Podcast appearances and mentions of Martin Casado

AI's breakout moment is here - but where is the real value accruing, and what's just hype?Recorded live at a16z's annual LP Summit, General Partners Erik Torenberg, Martin Casado, and Sarah Wang unpack the current state of play in AI. From the myth of the GPT wrapper to the rapid rise of apps like Cursor, the conversation explores where defensibility is emerging, how platform shifts mirror (and diverge from) past tech cycles, and why the zero-sum mindset falls short in today's AI landscape.They also dig into the innovator's dilemma facing SaaS incumbents, the rise of brand moats, the surprising role of prosumer adoption, and what it takes to pick true category leaders in a market defined by both exponential growth - and accelerated wipeouts.Resources: Find Martin on X: https://x.com/martin_casadoFind Sarah on X: https://x.com/sarahdingwangStay Updated: Let us know what you think: https://ratethispodcast.com/a16zFind a16z on Twitter: https://twitter.com/a16zFind a16z on LinkedIn: https://www.linkedin.com/company/a16zSubscribe on your favorite podcast app: https://a16z.simplecast.com/Follow our host: https://x.com/eriktorenbergPlease note that the content here is for informational purposes only; should NOT be taken as legal, business, tax, or investment advice or be used to evaluate any investment or security; and is not directed at any investors or potential investors in any a16z fund. a16z and its affiliates may maintain investments in the companies discussed. For more details please see a16z.com/disclosures.

Martin Casado is a General Partner at Andreessen Horowitz (a16z), where he focuses on AI and infrastructure investments. He previously co-founded Nicira which was acquired by VMware for $1.2 billion in 2012.In this episode of World of DaaS, Martin and Auren discuss:Economics of open source AIChinese AI innovation with DeepSeekModel collapse and data moatsRegulatory challenges in AILooking for more tech, data and venture capital intel? Head to worldofdaas.com for our podcast, newsletter and events, and follow us on X @worldofdaas.You can find Auren Hoffman on X at @auren and Martin Casado on X at @martin_casado.Editing and post-production work for this episode was provided by The Podcast Consultant (https://thepodcastconsultant.com)

Today we're sharing a conversation between Martin Casado, general partner at Andreessen Horowitz and Nathan Labenz, AI scout, which originally aired on The Cognitive Revolution podcast from Turpentine. Their discussion explores AI systems complexity and debates whether AI development will lead to AGI. The conversation covers model scaling, biological AI, driverless cars, and AI safety concerns. — 

Cerebral Valley is tomorrow! I've been listening to old interviews, brainstorming with Claude and ChatGPT, and talking to investors to prep for my conversations with Dario Amodei, Martin Casado, and Alexandr Wang. We'll be sharing those conversations here in the newsletter. Expect video highlights on our social media feeds, a detailed rundown of the biggest moments in the newsletter Thursday, and full-length conversations on our YouTube channel.To satiate your AI appetites until then, give a listen to the latest edition of the Cerebral Valley Podcast with my friends and co-hosts Max Child and James Wilsterman. You've listened to us assess whether startups are underrated or overrated and make our draft picks. Now we're looking to the future. We asked Claude and ChatGPT o1 to make some predictions about what will happen in artificial intelligence over the next year. And then we took the over or under on those predictions.Brought to you by BrexBrex knows runway is everything for venture-backed startups, so they built a banking solution that helps them take every dollar further. Unlike traditional banking solutions, Brex has no minimums and gives startups access to 20x the standard FDIC protection via program banks.Plus, startups can earn industry-leading yield from their first dollar — while being able to access their funds anytime. If you want to make sure your portfolio companies have a place to save, spend, and grow their capital, check out Brex here.Chapters* 00:00 — Introduction to AI Predictions* 02:48 — Exploring Predictions for AI in 2025* 06:06 — AI Regulation in Healthcare* 08:53 — Self-Driving Cars and Tesla's Future* 12:04 — AI in News Media* 14:55 — AI-Generated Films and Entertainment* 17:53 — Anthropic's Predictions and AI Co-Processors* 20:59 — AI in Pharmaceutical Development* 24:13 — International AI Treaties and Regulations* 26:47 — Comparing AI Models: ChatGPT vs. Claude* 30:06 — Future of AI and Human Systems* 32:46 — Conclusion and Reflections on AI Predictions Get full access to Newcomer at www.newcomer.co/subscribe

Cerebral Valley is tomorrow! I've been listening to old interviews, brainstorming with Claude and ChatGPT, and talking to investors to prep for my conversations with Dario Amodei, Martin Casado, and Alexandr Wang. We'll be sharing those conversations here in the newsletter. Expect video highlights on our social media feeds, a detailed rundown of the biggest moments in the newsletter Thursday, and full-length conversations on our YouTube channel.To satiate your AI appetites until then, give a listen to the latest edition of the Cerebral Valley Podcast with my friends and co-hosts Max Child and James Wilsterman. You've listened to us assess whether startups are underrated or overrated and make our draft picks. Now we're looking to the future. We asked Claude and ChatGPT o1 to make some predictions about what will happen in artificial intelligence over the next year. And then we took the over or under on those predictions.Brought to you by BrexBrex knows runway is everything for venture-backed startups, so they built a banking solution that helps them take every dollar further. Unlike traditional banking solutions, Brex has no minimums and gives startups access to 20x the standard FDIC protection via program banks.Plus, startups can earn industry-leading yield from their first dollar — while being able to access their funds anytime. If you want to make sure your portfolio companies have a place to save, spend, and grow their capital, check out Brex here.Chapters* 00:00 — Introduction to AI Predictions* 02:48 — Exploring Predictions for AI in 2025* 06:06 — AI Regulation in Healthcare* 08:53 — Self-Driving Cars and Tesla's Future* 12:04 — AI in News Media* 14:55 — AI-Generated Films and Entertainment* 17:53 — Anthropic's Predictions and AI Co-Processors* 20:59 — AI in Pharmaceutical Development* 24:13 — International AI Treaties and Regulations* 26:47 — Comparing AI Models: ChatGPT vs. Claude* 30:06 — Future of AI and Human Systems* 32:46 — Conclusion and Reflections on AI Predictions Get full access to Newcomer at www.newcomer.co/subscribe

Martin Casado, general partner at venture-capital firm Andreessen Horowitz, says concrete risks from the artificial intelligence boom haven't materialized. Casado spoke with WSJ global tech editor Jason Dean about the U.S. government's stance on AI policy and the outlook for investing in the space at WSJ Tech Live. Plus, scientists and engineers are working to build more efficient electric motors using a technology pioneered by Benjamin Franklin. Zoe Thomas hosts.  Sign up for the WSJ's free Technology newsletter.  Learn more about your ad choices. Visit megaphone.fm/adchoices

Deepfakes—AI-generated fake videos and voices—have become a widespread concern across politics, social media, and more. As they become easier to create, the threat grows. But so do the tools to detect them.In this episode, Vijay Balasubramaniyan, cofounder and CEO of Pindrop, joins a16z's Martin Casado to discuss how deepfakes work, how easily they can be made, and what defenses we have. They'll also explore the role of policy and regulation in this rapidly changing space.Have we lost control of the truth? Listen to find out.Resources:Find Vijay on Twitter: https://x.com/vijay_voiceFind Martin on Twitter: https://x.com/martin_casadoStay Updated: Let us know what you think: https://ratethispodcast.com/a16zFind a16z on Twitter: https://twitter.com/a16zFind a16z on LinkedIn: https://www.linkedin.com/company/a16zSubscribe on your favorite podcast app: https://a16z.simplecast.com/Follow our host: https://twitter.com/stephsmithioPlease note that the content here is for informational purposes only; should NOT be taken as legal, business, tax, or investment advice or be used to evaluate any investment or security; and is not directed at any investors or potential investors in any a16z fund. a16z and its affiliates may maintain investments in the companies discussed. For more details please see a16z.com/disclosures.

