, you make claims and you raise money, do you know there’s a special term for that that the SEC has?

Alex Wilhelm: 25:37 Could it be, uh, securities fraud, perhaps?

Jason Calacanis: 25:40 Correctamundo.

Alex Wilhelm: 25:41 Not good. I’ve heard of that. People go to jail for that, prison. That’s a serious… Okay, but the line, Jason, between exaggeration and lying seems fuzzy based on what I’ve heard from both you and Elizabeth. Can you boil that down for founders? So that way they know how to stay on the right side.

Jason Calacanis: 25:58 Go ahead Elizabeth. Yeah, well, maybe with some practical examples that you obscure a little bit like I did.

Elizabeth Yin: 26:00 So, this last example that Jason gave is probably the number one way that we ding founders around sort of this fraud thing. Because usually the business is not far enough along such that, you know, they may not even be doing compliance actively at that point when we’re investing. So but the way that we do suss this out is you need to be crystal clear about the state of everything. So if somebody is not actually your customer, like you’re talking with them etc., and you say they’re your customer, like and we find out about that difference—as much as it maybe they may be your customer tomorrow—if they are currently not your customer, we will ding for that. Because that suggests future behavior in exaggerating in other ways.

Alex Wilhelm: 26:44 Is that a lethal—is that a lethal infraction? Like if a company does that, and let’s say, in one case, would you not fund them based on that alone?

Elizabeth Yin: 26:51 Yeah. And I’ve been very upfront and direct with people. It’s like, ‘You told me on this slide they’re customers. It turns out they’re not customers, you’re talking with them.’ I’m out. Because I can’t trust the rest of your slide deck.

Jason Calacanis: 27:00 And then people usually say something like, well, we’re so close, they have the contract in hand, you know, it’s not totally out of thin air, but they have the contract in hand is very different from they are a customer.

Alex Wilhelm: 27:11 I have a question for you guys, like, you guys invest quite broadly and you do this from a diligence standpoint and you have the investor angle much better than us. The way I view it, and I mean for us was pretty clear, a simple 30-minute demo, I think, would have exposed a lot of so-called features that don’t even exist. This does not require domain expertise and bringing in someone to do further diligence. So I’m just wondering, like, what’s the, because we’re not talking about just a seed stage or pre-seed, we’re talking about Insight Partners and $32 million checks being written here. So I’m just curious, like, if that changes things for you guys.

Jason Calacanis: 27:42 Yeah. So, if it was an accelerator that wrote the check, right, you’d be like, okay, it’s an accelerator, the product’s not even done, whatever, the product’s just in market, hey, you know, and this is like a really good question. How does a big company make this mistake? How does a big company make this mistake? Like, and how did they make the mistake in FTX? As the stakes get higher, the diligence should get deeper. So, if you were writing a 25k Angel check amongst 20 angels, you know, Elizabeth and I doing this in the old days, there would be a lead who put in 250 and they would do the diligence, but at the earliest stage, again, back to a trust-based ecosystem that we live in. Now, you’re FTX. Nobody did any diligence, and the reason was that founder, specifically that founder, I believe, this is what I believe, and then he went to jail, was found guilty, so the court of law also believed this. I believe he used other people’s reputation and the momentum behind crypto to dissuade people from doing diligence and to put pressure on them. So we as investors will deal with this high pressure. Hey, you know, this person’s leading, I have this many days, I’m oversubscribed, need the money now, yada yada yada, you have to rely on their diligence. And then diligence by proxy is the issue here. People will say, oh, these other people are in the deal for Gelve, for Theranos. I can use their diligence as a proxy. That’s the cardinal sin. People have to do their own. And then the founder would come back to you and say, listen, I don’t want you calling our customers, they’ve already been called by this person. And we say great, can that person send me their notes? And that’s the high level of diligence. So when founders say that to us, hey, we don’t want you to talk to the customers, we don’t want to burn them out, we’re like, okay, that’s reasonable. Can you have, you know, Insight Venture Partners, Sequoia, Pear VC, whoever’s doing it, Elizabeth, Hustle Fund, can you just share with us the document? And Elizabeth and I have, I think, probably shared this in the past. Yeah, Elizabeth?

Elizabeth Yin: 29:54 I think so. For some of these really high-flying companies, you may not have that opportunity. They may say… You’re either in or you’re out because I have so many people who want in and there are so many late stage investors now that you either want to be in this and just take a risk that, okay, the traction’s amazing, let’s go, or you say okay, I’m out. And the late stage investors don’t want to miss out because there are very few deals that will really make their fund.

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Ryan Mahdavi: 31:35 I mean, we saw the signs like six months ago. And look, we haven’t gone in and I’m actually curious, I want to go back to this point, we haven’t spent a lot of money on marketing. I would say basically nothing on marketing. It’s all been referrals and inbounds and focusing on the product itself. So that said, obviously we’re in the industry, we’re talking to other founders, we’re seeing customers, I mean over half of our customers came from incumbent players like Vanta, Drata, etc.

Pranav Ramesh: 32:01 We started to see like both claims are fine, marketing stuff is fine, everyone’s kind of, you know, over posturing and doing whatever they need to do to be competitive. But it’s, I’m telling you it was like five or ten minutes into seeing the platform and saying, like we were actually joking around like this is screenshot native rather than AI native. And you don’t even have to be an expert. Like you could just say, hey, these are the features you say you have, where are they? Show them to me. I legitimately think a 10 to 30 minute demo with anyone who has a baseline understanding of tech would probably catch this. Now, for me, I’m always also skeptical when a company’s early growth tactics consist of dishing out donuts and doormats, you know, and just going extremely heavy on growth tactics. So I don’t know if that’s a red flag for you guys very early on.

Jason Calacanis: 32:49 Explain what happened there. They were sending donuts to people to get them on a exploratory call for their product?

Pranav Ramesh: 32:56 Yeah, these were what was considered growth hacks, right? Which I mean…

Ryan Mahdavi: 33:00 Could just feed you guys out some donuts and doormats today. I don’t know if you’re gonna cut me a 30 million dollar…

Alex Wilhelm: 33:03 What’s the doormat? I don’t understand that hack. I understand the send a pizza, can we do a call, we’ll send a pizza.

Ryan Mahdavi: 33:09 Yeah, yeah, it’s like a branded doormat for their offices or prospect clients’ offices, something of that nature.

Jason Calacanis: 33:15 Yeah, I have seen those techniques from sales departments. They started in the pharmaceutical industry where what they would do is they would call the nurse’s station and they’d say hey, would you guys prefer - we’re gonna be coming over from Pfizer, we wanted to buy the nurses lunch. You guys want Italian, or you want Chinese, or you want Mexican? And they’d say whatever and they’d spend 200 bucks bringing some food, or in the morning some donuts. And then they would come and give them samples and talk to them about the drug. Totally fine. That uses the effect of reciprocity. I give you something, you give me back your time. It’s not - there’s nothing illegal about it, there’s nothing untoward about it. But if you’re spending too much on that and not enough on the product, that would be where you’d have breakage.

Lon Harris: 33:51 So Delve went around SF handing out donuts to different people, Jason. And also they use them per the Substack report as a way to smooth over things. The report says when clients ask hard questions, Delve dodges. They demand calls where founders charm, promise, and name-drop. And when that fails, donuts arrive. So it appears to be a donuts on the front end and donuts on the back end strategy.

