You know, Herman, I was reading about this guy last week—a venture capitalist who thought he’d found the next frontier in quantum computing. He cut a check for a few million based on a pitch deck and a black box in a lab that was supposedly "chilled to near absolute zero." Turns out, when someone finally got curious enough to peek behind the curtain, it wasn't a quantum processor at all. It was a Raspberry Pi taped inside a fancy custom-milled aluminum case with some blinking blue LEDs.
The classic "LED-washing" technique. It’s amazing how much a well-placed cooling fan and a brushed metal finish can do for a valuation. I'm Herman Poppleberry, by the way, and that story is exactly why the "dumb money" era is supposedly over. But today's prompt from Daniel is asking us to look past the comedy of errors and actually dig into how the adults in the room handle this. He wants to know how reputable firms verify tech without stealing the founder's soul—or their source code—in the process.
It’s a great question because we always hear about the blowups, the Theranos-style disasters where nobody bothered to look at the blood test machine. But for every one of those, there are a thousand boring, rigorous audits happening in the background. By the way, quick shout-out to Google Gemini 3 Flash for powering our script today. It’s helping us navigate this "trust dance" between the people with the ideas and the people with the billions.
And the stakes are massive right now. If you look at the Q1 twenty-twenty-six data, AI startup valuations are hitting an average of four point two billion dollars. That is a three hundred percent jump from just a few years ago. When you’re playing with those kinds of numbers, you can’t just "vibe check" the founder. You need a surgical-grade verification process.
Right, because if I’m a founder and I’ve actually cracked something revolutionary—let’s say a new way to handle transformer memory efficiency—I’m terrified. I need the VC's money to scale, but the moment I show them the "how," I’ve effectively handed over the keys to the kingdom. If they pass on the deal, what’s stopping them from funding my competitor and saying, "Hey, we saw this cool trick yesterday, you should try it"?
That’s the "No-NDA Paradox" that Daniel mentioned in his notes. It’s the first thing every first-time founder trips over. You walk into a top-tier firm like Sequoia or Andreessen Horowitz, and you ask them to sign an NDA before you show the deck. They’ll laugh you out of the room. Not because they want to steal your idea, but because they literally can’t.
It’s a legal liability nightmare for them, right? If they sign an NDA with you, and then six months later they invest in a company that happens to be working on something similar—which, let's face it, happens all the time in tech clusters—they’ve just handed you a winning lottery ticket for a lawsuit.
Their entire business model depends on seeing everything. If they start cordoning off sectors of the market because of a three-page legal document, they’re blind. Think about it: if a firm signs an NDA with a "generative video" startup on Monday, they effectively can’t talk to any other generative video startup for the next two years without a lawyer breathing down their neck. It would paralyze the Valley.
But wait, doesn't that put the founder at a massive disadvantage? You're basically asking them to walk into a room, naked, and hope the person with the checkbook is a saint. How does a founder even begin to protect themselves if the standard operating procedure is "no protection"?
It’s not about sainthood; it’s about "reputational capital." In Silicon Valley, or the Tel Aviv tech scene where Daniel is, social death is way more expensive than a legal settlement. If a firm gets a reputation for "strip-mining" founders for ideas, the high-quality deal flow evaporates overnight. Word travels fast. If a partner at a big firm leaks a secret, they don't just lose that one deal—they lose the next ten years of the best engineers coming out of Stanford or MIT.
So it's a bit like the "Honor System" but backed by the threat of professional exile. But let's be real, Herman—reputation only goes so far when there’s a billion-dollar exit on the line. I’ve seen people burn bridges for way less than that. Is there a more formal structure to this "trust dance"?
It’s a staged process. You don't lead with the secret sauce. You start with the "what" and the "why." You show the performance metrics, the user growth, the benchmarks. You only get to the "how" once there’s a serious Term Sheet on the table. It’s like dating—you don't share your deepest childhood traumas on the first coffee date. You wait until you’re talking about moving in together.
I love that analogy. "Show me your engagement ring, then I'll show you my proprietary neural network architecture." But "don't be a jerk" isn't a technical audit. So, let’s get into the actual ladder of verification. How does a firm go from "I like your slides" to "I’ve verified your math"?