Timestamps:1:57 Interview starts / Will there be an AI monopoly?5:33 The Bitter Lesson19:30 Government AI Scaling Projects25:09 AI Agents Versus Information Theory34:25 Little Tech and PoliticsFind Martin:https://a16z.com/author/martin-casado/https://x.com/martin_casadoMentioned in the Episode:William Perry and Martin's course at Stanford: https://web.stanford.edu/class/msande91si/slides/msande91si_course_information.pdfUS Senate AI Roadmap: https://www.politico.com/f/?id=0000018f-79a9-d62d-ab9f-f9af975d0000Entropy bounds in Information Theory: https://en.wikipedia.org/wiki/Entropy_(information_theory)Martin and Ion Stoica on Little Tech and Open Source: https://www.economist.com/by-invitation/2024/07/29/keep-the-code-behind-ai-open-say-two-entrepreneurs This is a public episode. If you'd like to discuss this with other subscribers or get access to bonus episodes, visit www.fromthenew.world/subscribe

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My guest today is Martin Casado. Martin is a partner at Andreessen Horowitz and first joined me on Invest Like the Best in 2022. So much has changed since then, and it was awesome to have Martin back to discuss all of the different implications of this AI revolution. Before joining a16z, Martin pioneered software-defined networking and co-founded Nicira, which was bought by VMware for $1.3 billion in 2012. He has studied, built, and invested in digital infrastructure his whole career which has primed him to go in-depth in this interview on the immense opportunities and challenges AI presents among creativity, policy-making, agentic systems, real-world data structures, and beyond. Please enjoy this conversation with Martin Casado.  Listen to Founders Podcast For the full show notes, transcript, and links to mentioned content, check out the episode page here. ----- This episode is brought to you by Tegus, where we're changing the game in investment research. Step away from outdated, inefficient methods and into the future with our platform, proudly hosting over 100,000 transcripts – with over 25,000 transcripts added just this year alone. Our platform grows eight times faster and adds twice as much monthly content as our competitors, putting us at the forefront of the industry. Plus, with 75% of private market transcripts available exclusively on Tegus, we offer insights you simply can't find elsewhere. See the difference a vast, quality-driven transcript library makes. Unlock your free trial at tegus.com/patrick. ----- Invest Like the Best is a property of Colossus, LLC. For more episodes of Invest Like the Best, visit joincolossus.com/episodes.  Past guests include Tobi Lutke, Kevin Systrom, Mike Krieger, John Collison, Kat Cole, Marc Andreessen, Matthew Ball, Bill Gurley, Anu Hariharan, Ben Thompson, and many more. Stay up to date on all our podcasts by signing up to Colossus Weekly, our quick dive every Sunday highlighting the top business and investing concepts from our podcasts and the best of what we read that week. Sign up here. Follow us on Twitter: @patrick_oshag | @JoinColossus Editing and post-production work for this episode was provided by The Podcast Consultant (https://thepodcastconsultant.com). Show Notes: (00:00:00) Welcome to Invest Like the Best (00:01:48) The Future of AI and Creativity (00:03:11) Economic Implications of AI (00:04:33) AI's Impact on Content Creation (00:08:21) Challenges in AI and Robotics (00:12:16) Human Data and AI Training (00:20:30) Investing in AI and Robotics (00:26:00) Defensibility and Competition in AI (00:33:22) Regulatory Considerations (00:35:26) Internet Era Parallels and Security Concerns (00:40:25) Open Source vs. Closed Source in Tech (00:43:45) Market Annealing and Category Creation (00:46:13) Data and Hardware Innovations in AI (00:55:55) Agents and the Future of AI

Dive into the profound discussion on AI expectations and the future with Martin Casado, General Partner at Andreessen Horowitz, as we unpack the complexity of AI systems and their potential impact on the world. Explore the differing viewpoints on AI's epistemics, possible regulatory standards, and the art of predicting AI advancements. Gain insights into the actionable outcomes of this dialogue and the significance of understanding AI before shaping policies. Join us for this episode of the Cognitive Revolution to contemplate AI's trajectory and what it might mean for humanity. Apply to join over 400 founders and execs in the Turpentine Network: https://hmplogxqz0y.typeform.com/to/JCkphVqj RECOMMENDED PODCAST: Byrne Hobart, the writer of The Diff, is revered in Silicon Valley. You can get an hour with him each week. See for yourself how his thinking can upgrade yours. Spotify: https://open.spotify.com/show/6rANlV54GCARLgMOtpkzKt Apple: https://podcasts.apple.com/us/podcast/the-riff-with-byrne-hobart-and-erik-torenberg/id1716646486 SPONSORS: Oracle Cloud Infrastructure (OCI) is a single platform for your infrastructure, database, application development, and AI needs. OCI has four to eight times the bandwidth of other clouds; offers one consistent price, and nobody does data better than Oracle. If you want to do more and spend less, take a free test drive of OCI at https://oracle.com/cognitive The Brave search API can be used to assemble a data set to train your AI models and help with retrieval augmentation at the time of inference. All while remaining affordable with developer first pricing, integrating the Brave search API into your workflow translates to more ethical data sourcing and more human representative data sets. Try the Brave search API for free for up to 2000 queries per month at https://bit.ly/BraveTCR Omneky is an omnichannel creative generation platform that lets you launch hundreds of thousands of ad iterations that actually work customized across all platforms, with a click of a button. Omneky combines generative AI and real-time advertising data. Mention "Cog Rev" for 10% off https://www.omneky.com/ Head to Squad to access global engineering without the headache and at a fraction of the cost: head to https://choosesquad.com/ and mention “Turpentine” to skip the waitlist. CHAPTERS: (00:00:00) About the Show (00:03:18) AI progress (00:05:20) Threshold effects (00:12:30) Heavy-tailed universe (00:14:53) LLMs are not very good at unique tasks (00:26:27) Sponsors: Oracle | Brave (00:28:36) Understanding meaning (00:31:44) How do LLMs work? (Part 1) (00:36:25) Sponsors: Omneky | Squad (00:38:12) How do LLMs work? (Part 2) (00:44:01) Post-training (00:51:09) Simulation (01:04:06) Regulation (01:08:53) What makes AI a paradigm shift (01:11:51) Compute limits (01:20:07) Sleeper agents (01:23:16) Surface area of models (01:25:49) AI regulation (01:27:35) AI in medicine (01:29:56) AGI, superintelligence (01:37:04) Competition in the foundation model space (01:40:57) The scaling laws (01:44:31) The AGI convergence (01:45:35) Bets on the future of AI (01:48:20) Outro

Milin Desai is the CEO at Sentry, an application monitoring tool for developers. Sentry has recently passed two key milestones: 100K customers and over $100M in ARR. Before Sentry, Milin was a GM at VMware and scaled their cloud networking into a billion-dollar business. Prior to stepping into leadership roles, Milin was a PM at Riverbed and a software engineer at Veritas. — In today's episode, we discuss: The key ingredients of Sentry's success Sentry's developer-centric approach Lessons on pricing, packaging, and product from VMware Being an external CEO at a startup Forging successful relationships with founders — Referenced: Building for the Fortune 500,000: https://blog.sentry.io/building-for-the-fortune-500-000/ Carl Eschenbach: https://www.linkedin.com/in/carl-eschenbach-980543/ Chris Jennings: https://www.linkedin.com/in/chriskjennings/ David Cramer: https://www.linkedin.com/in/dmcramer/ FRC's product market fit framework: https://pmf.firstround.com/ Martin Casado: https://www.linkedin.com/in/martincasado/ Pat Gelsinger: https://www.linkedin.com/in/patgelsinger/ Raghu Raghuram: https://www.linkedin.com/in/raghuraghuram/ Riverbed: https://www.riverbed.com/ Sentry: https://sentry.io/ Todd Bazakas: https://www.linkedin.com/in/todd-bazakas-b5a2533/ Veritas: https://www.veritas.com/ VMware: https://www.vmware.com/ — Where to find Milin Desai: LinkedIn: https://www.linkedin.com/in/milin-desai-464757/ Twitter/X: https://twitter.com/virtualmilin — Where to find Brett Berson: LinkedIn: https://www.linkedin.com/in/brett-berson-9986094/ Twitter/X: https://twitter.com/brettberson — Where to find First Round Capital: Website: https://firstround.com/ First Round Review: https://review.firstround.com/ Twitter/X: https://twitter.com/firstround YouTube: https://www.youtube.com/@FirstRoundCapital This podcast on all platforms: https://review.firstround.com/podcast — Timestamps: (00:00) Introduction (03:03) Joining Sentry as an external CEO (06:27) The CEO/founder relationship (09:37) Lessons from VMware (13:04) What PMs did differently at VMware (18:04) Becoming the need, not the want (20:53) Scaling Sentry (23:07) Building for the “Fortune 500,000” (27:02) Open versus closed source product (30:43) The key ingredients to Sentry's success (36:21) How Milin updated his playbook at Sentry (38:49) Focus on packaging, not pricing (40:29) “Build for the many, not the few” (41:53) Sentry's B2D model (45:10) The second product mindset (51:03) Contrarian take on building for enterprise (52:50) Several people who influenced Milin