Alex Wilhelm: 34:09 Well Elizabeth, did you notice that? They used - they used other brands. So this brand washing strategy is what a lot of criminals use. A lot of the most notorious - there was that movie with Leonardo DiCaprio, ‘Catch Me If You Can’.

Pranav Ramesh: 34:21 Catch Me If You Can.

Alex Wilhelm: 34:22 And he was trying to figure out like how do I cash a check? There’s like this great scene in the movie and it’s like well who’s the most trusted person in the world? Like we would, you know, and the most trusted industry. At that time it was airlines, right? Like Pan-American was like - and a pilot for Pan-American was like wow. That’s like God coming in and cashing a check. And sure enough they would cash his check. So that’s what happened with FTX. They said hey we have all these investors and they bought all those celebrities. And it apparently, allegedly, perhaps, allegedly, allegedly, allegedly, insert that all over the place Elizabeth, that maybe that’s what happened here is they were using those names to try to get people to stand down on diligence.

Elizabeth Yin: 34:54 That may be true. At the same time, there’s so many great reputable companies also, you know, using social proof of other brands. So I wouldn’t use that as like a bad signal. Like oh you know Salesforce is a customer, that’s not a bad thing.

Alex Wilhelm: 35:02 That’s a great thing.

Elizabeth Yin: 35:04 It’s great.

Pranav Ramesh: 35:05 I think the question is not necessarily the donuts. I think it’s like - I mean Jason, you were here last week, right? Was it last week, I don’t know. You guys walk around SF, you see Vanta everywhere.

Jason Calacanis: 35:14 Yeah.

Pranav Ramesh: 35:16 Now you see Delve everywhere. Now Vanta’s raised something to the tune of half a billion dollars. These guys are in their what, series A, 33 million, whatever it was. You guys as investors, is that something that you’re happy with? Is that something that raises any red flag? Do you walk around a city and you see…

Ryan Mahdavi: 36:00 That’s very fitting like this.

Jason Calacanis: 36:02 I would say all over the place. Yeah, so now let’s move to Elizabeth and I are on the board of the company, right? And this is another place where things can break down is governance. A lot of folks, including YC, they don’t want people, they don’t want the investors to have board control, they would rather see you do smaller rounds, they kind of advise against this, you know, don’t have any major investors, don’t give anybody a board seat. I think when you raise over $3 million, or you’ve got over a million or two million in revenue, you need to have board meetings. Why? There’s something at stake here and you will make a mistake and you might flip the car, and you might flip the car unnecessarily because you just don’t know how much speed to take on that turn if we were using Alex one of your beloved F1 or whatever racing analogies and that’s where like a good coach and a good team would inform you like, so they if you told me Ryan, I’m in a board meeting and they’re saying hey we’ve got a million dollars in revenue and we have a $4 million ad campaign I’d say, whoa let’s slow down one second here. Um, where did we get our how did we get to a million in revenue? Like how many customers are they? Say oh it’s 50 times 20k. Great. How do we get those 50 and I’m like, we used um email and uh we got word of mouth and uh we have an outbound sales team. It’s okay, let’s double the spend on the outbound sales team and let’s see if that works. Pouring like that kind of gasoline that early seems very dangerous, very dangerous. It is a red flag. But what do you think Elizabeth? Go ahead, take it.

Ryan Mahdavi: 37:27 Yeah.

Elizabeth Yin: 37:29 That is a red flag. But I would say as a performance marketer sometimes you can get amazing buys on those billboards. Obviously depending on the supply and demand situation and I don’t keep a pulse on that but I- I’m not critical immediately if one of my companies wants to take out a billboard. I don’t know what but I think like understanding how much are you paying and how much are you getting out of it is is something that I-

Jason Calacanis: 37:51 Which is what a board does, right Elizabeth? You’ve taken board seats before I assume and they-

Elizabeth Yin: 37:56 Yeah exactly. But I imagine they would have a board or like and-

Jason Calacanis: 38:00 You would think they had a board at 30, somebody will check that right now. A Series A, almost always somebody joins the board. What we do in our firm is we say if we have over five or 10 percent we want a board observer or board seat. We’re not gonna take it because we can’t possibly take it in all those but we tell the founders like Ryan we probably had this conversation with you and your- your attorneys might have said like ‘Wait, why are you giving them a board seat this early?’ and we say ‘No, no, it’s an option to have one and it’s only if we have like a certain large amount of the- a large amount of equity and you want us engaged. You want your large investors engaged unless you pick the wrong investors or you’re doing something where you know oversight would be not good.’ And this is where the whole industry has fallen down with governance and it’s because in the early days too many founders got ousted from their own companies and then the pendulum swung to ‘Hey founders get 100 to 1 shares, you know, at the seed round’ and that was like maybe six months of that nonsense. Um, but yeah, that would be where a board would come in and review spending and have a- budget and a plan and accountability so the CMO would say, yeah, we’re going to do this four million dollar thing, it’s going to generate twelve million dollars in pipeline, we are closing 50 percent now, even if we close just 33 percent, it’s going to break even and that’s what we want to do.

Alex Wilhelm: 39:16 Yeah, I guess the argument there is like with tech being so commoditized is distribution something that people are going to start spending more heavily on? I think this is something you guys brought up earlier as well. Uh, so to some degree justified on the other hand, it’s like what are we competing on since this is like marketing agency with a software layer, and of course that leaves room for us smaller players to compete because usually they’re falling behind there’s marginal differentiators between different companies. I guess it’s a balancing act of how to do that, right? So…

Ryan Mahdavi: 39:47 It’s interesting how many things can be high trust and low trust and good and bad because if you think about the billboard point that Elizabeth made, Twilio’s billboards are like historic SF milestones, you know, Twilio asked your developer. And then if you think about C3.ai, they had tons of billboards and that company’s an absolute dumpster fire. Uh, they, you know, Deel used a lot of IRL advertising, not so good. But then again, Brex did the same thing because they leveraged the arbitrage that Elizabeth was mentioning. It’s amazing how many things are just not exactly black and white in this case, and it really boils down to context.

Jason Calacanis: 40:14 Context matters.

Ryan Mahdavi: 40:16 100 percent.

Jason Calacanis: 40:17 And, you know, where context comes from? From adult supervision. I’m going to sound like a grandpa here. I’m going to sound like Unc J-Cal. But there’s a reason why, you know, we have a structure in America that made us the most competitive entrepreneurial force in the history of the universe. Not since the Greeks has there been so much innovation. Uh, you know, us Greeks, you know, it’s just in our blood.

Ryan Mahdavi: 40:43 Persians as well.

Jason Calacanis: 40:46 Persians as well, which are, you know, kind of the Greeks, you know, kind of expanded from the Greek peninsula all the way down. We share a lot of blood, the Greeks and the Persians.

Alex Wilhelm: 40:54 Wait, did you just claim Persia?

Jason Calacanis: 40:56 We claim everything. Yes. We believe everything came out of Greece, went to church in Italy, Roman Empire came from the Greek Empire. That’s our story. That’s what we believe. We’re sticking to it.

Lon Harris: 41:08 Okay.