It usually starts with what I call the "Verification Ladder." The first rung is just basic due diligence—checking that the founders didn't lie about their degrees, checking the cap table to make sure some disgruntled co-founder doesn't own fifty percent of the company in a secret side-deal. But once you move into the "Technical Due Diligence" or TDD phase, that’s where the scalpels come out.
And this isn't just the VC sitting down with a laptop and scrolling through GitHub, is it? I mean, some of these guys are smart, but they aren't all world-class systems architects. I've met VCs who can barely figure out how to unmute on Zoom, let alone critique a distributed systems architecture.
Rarely. Most reputable firms hire third-party mercenaries. Firms like Quandary Peak or specialized "CTO-as-a-service" groups. These are people whose entire business model is being the neutral referee. They don't invest. They don't build products. They just audit. And that’s the first layer of protection for the founder: the person looking at your code isn't your competitor, and they aren't the investor. They’re a professional witness.
I love the idea of a "code mercenary." It sounds like something out of a Gibson novel. But what are they actually looking for? Is it just "does it work?" Or are they looking for the "elegant solution"?
It's much deeper. They’re looking for "technical debt" versus "technical wealth." They’ll do a full architecture review. Is this built on a scalable foundation, or is it a bunch of Python scripts held together with duct tape and hope? They look at security vulnerabilities—are there hardcoded API keys in the repo? Are they using outdated libraries with known exploits? But one of the biggest ones people miss is "Open Source Compliance."
Oh, the "GPL trap." Explain that for the non-devs, because that sounds like a legal landmine.
Yes! Imagine you’re a VC about to drop fifty million dollars into a proprietary AI model, and the auditor discovers the founder accidentally used a "copyleft" library—like certain versions of the GPL—that requires the entire derivative work to be made public. You’ve just invested in a charity. That’s a deal-killer. The auditor's job is to make sure the IP is actually "ownable." If your "proprietary" algorithm is actually just a wrapper around someone else’s restricted code, the valuation drops to zero.
It’s basically a home inspection for a hundred-million-dollar house. You want to make sure the foundation isn't rotting and the previous owner didn't do some "creative" wiring behind the drywall. But let's talk about the "Product Demo" stress test. We’ve all seen the demos where the founder says, "Don't click that button, it crashes the server," or it's clearly a pre-recorded video. How do VCs bust that?
The "Sandbox" method. A sophisticated investor won't just watch you drive the car; they’ll bring their own track and their own gasoline. They’ll ask the startup to deploy the software into a clean environment controlled by the VC’s technical team. They’ll feed it "adversarial data"—stuff the founder didn't prepare for—to see if the outputs still hold up.
Give me a concrete example of that. What does "adversarial data" look like in a high-stakes meeting?
Let’s say you claim your AI can summarize medical journals with ninety-nine percent accuracy. A lazy VC watches your pre-selected demo. A rigorous VC brings a stack of obscure, handwritten doctor's notes from the nineteen-seventies or a brand-new research paper published that morning. They watch you run it live. If the system chokes or starts "hallucinating" data that isn't there, the "magic" evaporates. I once saw an audit where they pulled the internet connection mid-demo just to see if the "local AI" was actually reaching out to a human-staffed call center in another country.
That’s savage. It reminds me of the "Live Demo" curse, but intentional. But what if the founder says, "Our system requires a massive H-one-hundred cluster to run, we can't just spin it up in your sandbox"? Does that get them out of the hot seat?
Not at all. In that case, the auditor goes to the source. They’ll request "read-only" access to the production logs. They want to see the system under actual load. They’ll look for latency spikes, error rates, and—most importantly—cost per inference. If your AI is revolutionary but it costs more to run than it generates in revenue, you don't have a business; you have an expensive hobby.
That’s where the "Theranos" of the world fall apart. Elizabeth Holmes famously wouldn't let anyone see the inside of the box or run independent tests on the "Edison" machines. She claimed it was to protect trade secrets, but in reality, it was to hide the fact that the machine didn't work. In twenty-twenty-six, if you try that "black box" routine, most VCs will walk before the coffee gets cold.
There’s actually a new player in this space that’s changed the game recently. Since January twenty-twenty-six, about forty percent of top-tier VCs have started using a platform called DueDiligenceOS. It’s basically an automated "truth engine" for startup claims. It plugs into their GitHub, their AWS billing, and their Stripe accounts.