A reminder for new readers. That Was The Week collects the best writing on critical issues in tech, startups, and venture capital. I selected the articles because they are of interest. The selections often include things I entirely disagree with. But they express common opinions, or they provoke me to think. The articles are only snippets. Click on the headline to go to the original. I express my point of view in the editorial and the weekly video below.Thanks To This Week's Contributors: @TEDchris, @LilyWhitsitt, @RocketToLulu, @saeedtaji, @geneteare, @EricNewcomer, @jeffbeckervc, @jasonlk, @elonmusk, @benshapiro, @StevenLevy, @apple, @bheater, @bmw, @Growcoot, @illscience, @venturetwins, @omooretweets, @conniechanContents* Editorial: Civility and Civilization* Essays of the Week* US Seed Investment Actually Held Up Pretty Well For The Past 2 Years. Here's What That Means For 2024* Lower Valuations, Higher Bar: What It's Like To Raise A Seed Round In 2024 * Unicorns & Inevitabilities* Sequoia, Founders Fund, USV, Elad Gil & Benchmark Top Venture Manager Survey* Why 2024 May Be Tougher on Venture Capital Than 2023* Video of the Week* The Mac at 40* AI of the Week* BMW will deploy Figure's humanoid robot at South Carolina plant* Google's New AI Video Generator Looks Incredible* OpenAI's Sam Altman seeks funds for AI chip factories as demands surge* The Future of Prosumer: The Rise of “AI Native” Workflows* Andreessen Horowitz's Connie Chan to Leave as Consumer Focus Shifts to AI* OpenAI Is a (Relative) Steal* News Of the Week* Ted fellows resign from organisation after Bill Ackman named as speaker* Tesla's Slowdown Disqualifies It From ‘Magnificent Seven' Group* TikTok's Testing 30 Minute Uploads as It Looks To Expand Its Content Options* Instagram to scan under-18s' messages to protect against ‘inappropriate images'* Tiger Global Investor Relations Staff Depart After Fundraising Challenges* Worldcoin hints at new Orb for a friendlier iris-scanning experience* Startup of the Week* Loyalty Startup Bilt Rewards Hits $3.1B Valuation After $200M Round* X of the Week* Elon Musk visits Auschwitz with Ben ShapiroEditorialThere is a lot to digest in this week's newsletter. Gené Teare's two essays on Seed investing head up the Essays of the Week, along with Jeff Becker talking about unicorns and inevitabilities, Eric Newcomer on who are the top investors and Jason Lemkin on the reasons 2024 might be harder for Venture Capital than 2023.But my attention was distracted from venture capital by a Guardian article announcing (triumphantly, I might add) that several TED fellows had resigned from the organization due to an invite to Bill Ackman to speak at this year's TED event in Vancouver.“Lucianne Walkowicz and Saeed Taji Farouky accuse Ted of taking anti-Palestinian stand over controversial billionaire's inclusion”It seems Ackman is not alone. They also object to Bari Weiss being invited. The leavers are also not alone; up to 30 others have signed a “solidarity” letter.The accusations echo much of the discussion around the medieval assassination of Jews on 7 October and Israel's efforts to defeat Hamas in the aftermath. Because these speakers are against anti-Semitism and so supportive of Israel's war against Hamas, they are accused of the ridiculous claim of supporting “Genocide” against Palestinians.“We refuse for our work and identities to be exploited to promote the Ted brand while the organisation and its speakers generate income and advance their careers through dehumanising Palestinians and justifying their genocide,” the pair said.It probably will not surprise readers of this newsletter that I applaud TED curators Chris Anderson and Lily James Olds for not backing down on the invitations. Whatever one believes about the current conflict in Israel, it is clear that banning opponents of anti-Semitism because of their stance is not a solution to anything. I believe the cause of fighting anti-Semitism should be close to the heart of any progressive person. It is not anti-Palestinian to support Jews against being slaughtered in the street, to oppose anti-Semitism, or to condemn Hamas as anti-Jewish murderers. Supporting Jews against slaughter by Hamas is not incompatible with supporting Palestinians. The Guardian reported that Ackman responded to the resignations with a statement:“I stand unapologetically with Israel and against antisemitism and terrorism, while strongly supporting the Palestinian people. Attempts to cancel speech and eliminate the free and respectful exchange of ideas among people with differing views are driving much of the divisiveness that plagues our nation. Truth, wisdom and ultimately peace are the result of the free exchange of ideas and debate, precisely what Ted is all about. It is sad that this is not more widely understood,”Unsurprisingly, one of the resigners, Farouky, told the Guardian he did not regard the issue as freedom of speech. It clearly IS about freedom of speech. Speech only needs protecting when opinions are wide apart and strongly held.For example, here are my views on the actual issues:These are trying times. Over 25,000 deaths in Gaza are hard to comprehend. And I certainly cannot. But I can understand that Jews have to defend themselves. And I can understand that progressive thinkers MUST stand up to anti-Semitism, whatever form it takes.In case there is doubt about my support for Muslim victims of racism, my book Under Seige is about the attacks on Muslims in the UK between 1961 and 1981. It starts with recognizing that racism targets differences and that Jews and Muslims are both targets. Indeed, the very ghettoes that Pakistani and Bengali immigrants were being attacked in had earlier, in the 1930s, been inhabited by Jewish settlers fleeing pogroms. I am not Jewish, and I am not Muslim. But I will always be on both of their sides when they are attacked for their ethnic and racial origin.In Israel, Jews were killed for being Jews. Palestinians are being killed because Hamas is hiding in their cities and buildings. I do not consider Israel's response to be racist against Palestinians. I consider it reasonable in the context of 7 October. I consider that Hamas has done this to Palestinians and probably wanted that outcome. I am sad that Hamas has done this for the Palestinian victims. But I do not doubt that Hamas is to blame.My views may anger you. But do you want me banned or silenced?My title this week is Civility and Civilization. The TED events bring both to the fore. Like those I write here, opinions are there to be disagreed with, debated, and interrogated. Civilized behavior requires dialogue and civility within the dialogue. I certainly understand opinions I disagree with, and far from banning them or walking away so that I do not have to hear them, I want to hear them. We all should.This is a different editorial than usual. I hope the humanity of refusing to forget 7 October and the determination to preserve the view that fighting anti-Semitism is a non-negotiable minimum requirement of civilization are grasped. By the same token, Islamaphobia must be fought. But in Israel, there is no Islamophobia at work. Jews are simply reacting to an atrocity. They are right to blame Hamas.Essays of the WeekUS Seed Investment Actually Held Up Pretty Well For The Past 2 Years. Here's What That Means For 2024Gené Teare, January 24, 2024, @geneteareEditor's note: This is the first in a two-part series on the state of seed startup investing at the start of 2024. Check back tomorrow for Part 2.Despite a broad pullback in global startup investment over the past two years, investors say the U.S. seed funding environment was the most vibrant compared to other funding stages during the downturn.In fact, U.S. seed funding in 2022 grew by close to 10% in terms of dollars invested, in contrast to a downturn at all other funding stages. In 2023, U.S. seed funding fell 31% — a significant proportion — but still less than other funding stages year over year, an analysis of Crunchbase data shows. (It's also worth noting that those other stages had already experienced year-over-year declines in 2022.)In the current startup funding market, “we're seeing a lot more great talent excited about starting things,” said Renata Quintini, co-founder of Renegade Partners, a Bay Area-based investment firm that focuses on Series A companies and is therefore close to the seed ecosystem.Other investors share that enthusiasm. “Valuations are coming down, more talent is available in the market,” said Michael Cardamone of New York-based seed investor Forum Ventures. “A lot of these companies at seed and Series A are going to scale into what will likely be the next bull market.”Seed trends over the decadeSeed as an asset class, not surprisingly, has grown in the U.S. over the past decade. In 2014 less than $5 billion was invested at seed. At the market peak in 2022, seed investment was more than $16 billion, although it fell to $11.5 billion in 2023.Despite the downturn, seed funding in 2023 was still $2 billion to $3 billion higher in the U.S. than in the pre-pandemic years of 2019 and 2020.Higher bar, pricier rounds, better valuedBut in a tougher market, seed investors are being more selective about which companies they fund.“We're being far more disciplined and patient knowing how hard it is for these companies to get to Series A and beyond,” said Jenny Lefcourt, a general partner at Bay Area-based seed investor Freestyle Capital. “Our bar for conviction is higher than it had been in the heyday where everything was getting funded.”In the slower funding environment, the firm has been investing later at the seed stage, “gravitating toward ‘seed plus' or ‘A minus' — pick your favorite term for it — because I feel like I get to see more risk mitigated. I get to see more data,” she said.Freestyle seeks to have ownership of around 12% to 15% in the companies it backs. “The reason is because of our model,” Lefcourt said. “We are low-volume, high-conviction investors.”And because the firm invests in companies that are pre-Series A, “our reality has been that our valuations have actually been higher in this market, which is not what we would have predicted.“But the data we've seen is, we're not alone in that,” she said.…MoreLower Valuations, Higher Bar: What It's Like To Raise A Seed Round In 2024 Gené Teare, January 25, 2024, @geneteareEditor's note: This is the second in a two-part series on the state of seed startup investing at the start of 2024. Read Part 1, which looked at seed funding trends over the past decade and the median time period between seed and Series A funding, here.Seed funding to startups has grown into its own asset class over the past decade, with round sizes trending larger, and a bigger pool of investors backing these nascent startups. But in the aftermath of 2021's venture funding heyday and subsequent pullback, investors say that while seed funding has held up better than other startup investment stages, these very young startups will see lower valuations and must now clear a much higher bar to get backing.More companies raised seed funding above $1 million in 2021. Those companies — which raised during a record-smashing year for venture funding — are saddled with valuations that could be too high for this current market — even at seed. Many of those startups have been forced to cut costs to extend their runways, and face a tougher sales environment.