Now is the exact time @spacex and @meta should release an iPhone competitor with no apps — just agents and optimized for local AI and privacy

We are excited to announce we are partnering deeply with Muse to enable agentic checkout with Shop Pay on all Shopify stores, offering people an easy and delightful way to shop and check out with Muse.

AppLovin CEO Adam Foroughi says agentic shopping is overhyped, because the typical shopper wants the dopamine hit of buying it themselves "The reality is part of the world will start using things like agents to optimize per certain shopper behavior that's consistent." "For instance, I might put my supplement subscription into an agent and have it optimized every single month and delivered on time." "But these discovery platforms aren't that. And the typical shopper is not the person who's deep into agents and sitting on Twitter and adopting the latest technology. I sort of say our audience is the New York Times audience." "There's still a ton of people using Yahoo properties every single day. The typical shopper wants to find a product and wants to actually go through that shopper behavior. They want to window shop, they want to go through the transaction experience, they want to track it." "And if you told them after the fact, hey, an agent could have done this for you and saved you 20%, I don't think that matters on a $50 transaction, because the dopamine hit from going through it is what they enjoy..." "I just think we really overindex on the Twitterverse and forget that the average shopper is not that."

JUST IN: Amazon blocks Meta’s Muse AI agent from shopping on behalf of users, citing unauthorized access and privacy concerns.

pretty remarkable that meta gives every user a 2 vcpu / ~8gb ram / 100gb storage vm for their agent to use. & this compute is outside of inference which is 100k free tokens per week (not easy to burn through). this is why you’re seeing consumer competitors try to raise a lot more money & there are only a handful of players that can even compete, i.e. even openai can’t remotely allocate any of this to any of the non business / unpaid users. turns out having an already insane ad business to back this up for consumers is key.

The hottest category in tech right now is AI assistants. The question is; who is going to win? Instinct raised at $2.5BN. Has Benchmark and Index behind them. Grok Bot is ripping with Elon and has the distribution machine of X. And then there is Town, one of the only ones that’s actually making real money from real businesses. Don’t write Zuck off. This will be his next play and integrated into every WhatsApp user’s product. I sat down with Town Founder, @jgreze to understand WTF is going on, who wins and who loses? Condensed my notes below! 1. We Have Passed the Point Where Humans Look at Lines of Code Software engineering has crossed a threshold where machines increasingly write and ship code into production under model-based guardrails. Outside critical security controls, humans will spend far less time reviewing raw code. The future belongs to systems that manage autonomous AI agents writing software, running tests, and validating their own work. 2. You Can Build at the Speed of Machines, but You Can Only Learn at the Speed of Humans AI development tools allow competitors to clone features in weeks, erasing traditional software head starts. But deep user feedback cannot be automated. While machines accelerate execution, true competitive advantage comes from maximizing human learning cycles and understanding customers faster than anyone else. 3. Why None of the AI Assistants Have True Product-Market Fit Today Despite immense market hype, no current AI assistant has achieved deep product-market fit with mainstream users. Most products still cater primarily to power users rather than everyday workers. Before worrying about moats, founders need to create frictionless experiences that resonate with the mass market. 4. Network Effects at the Agent Level Will Separate AI Winners Sustainable moats in AI assistants will come from multi-user network effects at the agent level, not single-player productivity. When autonomous assistants collaborate across teams to resolve queries and execute work, switching becomes increasingly difficult. Multiplayer workflows create organizational lock-in that personal assistants cannot replicate. 5. How Much of the Workload Stays at the Frontier Versus Open Weight? AI application margins depend heavily on how much work requires expensive frontier models versus cheaper open weights. Complex reasoning may still demand frontier intelligence, while routine tasks like scheduling and email tagging continue moving down the cost curve. Shifting 80% of workloads to open weights over time could create far more sustainable economics. 6. My R&D Is Just Spent Getting Product Parity With the Giants Competing with giants like OpenAI requires massive investment simply to maintain feature parity. Startups cannot rely on unique distribution if their underlying harness falls behind on core capabilities. AI assistants must invest heavily to match the execution speed and product depth of frontier teams. 7. Why Instinct Is Not a Competitor to Town Consumer assistants like Instinct focus on rapid acquisition through subsidized personal tools, while enterprise platforms build monetizable team workflows. Although their technical harnesses may overlap, their target ICPs and business models diverge sharply. Enterprise agents monetize by embedding collaboration directly into daily operations. (links below)