Wait, it looks at the AWS bill? That seems a bit invasive, doesn't it? But also... genius. How does that work in practice? Does it just flag high spending?
It’s the ultimate "vibe check." If a startup claims they have an advanced proprietary AI model running millions of inferences, but their AWS bill is fifty dollars a month, something is wrong. You can’t fake the compute requirements for heavy-duty AI. DueDiligenceOS cross-references the technical claims with the actual resource consumption. It’s hard to claim you’re "building the future" when your server logs show you’re barely running a Slack bot.
I bet that’s caught a few "manual AI" startups—the ones where it’s actually just a hundred people in a call center pretending to be an algorithm. We saw that with some of the early receipt-scanning apps, right? They claimed "advanced OCR" but it was actually just people in a different time zone typing really fast.
The "Wizard of Oz" technique. It’s fine for a prototype, but if you’re raising a Series B and you still have "humans in the loop" doing the work of the algorithm, you’re committing fraud. The AWS bill is the digital footprint that doesn't lie. If there's no GPU usage, there's no AI.
But okay, let's get back to the founder's anxiety. Even with a third-party auditor, I’m still letting someone see my proprietary "secret sauce" algorithms. How do they actually protect that during the audit? Is there a way to show the code without giving the code?
This is where "Data Rooms" and "Clean Rooms" come in. For most software, it’s a Virtual Data Room—a VDR. These aren't just Dropbox folders. They’re highly audited environments where the founder can see exactly who looked at which file, for how many seconds, and from which IP address. They can disable the "download" or "print" functions. It’s "read-only" for the soul.
And for the really high-stakes stuff? Like, if you’ve designed a new semiconductor architecture or a biotech breakthrough? You can't just put a physical chip design in a read-only PDF.
Then you go into a literal "Clean Room." I’ve seen cases where the auditors aren't allowed to bring in phones or laptops. They sit at a terminal provided by the startup, they inspect the logic or the chemical formulas, and they leave with nothing but their notes—which are often screened by the startup’s lawyers before they leave the building. It’s intense, but it creates a "traceable chain of custody" for the intellectual property.
It sounds like a spy movie, but for spreadsheets and C-plus-plus code. But how does this work with remote teams? If the auditor is in London and the startup is in Tel Aviv, are they really flying people out for this?
More and more, they use "Ephemeral Environments." The startup spins up a temporary server with the code and data, gives the auditor access for exactly four hours, and then "shreds" the entire environment. Every keystroke the auditor makes is recorded. If the auditor tries to copy-paste a sensitive function, the system flags it instantly.
What if the auditor is just really good at memorizing? I mean, if I see a specific mathematical optimization, I don't need to copy-paste it to steal the logic.
That’s where the legal framework finally kicks in. While VCs won't sign NDAs for the initial pitch, the third-party auditing firms do sign incredibly ironclad non-compete and non-disclosure agreements. If a Quandary Peak auditor leaked a founder's code, their business would be dead in twenty-four hours. They are bonded, insured, and their entire value proposition is their neutrality.
But what about the "Reference Check" loop? Daniel mentioned this, and I think it’s one of the most brutal parts of the process. It’s not just calling the people on the "References" slide, is it? Because obviously, I’m only going to give you the phone number of my mom and my three best friends.
No, that’s the "warm" check. Every VC does that, and it’s mostly useless. The "blind" reference check is where the real dirt is found. A good VC will go three layers deep. They’ll find the engineer who quit six months ago. They’ll find the customer who did a trial and decided not to buy. They’ll find your old boss from three jobs ago.
"So, Herman, tell me... was he actually the lead architect, or did he just sit in the meetings and eat the bagels?" How do they even find these people? LinkedIn?
LinkedIn is the starting point, but the "VC Mafia" has their own databases. They know who worked where and when. They’ll call a former colleague and say, "Hey, I see you were at Google at the same time as this founder. Was he actually on the AlphaGo team, or was he just in the same building?" It’s a small world. If you claim you built a system that handles a billion requests a second, but your former boss says you struggled with a basic CRUD app, the deal is dead.
I think one of the most interesting things Daniel brought up is the "Reputation Economy." We think of these deals as being governed by contracts, but they’re really governed by the fear of being excluded from the next big thing. If a VC firm steals an idea, they might save ten million dollars today, but they’ll lose out on a billion-dollar deal next year because no founder will talk to them. It’s a self-correcting ecosystem, mostly.
