Meet the newest member of Team Menlo, Deedy Das, aka @debarghya_das. At Menlo, Deedy will focus on early-stage investments in AI/ML, next-generation infrastructure, and enterprise software. To learn more about Deedy, where he’ll invest, and why we are so excited to have him on board, read this post mnlo.vc/welcome-deedy fm @timt

Just uploaded my brain to Delphi’s Library of Minds. 🧠 I recorded a pod with @withdelphi founder @daraladje. That conversation—along with all my past interviews, articles, blog posts, and talks—is now live inside my Delphi digital mind. You can now chat with all my past content and ask me questions: delphi.ai/jesslee Delphi captures not just your knowledge and stories, but the way you think. In the podcast, I shared several powerful mental frameworks I've collected over the years: 1) The EQ/IQ/PQ/JQ framework, h/t to my partner @shaunmmaguire 😀 Emotional Quotient: One-on-one people skills 👫 Political Quotient: System-level people skills 🤓 Intellectual Quotient: Raw intellectual smarts 🎯Judgment Quotient: Good judgment Some brilliant people (high IQ) make terrible decisions (low JQ). PQ is a force multiplier because leading teams requires navigating group dynamics. Very few people excel at all four dimensions. 2) Moving 3 points on a 10 point scale, via Cheryl Dalrymple, CFO of AdMob, Confluent, and my startup Polyvore: 💪 Hard work typically moves you just 3 points on a 10-point scale. 🎯 It’s far better to push from 7→10 in your strengths than struggle from 2→5 in your weaknesses. ⚡ Since your energy is finite, invest it where you naturally excel. 🤝 Hire exceptional people who thrive where you don’t. 🚫 A common startup mistake: seeking perfectly well-rounded people who score 7+ across every dimension—they’re rare and expensive. 🦔 Instead, hire “spiky” talent—people who are 10s in one dimension, even if they’re 1s elsewhere. 🧩 Build teams where collective strengths cover all critical areas. 3) Startups are turn based games and why velocity matters, h/t @mvernal: 🎮 Startups are like turn-based games. 🂡 You’ll flip a lot of cards and make a lot of moves. 🔁 Most moves won’t be perfect—but what matters is how quickly you turn the next card and learn the next lesson. 🏆 Winning requires a mix of playing the right card and playing quickly. ⚡ It’s easier to be faster than it is to be right-er. So play fast. 🚀 Speed compounds. If you want to go deeper into lessons from my time at Google, the truth of my founder journey at Polyvore, or my hot takes on the future of consumer AI, watch below or have a conversation with my Delphi. 00:00 Intro 1:00 Who is Jess Lee 02:50 The EQ / IQ / PQ / JQ framework 03:44 What early Google taught her 05:35 How ambition is a double-edged sword 07:34 Customer discovery vs visionary intuition 09:31 Polyvore: from user → CEO 12:37 Imposter syndrome & finding authentic leadership 15:20 Picking the wrong market 18:24 Firing fast & setting high performance bars 20:12 Building cult-like community and emotional loyalty 22:13 Velocity vs delight in product 24:32 What she looks for in founders (turn-based velocity) 25:59 The business model wake-up call 27:27 Storytelling as a founding superpower 28:26 Hot take: consumer isn’t dead, it’s being reborn 31:50 AI-generated media, fanfic, and the next YouTube Check out the full library minds at libraryofminds.com/ Or create your own Delphi at delphi.ai!

We just raised $20M (Menlo, Sequoia, Felicis, Snowflake, Databricks) and launched Kai—the first superintelligent AI co-worker for customer success. It shouldn't take 100 people to serve 1,000 customers. Kai knows every customer, acts instantly, never drops the ball. Agency.inc fortune.com/2025/11/12/elias…

New short course on Building Applications with Vector Databases, taught by @pinecone’s @timt! At the heart of a vector database is the ability to store a collection of vectors and then query against that, meaning input a new vector and find similar ones. This is useful for many AI applications. In this course, you'll learn how to use vector databases to build: (i) Semantic Search: Create a text search tool that goes beyond keyword matching, and instead focuses on the meaning of content. (ii) RAG (retrieval augmented generation): Enhance your LLM output by incorporating context from sources the model wasn't trained on. (iii) Recommender System: Combine semantic search and RAG to recommend topics, and demonstrate it with a news article recommender. (iv) Hybrid Search: Build an application that finds items using both images and descriptive text -- by combining both sparse and dense vector representations of the data -- using an eCommerce dataset as an example. (v) Image Similarity: Use image vector embeddings to create an app to compare facial features, using a database of public figures to determine the likeness between them. (vi) Anomaly Detection: Build an anomaly detection app that identifies unusual patterns in network communication logs. I hope you’ll enjoy learning how to build all these types of applications! Please sign up here: deeplearning.ai/short-course…

We're delighted to announce that we crossed 10,000 @github stars🌟! github.com/neondatabase/neon

We are excited to announce the Anthology Fund, a $100M fund we created with our partners at @AnthropicAI to support the next generation of breakthrough companies. With funding from the Anthology Fund, we will back visionary founders using Anthropic’s cutting-edge AI to reshape industries. Join us in building the future of AI. Apply now: mnlo.vc/anthology-fund-appli… #AIInnovation #ALLINonAI Or reach out to our Anthology Fund team: @mmurph, @timt, @mejoff, @amytongwu, @deedydas, and @venkyganesan, who will work closely with President @DanielaAmodei, CPO @mikeyk, and the rest of the Anthropic team to support the most promising AI startups. You can learn more here: mnlo.vc/anthology-fund

So proud of @mavenclinic for today’s funding milestone at $1B🦄 valuation. I took a moment to reflect on @_KateRyder’s battle to build a category-defining company in women’s & family health. “Women’s health is too niche” is what some said. They were wrong. seq.vc/Maven_Medium

Elon believes a majority of AI workloads will be diffusion models. I’d pay close attention to Inception Labs, a team of Stanford professors who are doing foundational work here. In the history of computing, no single ML architecture has been dominant for more than a decade.

Neon is now GA 🎉🎉🎉

New $100M fund from Menlo in partnership with Anthropic — take a look if you’re building in this space! I’ll be joining demo days for fund companies and you’ll have a direct line to our team

Welcome @Y2Kandace, our new Director of GTM #Talent! She's building on our relationships with the top sales & marketing executives in tech, focusong on #SaaS, #infrastructure, & #cybersecurity. #GTM leaders should connect & follow. More from @jormont1978: bit.ly/KandaceGTM