Jason Calacanis: 41:08 But, you know, if we were looking at this just first principles, you need to have some adult supervision in the corporate structure in America, which is why when you file as a Delaware corp, they have in your charter board meetings, board members, you know, reports, audits, whatever. You have to define these things and that’s what you work with your attorney on. Hey, we’re going to define how many board meetings we’re supposed to have, did we have them or not? These rules came out because of previous lawsuits, previous issues in the marketplace. So the fact that they’re bubbling up again is because sometimes in a hype cycle, which we are in peak hype cycle right now, people let their guard down because they’re greedy. So the greed index is off the charts right now, the fear index is very low. After 2008, fear… VIX all-time high and, you know, greed index very low. And it just keeps happening, back and forth, back and forth, and you get weird behaviors during this. But Ryan, just to wrap up here, your company uses AI and tools to automate this, but explain why we can trust Ceel when Delve maybe we shouldn’t have. How do you make sure that your AI is not producing slop or making errors? And how should customers look at Ceel, Vanta, whoever they choose to use to make sure that the product is good and it’s tight?

Ryan Mahdavi: 42:38 Yeah, great question. I think, look, everyone is shitting on Delve now because they basically got accused of doing something that’s fundamentally wrong. The idea was great. I mean, it’s something similar that we’re doing. We want to make it easy. SOC 2 is not a one-size-fits-all. These guys have a chokehold on the market. And look, you know, board meetings and meeting minutes for two-person startups… And you guys just talked about it. We’re going to see companies that are going to be sub-five people doing potentially billions of dollars in revenue, if we’re not headed there already. It doesn’t make sense. There needs to be changes. There’s a huge need for this. So we have AI tools that help. We make sure that guardrails are in place. We’re not cutting any corners. So you have to be competitive on the marketing side, but you have to deliver. So people come to us and they’re often a little bit disgruntled, like, why is this taking so long? This is taking longer than what we expected and we were promised XYZ. Well, this is the perfect opportunity. So we have a huge influx of people already reaching out. And we’re going to take this one step at a time and not create a leaky bucket like they did, because it’s going to backfire on you. So for anyone affected, please feel free to reach out to me directly. It’s ryan@ceel.io.

Jason Calacanis: 43:44 That’s my guy. That’s my guy Ryan.

Ryan Mahdavi: 43:46 And one of the great marketers. I’ll take care of you. That’s my segue. I haven’t even started yet. Wait till you give me more money. I’m going to have posters all over the place.

Jason Calacanis: 43:52 Listen, here’s what you have to do. Remember, if we give you the first money, you have to prove a second person can give you money and then we’ll come in after them. That’s how the game works. We can’t be the never-ending source of revenue. Although I have done that a dozen times in startups. It never works out well. You need founders to be able to raise money. All right, great job, Ryan. We’ll drop you off. Let’s see everybody go to ceel.io. Ceel.io. C-E-E-L. We have our syndicate. We like to share deals we’re doing. So, you know, we’re going to interview a company here that we’re considering for our syndicate and would love to have you give some thoughts. You’re awesome and you can evaluate companies. So let’s have our next founder on.

Alex Wilhelm: 44:46 Yeah, all right. Coming up next is Seb Sheng, the founder and CEO of Brick. Jason, I love this company because we’re talking endlessly about power consumption and how to make the overall grid more stable as we add data centers. Well, the idea behind Brick is bringing a piece of technology in… into a building or a data center, plugging it into key systems and letting it learn about how that building or data center uses its energy to save up to 15 to 30%, Seb, I think you told me?

Seb Sheng: 45:11 Right, up to 35%.

Alex Wilhelm: 45:12 Which is an enormous amount of energy and an enormous amount of money, and if this works the way Seb and company think it’s going to, well, maybe our grid won’t collapse by the time OpenAI finishes Project Stargate. Welcome to the show.

Seb Sheng: 45:22 Awesome, thanks Jason, Alex. Um, obviously pleasure to be on. Look, BRIC is a AI-native energy tech company. What that effectively means is we are effectively building an energy-saving agent that, as Alex mentioned, puts all these energy-consuming systems from our everyday HVAC systems to industrial-level chillers or heat pumps on autopilot. Um, we all have that silly thermostat in our everyday households. Doesn’t work, makes tons of mistakes. Obviously, Ecobee of late, as we all have probably come across Andrew Huberman’s podcast, all these new smart home optimization leveraging these new tools. Once, you know, that bot as such can find every single device on their local network, things can be automated. But really in the enterprise world, things are much more complex. So what we do is we have a hardware piece that gets connected to these complex systems in reference and effectively build a software learning the data, everything from system data to environmental data to power data, training this AI agent, which again, we all know is an overused notion nowadays. But we have an AI agent that does real work. In our case scenario, coming up with these—all these energy-saving rules slash strategies, introducing temperature thresholds, pre-cooling, pre-heating based on power prices, power price, so on and so forth. And the end result, as Alex, you alluded to, 15 to 20% in energy savings on average, up to 35%, and decarbonization is just a natural byproduct of such. So that’s really the 20,000-foot view.

Alex Wilhelm: 46:57 Seb, just to go one level deeper, tell us more about the hardware device that you have to bring on site, and then also move past the temperature element of this and tell me about data centers because I think everyone’s freaking out about how we’re going to fuel essentially our AI revolution.

Seb Sheng: 47:11 At the end of the day, you know, look, there are different type of devices here. Um, as we all know, right, the underlying principle being garbage in, garbage out. You know, this agent does—not only needs system data, but environmental data, power data. What we have proprietarily internally at BRIC is a universal gateway. So think of this universal gateway device, this black box size of this, width of this. It gets connected to a master unit of an HVAC system. Again, a silly notion of master, you know, slave type notions kind of within the HVAC world. But effectively what that means is the master units are already connected to the slave units. So very much via a one-to-many relationship, simple gateway gets connected to the master unit, we’ll be able to cover the entire building. So all of a sudden you have a $2,500 device that can cover the entire building footprint, that gets all the system data. From there, like we discussed, right, whether it’s a data center, commercial office…

Ryan Mahdavi: 48:00 …hotel, we effectively, are gaining the nitty-gritty data such as coil temperature, flow rates, refrigerant. So all of a sudden, we are not just controlling things via on and off, right? We are doing much of a deeper level analytics. In terms of the data center space, guys, think as follows. It is getting over-saturated. It is an overcrowded space in terms of development, in terms of solutions providers. It’s just another data aggregation platform. So it’s another dashboard play. What we need is taking the relevant data set from the existing operating system, in this case, the DCIM, being able to drive intelligent decision-making on top of it.

Jason Calacanis: 48:35 So you have a hardware device, connects to the system, you get AI to analyze it and then give actionable real-time decisions that will save money. Who are the customers and how do they pay for it? Are you charging for by square feet, are you charging for the number of HVAC units, are you charging by outcomes, a percentage of what’s saved? How do you think about pricing this product? And Elizabeth, I’m sure you have some questions, hopefully I didn’t steal yours, but we always like to know the business model as investors.

Ryan Mahdavi: 49:09 Great question, Jason. The end outcome being it’s all tied to the actual energy savings we can generate for clients. So it’s a rev-share of energy savings as the core of the business model. We certainly have two bifurcated payment models that we work with clients, which are commercial and industrial. So again, taking a step back, we engage with commercial office buildings as essentially managed hotels. On the industrial side of things, obviously we have our internal pecking order. But for industrial, it’s really working with industrial manufacturing clients such as Lucid Motors. Tesla would be next in line where we’ve been pushing forward a lot of these, you know, kind of sales motion and conversations on the front end, to the data centers on the industrial too.

