Investors Are Betting on… | Newcomer Newsletter Summary

1. Key Themes

AI shopping adoption is accelerating, but the market is still nascent

Consumer usage of AI in shopping surged this year, though most activity is still light-touch (search/discovery) rather than full agentic transactions.

"A survey by Adobe Analytics found that 41% of respondents used AI for online shopping in June — a number that includes simple searches with Google's built-in AI or ChatGPT."
"Around 53% of shoppers said they trust AI as a recommender as much as they trust brand websites, per an April survey conducted by Retail Dive and the commerce analytics platform Rithum."
"Mark Grace... said he has noticed consumer use of AI commerce tools accelerate significantly this summer... 'I think people have become more comfortable with outsourcing some of those tasks.'"

The real investment activity today is in infrastructure, not consumer-facing agents

VCs are pricing in a future where agents transact on consumers' behalf, but the actual money and building is going into the "plumbing" — identity, payments rails, and protocols.

"Most of the action today is in building the infrastructure and tools for the day when agents can be trusted with a customer's credit card and shopping choices."
"Agentic commerce is still a rounding error today, but a lot is happening behind the scenes to develop the necessary infrastructure and technical protocols to make it all work."
"Smart payments startups like Catena Labs are setting up the banking infrastructure for AI agents by giving them digital identification to match them with the person on the other side who wants a transaction to go through."

Protocol wars are underway among Big Tech and payment networks

Multiple competing standards for agentic commerce are being built simultaneously by the largest platforms, and none has clearly won yet.

"OpenAI and Stripe have launched a framework called Agentic Commerce Protocol (ACP)."
"Google owns and operates the Agent Payments Protocol, which can integrate with several other systems for agents to purchase products online."
"Visa and Mastercard also run systems called Trusted Agent Protocol and Agent Pay, respectively, to integrate AI purchasing into traditional financial services."
"The protocols themselves are somewhat unsettled: Instant Checkout, the first consumer product built on ACP, launched in September 2025 but was pulled back in March."

Trust and reliability remain the central bottleneck

Errors and scandals involving early AI shopping/agent products are undermining the case for consumers (and enterprises) handing over payment authority.

"An Instinct customer on X wrote that his agent canceled his flight without sharing that there would be hardly any refund, costing him around $300."
"Issues like these will certainly have to be figured out before regular consumers trust an agent with their credit card information."
"Many large businesses are still too concerned about the risk from compliance failures or security breaches, said Grace."

2. Contrarian Perspectives

Skepticism that AI shopping agents will meaningfully displace human shopping behavior

One investor pushed back on the prevailing enthusiasm, arguing that shopping is a leisure activity people want to do themselves, and that e-commerce's overall share of commerce limits the addressable opportunity for agentic disruption.

"One investor we spoke with remains bearish on AI shopping agents, despite the category picking up with early power users. Shopping is something people enjoy in their free time, and e-commerce is still just a portion of the global commerce market, the investor said, so consumers will continue to choose to individually shop offline."

Enterprise agentic commerce is over-hyped relative to actual adoption

Despite significant VC excitement, business-side procurement agents haven't gained real traction because compliance and security risk tolerance hasn't caught up.

"Agents buying on behalf of enterprises has excited many VCs but hasn't had as much traction yet: Many large businesses are still too concerned about the risk from compliance failures or security breaches, said Grace."

