andi schuster

One of my more controversial bets: the AI feed will be the form factor of 2027! Most people don’t know what to prompt, and they won’t prompt their way into complicated agentic workflows. With chat, we ask users for digital labor: figure out what AI can do, explain the task, provide the context, repeat. That’s a lot to ask if we want billions of people using agents every day. Meanwhile, people already spend hours in feeds. Twitter, Instagram, LinkedIn. They know how to scroll, discover something useful, and act on it. An intelligent system that knows you should bring you the next useful action. Here’s the email you need to answer, already drafted. Here are the latest sales numbers, with an update ready to send to your team. You approve, edit, dismiss, or jump into chat to go deeper. That’s how people will discover what agents can do, without having to invent a prompt first. And you can put ads in a feed, one of the biggest business models on the internet. A system that understands your plans can recommend a relevant restaurant, product, or service, clearly labeled as sponsored. You get a reason to come back every day, useful work ready to approve, and a business model to fund the agents doing it.

Assorted things I've been mulling over regarding agents in the economy: • Companies are in some sense the original superintelligence. It's often the case that they can use their amortized cognitive surplus to advance their interests against those of certain consumers: relative to the optimization capacity of companies, consumers can be inattentive, underinformed, irrational, etc. (Think, say, of some of the classic insurance upsells at the end of a booking process, which is typically priced substantially above what a regular policy would cost.) Herbert Simon introduced the idea of bounded rationality, and firms often end up benefiting from it. Thanks to personal agents, we will probably get somewhat more rational in how we engage with companies. • How exactly will outcomes change? Well, certain kinds of price discrimination will work less well (how do coupons work if every agent hunts fastidiously for them?), and certain kinds of customer cross-subsidy will change (today, people who forget to cancel subscriptions subsidize those who don't). Taken across the economy as a whole, I'm not sure what the incidence of all of this will be. • In corporate strategy, people have long debated the relative importance of distribution and product quality. Perhaps you've made something better, but does anyone know about it? Won't people just continue to buy the ACME Corp Mousetraps? Personal agents will, I think, act as a kind of structural subsidy for product quality. How would markets look different if individuals always spent at least 10 hours researching their purchases? On the margin, focusing on making a product better is, I think, going to become a more effective strategy for companies. This is good! • It true, a corollary is that information about product quality will become more important and impactful. Today, most people have very limited ability to aggregate and integrate such data, but agents will have insatiable thirst for such signals. (It's often said that data is becoming more valuable because it helps in the training of models. That's obviously true, but I think there's a secondary way in which it's more valuable simply as a complement to cheaper intelligence.) • A big question is whether agents will increase superstar effects (rational agents all settle on the same product) or increase dispersion (because everyone has slightly different tastes and preferences, which agents are good at eliciting, finally overcoming the artificial clustering we've been subjected to). • Many internet companies have monetized demand routing, which is in turn often predicated on short attention spans. "I'll click on the first thing I see." This has led to some amount of inefficiency, as companies try to propitiate capricious ranking algorithms and incur various placement fees. It's not all deadweight loss (willingness to pay is itself a kind of signal, which is valuable to buyers), but it's not great. How will the nature and value of this routing change in a world of personal agents? I don't know the answer, but I think that the effects might be pretty big. • Much of what I'm writing hinges on the assumption that personal agents will be on the consumer's side. I suspect that that will be the winning strategy, but whether it's true, and what it means to be true, involves a lot of other questions. Taken as a whole, the market is a massively parallelized, decentralized, and highly imperfect value attribution machine, and, taking stock of all of the effects, it seems to me that the quality point may well be the biggest: that agents will change the nature of the backpropagation such that the rewards for better products increase. Maybe this is too optimistic, but I suspect (and hope) that companies that make things that they're proud of will feel that the universe is a little more partisan in their favor.

My biggest takeaways from @tfadell: 1. When building a v1 of anything, decisions should generally be opinion-based, not data-driven. You have very few analogues when creating something the world hasn’t seen. You need one or two tastemakers charged with making those decisions. If you try to make everything data-driven, you either end up with an undifferentiated product or you’re using bullshit data. The key is informing your gut by gathering input, prototyping, then making the call. 2. The customer journey matters more than the product in isolation. You need to think about the entire journey—discovery, marketing, sales, distribution, installation, usage, and support—not just the product. The Nest thermostat reinvented how you bought it (Best Buy instead of installers), installed it (DIY instead of professional), and how it worked (learning instead of programming). You’re not building a product; you’re building a system. 3. Marketing is as important as the product itself, and most builders don’t realize this. When building, you’re living in the context—you understand the pain points and features. But customers don’t have that context. When the iPod launched in Europe using the same marketing they used in the U.S., it flopped because European consumers were at a different adoption stage. Even an amazing product like the iPod can fail without the right marketing. 4. Storytelling is an essential skill for builders, because humans are wired for narrative, not feature lists. Tony learned from watching his dad sell Levi’s—sometimes convincing customers not to buy, building trust. He watched Steve Jobs refine the iPhone story every day for two and a half years, pitching to friends, refining constantly. By launch, Steve had done it 10,000 times. The key is telling the why, not just the what. 5. Every new product needs three generations to succeed: make the product, fix the product, fix the business. The first iPod only sold to Mac enthusiasts (less than 1% of the market). It wasn’t until the third generation, with Windows connectivity and the iTunes Music Store, that the iPod took off. Same with the iPhone—it first worked only on AT&T with 2.5G; the third generation had margins and reliability dialed in. Stick with your idea through these three iterations. 6. Don’t cognitively surrender to AI. AI can help with prototyping and subtasks, but architecture, opinion-based decisions, taste, and ethics require human judgment. Just like Steve Jobs shut down porn in iTunes immediately, you need human leaders with clear principles. The companies that win will use AI to amplify human creativity and judgment, not replace it. 7. Tony predicts that the next breakthrough consumer device will be voice-first, screen last. Right now we tap first, use the keyboard second, and voice third. As AI improves, voice will become the primary way we interact with devices. But we’ll still need a screen of some kind. 8. Steve Jobs was wrong about several major product decisions. Steve refused Windows connectivity for iPod—“over my dead body.” Tony’s team kept working on it anyway. Eventually it shipped and became essential to iPod’s success. Same with the iPad stylus—Steve hated it—another skunkworks project, now a major feature. Sometimes you should keep working on things the leader doesn’t like when you can see it on the horizon. 9. The iPhone keyboard decision was the longest, most heated debate for the original iPhone. The team was split. After months of tests, where they compared typing speed and error rates, the data wasn’t definitively clear. Steve Jobs made the call: virtual keyboard, full screen. Those who couldn’t get on board were told to leave. 10. Start from pain, then ask “why now?” The biggest product breakthroughs pair an old, often habituated-away pain with a new technology that has made solving it possible. For Nest, it was AI that could finally learn your schedule and optimize your heating/cooling costs.