Rich Skrenta

Nathaniel Manning

While we haven't officially launched, can't help but be excited to see this great artcle in the @WSJ featuring LGND AI, Inc.(http://lgnd.io) and the opportunity for AI applied to earth observation data for all sorts of important uses. This is a huge and important data source that is vastly under represented in the current AI platform shift - and we aim to change that. Big stuff ahead! https://lnkd.in/ghd76mBB

While we haven't officially launched, can't help but be excited to see this great artcle in the @WSJ featuring LGND AI, Inc.(http://lgnd.io) and the opportunity for AI applied to earth observation data for all sorts of important uses. This is a huge and important data source that is vastly under represented in the current AI platform shift - and we aim to change that. Big stuff ahead! https://lnkd.in/ghd76mBB

Taylor Soper

Startup radar time! Meet another group of early stage Seattle-area startups: CaseGuild: Led by Vikas Rajvanshy, CaseGuild leverages AI to help legal teams wade through massive troves of evidence. GenSX: Led by Evan Boyle, GenSX is building a programming tool for building AI agents and workflows. GradPilot: Led by Nirmal Thacker, GradPilot gives students an "AI counselor" to help craft college essays. HA Arts: Led by Harshitha A., HA Arts blends generative AI and human creativity to produce commissioned artwork. Harte.io: Led by Christian Hammer, Harte aims to consolidate disparate software systems within a company’s tech stack into a unified model. Read more: https://lnkd.in/g_2CyBVP

Startup radar time! Meet another group of early stage Seattle-area startups: CaseGuild: Led by Vikas Rajvanshy, CaseGuild leverages AI to help legal teams wade through massive troves of evidence. GenSX: Led by Evan Boyle, GenSX is building a programming tool for building AI agents and workflows. GradPilot: Led by Nirmal Thacker, GradPilot gives students an "AI counselor" to help craft college essays. HA Arts: Led by Harshitha A., HA Arts blends generative AI and human creativity to produce commissioned artwork. Harte.io: Led by Christian Hammer, Harte aims to consolidate disparate software systems within a company’s tech stack into a unified model. Read more: https://lnkd.in/g_2CyBVP

Nick Grossman

Excited to share episode 5 of the Slow Hunch Podcast, with Zoe Weinberg, founder of ex/ante . Zoe makes a compelling case for why technology isn't neutral - it's purpose-built, and architectural choices matter enormously. We explored how the next wave of founders have the potential to build tech that enhances human agency rather than diminishing it. A key insight for me was that the tradeoff between user convenience and user control is not inevitable. We have the potential to build technology that's both magical to use AND preserves individual autonomy. Full episode here: https://lnkd.in/eaGc2sah

Excited to share episode 5 of the Slow Hunch Podcast, with Zoe Weinberg, founder of ex/ante . Zoe makes a compelling case for why technology isn't neutral - it's purpose-built, and architectural choices matter enormously. We explored how the next wave of founders have the potential to build tech that enhances human agency rather than diminishing it. A key insight for me was that the tradeoff between user convenience and user control is not inevitable. We have the potential to build technology that's both magical to use AND preserves individual autonomy. Full episode here: https://lnkd.in/eaGc2sah

Adam G.

⚠️ Founders - consider the below reasons to not use Forward Deployed Engineers (FDEs) to acquire your *first* customers. This signals (1) lack of PMF; (2) miscalculation b/w development and sales timeframes; and (3) mischaracterization of Palantir Technologies timing when they deployed their FDE model. 💡 At the early-stage, it's crucial to demonstrate ability to repeatedly acquire customers with limited resources - capital, team, & time - that supports the narrative of 'more funding will amplify my traction.' Bespoke solutions for one company demonstrates zero repeatability. These custom solutions will not carry over to other customers within the same cohort. 💡 AI accelerates engineering but sales, system integration, and stakeholder buy-ins are perpetually slow. This imbalance results in concentrating all your engineering resources into one company, ignoring other opportunities, and still not going live on an accelerated timeline. 💡 Palantir didn't start using FDEs until year 3 when they got their first *gov't* customer, not their first customer. Gotham was already built and had strong PMF. Gotham allowed Palantir to take GTM risk by using FDEs b/c if it didn't work, Gotham was humming in the background. TLDR: At the early-stage, repeatable customer acquisition is the holy grail. Don't let AI deceive you that it can accelerate human behavior like it has with development cycles. It C.A.N.N.O.T.