3. Companies Identified

Instinct — Multipurpose personal AI agent. Mentioned as an example of agents handling real-world shopping/booking tasks, but also as a cautionary tale on reliability. "Early users reported Instinct landing dinner reservations for popular restaurants and movie tickets to special-format screenings of The Odyssey." / "An Instinct customer on X wrote that his agent canceled his flight without sharing that there would be hardly any refund, costing him around $300."
Town — Multipurpose personal AI agent, similar to Instinct, recently well-funded. "These personal assistants, both of which recently closed big funding rounds..."
Daydream — Personalized AI shopping search engine founded by Julie Bornstein. Cited as an example of retail-embedded AI shopping assistants. "Daydream... started embedding into its clients' websites at the end of July, so now shoppers can use the search function directly on the website... Investors in Daydream include Forerunner, Index Ventures, GV, and True Ventures."
Phia — AI shopping deal-finder founded by Phoebe Gates. Cited as a cautionary tale involving a fraud scandal. "There's another cautionary tale in Phoebe Gates' shopping assistant Phia, which uses AI to find deals on online purchases. It's been embroiled in a cookie-stuffing scandal, where it claimed referrals to certain partners that it didn't actually earn. Phia has raised around $43 million to date, and counts Kleiner Perkins, Khosla Ventures, and Notable Capital among its backers."
Profound — GEO (generative engine optimization) marketing tech startup. Cited as a buzzy, well-funded example of the new SEO-for-AI category. "Profound, a buzzy startup in this space, raised $96 million in Series C funding earlier this year, led by Lightspeed Venture Partners, with Sequoia Capital, Kleiner Perkins, Evantic, Saga Ventures, and South Park Commons all participating."
Catena Labs — Smart payments/banking infrastructure startup for AI agents. Cited as an example of agent identity/payments infrastructure. "Smart payments startups like Catena Labs are setting up the banking infrastructure for AI agents by giving them digital identification to match them with the person on the other side who wants a transaction to go through."
Basis Theory — Payments security startup for agents. Cited for enabling secure agent transactions. "Basis Theory... helps agents make payments by creating secure short-term virtual cards for agents to use for added security."
OpenAI — AI company; cited for co-developing the Agentic Commerce Protocol and pulling back Instant Checkout. "OpenAI and Stripe have launched a framework called Agentic Commerce Protocol (ACP)." / "Instant Checkout... was pulled back in March, with OpenAI saying it would let merchants use their own checkout while it focused on product discovery."
Stripe — Payments giant; cited for co-building ACP and stablecoin infrastructure for agent purchases. "Stripe is building underlying infrastructure for agents to make purchases online through stablecoins."
Google — Cited for owning a competing agent payments protocol. "Google owns and operates the Agent Payments Protocol, which can integrate with several other systems for agents to purchase products online."
Visa / Mastercard — Cited for building competing trusted-agent payment protocols. "Visa and Mastercard also run systems called Trusted Agent Protocol and Agent Pay, respectively, to integrate AI purchasing into traditional financial services."
Ramp — Corporate card/spend management company; cited for deploying AI agents for procurement and fraud detection. "Ramp launched AI agents to handle routine business procurement and fraud detection."

4. People Identified

Mark Grace — Investor at M13 focused on fintech and blockchain deals. Cited as a source observing accelerating consumer adoption and enterprise hesitancy. "I think people have become more comfortable with outsourcing some of those tasks." / "Many large businesses are still too concerned about the risk from compliance failures or security breaches, said Grace."
Kirsten Green — Managing partner at Forerunner Ventures. Cited for a measured take on data scarcity around agentic shopping adoption. "It's still too soon to see hard data points on how much agentic shopping has taken off, but that anecdotally more consumers feel they're willing to trust AI tools."
Julie Bornstein — Founder of Daydream. Mentioned as building a personalized AI shopping search engine embedded in retailer websites.
Phoebe Gates — Founder of Phia. Mentioned in connection with the shopping assistant's cookie-stuffing scandal despite significant funding.

5. Operating Insights

Meet consumers where they already shop rather than pulling them into a new destination. Daydream's pivot to embedding its search tool directly into retailer websites (rather than operating as a standalone discovery layer) suggests a go-to-market lesson: "started embedding into its clients' websites at the end of July, so now shoppers can use the search function directly on the website to shop for that specific retailer's catalog."
Reliability failures directly threaten the core value proposition of agentic products. Founders building autonomous agents need to prioritize transparency around consequential actions (refunds, cancellations) before consumers will grant payment authority — illustrated by the Instinct flight-cancellation complaint costing a user "$300."
Enterprise sales for agentic commerce require solving compliance/security first, not after. Startups targeting business procurement should treat risk/compliance features as a prerequisite for adoption, not an afterthought, since "many large businesses are still too concerned about the risk from compliance failures or security breaches."

6. Overlooked Insights

The protocol layer is still genuinely up for grabs, and even OpenAI has already reversed course. The fact that "Instant Checkout... was pulled back in March, with OpenAI saying it would let merchants use their own checkout while it focused on product discovery" signals that even leading players are uncertain about the right architecture — a bigger deal than it may first appear, since it suggests the entire agentic checkout stack is far from standardized and open to new entrants.
GEO (generative engine optimization) is emerging as a whole new marketing discipline, implying a shift in how brands must optimize for AI-driven discovery rather than traditional search — a secondary but potentially large market shift buried in the "Marketing Tech" section: "Venerable search-engine optimization (SEO) approaches are now being challenged by GEO."