“You could then be sacrificing growth, which is one of the main levers that Series A investors are looking for,” said Michael Cardamone of New York-based seed investor Forum Ventures.2021 after effectsIn 2021 it was “grow, grow, grow, grow,” said Jenny Lefcourt, a general partner at Bay Area-based seed investor Freestyle Capital. “It's embarrassing to look back on, but that was the game being played.”Investors got sloppy during the boom times, she said. “I think a lot of VCs were thrilled to back you, and then say, ‘we'll figure it out.' ”“The reality is that almost anything that was done then — call it 2021 — was the wrong price,” she said.This led to down rounds, even at seed, though those are generally not viewed negatively like they were in the past, she said.In fact, “when our companies get their down rounds done, it's a sign of it's a good business. It just had the wrong price on it,” she said.While the bar is higher to raise funding these days, “I think it's so much better for a company who gets to start in this environment,” Lefcourt said.Down rounds can actually be a sign of conviction, she said. “None of us would do all the heavy lifting to not only give the company more capital, but recap it, which takes a lot. It's a heavy lift — none of us would do that if we weren't super jazzed about the company. The lazier approach, the easier approach, is to just put it on the note, keep it flat, and be done,” she said.Renata Quintini, co-founder of Renegade Partners, a Bay Area-based investment firm that focuses on Series A companies, is hearing of “more ‘pay-to-play' these days and it's starting to get ugly.” This happens when new investors wipe out the prior investors, and anyone seeking equity needs to pony up into the new funding round.Median and averages climbNonetheless, “seed round valuations haven't dropped a ton from even the peak,” according to Forum Ventures' Cardamone. But, “the bar to raise a seed [round] is a lot higher.”“Most first-time founders especially, and the vast majority of founders generally — they have to get significant traction to be able to raise that same round they used to be able to raise. And a lot fewer of those rounds are happening,” he said.“A priced seed round of $3 million at $15 million [pre-money] is still happening, but you might have to be at $500,000 ARR, to raise that round now. Whereas in 2021, it was the norm to raise that round pre-revenue,” he said.Series A fundings have gotten harder as “companies are going out and raising three seed rounds,” said Cardamone.Based on an analysis of Crunchbase data, median and average seed round sizes in the U.S. have climbed through the past decade.In 2023, median and average raises are not far from the peak of 2022, Crunchbase data shows, and were well above pre-pandemic levels. (However, this will shift downward somewhat as the long tail of seed fundings are retroactively added to the Crunchbase database.)Seed rounds got larger“If I have conviction, we may need them to have more money, cause we know it's going to take them longer to reach the milestones that are now higher,” said Lefcourt.Per an analysis of Crunchbase data, larger seed rounds — those $1 million and above — have increased through the decade.The amount of funding to seed-stage companies below $1 million hasn't budged much, and is a fraction of what it was earlier in the decade.Seed below $1 million in 2014 represented around 25% of all seed funding.That has come down as a proportion every year since then.And as of 2021 that proportion has dipped below 10% for the first time, ranging from 5% to 7% of all seed dollars invested in the U.S. since then.Earlier in the past decade, the number of seed deals in rounds below $1 million outpaced those rounds at $1 million and above significantly.But 2021 was once again a pivotal year. That's when $1 million and above seed rounds outpaced smaller seed for the first time.In 2023, they are neck and neck in count. (That might shift as the long tail of seed rounds are added to the Crunchbase database long after they close.)What this all shows is that seed has become an increasingly significant and elongated phase in a company's early life cycle, where companies are raising multiple million-dollar seed rounds. And as of late, more companies than ever before are wading in the seed pool.What does this mean for the seed funding market in 2024?…MoreUnicorns & InevitabilitiesUp and to the right, or not so much?JEFF BECKER, JAN 22, 2024TLDR: Go read Aileen Lee's update to the Unicorn Club… and a few inevitabilities.Did anyone catch Aileen Lee & Allegra Simon's Welcome Back to the Unicorn Club, 10 Years Later?If not, go read it. That's your MMM.If you did read it, you can't help but wonder if the tech sector isn't going to resemble the public markets over time. Ups and downs, but consistently up and to the right over a long enough period.After all, we are creating leverage in ways we've never seen before.And for unicorns, that meant 14X growth over a 10-year period.Could you imagine another 14 or even 10X from here? That would be stratospheric, from ~500 to ~5,000 unicorns? What if the exit sizes did too? $5B, $10B, $50B?Crazy to think, but hardly impossible. After all, we've already seen near-centicorns like Uber's IPO at $75B in 2019.The interesting part about that thought exercise though is not the crazy zero interest rate IPO's, but the fact that entry valuations didn't and don't move nearly as fast as top end outcomes because of the time horizon to realizing them.For example, Airbnb raised $20K from Y Combinator for 6%, then they took another $600K for 20% in their seed.That was 2009. The idea of an IPO for $47B just 11 years later in 2020 probably wasn't even a consideration. Paul Graham and the YC team would've had to believe Airbnb's IPO could compete with AT&T, General Motors, and Visa.Insane.Fast forward, that $333,333 valuation at YC has moved to $1.78m (125K for 7%), and they'll stack another 2.6% ownership on average from their $375K MFN with the average YC company raising seed at a $14.4m cap instead of Airbnb's $3m.That's a ~5X increase in valuation at pre-seed & seed for a 47X increase in IPO size if you were modeling $1B outcomes into your VC fund model in 2009.I'm not saying that will continue. There are counterforces of course.* Margins are way too high. The fact that software margins have persisted at 80% or more is just craziness. Companies will start to use price more aggressively to compete for market share as cheap AI tools enter the market and try to unseat them. This compression will change the value of discounted cash flow models.* Pricing models need to change. One way to reduce sticker price and maintain some semblance of healthy long-term margins is to pay a smaller implementation fee, but incur ongoing services & upgrade costs. This is a more traditional pricing model, and creative economics that leverage this kind of thinking run rampant in the titans of tech. It's a game of deeper roots, higher switching costs, and long-term contracts. With API calls and data usage more prevalent, we'll also see more pay-per-use models, the same way we buy copiers. We'll also see more pay-for-performance models with attributable ROI, akin to Amazon's ACoS model or Rakuten's affiliate marketing model. Customers will prefer it too, placing a higher emphasis customer value. This will also drive margins to condense.* AI, AI, AI. AI will cut OpEx costs dramatically. SDR teams, gone. Copywriters at agencies, you don't need as many. Data scientists? Just run a query against your data lakes. The list goes on. Costs of running these companies is going to get shellacked. Good for margins for sure, but also a compelling opportunity for newcomers to undercut and unseat incumbents too.* More hardware. With software margins condensing, hardware margins will start to feel more attractive too, the maintenance and upgrade fees will resemble what we see in SaaS, and the software that powers these machines will be incredible. Skynet for autonomous off-road vehicles, absolutely.* Less dilution, earlier exits, and stratification. We already see it in the S&P 500 with the top end accounting for an outsized share of total value. With that kind of cash on balance sheets, bigger companies will just buy the smaller ones. Think about how Broadcom rolls up companies. If you've built the business more efficiently, you've also raised less, incurred less dilution, and that $100m exit when you still own 50% is looking pretty prett-ty good compared to the same outcome 5-10 grueling years later to own 5% of $1B.* Massive founder salaries, less emphasis on growth. If you've built a company that's profitable from day one, and you have complete control of your board, what's your incentive to keep the pedal down on growth, or stay on the VC treadmill? World domination? Why not pay yourself 10X, stop fundraising, and continue to tighten the core business until someone acquires you? It's better for the founding team and employees for sure, and it's probably better for customers in most instances too.These are just some of things I think we'll see over the next five years until we approach ZIRPy-dirpy times again and massive growth becomes irresistible.But there are also a whole slew of things I think are inevitabilities that will benefit from these dynamics because we will not only have new technologies, with more attractive pricing, but we will be tackling new opportunities that were created by the prior evolutions across adjacent industries.For example…* Cost of energy is going to zero with nuclear fusion* Longevity is starting to work; check out Loyal for Dogs* Batteries & cameras continue to improve; medical devices, for one, will be more personal & affordable* Disintermediation of big ad networks with new global distribution channels; check out Benjamin* Massive cost reductions driven by AI* Software will be built by software* An aging population is retiring (10,000 per day); wealth transfer & SMB's with no exit paths* Climate change* …and so on and so on and so onThe list is long. Much longer than this. If you want the rest, just reply or comment so that I know, and I'll go deeper next week.Net of all of it, I think we're going to see a tale of two cities. Stronger, more profitable businesses, with smaller, but better founder founder exits in the near term, and a continued growth both in number of total unicorns, and what that top-end outcomes look like in the longer-term.And like I said, go read Aileen's post.Sequoia, Founders Fund, USV, Elad Gil & Benchmark Top Venture Manager SurveyI got my hands on a VC scorecard circulating among top founders & VCsERIC NEWCOMERJAN 25, 2024Before we get started, I want to be clear — this isn't the end-all, be-all list of the top venture capital firms or the most promising startups.But I got my hands on a survey of 91 people at 69 different venture capital firms conducted by a well-respected investor in venture capital firms.The survey results are spreading hand-to-hand in Silicon Valley. The results of the survey rank the most desirable venture capital firms and companies, according to VCs themselves. When I was out in San Francisco last week for The Information's 10th anniversary gala, sources kept bringing it up.My sources tell me that the survey was conducted by Ed Hutchinson, managing partner at Golden Bell Partners. Hutchinson is ignoring my emails.Which firms and companies would top VCs themselves put their money into? It's a question everyone wants to know the answer to.I've got my hands on their list of favorites:Firms* (1) Sequoia* (2) Founders Fund* (3) Union Square* (4) Elad Gil* (5) Benchmark…Much More (but only for subscribers)Why 2024 May Be Tougher on Venture Capital Than 2023by Jason Lemkin | Blog Posts, Fundraising, ScaleSo I thought the toughest times for venture would be behind us now.  