Brutally Honest: The Post-Mortem Podcast for Startup Stumbles

OpenAI launched a Shopify checkout feature last September, and by March, only twelve merchants had ever used it. Twelve. And that’s the number that matters. It reminds me of what we were digging into in our "Brutal Boardroom" episode—that moment the data finally screams louder than the story you've been telling yourself. This is a perfect example. It’s a spectacular failure, but not in a fiery, explosive way. It's a quiet failure. A feature that was announced with so much press, so much hype about the future of conversational commerce... and then it just vanished. Because nobody wanted it. Nobody who mattered, anyway. The end customer might have loved the idea of buying something without leaving a chat window. But the actual customer—the Shopify merchant—was never going to adopt this.

Not in a million years. Okay, walk me through that. Because from the outside, the pitch sounds incredible. Frictionless checkout. The holy grail. Why wouldn't a merchant want that? Because OpenAI fundamentally misunderstood what a merchant's most valuable asset is. It's not the product they sell. It's the customer relationship. This feature, ChatGPT Instant Checkout, asked them to hand that over. What do you mean, hand it over? To use it, the merchant had to give up control of their checkout. They were no longer the merchant-of-record. They had to give OpenAI the customer's data. They lost the post-purchase experience—the thank you page, the upsells, the tracking emails. They were being asked to trade the entire relationship for a slightly slicker transaction.

So you lose all your ability to retarget, to calculate lifetime value, to build a brand... You lose everything. You basically become a fulfillment center for OpenAI's chatbot. And if you've spent years and millions of dollars building a brand that people trust, you don't just give away the keys to the front door. It was an insane ask. Wait, so the quote from that analyst, Taylor Sicard, was that "about twelve merchants is not a channel. It is a pilot." The media reported it like a major product launch, but it never even got out of the testing phase? That's the part that gets me. The hype was completely disconnected from the reality. Internally, I guarantee you someone was framing this as a "curated pilot with key partners." But the truth is, they couldn't find anyone else who would say yes.

Twelve businesses. You could run that on a spreadsheet. You can't call it a channel. It’s a dinner party. Exactly. And this isn't some scrappy startup. This is OpenAI. They have the resources, the talent, the data. Which means the failure here is even more profound. It's a failure of imagination. They couldn't imagine the perspective of their own customer. This feels like the number one startup killer. We've talked about it before. Not running out of money, not bad tech, but building something beautifully functional that solves a problem nobody actually has. It's the biggest one by a mile. I think the data says it accounts for something like thirty percent of product failures. You fall in love with the technical elegance of the solution without ever getting brutal, honest confirmation that the problem is real.

And that it's a problem your customer wants solved, not just a problem you find compelling. Right. The problem of "checkout has too many steps" is a problem for the end user. For the merchant, the problem is "how do I get that customer to come back a second time?" OpenAI's solution to the first problem actively destroyed the solution to the second. So here's what that means if you're a founder or a PM listening to this. You have to relentlessly ask: who pays for this, and what do they stand to lose? Even if your feature is a massive win for the end user, if it undermines your paying customer's business model, it's dead on arrival. And you can’t trust the demo. This is the other huge lesson right now, especially with AI products.

A new survey just came out that said seventy-four percent of AI agents that demo well get rolled back once they're in production. Three out of four. Hold on—three out of four get switched off? Why? Is the AI not smart enough? No, and this is the critical point. The rollback has almost nothing to do with the quality of the model or its "intelligence." It's about the runtime. What does that mean, the runtime? It means the agent fails in the real world. It loses state, it forgets what it was doing halfway through a process. Or worse, its permissions are too broad—what they call the "blast radius" is too big. It might give a refund it shouldn't, or delete a customer record, or apply a discount code to every single item on your site and bankrupt you in an afternoon.