Astasia Myers

GPUs have gotten faster, and models have gotten larger. But storage is still stuck in the past. Modern AI workloads need instant access to huge datasets. Instead, teams waste time on slow retrieval, idle GPUs, and costly pipelines. Archil is changing this. It delivers object-storage scalability at block-storage speeds. The platform allows for seamless, high-performance access to massive datasets. By eliminating cold starts and accelerating throughput 30X, Archil enables teams to fully utilize their infrastructure and move faster on training, analytics, and AI deployment. Archil’s founder Hunter Leath brings rare technical depth and operating experience from building Amazon EFS and optimizing Netflix’s cloud performance. This is a team building the foundational layer that AI workloads desperately need. I’m thrilled to lead Archil’s seed at Felicis with Nancy Wang and support their mission to reinvent cloud storage for the AI era. https://lnkd.in/gWueXhzz

GPUs have gotten faster, and models have gotten larger. But storage is still stuck in the past. Modern AI workloads need instant access to huge datasets. Instead, teams waste time on slow retrieval, idle GPUs, and costly pipelines. Archil is changing this. It delivers object-storage scalability at block-storage speeds. The platform allows for seamless, high-performance access to massive datasets. By eliminating cold starts and accelerating throughput 30X, Archil enables teams to fully utilize their infrastructure and move faster on training, analytics, and AI deployment. Archil’s founder Hunter Leath brings rare technical depth and operating experience from building Amazon EFS and optimizing Netflix’s cloud performance. This is a team building the foundational layer that AI workloads desperately need. I’m thrilled to lead Archil’s seed at Felicis with Nancy Wang and support their mission to reinvent cloud storage for the AI era. https://lnkd.in/gWueXhzz

Noah Greenberg

NVIDIA just hired WSJ's tech editor as their new managing editor. RH's Editor in Chief is the former EIC at Architectural Digest Robinhood's Editor in Chief is the former EIC at The Outline and BDG The Trade Desk's Editor in Chief is the former EIC at AdWeek Jerry's Lead Data Journalist is former Bloomberg/Mother Jones Data Reporter Mastercard's VP of Editorial Content is former cnet/wsj reporter CARFAX's EIC is the former editor at Consumer Reports IBM's Editorial Lead is a former AFP reporter BlackRock's VP Content is former editor @ Fortune SoFi's Managing Editor is former cnet managing editor Resy/Amex's Managing Editor is former SF Chronicle Wine Editor Redfin's Chief Economist came over from Boston Fed ... and so many more These companies are not replacing journalists with AI. They are hiring great talent and putting them to work on great coverage. A real reason to be excited about the reporting coming out of these orgs you would not traditionally think of as media companies. And a reason to be excited about job prospects for talented editorial folks. Slowly curating the best of the best of the output from this effort - if your team is following suit, or you're looking for roles in this space... say hi//follow along. Also - a follow up conversation here with examples of the work these orgs are doing (and tradeoffs they face) - https://lnkd.in/egkmumhM

Tim Frick

We just crossed the 100th GitHub issue threshold in our work on the W3C's Web Sustainability Guidelines (WSGs for short, because we love acronyms). Recommendations in the spec are evolving quickly based on an incredibly passionate group of smart volunteer technologists, designers, developers, content strategists, and business leaders. Next version will come out in September for horizontal review as we barrel toward our goal of publishing first a W3C Note next April and, eventually, a W3C Statement. In the meantime, here's the latest: https://lnkd.in/gU5CDRXx

We just crossed the 100th GitHub issue threshold in our work on the W3C's Web Sustainability Guidelines (WSGs for short, because we love acronyms). Recommendations in the spec are evolving quickly based on an incredibly passionate group of smart volunteer technologists, designers, developers, content strategists, and business leaders. Next version will come out in September for horizontal review as we barrel toward our goal of publishing first a W3C Note next April and, eventually, a W3C Statement. In the meantime, here's the latest: https://lnkd.in/gU5CDRXx

Michael Spencer

Amid Meta's deal for Scale AI and its new Superintelligence lab, what do the headlines miss? I have some concrete ideas on this: https://lnkd.in/g6W_myfi Meta has agreed to invest 14ドル.8 billion for a 49% stake in Scale AI, marking one of the largest AI-related investments to date and Meta’s biggest deal since its acquisition of WhatsApp in 2014. But what isn't being told in the PR on the deal? Meta will acquire a 49% minority stake in Scale AI, rather than a full acquisition. This structure is designed to avoid triggering further antitrust scrutiny, as Meta is already engaged in legal battles with regulators over previous acquisitions. Scale AI’s CEO, Alexandr Wang, will assume a prominent role at Meta, leading a new "superintelligence" lab focused on advancing cutting-edge AI research. Wang will remain CEO of Scale AI, which will continue to operate independently. But is that what he will really be working on?

Amid Meta's deal for Scale AI and its new Superintelligence lab, what do the headlines miss? I have some concrete ideas on this: https://lnkd.in/g6W_myfi Meta has agreed to invest 14ドル.8 billion for a 49% stake in Scale AI, marking one of the largest AI-related investments to date and Meta’s biggest deal since its acquisition of WhatsApp in 2014. But what isn't being told in the PR on the deal? Meta will acquire a 49% minority stake in Scale AI, rather than a full acquisition. This structure is designed to avoid triggering further antitrust scrutiny, as Meta is already engaged in legal battles with regulators over previous acquisitions. Scale AI’s CEO, Alexandr Wang, will assume a prominent role at Meta, leading a new "superintelligence" lab focused on advancing cutting-edge AI research. Wang will remain CEO of Scale AI, which will continue to operate independently. But is that what he will really be working on?