In 2022, we were in free fall, with public market caps falling like a knife, and the IPO markets frozen.  And 2023 was the year of the Work Out in venture.  Bridge rounds slowed down, and VCs acknowledged a lot of portfolio companies just weren't going to make it.  It got real in 2023, and that realness got normalized.  The drama mostly was behind us.  And public SaaS stocks in many cases did really, really well in 2023.  So shouldn't 2024 at least be better for venture?So I thought.But the reality is I'm a bit more worried the venture drama in 2024 will be bigger than 2023.  Why?  Four core reasons:#1:  Now We Have to Deal With the Reality of the Stumbling Unicorns.The ones that are doing $100m+ ARR, still growing, but there just isn't going to be any more money coming.  This is going to burn up a ton of energy in VC funds.  Even tougher, the reality is while many VC funds marked down their unicorns to lower valuations in 2023, they often didn't mark them down enough.#2.  The Chase for AI Unicorns and Decacorns is All-consuming.  It's Still 2021 There.The one place where paper money seems easy to come by is Hot AI Startups.   And that's probably not you.  It's just consuming all the oxygen in venture, trying to get into the next Imaging AI startup worth $1B in 10 months.  In AI, 2021 never went away.  In AI, it's still 2021.#3.  A Lot of Seasoned VCs are Discouraged. This Doesn't Help Founders.A lot of VCs who have been around for a while are quietly discouraged.  They just don't see a great path to making a ton of money in venture these days.  We're in Year 3 of a venture downturn, and that weighs of most of us.  At a practical level, for founders, it makes it harder to lean it.#4.  More Valuation Markdowns Are Still to ComeRelated to the first point, but more markdowns are like mutliple rounds of layoffs.  They're just tough.  LPs lose confidence.  Coworkers lose confidence.  We should have gotten through a lot of this in 2023, but we didn't.  Personally, I've got several investments for example that I marked down. 70%-80% or more — that my co-investors didn't mark down at all.#5.  VCs Have Run out of ReservesVCs used what extra “reserve” capital they had for bridge rounds in 2022 and 2023.  Now it's gone.  That's adds to the stress as companies struggle.  You don't have a play anymore.The bottom line is there likely is at least another full year of working through the excesses of 2021.  That will weigh across venture.  No matter what some AI headlines suggest.Video of the WeekThe Mac at 40Apple Shares the Secret of Why the 40-Year-Old Mac Still RulesThe pioneering PC revolutionized how people interact with computers. As the Mac enters its fifth decade, Apple says it will continue to evolve.STEVEN LEVY, Jan 19, 2024 10:00 AMON JANUARY 24, Apple's Macintosh computer turns 40. Normally that number is an inexorable milestone of middle age. Indeed, in the last reported sales year, Macintosh sales dipped below $30 billion, more than a 25 percent drop from the previous year's $40 billion. But unlike an aging person, Macs now are slimmer, faster, and last much longer before having to recharge.My own relationship with the computer dates back to its beginnings, when I got a prelaunch peek some weeks before its January 1984 launch. I even wrote a book about the Mac—Insanely Great—in which I described it as “the computer that changed everything.” Unlike every other nonfiction subtitle, the hyperbole was justified. The Mac introduced the way all computers would one day work, and the break from controlling a machine with typed commands ushered us into an era that extends to our mobile interactions. It also heralded a focus on design that transformed our devices.That legacy has been long-lasting. For the first half of its existence, the Mac occupied only a slice of the market, even as it inspired so many rivals; now it's a substantial chunk of PC sales. Even within the Apple juggernaut, $30 billion isn't chicken feed! What's more, when people think of PCs these days, many will envision a Macintosh. More often than not, the open laptops populating coffee shops and tech company workstations beam out glowing Apples from their covers. Apple claims that its Macbook Air is the world's best-selling computer model. One 2019 survey reported that more than two-thirds of all college students prefer a Mac. And Apple has relentlessly improved the product, whether with the increasingly slim profile of the iMac or the 22-hour battery life of the Macbook Pro. Moreover, the Mac is still a thing. Chromebooks and Surface PCs come and go, but Apple's creation remains the pinnacle of PC-dom. “It's not a story of nostalgia, or history passing us by,” says Greg “Joz” Joswiak, Apple's senior vice president of worldwide marketing, in a rare on-the-record interview with five Apple executives involved in its Macintosh operation. “The fact we did this for 40 years is unbelievable.”…Much MoreAI of the WeekBMW will deploy Figure's humanoid robot at South Carolina plantBrian Heater @bheater / 3:00 AM PST•January 18, 2024Image Credits: FigureFigure today announced a “commercial agreement” that will bring its first humanoid robot to a BMW manufacturing facility in South Carolina. The Spartanburg plant is BMW's only in the United States. As of 2019, the 8 million-square-foot campus boasted the highest yield among the German manufacturer's factories anywhere in the world.BMW has not disclosed how many Figure 01 models it will deploy initially. Nor do we know precisely what jobs the robot will be tasked with when it starts work. Figure did, however, confirm with TechCrunch that it is beginning with an initial five tasks, which will be rolled out one at a time.While folks in the space have been cavalierly tossing out the term “general purpose” to describe these sorts of systems, it's important to temper expectations and point out that they will all arrive as single- or multi-purpose systems, growing their skillset over time. Figure CEO Brett Adcock likens the approach to an app store — something that Boston Dynamics currently offers with its Spot robot via SDK.Likely initial applications include standard manufacturing tasks such as box moving, pick and place and pallet unloading and loading — basically the sort of repetitive tasks for which factory owners claim to have difficulty retaining human workers. Adcock says that Figure expects to ship its first commercial robot within a year, an ambitious timeline even for a company that prides itself on quick turnaround times.The initial batch of applications will be largely determined by Figure's early partners like BMW. The system will, for instance, likely be working with sheet metal to start. Adcock adds that the company has signed up additional clients, but declined to disclose their names. It seems likely Figure will instead opt to announce each individually to keep the news cycle spinning in the intervening 12 months.Unlike some other humanoid designers (including Agility), Figure is focused on creating a dexterous, human like hand for manipulation. The thinking behind such an end effector is the same that's driving many toward the humanoid form factor in the first place: Namely, we've designed our workspaces with us in mind. Adcock alludes to Figure 01 being tasked with an initial set of jobs that require high dexterity.As for the importance of legs, the executive suggests that their importance for maneuvering during certain tasks is as — or more — important than things like walking up stairs and over uneven terrain, which tend to get most of the love during these conversations.…MoreGoogle's New AI Video Generator Looks IncredibleJAN 25, 2024MATT GROWCOOTGoogle has announced Lumiere: an AI video generator that looks to be one of the most advanced text-to-video models yet.The name Lumiere is seemingly a nod to the Lumiere brothers who are credited with putting on the first ever cinema showing in 1895. Just as motion picture was cutting-edge technology at the end of the 19th century, the Lumiere name is once more being associated with something new and original.The demo of Lumiere that Google put out focuses firmly on animals. The model can generate a scene using just text; much the same way AI image generators work, the user can dream up any scenario they would like to see a short video clip of.However, the user can also use an image as a prompt. Google provided multiple examples: including some that are real photos such as Joe Rosenthal's iconic Raising the Flag photo; “Soldiers raising the united states flag on a windy day” saw one of the 20th-centuries most recognizable photos suddently come to life as the soliders struggle with the flag that's being affected by gusts.Also in Lumiere is a “Video Stylization” setting which allows users to upload a source video and then ask the generative AI model for various element changes. For example, a person running may be suddenly turned into a toy made of colorful bricks.Another feature Google showed off is “Cinemagraphs”, where just a section of an image is animated while the rest stays still. “Video Inpainting” is included too which involves masking part of the image so that section can be changed to the user's desire.Space-Time Diffusion ModelLumiere is powered by “Space-Time U-Net architecture that generates the entire temporal duration of the video at once, through a single pass in the model.”This difficult-to-understand concept is apparently in contrast to existing video models which “synthesize distant keyframes followed by temporal super-resolution — an approach that inherently makes global temporal consistency difficult to achieve.”