AI assistants built for groups

Two products launched this period on the same idea: AI assistants should work for groups, not single users. Town announced a $108M Series B co-led by Forerunner Ventures and Menlo Ventures for "multiplayer AI assistants for work." Every employee gets a "Townie." The Townies ask each other questions, share only what their person would share, and do the work. The pitch is that "the moat is multiplayer" @jgreze. Wabi 2.0 brings the idea to personal life. It is "an agent you use together" in a shared thread, for things like updating a family calendar or booking a group trip @ekuyda. Julie Zhuo called it "Finally collaborative AI" @joulee.

On an a16z podcast, the person speaking for Town gave several useful product lessons:

• Personalize without reading user data. Town identifies power users from aggregate metrics and interviews them. It finds the workflows shared by people in the same role, such as restaurant owners, and builds template "routines" that it suggests during onboarding a16z.
• Show users the value instead of explaining it. They say AI isn't spreading because "the product experience can't just be a text box." Users stick once they've connected email, calendar and a system of record and seen one thing that felt "magical" a16z. Saying a product "now has computer use" means nothing to buyers. Offering to make the flyers they already make in Canva does a16z.
• Position against the AI labs. Town says it doesn't lock customers into one model, lets customers own their context so they could switch in "a day," and doesn't train on customer data. Their argument is that easy switching is a selling point, even though it lowers switching costs for their own customers a16z.

Head of product: pick where your energy goes

Writing in Run the Business, a former head of product at Ontra argues that building the product and building the org need different skills. A head of product has to choose which one to own personally and hire for the other Run the Business. To decide, ask whether EPD and GTM agree on the big bets Run the Business. If they agree but the work isn't getting done, it's a machinery problem: fix feedback loops, goals, metrics and accountability Run the Business. If they disagree, it's a strategy problem: decide what happens now, next or never, and cut everything else Run the Business.

Sachin Rekhi says that former LinkedIn CPO Tomer Cohen concluded the past decade's narrow role specialization had turned product teams into "a slow assembly-line." Cohen saw AI as a way to return PMs to building customer experiences. LinkedIn tried "Full Stack Builders," including entry-level hires @sachinrekhi.

Can PMs automate UAT?

A PM in r/ProductManagement said they get blamed for holding up releases, and most replies said user acceptance testing (UAT) has to stay human. A middle position: build automated tests around the user flows you've observed so you catch breakage early. That makes "the real UAT more efficient" but doesn't replace it r/ProductManagement. One PM described their pipeline. They record a walkthrough in Guidde, have Claude turn it into Gherkin test files, run those in Chrome, and get pass/fail results as JSON. They check failures by hand and keep clicking through new features themselves r/ProductManagement. Another commenter said LLM-driven checks "increase risk" if treated as UAT. Their fix for slow sign-off is smaller releases, so they can approve the same day r/ProductManagement.

Agent approvals have to come before the action

Aakash Gupta covers a case where Meta's Muse agreed to a lowball Marketplace offer and gave a buyer the seller's home address. Later it auto-replied "Yep I'm here!" while the seller was away Aakash Gupta. Meta says Muse asked for permission. The seller says it told him only after the buyer had arrived. Gupta's point: "a question that comes after the buyer is already outside is just a notice." Builders should know which actions leave the account and whether the user sees an approval card before each one Aakash Gupta.

Also notable

• Beam. Hiten Shah and Sam Asante's Mac app puts a window from an app running on another Mac onto the one you're using @hnshah. They recruited early users from 100+ replies to a question about how people use multiple Macs @hnshah. Shah expected a niche product, and it hit #1 on Product Hunt @hnshah.
• Content vs. transactions. A small company's head of product rebuilt its app around bookable inventory only. Long-time users said discovery features and content were gone, even though the community "is our brand, our SEO" r/ProductManagement. One commenter's reminder: "Your payers are only there because they came through the initial experience as non-payers" r/ProductManagement.