Andreessen Horowitz

LLMs are quickly solving what we call "the messy inbox problem" —the overwhelming flood of unstructured data that slows down businesses across industries, from healthcare to freight. These AI models are automating top-of-funnel manual tasks, historically responsible for clogging operations, wasting countless hours, and creating bottlenecks in downstream processes. By synthesizing voice and text data from faxes, emails, PDFs, and call transcripts, and systematically extracting key information, LLMs are automating top-of-funnel manual workflows—emerging as a powerful wedge strategy for companies to streamline operations and gain a competitive edge. In his latest post, David Haber explores how AI applications, particularly those leveraging LLMs, are reshaping industries by owning the top of the data funnel, positioning startups to eventually displace legacy systems. Companies like Tennr, Heron Data, Happyrobot, and Eve are already capitalizing on this trend. Read more on how on how AI is transforming workflows and disrupting legacy systems: https://lnkd.in/gkAVzFwF

Congrats to the a16z Bio + Health team on their first-of-its-kind partnership with Eli Lilly and Company to support ambitious founders advancing biotech and healthcare innovation!

Now is the time for infrastructure independence, says Anjney Midha. Data centers, the 'new atomic unit of sovereignty,' will play a huge role in ensuring countries including the U.S. stay competitive in AI. In his big idea for 2025, Anj explores how nations are racing to secure compute, energy, and data—the key ingredients to lead in AI—or risk falling behind. From the rise of hypercenters to the challenges of compute deserts, Anjney examines how energy, data, and regulation shape sovereignty. He draws parallels to historical technological shifts and highlights opportunities for technical founders solving these complex, global infrastructure challenges. Link to the full video in comments.

The U.S. is building again, creating opportunities in robotics, manufacturing, and defense. Erin Price-Wright believes that in 2025 engineers with full-stack skills to bridge hardware and software are expected to be in demand, as industries integrate AI into physical systems. On the a16z Podcast, she explains why now is the time to invest in building supply chains and talent pipelines domestically—and how this shift could transform the U.S. economy. Watch or listen to the full episode: https://lnkd.in/gDENx6d6

Our team tested hundreds of AI apps in 2024, experimenting with everything from writing songs and creating podcasts, to automating away everyday hassles. So what were the uses that really stuck? Justine Moore, Olivia Moore and the a16z Consumer team, as well as friends of the firm including Dylan Field, Amjad Masad, Aravind Srinivas, Roxanne VARZA, Grimes, and Garry Tan shared their picks from a weird and wonderful year. Link to the full, interactive list in the comments. This content is provided for informational purposes only, and should not be relied upon as legal, business, investment, or tax advice. Please see https://lnkd.in/gZB38psi for additional important details.

Can the government regulate … math? Ben and Marc shared their concerns about the Biden administration’s approach to AI policy, and shared what they’d like to see instead, in this episode of “The Ben & Marc Show." For more, check out the latest episodes here: https://lnkd.in/eEcuCgxE 

Marc tells the complete and behind-the-scenes story of how Netscape was created – never told in its entirety, or accurately – in this episode of “The Ben & Marc Show.” From his early life to pivotal moments at the University of Illinois, where he co-developed Mosaic, he reflects on the fierce competition, legal battles, and ultimate rise of Netscape, from his perspective. Revisit this episode of “The Ben & Marc Show,” which also covers the implications of Netscape’s success, the importance of an open internet and more: https://lnkd.in/eEcuCgxE

AI is transforming how software companies price their products. As automation replaces human tasks, traditional per-seat pricing is becoming outdated. Instead, companies are adopting models that charge for results—like successful outcomes or usage—reflecting the real value AI delivers. While there’s no one-size-fits-all for AI pricing, Ivan Makarov, James da Costa and Equals write, patterns are emerging: AI-native companies like Decagon, Cursor, and ElevenLabs favor new models, while incumbents such as Zendesk and Notion layer AI onto existing products. Dive deeper into these shifts in this week’s Enterprise newsletter 👇

The future of AI in operations isn’t just about automating tasks—it’s about transforming internal work into scalable, flexible workflows. Kimberly Tan explains how AI is fulfilling RPA’s promise: https://lnkd.in/ePvGjr2b

“This is a nightmare scenario.” Marc and Ben discuss the escalating U.S.-China competition in AI and robotics, highlighting concerns about China’s dominance in hardware—particularly Chinese drone manufacturer DJI’s share of the global drone market. For more, catch up on “The Ben and Marc Show” at 👉 https://lnkd.in/eEcuCgxE