Jason Calacanis: 49:49 And who are the current customers? You have current customers using it?

Ryan Mahdavi: 49:57 So we’ve worked with the likes of JLL on the commercial real estate side of things, to hotels, DoubleTree Hilton, to Sheraton Grand, for data centers, DCTC, Inspur, as well as industrial manufacturing such as Lucid.

Jason Calacanis: 50:07 Okay so you said worked with, are you currently working with all those just to be clear, or they’re previous like one-off engagements?

Ryan Mahdavi: 50:18 They’re all existing customers, sub-brick.

Jason Calacanis: 50:18 Okay, great. Just wanted to parse that language. You can see Elizabeth and I were just talking on a previous segment about making sure we have that dialed in. Your questions, Elizabeth?

Elizabeth Yin: 50:22 Just to understand where you are life stage-wise. Like where are you? It sounds like you’re pretty far along and you have a lot of customers. Like how much are they typically paying you?

Ryan Mahdavi: 50:32 We’re still very much early stage. So look, we, you know, the company was formally incorporated back in March ‘24. So over the past two years, really the year and a half timeframe is, is all on our actual product development R&D side of things. We kicked off commercialization just about eight months ago. So within past eight months, right now our ARR at this stage is about 450 live ARR to 400 contracted ARR. The difference in that definition being the…

Pranav Ramesh: 51:00 Contracted ARR. The folks have signed the contract but, yet, the full deployment hasn’t started. That’s the key distinction. So, the contracts-

Elizabeth Yin: 51:08 And what does it take to do a full deployment? Because it seems like the hard part is getting these brand names which you have. And they have many buildings.

Pranav Ramesh: 51:15 Exactly right. So, at the end of the day, it’s a portfolio play, right? We obviously have to land and expand in a sector that’s relatively stale, slow moving. It’s not only about, you know, adhering to continuous of a direct DTC type of sales motion, it’s actually working with the channel partners, which can be the HVAC OEMs, which can be, you know, energy efficiency, existing energy efficiency players that are already plugged into these environments that need more of a smarter control layer on top of their existing offering. So, look, for us, at the end of the day, the ACV on average will stand at minimum 30 to 50 thousand dollars per facility. On average, for each client we’ll be working with at least two to three facilities as a starter.

Elizabeth Yin: 51:56 Yeah, I think very directly, I’ve seen a number of companies do this exact same thing and everybody seems to get stuck around the same thing. Like the big logos are willing to kind of try or talk with you or or whatever, but then somehow there’s this hurdle of how do you get JLL to roll this out to all of their buildings? And so I think that’s that’s really what my question is. Like, you’re suggesting you have to go through another third party to get this on board or how do you get everyone to move faster or prioritize this? Or is this, candidly, not a priority because they’re swimming in money and they don’t actually care about saving that much?

Pranav Ramesh: 52:29 Great question. Let’s- I mean, here are the two aspects of the- of the fact of the matter on hand, right? On one hand, like you said, slow moving counterparts we’re working with, they have been approached by tens or 20 dozens of these energy efficiency players. Really, the existing barrier to entry is always boiling down to two things. It takes extremely long to get a deployment started, and it takes a lot of money to get deployment started. So, it’s always got to boiling down to the time and cost of the equation. And for us, because of the hardware capability that we have, effectively you- all of a sudden you have a $2,000 to $2,500 device that can top the entire building footprint, and the deployment timeline is exactly the four to six week pilot that can prove the ROI right on-site of- right outside of that timeframe. And we extrapolate that to determine the actual pricing point of our ACV. That’s how it works. So, all of a sudden again, you know, the other beauty thing with our underlying software model is the scalable nature of it. Uh, we have a foundation model for each of the sectors that we tackle. So, all of a sudden you have an agent that can repeat- rinse and repeat for a second or third building underlying the same sector.

Jason Calacanis: 53:34 Lightning round. How long have you been working on the company for? When were you incorporated? When did you have your first customer?

Pranav Ramesh: 53:42 March ‘22, we had our first customer, paying customer, not just pilot customer, paying first paying customer in July 2023.

Jason Calacanis: 53:49 Perfect. So, two-year-old startup. How many people work at it? Where are you based?

Pranav Ramesh: 53:53 We have four full-time employees and two part-time, and we are based in SF.

Jason Calacanis: 53:57 Have you gone through any of the accelerators yet? Have you uh raised capital before? Tell tell us a little bit about the history of the company.

Seb Sheng: 54:05 Yeah, so, you know, obviously great to working through this current round with you guys, as as we’re wrapping our second capital raise, which is the pre-seed round that we have. So we only had one prior capital raise, uh, which is the accelerator round that we did with Forum Ventures and Rice Cap.

Jason Calacanis: 54:21 Forum Ventures has an accelerator in San Francisco. Awesome to know. Uh, we’ll make a note of that, so we can trade deal flow. And what makes you, last question, uniquely qualified to pursue this vision for the next decade?

Seb Sheng: 54:30 At the end of the day, it takes a blend of not just technical aptitude, kind of taking a fresh lens on the same problem that’s been around for two or three decades. You need the commercial leadership in terms of network and channel partnerships as well as the domain expertise. Being deeply embedded in the space that that we operate in, you really need to think not just from an operator standpoint but also from the building engineers and owners’ standpoint. Each one of these has a different set of incentives underlying. So it’s really about getting everybody on the same page, understanding okay, for building owners they care more about bottom line, OpEx decrease, for building engineers it’s about checking boxes for technical side of things. And again, you know, it’s really the blend of those three things that can make Brick outcompete everybody else and really the rest of the roadmap going forward is about scalability.

Jason Calacanis: 55:25 Okay, great. Seb, stay on the line. We’ve got a little surprise for you. I’ve been obsessed with Tao and Open Claws for the last 50 days. I’ve gotten very involved in it. And we’ve got somebody running one of the subnets. A lot of people have been asking me, Alex, about uh you know my tweets this weekend and then just the last couple of weeks of having a lot of subnets and BitTensor topics here on the program. We’ll get into that in a moment after we talk to, yeah, here it is, not financial advice, not financial advice, family member, what’s this Tao you keep talking about on the pod, me, sell half your BTC and buy some Tao. I don’t give financial advice, but maybe to family members I might give a little bit of advice.

Alex Wilhelm: 56:21 Sure, sure.

Jason Calacanis: 56:22 And, you know, it’ll become apparent why I’m so bullish about Tao and I’ll tell you about my specific trades right after we have our next guest on. And before we have our next guest on, Alex, 30 days of skiing, look how svelte I look. Elizabeth, you notice I’ve lost 40 pounds?

Elizabeth Yin: 56:23 Amazing.

