Personal AI agents are here, and they’re shopping for us. Muse has been downloaded more than 5 million times in just 22 days. That may feel—and is—a tiny number for now, but my gut says we’re just reaching an inflection point. AI is no longer just searching for us. It’s choosing for us. That’s a good reason to figure out how these agents think today, before they become the majority of our sites’ traffic.
When we delegate shopping to agents, they decide which products we see and which sellers they consider. That begs the question(s): Who determines how Muse shops? What influences its decisions? What makes it choose one product over another? I don’t have all the answers, but I do have some leads.
Unlike chatgpt.com, personal agents are less constrained by response speed and a model’s training data, so they can do more work to find an answer.
By the time Muse starts your search, it’s already made a bunch of decisions: it has gathered your preferences and information from previous conversations, along with instructions on where to search, which stores to look at, which products to compare, and how to choose. Those instructions determine which products win the shopper’s attention and, ultimately, their purchase.
How does the Muse search sausage get made?
Luckily for us, someone has already dug into Muse’s literal instructions (Muse’s brain, if you will). Bare in mind Meta can change these at any time, and they may be outdated by now.
When you send a prompt, Muse first takes a look at what it remembers about you: your shoe size, your preferences, and relevant context that might improve the search.
Then, Muse goes down two rabbit holes: Meta’s product catalog, which contains products and merchants for Facebook and Instagram, and a browser it can use to search vendors outside that catalog. The catalog is neatly organized by product name, photos, prices, and availability. In the browser, Muse can look at up to three merchant sites and ten products, unless the user gives it more specific instructions.
Once it finds products, it’s asked to filter them. It removes bad matches, decides if a product is trustworthy, and tries to make sure the item is in stock. Once that’s finished, it ranks each result by relevance, fit, and seller trust. Who sells the product is explicitly part of the process.
If you ask for a deal, Muse has an extra round of work to understand typical price, find other offers, and check for coupons.