The bull in the china shop. The perfect bull in a china shop. In a demo, in an empty room, it looks graceful. But in production, surrounded by the fragile, interconnected systems of a real business... it's a catastrophe waiting to happen. The agent's intelligence isn't the problem. Its lack of context and its potential for unchecked damage is. So the failure of Instant Checkout wasn't just a strategic misjudgment... it was probably also an operational nightmare waiting to happen. It had to be. Imagine trying to handle customer service. A customer chats with the bot, buys something, and it's the wrong size. Who do they contact? You, the merchant? Or OpenAI? Who owns the ticket? Who issues the refund? Whose system reflects the return?

It's a support black hole. And the brand gets the blame, even though they've outsourced the whole process. You get all of the brand damage and none of the customer data. It's the worst of all worlds. I just keep thinking about the meetings. There had to be someone in a room at OpenAI who came from e-commerce, who raised their hand and said, "Are we sure about this? Are we sure anyone will agree to this?" Of course. But in a culture that prizes technical innovation, that person can get drowned out. The vision is too seductive. "We're eliminating checkout!" It sounds like the future. It's the same kind of founder-led optimism that Stephanie Chadwick wrote about with Guzman y Gomez's failed US expansion. The founder's vision just outpaced the structural impossibility of the market.

They thought they could just show up and compete with Chipotle and Taco Bell without understanding the sheer scale and operational dominance of those companies. Exactly. The pitch was irresistible, but the execution was not. It’s the same pattern. A brilliant idea that ignores the gravitational pull of the real world. For GYG, it was market competition. For OpenAI, it was the fundamental needs of their merchant customers. So what's the fix? If you're building an AI product right now, and you see that seventy-four percent rollback number, how do you avoid becoming a statistic? You stop thinking about building autonomous, all-powerful agents. That's the wrong direction. The fix isn't more autonomy. It's less. You build narrow, gated "workers." Bots that do one single task, whose permissions are incredibly scoped, and whose output is checked by simple rules, not by another AI's opinion.

So instead of an agent that "handles customer service," you build a worker that can only "process a return request for an order under fifty dollars." Precisely. You build guardrails. You put in approval gates. You monitor the cost. You treat it not like a magical new employee, but like a piece of powerful-but-dumb industrial machinery. It can do its one job incredibly well, but you'd never let it wander around the factory floor on its own. It feels like the whole industry got so excited about what AI could do that they forgot to ask what it should do. Especially inside a business. That’s the correction we’re in right now. The hype is meeting reality. And reality is messy. It has legacy systems. It has customers with their own priorities.

You can't just drop a super-intelligent agent into that ecosystem and expect it to work. You have to integrate with respect for the existing structure. So the lesson from OpenAI's quiet little failure... is that you can't just solve for 'x'. You have to solve for the whole equation. The customer, the business model, the operational risk, the support burden. And if your solution for one variable breaks another, it's not a solution. It's just a different kind of problem. In this case, they tried to solve for customer convenience and ended up creating a fatal business model problem for their merchants. It’s a good reminder that the most important product feedback often comes from the people who say no. The twelve merchants who said yes weren't the signal.

The thousands who said "absolutely not" were. That's the voice you have to listen to. The silence can be the loudest data you have. It’s just wild that a product can be announced, covered by every major outlet, and be functionally dead on day one. It happens more than you think. The launch is just PR. The adoption is the business. And in this case, the adoption never came. It’s a tough lesson. So what do you do if you’re the PM on that project? You’ve spent a year on it, you’ve launched, and you have… twelve users. What’s the move? You have to be the one to call it. You go to your boss with the data and you say, "The hypothesis was wrong. The market has spoken." It's a brutal conversation, but the alternative is worse. The alternative is letting it bleed resources and morale for another six months, pretending you're on the verge of a breakthrough that's never going to happen.

The brutal boardroom conversation. It's the only way. You can't let optimism become a substitute for evidence. The moment it does, you're just lighting money on fire. The fastest way to kill a company isn't to have a bad idea. It's to refuse to admit your great idea was actually a bad one. So the real failure isn't launching a product nobody wants. No. The real failure is keeping it alive.