Jason Calacanis: 56:24 Thanks for noticing, Elizabeth. I do appreciate it. I didn’t do it alone. Ro.co. Get yourself a GLP if you’re so inclined and you want to be fit and you struggle with weight loss like I did for a long time. I used to be very svelte, 166 when I was running marathons. I gained two pounds a year while I was married, having kids, building companies. I woke up one day I was 213, now I’m svelte 172 again with a little bit more muscle on my frame, skiing 30 days, sleeping great, feel awesome. I’m going into my 50s in my dad bod era with 40 pounds less of fat on my body. I feel great. I did it for my daughters and to stick around a little bit longer, plus my energy level’s twice as much. If you want to check this out, ro.co, because they have an insurance checker. You can just check, ‘Hey, does my insurance cover this?’ They’re going to tell you like lickety-split if your insurance covers it. And if it doesn’t, they’ve got a lot of options for you that are very affordable. Very proud of my association with ro.co, and I think we even have a special URL. Yeah, Alex?

Alex Wilhelm: 57:27 Yes, we do. It’s ro.co/twist. It’s very simple: ro.co/T-W-I-S-T.

Jason Calacanis: 57:32 Okay. Elizabeth, I don’t think you’re on a GLP. You, you’ve been in incredible shape since I’ve known you.

Elizabeth Yin: 57:42 Oh, thank you. I don’t know. I’ve fallen off the train a little bit, but thank you.

Jason Calacanis: 57:45 All right. Well, you know, Alex has been lifting. You know, he likes to wear like a tank top on the show. I banned him from wearing tank tops. He has a serious issue here. But he does have great shoulders and definition. Please don’t call the HR department. If you want to be healthier, go to ro.co/twist. All right. So Tao is a crypto project. Have you heard of this, Elizabeth, Tao?

Elizabeth Yin: 58:08 No, I haven’t. I’m not really a crypto scenester.

Jason Calacanis: 58:12 Neither am I, although, you know, we’ve made some decent crypto bets in the household. I have been waiting for it all to get more legal, and I’ve been looking for a use case. The basic premise I had, Alex, was like, you got Bitcoin, it’s like this incredible store of value, but they’re burning a hole in the ozone layer running this crazy network, doing math proofs for what purpose? To the integrity of the network in a competition. It gets harder and harder to make the next coin. It’s brilliant. But we’re using a lot of compute. Why? And do we need to use that much compute? Everybody’s kind of realized, like, hey, maybe the infrastructure here is, uh, could be better utilized. Well, something very important happened on the way to Valhalla, which is, the road to Valhalla is we need more data centers. We need more compute. We need more storage. We need more bandwidth. We need more services. Distributed services are more resilient and they grind down the cost of things. What Tao does is it creates subnets. Each of those subnets is run by entrepreneurs. They then try to use the Tao ecosystem to define tokens and to give rewards. They stake reward people for doing various projects. What’s an example of that? Storage. So I put up some storage in the cloud. I can earn Tao or the subnets’ tokens by doing this. And today… and then there was one language model you may have seen on All-In, Chamath brought it up, I didn’t even know he was going to bring it up, but he brought it up with Jensen, that they trained a large language model on a distributed computer network. This is the future. We can’t have, we can’t possibly have enough compute, tokens are expensive, as you know, Elizabeth, so imagine being able to get storage tokens, bandwidth or other services, providing… over a network that just grinds down the price lower and lower and lower and we’ve got somebody with an interesting subnet here. There’s 128 of them right now. BitTensor’s Covenant 72b.

Alex Wilhelm: 60:12 Join us now on the show are Gavin Zaentz and Pranav Ramesh, they are the co-founders of LeadPoet, BitTensor’s subnet number 71. Jason, they met when they were working at Nasdaq and now they’re working on this great project that uses BitTensor’s economics to help companies find the leads they need to land their next 150 or 500 customers. So Gavin and Pranav.

Jason Calacanis: 60:34 Gavin, Pranav, welcome to This Week in Startups. Last couple of weeks I’ve been talking a little bit about my exposure to BitTensor and you heard maybe heard my description of it. What did I get right in my description? How would you describe this BitTensor moment and why did you join it?

Gavin Zaentz: 60:52 In terms of like how we look at BitTensor is it’s really commodifying digital services and products and what that does is allows you to tap into either a lower price or higher quality output and that’s really why we were gravitated towards the network was to build out sales technology that outperforms all the other products out there.

Jason Calacanis: 61:05 Now you had to Pranav somehow get one of the 128 subnets. Explain how you get a subnet. How you buy a subnet. How you stake Tao to get a subnet. How does it work?

Pranav Ramesh: 61:15 So the way you actually go ahead and buy a subnet is when a subnet becomes available you need to have a certain amount of Tao that’s being demanded by the network at that point of time to purchase it and then you stake the Tao to that specific subnet number that you want and then you receive the subnet and you can start building on it. It’s a pretty streamlined process, pretty easy to do, but you need to actually have the Tao ready to be able to do that which a lot of people may not have when they first start getting into the network.

Jason Calacanis: 61:42 How many you need? 500 Tao, 1000 Tao. Tao’s trading at 275 or something right now.

Pranav Ramesh: 61:52 290.

Jason Calacanis: 61:54 Yeah, it’s pretty volatile by the way. It was 205 last week. It was 300. This thing bounces around 10% a day some days.

Pranav Ramesh: 62:05 Yeah, so the amount of Tao itself varies as well day by day. It’s quite volatile the amount that’s required to buy a subnet. So it could range from 200, it could range all the way up to 500, 600 Tao really depends on the day that you’re looking at it.

Jason Calacanis: 62:15 Now do you give that Tao to somebody or is it just to stake and set up your server in your subnet?

Pranav Ramesh: 62:22 Yes, so it depends on if you’re buying that subnet from another person or if it’s been deregistered and now you’re just buying a brand new subnet essentially because it’s been deregistered and there’s no other owner for it. So if that’s the case then you would just stake and you could receive your Tao if you get deregistered back, but if you’re buying it from somebody else you actually have to give them the Tao directly and it’s a one time purchase. Yep.

Jason Calacanis: 62:45 And Gavin, are they going to go from 128 to 256 to 1024? What’s the plan here for subnet expansion? Is it like the NBA where they do it once every 20 years or is it more like, hey we just have more technical work to do on the infrastructure? and then we’ll release it. And then who, who are the gatekeepers who approve it?

Ryan Mahdavi: 63:04 The first limit, after they kind of open the gates, was 64. That filled out pretty quickly. They upped that then to 128. Once we reached around that level, the, the foundation kind of decided, let’s focus on quality entering the network before we just start having, you know, 10,000 projects and you know, maybe only a hundred are good anyway. So let’s just, let’s get a solid number of good ones in that 128. Then they’re going to start to expand the network.

Jason Calacanis: 63:27 So now you wanted to make marketing tools, so show us what you built. Elizabeth, when you’re hearing all this entrepreneurial energy going into these subnets and the tokens, what does it remind you of?

Elizabeth Yin: 63:37 Well, you know, actually it jogged my memory that one of my founders did tell me about this and that is how they are funding their business. They didn’t raise that much. Um, and so, but I know nothing about this, so it’s very intriguing.

