one of the most common frustrations i hear from founders crafting a fundraising narrative is: "VCs want to hear this grand future vision, but i'm only at the preseed stage. I see a big customer need that i can solve right now. But i don't know exactly what it becomes in 10 years" first off, I hear you. So much of success is post-rationalized. its hard to tell which parts of a decacorn founder's story is "Hindsight is 2020" versus....not. AirBnB is a classically debated example....those first experiments when they couldn’t afford rent and realized hotels were sold out around a design conference and put airbeds in a living room.....it wasn't exactly the "we will change hospitality" pitch in 2009 when they went to YC. it is one step at a time. but the founders with the biggest visions have spent a LOT more time "living in the future" They're able to sell the bigger vision because they spend more time thinking about 2nd and 3rd order effects. They have insights about why the recent tailwind will change how everyone does X thing and that makes this new vision possible. it really all boils down to depth of thinking in a specific area with hypotheses & constraints. what will change, what will not, now that we have this new tailwind. depth. i think this is ultimately why VCs obsess over having that big vision so much. it's one of the stronger signals for depth of thinking. in my experience, VCs are looking for 2 things in a vision: 1) a huge future vision 2) a credible path to get there 1) A huge future vision: - VCs want to walk away feeling like they learned something entirely new - VCs want to feel like the founders has spent way more time living in the future, have a vocabulary and clear mental picture. almost like how an author has built a world for its characters and then later builds the story through that world - you've already thought about where all the ecosystem actors will be and how they'll behave economically 2) credible path to get there - working backward from th?at future vision - what would need to be true to get there - why is the first wedge you've set up the right first step to get to that future vision, what does it unlock? - this is is where depth of thinking really shines. - this credibility part is what makes or breaks vision in a fundraise narrative ok that's my fundraising 2 cents for tonight

Stanford Prof. @chrmanning on why Moonlake is betting against one giant neural net for its world model, and how coding models changed what’s possible in robot simulation: "Moonlake is building a world model and simulation platform for robotics deployment and testing." "There's been these dramatic developments in coding models, with Claude Code, Codex, and other products. That means you can now be using coding-based AI products to build simulation environments." "The default has been a room full of robots folding the T-shirt, recording all the interactions, which is very slow, very expensive, and not very scalable. That's a large part of what's held robotics back." "Some other companies are based around, the whole thing is gonna be this one big neural net. Our bet is that that technology is not ready in terms of physical accuracy, long-term consistency." "Code-based physics-grounded simulation, overlaid with diffusion models for more accurate material surfaces, can provide the accuracy and the long-term consistency." @moonlake @Stanford

Exa is now one of the largest indexes in the world. We serve 80B pages, track 1.4T urls, and are on track to be Google-scale in early 2027. It's difficult to know the size of indexes, but we estimate Google to be ~1T, Bing to be ~500B, and Yandex ~200B. Brave mentioned in April that they're at 40B. Most of the web is trash that can hurt AI outputs, so you actually have to crawl way more than you serve and train models to filter out the trash. In terms of peak QPS, we estimate Bing at roughly 30k/s and Google at ~500k/s. In our case, because agent traffic often requires large fan-out (deep searches can use dozens of sub-searches) and can be spiky (like when AI labs RL with us), we're already starting to provision for Bing-scale traffic. Within 2 years, agents will search at many millions per second. They'll also want comprehensiveness over all data, far bigger than any index today. So the retrieval infra required will be larger than Google-scale in both dimensions.

At @Cadre, I saw the gap firsthand. Large “institutional” firms built their own systems. But everyone else had to deliver with fewer resources, spreadsheets and manual work. forbes.com/sites/jeffkauflin… “Institutional” should describe a standard, not a budget. That conviction became @ellis_company @JeffKauflin, @Forbes Ryan Williams’ Next Act After Cadre: A Fintech Fix For Private Credit’s Data Mess

What comes after language? Join us at AGI Summit 2026 for “Beyond Language”—a conversation on world models, spatial reasoning, and embodied intelligence. Featuring Christopher Manning, Mercedes Bent, Fan-Yun Sun, and Christian Laforte. @chrmanning @mercebent @sunfanyun @chrlaf 📅 July 18, 2026 📍 Palace of Fine Arts, San Francisco 🎟️ agisummit.ai #AGISummit #ArtificialIntelligence #AGI #WorldModels #EmbodiedAI #SpatialReasoning

Why are you paying for dictation? We're releasing free, unlimited AI dictation. And it's not a slow, local model. Willow Frontier Mini is cloud-based with zero-data-retention. More accurate and faster than Wispr Flow, OpenAI, Deepgram, and more. See video comparison.

Introducing Willow Frontier Mini and Willow Frontier Pro. Frontier Mini gives everyone free, unlimited dictation. Frontier Pro is our most accurate model yet, built for power users and teams who want the fastest and best dictation experience.

