Earlier this week, OpenAI cemented its push into shopping and commerce when it announced a deal with PayPal, which will allow users to buy items through ChatGPT using PayPal. As part of the integration, PayPal merchants will also be able to sell their items via ChatGPT. PayPal stock jumped 4 percent on the news but had fallen back by Wednesday—a decline that continued into Thursday.

And now for the main event…

Last week, I walked to a hotel in New York’s Financial District, where a robot cooked me lunch. You might be envisioning a vaguely humanoid figure—like Tesla’s Optimus wearing a chef’s hat—rummaging through the fridge or julienning carrots. But Posha, the “private robot chef” responsible for my meal, looks more like an open-door microwave than a robo–Gordon Ramsay. The $1,500 countertop device features an induction plate, a specially fitted pot, a robotic arm, a spice and oil dispenser, and ingredient containers. Nestled in the hood is a small camera that sits above the pot and feeds information to a computer vision model, which directs the robot’s actions.

Raghav Gupta, the co-founder and C.E.O. of Posha, had already done a little bit of prep before I arrived for the demo, filling each of Posha’s four ingredient containers with chicken, spinach, sun-dried tomatoes, and cream. He selected a preloaded recipe—“creamy Tuscan chicken”—and clicked “start.” With all the hard work done, we retreated to a table so he could tell me about the company while its core product prepared us a meal. Posha is just one among hundreds of robotics startups that have sprung up in recent years, fueled by an influx of venture capital and advancements in A.I. that have transformed ideas once relegated to science fiction—like box-moving and strawberry-picking robots—into reality. But unlike other Jetsons tech, like 1X’s new $20,000 robot that promises to fold your clothes, Posha actually… works. According to Gupta, what makes the system unique is the process of “staged” cooking, whereby its specially trained computer vision models ensure that cooking unfolds in a precise, timely fashion. The target market, he said, is people who prefer to eat healthy, home-cooked meals but don’t always have time to cook, à la Sunday meal-preppers. Silicon Valley has developed a somewhat disordered view of food, seeing it as just another layer of the nutritional stack that can help you land your next fundraising round. The actual love language of food, Gupta argues, has been lost—and, ironically, A.I. itself might be the remedy. “I feel we need to use technology to help us eat healthy, to help us continue to express love through home-cooked food,” he told me. “I enjoy cooking, but some days it’s just too hard to find the time, and then those days I don’t want to be eating a frozen pizza or putting junk into my body.” Of course, Posha isn’t perfect. Like all A.I. applications—especially those that interface with real-world complexities—edge cases aren’t hard to find. Gupta offered a few himself: A customer might boldly substitute purple potatoes into a given recipe, for example, which would likely confuse the small language models that power Posha, at least until the team can ship a fix. But after running a yearlong beta trial in consumer homes, Gupta seems to have ironed out most of the major issues. Posha didn’t run into a single problem while preparing my Tuscan chicken dish. Not including prep time, the cooking process took half an hour, by the end of which I had an actual meal in front of me. Frankly, the creamy Tuscan chicken wasn’t bad. It also wasn’t great—but that could’ve been solved with another 10 or 20 minutes of simmering. (I like my one-pot chicken to fall apart.) I also got a taste of a paneer tikka masala, cooked by Posha before I arrived, that Gupta said was the best in the Bay Area. I’ll spare you the details, but it was actually good. I never would’ve guessed that the secret ingredient was a G.P.U., rather than love.

With their beta trials behind them and an $8 million Series A secured, Posha is beginning to scale up their operations. Gupta said they have “a few thousand” people on their waitlist, and have shipped 300 units to date. At the end of 2024, Posha was in 50 homes; as of early October, they were in 300, and they expect to be in 800 by the end of the year. The waitlist, he said, should be cleared out by the middle of 2026. Around that time, Posha plans to complete a significantly larger funding round—money that will fuel the company’s growth plans. “The reason we’re not raising right away is because we want to prove product-market fit, and then raise for growth,” Gupta said, adding that they currently have a runway of a little less than two years.

Gupta’s goal is to achieve 70 percent gross margins on the hardware when it’s produced at scale. However, the biggest opportunity might be recurring revenue: A subscription to Posha’s library of recipes and A.I. tools costs $15 a month, and includes an integration with Instacart, complete with an auto-populating grocery cart. The margins on the software, Gupta said, should be closer to 95 percent. The Posha team is already contemplating other A.I. appliances, too. Gupta told me his team has plans to develop a partially automated stovetop, with far more automation and augmentation capabilities than the current version of Posha, with features like a meat thermometer and an auto-scroll feature for recipes, so you don’t have to keep washing your hands to wake your laptop up. The idea is to overcome Posha’s current one-pot-meal constraints while appealing to those who don’t want the robot to make their meals all the time. Gupta said the goal is to drop the first version in four years, with aspirations to be in 70 percent of U.S. households a decade later. Unlikely, perhaps, but not impossible. Posha, which made Time magazine’s list of the best inventions of 2025, actually offers a quick-fix solution to an identifiable problem. And while A.I.-assisted cooking isn’t for me—I love being in the kitchen, assembling my own meals—I would be lying if I said I didn’t see the appeal. “My wife’s very happy,” Gupta said. “I’m here, but she’s still getting freshly cooked meals at home right now.”

For months, the major A.I. companies have been asking governments around the world for special exemptions that would legally protect them from the copious—and potentially devastating—copyright infringement lawsuits that keep cropping up. Australia’s government this week officially ruled that it will not grant this exemption. The move was celebrated by the Australian Recording Industry Association, among others. [The Guardian]

Brian Merchant talked to a couple of scholars who recently wrote a book on market bubbles, then applied their test to our current A.I. investment environment. His verdict? A.I. is “the bubble to burst them all.” [Wired] Now that OpenAI is hell-bent on treating adults like adults (e.g., removing limits on erotica), Steven Adler, an A.I. researcher who led product safety at OpenAI, detailed the company’s shifting policy on “smut,” all set against a backdrop of mental health issues among users and a history of “paying too little attention to established risks.” [NYT]

That’s all for today. I’ll see you next week.

Ian

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