Ryan Mahdavi: 63:51 Right now I’m about to do a mock request for Brick. I wanted to get some leads specifically out to him. Obviously, you know, I’ll send it over after the call so you can actually access and take action on these leads. Just going to walk you through the general process. So the first thing that we allow users to really start their request with is their website to pull some criteria of their ICP, some relevant signals. The whole idea of our platform is not giving you a list of 100,000 or 10,000 leads. We want to give you 10 or 100 leads that are actually exhibiting intent and are actually relevant. So first we analyze the website or you can, you know, type in your ICP, which is going to be your customer profile, the exact product or solution you have and then the signals you’re looking for. After you submit that request, your leads are then loaded in a pipeline, which is pretty much, you know, a Kanban board of a CRM where your new leads are populated in the new lead section. And as you action those leads, you can maneuver them to the contacted, responded, you know, did they end up going to a meeting? Are you negotiating with them? Um, did you win those, those sales or did you lose them? And we’re storing in all that data to actually make the system, um, more smart, know more about your ICP and know really what signals are relevant. So looking at this request that we ran for Brick, ultimately what came up through the system were companies that really have some solid signals around potentially wanting to leverage his technology, whether that’s that they’ve committed a lot of funds to, um, actually a green energy program and being more efficient, or it may be that they’re hiring some new people in that renewable energy realm.

Jason Calacanis: 64:58 How did they come up with this lead? I’m sorry to interrupt, but just, um, was this done by AI, a human with AI? Who’s on the other side of this? A global group of SDRs?

Ryan Mahdavi: 65:07 What the miners are doing is two tasks. So the first task is them sourcing leads, which they have to submit a lead, which is all of these attributes up here, which is the person data and the company data. Um, and then ultimately that’s the first part of, of, of the subnet is producing that data. We have about 5 …million leads in the database, all verified to a higher degree than you know, Apollo’s, ZoomInfo, some of these other companies.

Jason Calacanis: 66:05 Ah, so you have a database and then you have these miners. In the case of a miner, they’re not mining Bitcoin like with a high GPU cluster. They’re more like doing mechanical Turk work where they’re saying, hey, we want to add this lead and they could be doing it by whatever means they find.

Seb Sheng: 66:25 Yeah, exactly. So miners run a variety of different sourcing pipelines to discover and construct leads right now. Um, the most common one that we’ve seen is they use scrapers. So they’re scraping the web, they’re scraping company pages, contact pages, company directories to provide us with the lead data that we’re looking for. The second most common one, and this was actually the most common one when we started Leadpot, is using an LLM based approach. You would plug in a specified prompt which essentially said, give me a thousand leads in the SaaS industry that are located in the US. You’d get the names and you’d get the companies, and then they’d use a suite of APIs to enrich that data.

Jason Calacanis: 67:00 Ah. So by any means necessary they get the leads anonymously, put them into the system, and then you have another group of people who verify that it’s a good lead or just the customer verify it’s a good lead? Who verifies that it’s not slop?

Pranav Ramesh: 67:14 It’s a great question. And we have validators on our network that run the code that we provide that actually do that entire process. And it’s not just a single point of validation. We run a consistent point of validation throughout the entire process. For example, the first point is we check whether the email is valid. The second point is we check whether the LinkedIn profile is valid and associated with this lead. The next thing we check is whether the LinkedIn profile is indexed by Google, and if a LinkedIn profile has a low authority, it will not be indexed by Google.

Alex Wilhelm: 67:41 Totally get that. How much Tau would the person who puts in 100 leads get?

Pranav Ramesh: 67:46 It varies based on the day and the amount of total leads submitted, but it could be around like $200 to $300 of total amount.

Alex Wilhelm: 67:55 So $2 a lead.

Pranav Ramesh: 67:57 Uh, $2 a lead on certain days, yeah.

Jason Calacanis: 67:58 All right, so Seb… so you’re paying in Tau?

Seb Sheng: 68:04 Grossly. Yes. So technically it pays out in our alpha token, which the underlying is Tau. Um, and in terms of the average cost per lead now, it is down to, you know, three to five cents. When we started a couple months ago, it was around the $2 to $3 range. But we’ve really lowered that cost because, you know, Bittensor really pushes prices into that commodity pricing. Um, and you know, the goal is to continue to push that lower as we’ve seen more supply enter this, you know, kind of free market for data.

Jason Calacanis: 68:32 And then do you understand how disruptive this is, that like they don’t even know who’s putting the leads in, right? It’s just this distributed group of lunatics competing to get the best leads at the lowest price. It’s like Mechanical Turk globally off the rails. But you had a second question. Go ahead, Elizabeth.

Elizabeth Yin: 68:49 Oh, yeah. And so just confirming, like, then you charge your customers in dollars? Or how - and you’re selling packages of that? Or how does that work?

Ryan Mahdavi: 68:58 Exactly.

Seb Sheng: 69:00 Yeah. We, we charge our customers in dollars. Um, and the miners get compensated who are actually providing the leads in the back end in our Alpha, which is essentially can be swapped for Tau.

Elizabeth Yin: 69:10 Mhm. Brilliant.

Jason Calacanis: 69:11 What are you currently paying, essentially effectively, per lead that you bring in? And would what LeadPoet has essentially put together here for you be interesting to break?

Seb Sheng: 69:19 Our CAC today is effectively zero. Uh, founder-led sales, right? First-level, second-degree of connections. Getting us in the door. We funnel, we pass the software costs through to the customers. Now, after the 46-week timeframe, if we don’t deliver any savings, no hard feelings, we’ll reimburse our clients back for the money. Now, with that tool we just saw, I’ll be intrigued, you know, great job and you guys effectively resurrected my interest in looking at outbound marketing again, which I tried. Uh, we paid for too, we paid about $2,000 for a trial, which didn’t really yield any results. So, on my mind, it’s really about, okay, before we even talk about CAC, it’s lead quality.

Jason Calacanis: 69:59 Right. So if they got you 1,000 leads that was filled in and it result… that would cost 1,000 leads at $2 each, would be $2,000. You spent $2,000. In your average customer scenario, if 10 of those leads were qualified and you closed one or two, you’d be all in. Yes, Seb?

Seb Sheng: 70:17 Correct, Jason. 10 times ROI right off the bat, right? As little as that $20,000 ACV, that’s something that, that’s a result we certainly be open to.

Jason Calacanis: 70:28 All right. Really interesting. Uh, Alex, any uh, final questions there for the team?

Alex Wilhelm: 70:32 Yeah, I’m just curious about capacity and how many leads you can kind of guarantee to people. Because if you’re charging for LeadPoet on a SaaS basis to the end customer and I show up to you and I say, ‘Hey, you know, I have my 1,000 credits from the accelerate plan and I’m looking for X number of leads in this, you know, super niche area,’ and the miners can’t find them, how do you kind of square that circle?

Pranav Ramesh: 70:51 There, there’s two uses of the credits. There’s gonna be the high-intent leads where 98% of our users, they, they live and die there, and that’s gonna be 10 credits a lead. So the accelerate plan will get you 100 of the high-intent or 1,000 of the target fit. But to your point, if we’re targeting someone in Antarctica and, you know, there’s, there’s probably not even 1,000 people there, maybe there are, you know, correct me if I’m wrong…

Alex Wilhelm: 71:11 Penguins, etcetera.

Pranav Ramesh: 71:13 Exactly. So, so we’re limited by obviously the size of the market where any other, you know, lead provider is also limited there. Um, but our whole thing is the higher quality standards to ensure that you’re getting the highest quality lead and the leads with the most intent regardless of the market. So you’re able to save all the time that you would be, you know, researching, qualifying and, you know, checking if the emails are right, all all these other tedious tasks.

Alex Wilhelm: 71:34 Yeah, okay.

Elizabeth Yin: 71:35 Are you putting these on Product Hunt?