…Much MoreOpenAI's Sam Altman seeks funds for AI chip factories as demands surgeOpenAI CEO Sam Altman has opened discussions with global investors over the possibility of funding a network of artificial intelligence (AI) chip factories to keep pace with soaring demand.Altman is seeking around $8 billion to $10 billion worth of funds to set up several AI chip fabrication plants around the globe, an endeavor that will require synergy between leading chip manufacturers backed by investment giants.Altman is reportedly in talks with Japanese-based financial giant SoftBank Group (NASDAQ: SFTBF) and Abu Dhabi's G42 over funding plans, but details remain sparse. The discussions with G42 have been underway since 2023, with Altman describing a potential chip partnership as laying the foundation “for equitable advancements in generative AI across the globe.”Aside from SoftBank and G42, insiders say that Altman is still pursuing collaborations with other industry players to set up a network of chip fabrication plants. Although exact entities were not namechecked, industry experts are noting Intel Corporation (NASDAQ: INTC), Samsung Electronics, and Taiwan Semiconductor Manufacturing Co. (NASDAQ: TSM) as potential partners.Altman's approach to raising funds hinges on concerns that the chip supply will not be able to meet global demands for AI offerings by 2030. The OpenAI's CEO argues that the ideal solution will be a collaborative effort to set up chip manufacturing plants rather than build in silos.OpenAI has had its fair share of chip scarcity, rolling back a number of its offerings over a steady chip supply. To meet the rising demand, the company is reportedly mulling several options, including the prospect of building its chips from scratch and joining ranks with Google (NASDAQ: GOOGL) and Amazon (NASDAQ: AMZN) to explore an in-house solution.Given the costs associated with an in-house approach, OpenAI may pursue the acquisition of a chip manufacturer as a short-term solution or expand its collaboration with existing partners. However, a potential acquisition opens its own can of worms, including an inquiry by antitrust regulators.Governments are also involvedIn 2023, Altman urged the South Korean government to double their investments in AI chip manufacturing as a veritable strategy to play a leading role in the nascent ecosystem. Currently, South Korea ranks behind the U.S., China, and Japan in chip manufacturing, but a concerted government involvement could see the country climb up the charts.The OpenAI boss disclosed during his visit to South Korea that his firm will back local entities building chips for AI and other emerging technologies, with Samsung rumored to be in top position.“We are exploring how to increase our investment in Korean startups,” said Altman. “We are excited to meet as many as we can here today. I think this type of collaboration is essential to our work.”..MoreThe Future of Prosumer: The Rise of “AI Native” WorkflowsAnish Acharya, Justine Moore, and Olivia MoorePosted January 25, 2024Few people love the software they use to get things done. And it's no surprise why. Whether it's a slide deck builder, a video editor, or a photo enhancer, today's work tools were conceived decades ago — and it shows! Even best-in-class products often feel either too inflexible and unsophisticated to do real work, or have steep, inaccessible learning curves (we're looking at you, Adobe InDesign). Generative AI offers founders an opportunity to completely reinvent workflows — and will spawn a new cohort of companies that are not just AI-augmented, but fully AI-native. These companies will start from scratch with the technology we have now, and build new products around the generation, editing, and composition capabilities that are uniquely possible due to AI. On the most surface level, we believe AI will help users do their existing work more efficiently. AI-native platforms will “up level” user interactions with software, allowing them to delegate lower skill tasks to an AI assistant and spend their time on higher-level thinking. This applies not only to traditional office workers, but to small business owners, freelancers, creators, and artists — who arguably have even more complex demands on their time. But AI will also help users unlock completely new skill sets, on both a technical and an aesthetic level. We've already seen this with products like Midjourney and ChatGPT's Code Interpreter. Everyone can now be a programmer, a producer, a designer, or a musician, shrinking the gap between creativity and craft. With access to professional-grade yet consumer-friendly products with AI-powered workflows, everyone can be a part of a new generation of “prosumers.”In this piece, we aim to highlight the features of today's — and tomorrow's — most successful Gen AI-native workflows, as well as hypothesize about how we see these products evolving.What Will GenAI Native Prosumer Products Look Like?All products with Gen AI-native workflows will share one crucial trait: translating cutting-edge models into an accessible, effective UI.Users of workflow tools typically don't care what infrastructure is behind a product; they care about how it helps them! While the technological leaps we've made with Generative AI are amazing, successful products will importantly still start from a deep understanding of the user and their pain points. What can be abstracted away with AI? Where are the key “decision points” that need approval, if any? And where are the highest points of leverage? There are a few key features we believe products in this category will have: * Generation tools that kill the “blank page” problem. The earliest and most obvious consumer AI use cases have come from translating a natural language prompt into a media output — e.g., image, video, and text generators. The same will be true in prosumer. These tools might help transform true “blank pages” (e.g., a text prompt to slide deck), or take incremental assets (e.g., a sketch or an outline) and turn them into a more fleshed-out product.Some companies will do this via a proprietary model, while others may mix or stitch together multiple models (open source, proprietary, or via API) behind the scenes. One example here is Vizcom's rendering tool. Users can input a text prompt, sketch, or 3D model, and instantly get a photorealistic rendering to further iterate on.Another example is Durable's website builder product, which the company says has been used to generate more than 6 million sites so far. Users input their company name, segment, and location, and Durable will spit out a site for them to customize. As LLMs get more powerful, we expect to see products like Durable pull real information about your business from elsewhere on the internet and social media — the history, team, reviews, logos, etc. — and generate an even more sophisticated output from just one generation. * Multimodal (and multimedia!) combinations. Many creative projects require more than one type of content. For example, you may want to combine an image with text, music with video, or an animation with a voiceover. As of now, there isn't one model that can generate all of these asset types. This creates an opportunity for workflow products which allow users to generate, refine, and stitch different content types in one place.…MoreAndreessen Horowitz's Connie Chan to Leave as Consumer Focus Shifts to AIBy Kate Clark, Erin Woo and Cory WeinbergJan 23, 2024, 7:22am PSTFor years, partners at Andreessen Horowitz proclaimed they would scour the startup world for the next big consumer marketplace like Airbnb or the next hit consumer app out of China, areas in which the firm had unique expertise. Now, it's shifting toward an area more en vogue across venture capital: consumer apps powered by artificial intelligence.Those changes are happening amid an overhaul of its consumer team. Connie Chan, a general partner at Andreessen Horowitz who formerly led a team of consumer investors and was known for spotting internet trends coming from China, said she is leaving the firm.  She may raise her own fund, a person familiar with the matter said. Anish Acharya, a general partner at the firm who invested in enterprise-focused and financial technology businesses, now leads the consumer team, said people familiar with the change.Chan's move also follows a distancing by U.S. VC firms from investments in China tech, once a hotbed for U.S.  investors. In recent months, Chan has privately said it's becoming more difficult for her to work at Andreessen Horowitz because the partners have been increasingly disinterested in anything China related, another person said.The Takeaway• Fintech-focused GP Anish Acharya leading consumer deals• Consumer GP Connie Chan is leaving the firm• Consumer partner Anne Lee Skates left to start own fundThe changes are part of a broader personnel shakeup, including the decision by senior consumer investor and Airbnb board member Jeff Jordan to step back from making new investments last year. Of the four general partners that led the firm through a consumer deal blitz, none remain on the consumer team.Meanwhile, Anne Lee Skates, a consumer partner who worked on the firm's investment in live shopping app WhatNot, left in the fall to raise her own fund, according to two people familiar with the matter. Axios first reported that Chan was leaving the firm.The Andreessen Horowitz changes are emblematic of a broader VC industry gravitation toward AI and away from once-hot sectors like consumer marketplaces and financial technology, as a spike in interest rates undercut the growth aspirations of startups trying to elbow out incumbent social platforms and banking institutions.