Andreessen Horowitz

Roughly 55 million American homeowners have a mortgage. The servicing industry that collects monthly mortgage payments makes $1T in revenue each year - but most of the software that powers that industry hasn’t been updated since it was first built on mainframe computers as early as the 1960s, which causes a ton of unnecessary friction and stress for homeowners trying to repay their loans. Andrew W., Linda Du, and Jonathan Hsu just raised $150M for Valon to solve this problem - and to rebuild some of the oldest, most critical financial infrastructure in the country. The company hires based on grit, talent and determination, not years of experience. They happily hire hungry, hard-working early-career employees and invest in training them. There’s also a ton of upward growth for people within the company. 70% of the team’s leadership is home-grown and have been at the company for 4+ years. “The sky is the limit if you prove yourself, and the upside is enormous.” Read more about their story and open roles:

Ben Horowitz on what he's evaluating when a founder pitches: the idea is just the lens, the person is the bet. "If you had a perfect rating system and could go, 'Do you want this entrepreneur or this idea?' you'd take the entrepreneur every time." "The problem is it's hard to evaluate entrepreneurs. You don't know that much about them when they come in, and you don't know how they're going to perform under pressure. So you need the idea to help you evaluate the entrepreneur." "What did they go through in their life to get to that idea? How good an idea is it? How much original work did they do to get there? That ends up being the lens at which you see the entrepreneur." "The mistake to make is, there's something you don't like about the idea, and you pass on a great entrepreneur. Or vice versa: 'This is a great entrepreneur,' but you don't realize his idea is no good." "What matters is, are their strengths world-class? Are they the best in the world at something? And then you overlook everything else." "Every entrepreneur we see who gets to us is pretty good. But are they outstanding? Are they better than everybody else at this? That's what makes a company great." With James Norman

We're thrilled to lead General Medicine’s $120M Series B as they build the general store for healthcare. General Medicine is built on the belief that facilitating access to care is a core part of delivering it. The company brings patient history, ongoing clinical guidance, transparent pricing, and help accessing care into one experience. Its own medical group combined with a marketplace of external clinicians connects patients almost immediately with services far beyond what a single practice could ever provide. Alongside its direct consumer offering, General Medicine is also building for the enterprise. The same underlying infrastructure for clinical guidance, transparent pricing, and rapid access that General Medicine has already built can be ‘turned on’ for consumers in partnership with any number of enterprise organizations. We’re excited that the PillPack team is back together. Congrats, TJ Parker, Elliot Cohen, Ashwin Muralidharan, and the General Medicine team! By Vineeta Agarwala, Jorge Conde, Daisy Wolf, and Eva Steinman

Make the first move.

OpenRouter co-founder Alex Atallah on the "everyone is building the same thing" take: "This reminds me of this tweet I saw... Everybody's building an agent loop with notifications, third-party connectors, context management, memory, sandboxes, agentic web search, an always-on agent on top." "This product is showing up everywhere. It is showing up everywhere, but these are just the new table-stakes primitives." "A 2005 version of that tweet would be: 'Oh, everybody's building the same thing. A database, a users table, a sign-in page, a sign-up page, a profile page, a logout page. Everything's the same.'" "There's like a lot of differentiation really. There's table-stakes needs for AI just like there's table-stakes needs for the web." With Amjad Masad

There's a race to become your personal assistant. The channel du jour is iMessage, where viral agent Instinct launched in August 2026. Companies like DoorDash have since launched their own iMessage agent for text-to-order. More prosumer-oriented agents, or consumer agents focused on a specialized use case, often also have their own mobile or web app to provide a deeper experience. Instinct founder Noah Shinn reported that 40% of users connect a personal credit card within three weeks, with more than $1 billion in annualized transaction volume is already flowing through Instinct - half of this attributable to travel. As agents start to drive meaningful traffic (and revenue), the platforms are choosing sides. Amazon shut down access for Meta’s Muse in under two weeks, while Shopify, Instacart, OpenTable, Expedia, Ticketmaster, Plaid, and others have signed official integrations.

Between Anthropic, Google, and OpenAI, there were 127 new launches over the past six months. Anthropic has focused almost entirely on the prosumer (Claude Design, Code Review, Claude Science). Google has led on creative models (Lyria 3 Pro, Gemini Omni). OpenAI has tackled both consumer and enterprise - with tools for enterprise (ChatGPT Work, Sites, Dots) and for consumers (Images 2.0, Health, Personal Finance, job search).

Consumer AI still has a lot of room to grow. Amazon, Facebook, Airbnb, Tinder, Zillow, and PayPal all helped define past consumer internet eras. Many of the biggest were built around transactions and networks. Almost none of the top consumer AI products today have any real multi-player appeal. Retail, social, travel, dating, real estate, and personal finance all produced category-defining winners on the web. In AI, none of those categories has a dedicated product on our list. What do the startups that did break through have in common? 1. Own a differentiated model. A distinctive sound, visual style, or training dataset can matter more for a particular creative task than which lab has the strongest general-purpose model. 2. Own a multi-model experience. Cursor supports models from several labs; OpenRouter gives developers access to multiple providers. Choosing models around the customer’s task can be a product advantage. A lab selling its own model may have less incentive to send that customer to a competitor. 3. Own an audience with specific needs. Sources, privacy, and fit with the customer’s work can matter as much as the underlying model. 4. Own an experience that would require changing a legacy interface. “Legacy” can mean Google Docs or Calendar, or the blank prompt box of ChatGPT or Claude. Startups have fewer existing user habits and revenue streams to protect, which may give them more freedom to change how the product works. AI may also create categories of consumer attention and spend that we haven't seen before.