We raised $4.3M, led by @PanteraCapital Soon, there will be more agents than people online. Those agents will book flights, hire contractors, enrich customer data, conduct research, and complete transactions without a human in the loop. But today, agents are stuck with whatever tools they were originally given. The moment they need something new, they fail, hallucinate, or hand the problem back to a human. Orthogonal fixes this. Through a single integration, agents can discover the capabilities they need in the moment, orchestrate them, and pay for them instantly. An agent describes what it wants, and Orthogonal composes the result, calling the right services in the right order. Our goal is simple: when an agent needs a capability it doesn't already have, Orthogonal will be the first place it goes. Thanks to @PanteraCapital , @ycombinator, @pioneer_fund, @decasonic, Blast Club, Outbound Capital, Rice Capital (@taro_f), Surreal by Premise (@mercebent & @veelarco), Batch Ventures (CTO Fund), and our strategic investors for backing us. We're building the default front door for the internet.

A new internet economy, built for agents: Agents break the old economics of the internet - when everyone has an AI assistant consuming and taking actions, what happens to ads? Exa Connect is a step toward a new internet economy built on data, not ads. It's a marketplace where data providers choose what to charge for their data, and developers choose which data providers their agents use. We feel this is the right economic model -- market-based, transparent, value-aligned, and as agent requests scale >1000x over the coming years, will be a more valuable market for providers than the ad market is today. This is also a good path forward for the internet. It's one that monetizes transformer attention, not human attention. We don't know exactly what that great intercontinental information exchange called the internet will become, but it's going to change, and we think very much for the better.

We saw the action and control layer coming. Now we're going to own it. Everyone focused on the models. We focused on what happens when the agent actually does something. @WSJ covered our $60M Series A today: wsj.com/cio-journal/arcade-d…

just closed our 2nd fortune 500 customer a decade ago, they were the first client i worked with straight out of college 498 to go

Introducing Willow Scribe: a voice AI writing assistant that clears your emails, docs, and messages in seconds. It uses your style and context to write exactly what you want, in your voice. Just say it and Scribe writes it. See the future of voice AI for knowledge work 🧵

just closed our first fortune 500 customer 499 to go

we just launched agent-to-agent hiring at @hyperspell we're hiring engineers and your agent is your application no resume, no leetcode apply with your own agent or spin one up via @SuperMeAI we will interview every single agent

Janitor was profiled in Forbes yesterday. A few of the things they recognized 👇

1 big clarification on the memo fundraising advice....yes its a good idea BUT.... you still need a deck! why? Decks are better for first impressions. They're simpler to consume, better test of whether you're able to distill complex topics. They're for people who haven't decided if they want to invest 10 minutes into reading your memo need a faster way to consume your content. It's easy to make an okay deck today. It's still as hard as it was pre-AI to make a great deck today....so it also separates out for investors whether you invested in what you're giving them. If you got an intro for the first meeting + didn't need deck to get Yes to meeting, I would still share it before the meeting or right after to cement the concepts. Investors forget fast. Many of the Notion memos I read are not well put together and I still think the Deck would have done better. Decks overall are just less friction and you want less friction at every step in your process. The memos later on become less friction ONCE someone is bought into doing "Due Diligence"

the SF version of "kids flocking in the fields" 😍

My rule of thumb: never sell more than 20-25% of equity on SAFEs why? if you raise too much on SAFEs, it will hurt your future fundraises i've seen this happen a lot. raising on SAFEs is so seductive because its simple + quick but the total ownership impact at the seed or A can be really large if too much was given away your first priced round can see 50% of the company being given away but an investor has to convert that to a priced round and if too much ownership has already been given away, it disincentivizes future investors from wanting to price a round where founders will end up owning too little then founders will say its okay you can clean up the cap table, can cram down my existing investors but VCs aren't set up to do recaps easily or well. its' just not our normal transaction. and it's a lot more headache than its worth most VCs want as clean a deal as possible so my rule of thumb is to never sell more than 20-25% of equity on SAFEs. If you're raising more, move to a priced round.

How to get acquirers to want to buy your startup: The best time to set yourself up for a strong M&A is 1 year before you ever realize you want to sell. There's an adage that startups are bought, not sold. Meaning the buyer should be bought into your asset, to the point that they've already convinced themselves of the value. So how do you get buyers to want to buy your startup? There's a lot of ways, but I'll tell 1 story. I remember one M&A process where a VC-backed SaaS startup got 2 offers in < 3months. The company had positioned itself well long before M&A ever kicked off, by setting up partnerships..... Specifically, product distribution partnerships. These agreements were to co-market and co-distribute their products together, to each others customers. In this company's case it wasn't intentional design But it ended up working out so well because: + Leadership teams already knew each other + Mid level teams already knew how to work together + Both knew value of asset to their customers (conversion rates) + Both understood tech stack Everyone was already bought in, so the company was bought, not sold. it also helped that this company was m&a ready: + breakeven / profitable + greater than $5M ARR+ more, but less than $20M (not too big for smaller acquisitions) + leadership team that spoke M&A language + strong data room operations There's a lot of companies with M&A goals today Set your startup up to be bought.

Once you have this, AI will seem magical

why is everyone leaving OpenAI today