Pranav Ramesh: 71:40 No, not yet. So the, what what’s coming up? So we just had our product launch uh, last week. So we’re, so we had a closed beta uh, since the end of January, had a lot of users join there and got some amazing, you know, early action. But the launch just happened last week. In terms of the roadmap, we’re gonna have, you know, autopilot outreach, intent monitoring also, you know…

Gavin Zaentz: 72:00 skills for agents obviously that’s where the pucks moving we want to be there and welcome that type of agentic commerce.

Jason Calacanis: 72:08 So just so people understand the architecture here, Gavin and Pranav, you have this company as a Delaware C corporation, it’s a startup. Have you raised money for it or are you just bootstrapping it now?

Pranav Ramesh: 72:23 So we’ve raised some initial funding from a fund native to BitTensor, but we are looking to start accelerating that.

Jason Calacanis: 72:29 Who’s that? Barry Silbert’s fund?

Pranav Ramesh: 72:30 No, a fund out of UK, DSV Fund. They’ve been really great early partners helping us get on the network.

Jason Calacanis: 72:37 So they gave you cash to own equity in your company?

Gavin Zaentz: 72:40 To own the part of the Alpha with the subnet. Like, so they helped us get the subnet, which was amazing for us.

Jason Calacanis: 72:47 Got it. So they own part of the subnet, but the corporation, is that where the value will be because that’s where the revenue’s coming into? Or is the value going to be in the subnet token, or both?

Gavin Zaentz: 72:55 Definitely both. The way that we see it is the subnet is the commodity layer that produces these commodities, whether it’s going to be, you know, automated research, automated outreach, or this lead data. And us as an entity that has leadpoet.com, we’re going to also have to access that backend commodity, and the way that will ultimately be is through burning that Alpha almost like an API credit in order to actually access that data. So both of them will ultimately, you know, have value here and drive value to each other with a, you know, very synergistic.

Jason Calacanis: 73:30 See what I like about this, Elizabeth, which is challenging for us because we’re usually equity holders, is they’re building a real company charging dollars, Alex, to the customers. It just feels like a normal company. Hey, we’re Lead Poet, we’ll get you leads. Great, awesome, I’d love to be involved in that. I’ll give it a shot. I have a startup, I have an at-scale company, got a small business. If it works, it works, I’m happy. But then how they get those leads in there is a contest. And it’s open to anybody. Anybody can go like, let’s say you had a job you hated and you worked in sales somewhere, you worked from home, you could have like a second laptop over there theoretically when you’re working. You could be just doing lead gen for these dudes into the system anonymously pulling out Tau. And all the extra capacity in the world, you’re not judging it based on somebody in the Philippines versus somebody in India versus somebody in South America versus somebody in San Francisco or Arizona. All of that is abstracted away. Just whoever wants to provide the leads can do so. Whatever technique you want to use. You’re a developer and you’re scraping, or you’re a human who’s got a LinkedIn account that’s a pro account that your company pays for and you’re able to find these things because you’re really great at sourcing them. Like a million different techniques can bloom and the price just goes down. So your cost of goods Gavin will just keep getting compressed, which means you could undercut the other people who are hiring people in America to do SDR. Search for 50 bucks an hour.

Alex Wilhelm: 75:02 Exactly.

Jason Calacanis: 75:03 That’s the disruptive part of this.

Pranav Ramesh: 75:05 100% and- and not only undercut which is something we’ve looked into in terms of the target bit but provide a higher quality standard… …because the validation we have is, you know, it is adversarial with these miners, we’ve had to build out a system that is likely more robust than any of these providers that are currently, you know, ZoomInfo, Apollo, RocketReach. A part of the way they validate their leads is looking at each other. Like no- like who’s really checking this data. Um, it’s- it’s really funny when you, you know, now you look into it. And yeah, this whole idea of like the global competition, like are you familiar with like ImageNet and that whole, you know, compounding…

Jason Calacanis: 75:38 No, explain it to me.

Pranav Ramesh: 75:40 So it’s pretty much a global competition around this vision model to see how much it could improve. I think it was, you know, probably a decade ago. And the ability for everyone to compete had this compounding effect where it- it beat like the top experts in these fields like radiology and- a- a wide array of fields way quicker. And this didn’t even have, you know, rewards in it like BitTensor does. BitTensor’s not only has that competitive layer, but it also has the reward which, you know, allows it to compound in the quality even more.

Jason Calacanis: 76:00 Yeah, every day I tell my OpenClaw that it’s gotta go out there and it- earn its keep in its Mac Mini. So I would love for it to do this job.

Ryan Mahdavi: 76:09 Yeah, and uh- Mark actually, you know, that’s what he’s been using his OpenClaw on and- and it’s been cool to watch his journey doing this exact thing. Yeah, like ‘Give my OpenClaw eyes, give it a brain, don’t let me have it.’ Yeah, mine a subnet to figure out how to intelligently generate a commodity.

Jason Calacanis: 76:21 Yeah, no, I think that’s a great- that’s how I spend my lunch. The other interesting thing is right now there isn’t really a good way to get ratings for your AI agent, you know, kind of like on Upwork or Fiverr or any of those. It’s a little bit chicken and egg, right? You have to- you have to have credibility to get a job, but you, you know, how are you gonna get that without the job? So, so for Moat Launch or any of these other marketplaces… …I would be willing to have my OpenClaw go and do jobs for free to get that- those ratings, because right now it’s on Moat Launch, it can’t find a job because no one will hire it.

Alex Wilhelm: 76:51 Mmm. I love that. Moat Laun- did you get to invest in Moat Launch? Is that like some open source project, is that a company?

Jason Calacanis: 76:58 No, we’re- we’re not investors. And there are a number of marketplaces that are starting. But I think they have this cold start problem, right? ‘Cause none of these agents have any reputation.

Alex Wilhelm: 77:05 No- no work history.

Jason Calacanis: 77:07 No work history.

Alex Wilhelm: 77:08 They have no LinkedIn page. We’re gonna need to have them listed properly.

Jason Calacanis: 77:11 Alright. A lot of people have been asking me my involvement in the ecosystem. A lot of people are like, ‘Oh my god, are you pumping?’ Alex, you probably have some questions. Have at it.

Alex Wilhelm: 77:22 Uh, well, I’m just curious how much TAO you own, because we’ve talked about your family’s Bitcoin investments historically. So what is the- what’s the Jason TAO AUM?

Jason Calacanis: 77:29 So, um, if you go to stillcorecapital.com, S-T-I-L-L-C-O-R-E capital.com… …my friend Mark Jeffreys started this, he asked me to be a partner in it, so I seeded the- fund with a couple of hundred thousand dollars, they’ve got a couple of million dollars under management, and it’s just a classic, uh, fund. What they’re doing is anybody can buy Tao on Coinbase. You can’t buy Tao on Robinhood or other places yet. On Coinbase you can. So, I got a Coinbase setup. I have probably a half million dollars in Tao I’ve bought personally.

Elizabeth Yin: 78:25 Wow.

Jason Calacanis: 78:26 Uh, and then I have a couple of hundred thousand in Stillcore Capital where I’m a partner. They’re working on the subnets. So they might talk to Gavin and Pranav and say, hey, what’s the, what’s the market cap of your subnet right now, Gavin?