“We've gotten into this cycle now where, generally speaking, investors are less interested in consumer,” said Ben Lerer, managing partner at Lerer Hippeau. Known for its consumer investments in Warby Parker and Allbirds, the firm has invested 70% of its latest fund in enterprise companies, he said. “And AI feels like this very hopeful, very exciting, fresh thing.”Founders of some consumer startups have noticed the shift at Andreessen Horowitz. One founder of a consumer startup in the firm's portfolio said they had heard little from investment partners over the last year, a contrast to a steady drumbeat of emails the founder got in prior years from Andreessen staff who support portfolio companies with marketing and operations advice.Andreessen Horowitz's consumer investing team has been perhaps most well known for its focus on backing digital marketplaces, from peer-to-peer self-storage to real estate investment marketplaces, that could turn into the next Airbnb. Every year, it releases a ranking of top marketplace startups. “We are obsessed with marketplaces and have been since our inception,” Chan, who led investments in  social fashion startup Cider for the firm in 2021.But some of those startups backed by the firm, such as self-storage startup Neighbor, have struggled to take off in recent years. And like other venture firms, Andreessen Horowitz has also stepped back from investing in Chinese startups, an area of focus for Chan. She had championed the idea that the next wave of breakout U.S. consumer startups will model themselves after China's internet success stories, like all-in-one app WeChat.With $53 billion in assets under management, Andreessen Horowitz is one of the largest of traditional Silicon Valley firms and closely watched among other VC firms as a trend setter. And its track record of sniffing out hitmakers primed its partners to find the next trendy consumer app.The number of consumer deals Andreessen Horowitz has led dropped to 13 last year from 30 in 2021, a record for the firm, according to PitchBook data. It's possible the firm completed more consumer deals and that those investments haven't been announced. Its investments in AI companies have jumped to 23 from nine over the same years, including leading a $415 million investment in Mistral, the French developer of an open-source large language model.The firm has beefed up this team of investors primarily focused on enterprise, software infrastructure and AI startups. Led by Martin Casado, a close confidante to the firm's founders Horowitz and Marc Andreessen, it is raising its first standalone fund and has brought on two new general partners, Anjney Midha and Zane Lackey, since 2022, as well as a number of junior partners.As the infrastructure team gained power, the consumer team's profile shrank. The firm in 2023 combined its consumer and fintech teams and created a new group, called apps, led by general partner Alex Rampell, who previously co-founded installment lender Affirm, The Information reported last year. Under Rampell's leadership, the newly formed apps team will also soon launch a dedicated apps fund, according to people with direct knowledge of the matter. The consolidated team has been encouraged to pursue AI deals.Within Rampell's apps group, Acharya now leads the consumer sub-group. His portfolio of companies includes payroll company Deel and Silo, a provider of supply chain automation software. He's also an investor in Titan, a consumer investment application.Fueling the firm's shift away from consumer apps are likely disappointing returns. The startups that captivated consumers during the pandemic shutdowns have failed to retain their attention. Growth at companies the consumer team bet on, like Clubhouse, which Andreessen Horowitz backed three times in one year, and photo-sharing app BeReal, which it backed in 2021, has stalled.…MoreOpenAI Is a (Relative) StealBy Stephanie PalazzoloJan 22, 2024, 7:35am PSTOver the past year, we've seen billions in funding thrown at AI startups at eye-popping valuations. More important than the absolute valuation figures, though, is how they stack up to those startups' revenue numbers.In the chart above, we've tracked the valuations of eight AI startups that have recently raised funding, calculated against their projected revenue. On average, these companies raised money at a price that is 83 times their projected sales for the next twelve months. That's a big multiple by any measure, reflecting the rocket ship nature of these startups. But what makes the comparison noteworthy is that OpenAI has one of the lowest multiples, even though its business has the most traction.Venture capitalists tend to value early-stage startups at a premium based on their growth rates. OpenAI's business is far bigger and more mature—if we can use that word for a company growing as fast as OpenAI—than other generative AI companies. So, as fast as its revenue pace is growing—more than 20% in just two months most recently—newer firms are growing even faster.For instance, AI-powered search engine Perplexity AI doubled its annual recurring revenue from $3 million to $6 million from October to January. VCs were likely taking that expected growth into account at the time of investment, as the company would have garnered a much lower 75-times forward revenue multiple if it had raised at the same price just a few months later. Similarly, even though OpenAI rival Anthropic was likely generating around $200 million in annualized revenue at the end of last year (according to its October estimates), its projection that it would reach $850 million in annualized revenue by the end of this year surely made its mind-boggling valuation more palatable to investors.When you see the details of these AI startup funding rounds, it can sometimes feel like investors are throwing darts at nine-figure numbers on a wall. The chart suggests there's a method to the madness. Typically, startups selling to companies are valued based on the sector in which they operate. The lowest valuation multiples are accorded to startups offering industry-specific applications, while those offering more generalized applications draw a premium. The most highly valued firms are often infrastructure startups, which create the tools that developers use to build these apps. This order stems from how big the target market of these startups are, ranging from a specific industry (like healthcare or education) to all developers. We can see that general order reflected in burgeoning AI startups. For instance, Harvey, which sells an AI application for lawyers, has one of the lower multiples, while broader-reaching companies like Glean and VAST Data land higher multiples.It seems like investors aren't quite sure yet where model developers like OpenAI and Anthropic fall on this spectrum. Their costs are very different from a typical software startup due to how much computing power they need, and many investors are still worried that closed-source model developers may be overtaken by their cheaper, open-source counterparts.…MoreNews Of the WeekTed fellows resign from organisation after Bill Ackman named as speakerLucianne Walkowicz and Saeed Taji Farouky accuse Ted of taking anti-Palestinian stand over controversial billionaire's inclusionChris McGrealThe Ted organisation has been hit with resignations and criticisms after naming the controversial activist billionaire Bill Ackman, who was instrumental in forcing out Harvard's president over antisemitism allegations, among its main speakers at this year's conference.Four Ted fellows, led by the astronomer Lucianne Walkowicz and the filmmaker Saeed Taji Farouky, resigned from the group on Wednesday, accusing it of taking an anti-Palestinian stand and aligning itself “with enablers and supporters of genocide” in Gaza.“2024 main stage speaker Bill Ackman has defended Israel's genocide and ethnic cleansing of the Palestinian people and has cynically weaponised antisemitism in his programme to purge American universities of Pro-Palestinian freedom of speech,” the pair wrote to Chris Anderson, who leads Ted, and Lily James Olds, director of the fellows programme.“We've become increasingly concerned about the fundamental values and moral compass of the organisation over the years, but with this year's speaker selection, it is clear Ted has crossed a red line.”The conference will be held in Vancouver, Canada, in April, under the banner The Brave and the Brilliant”. The theme of Ackman's talk has not been revealed but his selection was announced last week after he was accused of using his money and influence to help force Claudine Gay's resignation as Harvard's president following her disastrous appearance before Congress in December when she was questioned about on-campus antisemitism during the Israel-Gaza war.Ackman has taken stridently pro-Israel positions, including justifying the scale of the attacks on Gaza in which more than 25,000 Palestinians have been killed, mostly civilians, and the forced removal of about 2 million Palestinians from their homes. He has described criticism of Israel as antisemitism and called for the blacklisting from employment of American students who signed petitions denouncing the offensive in Gaza in the wake of the 7 October Hamas attack on Israel.Farouky and Walkowicz's resignation letter noted that other speakers announced by Ted include the journalist Bari Weiss, who they describe as having “a long, sordid, and well-documented history of anti-Palestinian speech”, but that there are no Palestinians in the line-up.“We refuse for our work and identities to be exploited to promote the Ted brand while the organisation and its speakers generate income and advance their careers through dehumanising Palestinians and justifying their genocide,” the pair said.After the resignation letter was published, two other fellows – the entrepreneur Ayah Bdeir and cosmologist Renée Hlozek – also quit. Nearly 30 others added their names “in solidarity” without leaving Ted.…MoreTesla's Slowdown Disqualifies It From ‘Magnificent Seven' GroupBy Martin Peers, Jan 24, 2024, 5:00pm PSTStock market pundits may want to come up with a new name for the big tech stocks driving the overall market. The “magnificent seven” descriptor—referring to Apple, Microsoft, Alphabet, Amazon, Meta Platforms, Nvidia and Tesla—no longer seems to make much sense. I'd like to suggest that's because none of the company CEOs look like cowboy gunslingers from the 1960 movie that made the phrase famous. It's hard to imagine Steve McQueen playing Tim Cook or Andy Jassy, for instance (although Yul Brynner admittedly could have filled the role of horseback-riding Jeff Bezos).The real reason the moniker no longer works, however, is that at least one member of the group, Tesla, has had anything but a magnificent 2024 so far, and its fourth-quarter earnings report, released Wednesday, only made things worse. Before Tesla reported earnings tonight, its stock had fallen 16% so far this year, and it tumbled another 3% after hours to around $200 a share. This isn't a reaction to CEO Elon Musk's antics, which include asking for a bunch more stock, although that surely doesn't help. The stock decline reflects the slowdown in sales suffered by Tesla, which observers attribute to increased competition and a loss of government incentives. Automotive revenues, which make up the bulk of Tesla's top line, grew just 1% in the fourth quarter—down from 18% in the first quarter.In its outlook for this year issued today, the company said its growth in the volume of car sales would be lower than in 2023, and noted that its team is working on its “next-generation vehicle.” Meantime, expenses have been skyrocketing, eroding its profit margin. But our less-than-rigorous takedown of the magnificent seven branding isn't just about Tesla. If you look at the year-to-date performance of big tech stocks, or even their 2023 performance, you can see that just two tech stocks have roared this year. One is Nvidia, which is in a class of its own: up 27% since Jan. 1, thanks to its stranglehold on the specialized chips used in artificial intelligence. The other is Meta Platforms, which is up nearly 13%, reflecting confidence in its ad business.  