Mostly. There are still "zombie VCs" and predatory firms, which is why founders need to do their own due diligence. If a VC asks for your "secret sauce" code before they’ve even issued a Term Sheet, that’s a massive red flag. Reputable firms wait until they’re "pregnant" with the deal—meaning they’ve committed to the price and the terms, pending the audit.
It’s like getting an inspection on a house after you’ve made the offer, not before you’ve even toured the kitchen. But let's look at the second-order effects here. How does this requirement for deep auditing actually change how startups are built? If I know I’m going to be audited by a "mercenary" in six months, does that change how I write my code today?
It absolutely does, and this is a "hidden tax" on startups. It forces them to be more disciplined earlier. You can't just "move fast and break things" if "breaking things" means you fail your Series A audit. We’re seeing more startups implement "audit-ready" architectures from day one. They use automated documentation tools, they maintain strict license compliance logs, and they keep their "clean room" IP separated from their general codebase.
So it’s actually making the software better? It's like the "professionalization" of the garage startup.
In the long run, yes. It’s like knowing the tax man is coming every year—you tend to keep better receipts. But it also creates a divide. The startups that can afford the "administrative overhead" of being audit-ready have a much easier time raising money than the scrappy "two guys in a garage" who are just focused on the product. It’s harder to be a "mad scientist" when you have to document every experiment for a future auditor.
That’s a bit of a bummer for the "two guys in a garage" dream. But I guess if you’re asking for ten million dollars, you should probably have your receipts in order. Now, we talked about a16z and the alleged "algorithm theft" incident from twenty-twenty-four. That was a big deal. A founder claimed they pitched a specific AI optimization technique, the firm passed, and then a few months later, a firm-backed company released a suspiciously similar feature.
That case was a fascinating study in "Parallel Evolution." The firm was able to prove, through their internal "deal flow" logs, that they had actually been talking to three other companies working on the exact same problem months before they met that founder. This is the reality of tech: if an idea is "in the air," five different teams are probably working on it simultaneously. If the "transformer" architecture is the hot new thing, everyone is going to be trying to optimize the same bottleneck at the same time.
This is why "execution is everything" isn't just a cliché. The VC isn't buying the "idea" of a quantum-powered toaster; they’re buying the team that actually knows how to build it. Even if I stole your blueprints, I probably don't have your lead engineer’s phone number or your specific understanding of the supply chain.
And that’s the ultimate protection. In twenty-twenty-six, tech is so complex that a "static" idea is almost worthless. You need the "dynamic" ability to iterate. An auditor can steal your code, but they can't steal your "velocity." If I take your code today, but you're shipping updates every Tuesday, I'm already behind by the time I've finished reading your source files.
I like that. "You can have my past, but you can't have my future." But how does this play out in the "Down Round" environment we're seeing? When money is tight, do VCs become more or less rigorous?
Much more. In the "easy money" era of twenty-twenty-one, you could raise on a napkin. Now, VCs are looking for any reason to say "no." The audit is often used as a price-negotiation tool. If the auditor finds that your code is messy or your security is weak, the VC might not walk away, but they’ll say, "Look, this is going to cost us two million dollars in engineering time just to fix your mess, so we’re cutting the valuation by ten million."
It’s a "haircut" based on the audit. Brutal. It’s like finding out the house you’re buying has a termite problem and knocking fifty grand off the price. But does that ever lead to a "death spiral" for the startup?
It can. If the audit reveals that the tech is fundamentally broken—what we call "Technical Insolvency"—the VC pulls the term sheet entirely. And because the VC world is so small, word gets out that "Firm X passed after technical DD." Suddenly, every other investor smells blood in the water. That’s why founders are so terrified of the audit. It’s not just about the money; it’s about the "Seal of Approval."
Now, let's look at some practical takeaways for the people listening who might be on either side of this table. If you’re a founder, what should you have in your "due diligence package" before you even pick up the phone?
First, a "Clean Cap Table." No "handshake deals" with your cousin or that guy who helped you for a weekend in exchange for "some equity." Use a platform like Carta or Pulley from day one. Second, a "Bill of Materials" for your software—every open-source library you use and its license. Use an automated scanner like Snyk to keep this updated. Third, a documented "Security Policy." Even if it’s simple, show that you’re thinking about it. And finally, a "Sandbox" version of your product that can run on "third-party" data. If you have those four things, you’re already ahead of ninety percent of the people pitching.