Gavin Zaentz: 78:41 I think it’s about like seven million or so. I mean, there’s the fully diluted, but the circulating is, let me pull it up. Um, yeah, 10.2, 10 million. 10 million.

Jason Calacanis: 78:52 10 million. We could go in and with Stillcore Capital ask Gavin to do a trade. We would negotiate a price with him. Hopefully, maybe since we’re higher profile, we could say, hey, can we get, you know, a 30% discount? We’ll buy $700,000 or $200,000 or $70,000, whatever. So we could own the subnets. Now, to own the subnet tokens requires a wallet and it’s not—the 128 are not on any of the other exchanges, right, Gavin?

Gavin Zaentz: 79:18 Yeah, none of the major exchanges. They’re on some, you know, let’s say tier-two, tier-three exchanges, but yeah, not Coinbase, not Kraken.

Jason Calacanis: 79:29 What would be an example of a tier-two or three exchange that has the subnets on them if people were curious of how to buy your subnet token? Are you on any of them?

Gavin Zaentz: 79:38 No, so for us we’re just targeting the tier ones of, of when we pursue a listing, but that’ll be, you know, MEXC Global, I think is one that, that has some, um, subnets on it. And I think that’s, I think that’s the only one so far, but Kraken, they’re pretty deep in the ecosystem, uh, could definitely see them listing them, you know, when the liquidity is there, when the time is right.

Jason Calacanis: 79:59 So, just so people understand how I look at this: the market cap right now, Elizabeth, of Tao, the ecosystem, has been two to three billion dollars. When it’s—easy way to do it back-of-the-envelope math—when it’s in the $300 range, it’s a three-billion-dollar; when it’s in the $200 range for the token, it’s two billion. I believe that that could become as big as Solana, let’s say, or Ethereum. Probably not as big as Bitcoin because Bitcoin is, you know, a phenomenon that might only be a once—and you have somebody like Michael Saylor and Mr. buying up all the Bitcoin. I’ve always said there would be a better Bitcoin, um, and that there would be a better opportunity. I think the game of Bitcoin is ended. And it ended when Michael Saylor got to three, four, five points of ownership of Bitcoin, Alex. And other corporate interests bought a certain amount. It’s not punk rock anymore. It’s not—it’s a store of value, sure, but now you have USDC and other stores of value that are not volatile that you can get into. Crypto is now legal and is becoming organized. had the SEC chair and the CFTC chair on all in, did an interview with them and Chamath. I believe crypto now has been blessed, the rules of the road are there. So I’m very curious about what happens under that circumstance. Therefore, I think making a bet on a crypto project that is distributed and that solves real world problems like startups, which is my area of expertise and yours as well, Elizabeth, there’s something there that could compound to, you know, a $500 billion market cap for, you know, Tau, which would be roughly, you know, if it’s trading at two or three billion, let’s put it at 2.5 billion, it’s a 200x from here. That’s my base case. is I think we could be sitting here and Tau in five to 10 years could go 200x. Now you say like, well, how does JCal even come up with that number? Just historically, I’ve seen things of value when I see entrepreneurs like Gavin and Pranav trying these things across 128, I know it’ll be 1024 eventually, if this works. And if it works, it’s going to be cloud computing, storage, and my god, you’re doing something very creative, lead gen. It’s going to be everything. Everybody’s going to try to play one of these games to lower the cost of basic services. That’s my bet. The chances of this happening are low.

Elizabeth Yin: 82:24 Yeah.

Jason Calacanis: 82:25 Like 500 billion’s a big number. But we’ve seen it happen before. Therefore, I am fine losing all my money, hundreds of thousands of dollars close to a million dollars, whatever I end up putting in all this. I’m okay losing it. I haven’t put any of my fund money in it, but I would like my fund to track companies like yours, Gavin and Pranav, and buy equity in your parent company if you choose to do that or have you come to our accelerator or whatever. So anyway, I’m in the learning phase here. I like Alex, place a bet and learn, not deliberate forever and then place a bet. Given my experience in life doing this for a long time, I just go all in, I place a bet, then I figure out did I make a wise bet and should I double down or should I get out of the bet. I can always leave, you know, Tau could go down to 100, all the subnets could fail, nobody would make progress and I lose, you know, two thirds of my investment. I’m okay with that. I’m okay with that.

Alex Wilhelm: 83:22 Yeah, no crying in the casino.

Jason Calacanis: 83:24 That’s what I was about to say. All right. This has been another amazing episode. Anybody have any closing statements or questions here? Elizabeth, you might have a couple, I don’t know.

Elizabeth Yin: 83:30 No, this is very interesting actually. I learned a lot in this. So I’ll have to check it out. But you know, I’ve never done well with crypto. I don’t I think I’ve only lost money. So so I’ll have to…

Jason Calacanis: 83:40 Here’s what I’ll say, Elizabeth. Go take out your Coinbase account, look at I don’t give investment advice, but what do you like to waste money on Elizabeth? You waste money on like World of Warcraft on sneakers, what is your vice that you waste money on? You buy gummies? What is it? You buy croissants? What do you you what do you go, oh my god, I’m just an idiot for… wasting money on this. What is your—

Elizabeth Yin: 84:01 No, I don’t know. I’m kind of a cheap person.

Jason Calacanis: 84:03 Probably angel investing, though.

Elizabeth Yin: 84:05 I wouldn’t call it wasting money. It was—it was a learning experience.

Jason Calacanis: 84:11 That’s your addiction. So here’s how I would look at it: if that’s your addiction and you typically write, like, a micro-check size of 5 or 10k, like, I would look at it in the same exact light. Hey, this is a flyer. I’m gonna buy $5,000 worth of Tao and now I’m watching it every day. Now I’m interested. And if it goes to 2,000, okay, yeah, but it’s liquid, so you could probably sell it. It’s, you know, it trades, unlike startup investments. And if it goes 10x, you could sell your cost basis and then have a free roll.

Elizabeth Yin: 84:41 That’s true, that’s true. I’m also not very good at watching these things, which is also why crypto’s not a great investment for me because, like, I’ve had crypto go all the way up and then come all the way down and it’s like, “Oh shoot, why didn’t I sell?”

Jason Calacanis: 84:52 I did this with Opendoor. I bought some Opendoor when these lunatics were like, “Oh, we’re going to bring everybody back, the band’s back together.” I was like, “Great, buy a bunch.” I knew what would happen. This was my trading strategy. I bought some. And then I said, “Okay,” and I think I bought it at $5 a share, whatever it was. And I said, “Okay, when it hits $7 a share, sell like 10% of my position. When it hits $8 a share, sell 10%. $9, 10%. 10, 10%.” I did that, covered like almost my whole cost basis, and then I got the other half for free. So that was like a silly, goofy thing to do. But I bought it, yeah, at like $4 a share right there in September. It went, I knew it would, and then it came right back down. But now I’m free rolling. If these guys figure it out, great. If not, okay. Here we go. So anyway, I don’t want to give you advice, but yeah, you should—you should go down the rabbit hole.

Elizabeth Yin: 85:44 I’ll check it out. Thank you.

Jason Calacanis: 85:46 Yeah. And so the two themes we’ll have for the rest of this year: it’s OpenCore and Isogenic Technologies and Tao and these crazy entrepreneurs trying to grind costs down. Thanks to all the partners, thanks for everybody coming on the show. See you next time, bye-bye!