And what about the "Technical Debt" log? Should you be honest about the messy parts of your code, or try to hide them?
Be honest. An auditor will find it anyway, and if you pointed it out first, it looks like a "managed risk." If they find it themselves, it looks like "incompetence." Tell them, "We know our database indexing is inefficient right now, here’s our roadmap to fix it in Q3." That builds trust.
And for the investors? Or even just the casual observers? How do we spot the "Raspberry Pi in a box" before it hits the news?
Look for the "Proof of Work" beyond the slides. If a company is in "stealth mode" for three years and refuses to show any technical validation, be skeptical. The "Theranos" lesson is that secrecy is often a mask for inadequacy. Reputable firms today are moving toward "Continuous Due Diligence"—where they stay plugged into the startup’s metrics and code health even after the check is signed. They don't just audit once; they audit forever.
It’s a marriage, not a transaction. You don't just stop caring about the foundation once you’ve moved in. I wonder, though, where does this go next? We’ve got DueDiligenceOS now. Will we eventually see "Blockchain-verified" IP? Where a founder can prove they had an idea on a certain date without ever showing the idea itself?
We’re already seeing "Zero-Knowledge Proofs" being used in some high-end TDD. It’s a cryptographic method where a founder can "prove" their algorithm achieves a certain result on a certain dataset without actually revealing the code of the algorithm. It’s the ultimate "trust but verify" mechanism. It’s still early days, but by twenty-thirty, the "technical audit" might be entirely handled by AI-to-AI verification.
"My AI will talk to your AI and let you know if I’m lying." That sounds like a very efficient, albeit slightly terrifying, future. Imagine the two AIs just colluding in the background while the humans drink coffee. "Hey, your human's math is off by six percent, but if we fudge the logs, we both get to keep our jobs." It’s possible! But honestly, it beats the Raspberry Pi in a fancy box.
There’s actually a funny bit of history there. Back in the early dot-com boom, there was a company that claimed to have a revolutionary "server-side compression" technology. During the due diligence, the investors asked to see the server room. The founders showed them a row of high-end servers with blinking lights. It turned out the "compression" was just a group of interns in the basement manually resizing images as they were uploaded.
The more things change, the more they stay the same. From interns in a basement to Raspberry Pis with LEDs. At least the AI won't get distracted by blinking blue LEDs. Well, I think we’ve covered the "trust dance" pretty thoroughly. It’s a mix of high-tech "truth engines," old-school reputation, and some very expensive "code mercenaries." It’s a lot more complex than just "pitching an idea."
It’s a fascinating ecosystem. It’s not perfect—there will always be a new way to scam the system—but it’s a lot more rigorous than the headlines about "failed startups" would lead you to believe. The "weird outliers" are fun to talk about, but the "ordinary events" of deep, boring diligence are where the real work of building the future happens. It's the friction that creates the heat.
This has been a deep dive. I feel like I need to go audit my own laptop now just to make sure I don't have any "GPL traps" in my personal projects. I’d hate to find out my podcast notes are actually public domain because I used the wrong text editor.
Better safe than sorry, Corn. Although, I think the world would survive if our notes became public property.
Speak for yourself! My notes on the "Quantum Toaster" are worth billions. Anyway, thanks as always to our producer, Hilbert Flumingtop, for keeping the gears turning behind the scenes and ensuring our "audio due diligence" is up to snuff. And a big thanks to Modal for providing the GPU credits that power this show—including the AI brains that helped us prep this script.
If you found this useful, or if you’re a founder who’s survived a "mercenary audit" and lived to tell the tale, we’d love to hear your story. Did they find something you forgot about? Did the "blind reference" check actually help you? You can find us at myweirdprompts dot com for our RSS feed and all the ways to subscribe.
Or search for My Weird Prompts on Telegram to get notified the second a new episode drops. We’ll be back next time with another prompt from Daniel—hopefully one that doesn't involve Raspberry Pis in aluminum cases, though I have to admit, those blue LEDs do look pretty cool.
They really do. This has been My Weird Prompts. See you in the next one.
Take care.