In comparison, Microsoft and Alphabet are each up around 8%, likely thanks to expectations that AI will lift their businesses, while Apple and Amazon lag behind with year-to-date stock price rises of less than 5% each. Instead of the magnificent seven, it might be more appropriate to refer to the group as Nvidia, Meta and the humble five.… MoreTikTok's Testing 30 Minute Uploads as It Looks To Expand Its Content OptionsBy Andrew Hutchinson Content and Social Media ManagerThe next stage of TikTok is coming, with some users now seeing the option to upload 30 minute long videos in the app.As you can see in this example, shared by social media expert Matt Navarra, TikTok's currently testing the new 30 minute upload option in the beta version of the app.Which, if you've been paying attention, is not really any big surprise.TikTok has been steadily increasing its maximum post limit for years, with the platform originally starting at 15 seconds per clip, which was then extended to 60 seconds, then 3 minutes, then 5 minutes, before rising to 10 minutes in 2022.Last October, TikTok began experimenting with 15 minute uploads, so the trend towards longer clips isn't new.Though 30 minutes is likely the upper limit, based on the Chinese version of the app. Douyin, which is TikTok in China, expanded its upload limit to 30 minutes per clip in 2022, and it hasn't gone any further as yet.And presumably, Douyin has also seen good response to this longer time limit, which is why TikTok is now looking to implement the same, though it does seem like a long time to be watching a TikTok clip in-stream.Will users really warm to TV show length clips in the app?…MoreInstagram to scan under-18s' messages to protect against ‘inappropriate images'Feature will work even on encrypted messages, suggesting platform plans to implement client-side scanningAlex Hern and Dan MilmoInstagram will begin scanning messages sent to and from under-18s to protect them from “inappropriate images”, Meta has announced.The feature, being kept under wraps until later this year, would work even on encrypted messages, a spokesperson said, suggesting the company intends to implement a so-called client-side scanning service for the first time.But the update will not meet controversial demands for inappropriate messages to be reported back to Instagram servers.Instead, only a user's personal device will ever know whether or not a message has been filtered out, leading to criticism of the promise as another example of the company “grading its own homework”.“We're planning to launch a new feature designed to help protect teens from seeing unwanted and potentially inappropriate images in their messages from people they're already connected to,” the company said in a blogpost, “and to discourage them from sending these types of images themselves. We'll have more to share on this feature, which will also work in encrypted chats, later this year.”…Much MoreTiger Global Investor Relations Staff Depart After Fundraising ChallengesBy Francesca Friday and Maria HeeterJan 24, 2024, 4:46pm PSTSeveral Tiger Global Management employees focused on raising capital for the New York firm's venture funds have taken buyout offers, according to a person familiar with the matter. The departures of the staff, who worked with prospective investors, come as the firm has struggled to raise money for its latest venture capital fund after a collapse in startup valuations soured its paper returns for earlier funds.As of the second quarter of 2023, a $12.7 billion fund that Tiger started making investments from in October 2021 had a paper loss of 18%, calculated as an annualized return net of management fees, according to internal data distributed to investors in the fund. That's a slight improvement from six months earlier, when the 2021 fund showed a loss of 20%. The fund's performance is in the bottom quartile of funds started that year, the document said, and has also lagged the S&P 500's annualized net return in the same period.The Takeaway• Tiger employee buyouts are the latest example of VC cost-cutting• Tiger's $12.7 billion had lost 18% on paper as of June* Tiger could soon show a $350 million gain from OpenAI stakeAs of June 30, 2023, the $12.7 billion fund hadn't returned any cash to investors, which isn't unusual for such a young fund. But the paper losses are closely guarded secrets that reflect the kind of write-downs other venture firms have been making over the past two years as tech valuations have fallen.It isn't clear how big Tiger's investor relations team is, but the departures are the latest example of belt-tightening across the venture industry. Firms are raising smaller funds and striking fewer deals, reducing the need for sprawling support staff—including those who help firms raise money from pension funds and endowments...MoreWorldcoin hints at new Orb for a friendlier iris-scanning experienceby Vivian NguyenThe next-gen device will feature various colors and shapes to enhance its visual appeal.Worldcoin, an iris biometric crypto project, is set to launch a new Orb that aims to offer a more user-friendly iris-scanning experience, said Alex Blania, CEO and co-founder of Tools for Humanity, the developer behind the project, in an exclusive interview with TechCrunch today.“The next Orb will roll out in the first half of this year and will feature alternative colors and form factors in an effort to look ‘much more friendly,'” Blania explained. “Overall, it is going to look way more tuned down and similar to an Apple product.”Blania acknowledges that the initial design of the Orb predated his time at the company. “The new orb is coming and the next iterations will look quite different,” he remarked during a fireside chat at a recent StrictlyVC event, signaling a departure from the current, more controversial design.The goal of Worldcoin, as described by Blania, is to reach billions of users as fast as possible.“The thesis is very simple. We race toward billions of users as fast as we possibly can,” said Blania.Founded by Blania, Sam Altman, and Max Novendstern, Tools for Humanity has raised around $250 million from prominent investors like a16z and Bain Capital Crypto, among others. The project is famous for its unique Orb device designed to scan people's irises and assign them a “World ID,” granting access to Worldcoin's application and a digital passport. Worldcoin's vision is to authenticate individual identities and prevent the creation of multiple accounts.The current design of the Orb has been a topic of much debate due to its intimidating look, similar to a prop from a sci-fi movie, according to Blania. The company has also faced criticism for its beta testing approaches in developing economies and concerns over privacy and data security.Despite some skepticism, the Orb has seen practical use. At the StrictlyVC event in downtown San Francisco, a Tools for Humanity employee reported that a “couple dozen” attendees scanned their iris to receive a World ID. There has also been “field testing” of the new Orb design.…MoreStartup of the WeekLoyalty Startup Bilt Rewards Hits $3.1B Valuation After $200M RoundChris MetinkoJanuary 24, 2024Bilt Rewards, a loyalty rewards startup, raised a $200 million round led by General Catalyst at a $3.1 billion valuation — more than double the number after its last fundraising in 2022.The round also included participation from Eldridge Industries, Left Lane Capital, Camber Creek and Prosus Ventures.The New York-based startup allows consumers to earn rewards on the rent they pay. Bilt plans to use some of the proceeds to expand its network to include local dining, grocery stores, ridesharing and other retail purchases.“We're not just building a loyalty program; we're creating a community-centric ecosystem that benefits everyone from renters to local businesses,” said founder and CEO Ankur Jain.The company also appointed some big names to roles in the company. Bilt named Ken Chenault, former chairman and CEO of American Express, as its chairman, and Roger Goodell, the commissioner of the NFL, as an independent director.Big moneyThe company reported its annualized member spend is nearing $20 billion. It also became profitable on an earnings before interest, taxes, depreciation and amortization basis last year.Those metrics must have impressed investors, as Bilt has seen its valuation shoot up after raising a $150 million Series B at a pre-money valuation of $1.4 billion in October 2022. Founded in 2021, the company has raised a total of $413 million, per Crunchbase.Last year was a slow go for loyalty startups. Such companies raised only $74 million, per Crunchbase data. However in 2022, loyalty startups raised more than a half-billion dollars thanks to big raises that included Bilt's Series B and Madison, Wisconsin-based Fetch's $240 million Series E.With this fundraise, things are looking up for loyalty startups again.X of the Week This is a public episode. If you'd like to discuss this with other subscribers or get access to bonus episodes, visit thatwastheweek.substack.com/subscribe

Geoffrey Moore is an author, speaker, and advisor, widely known for his seminal book Crossing the Chasm: Marketing and Selling Disruptive Products to Mainstream Customers, which many consider the most important book ever written on go-to-market strategy. Moore's work is focused on the market dynamics surrounding disruptive innovations, and how one overcomes the challenge of transitioning from serving early adopters to the mainstream. In this episode, we discuss:• What “crossing the chasm” means• What steps to take before you try crossing the chasm• The importance of winning a marquee customer• The role of executive sponsors in the sales process• The differences between visionaries and pragmatists, and how to build for each• Geoffrey's four go-to-market playbooks based on stage: Early Market, Bowling Alley, Tornado, and Main Street• The problem with discounting before crossing the chasm• “Deadly sins” to avoid when crossing the chasm—Brought to you by:• CommandBar—AI-powered user assistance for modern products and impatient users• WorkOS—An API platform for quickly adding enterprise features• Arcade Software—Create effortlessly beautiful demos in minutes—Find the full transcript at: https://www.lennyspodcast.com/geoffrey-moore-on-finding-your-beachhead-crossing-the-chasm-and-dominating-a-market/—Where to find Geoffrey Moore:• X: https://twitter.com/geoffreyamoore• LinkedIn: https://www.linkedin.com/in/geoffreyamoore/• LinkedIn posts: https://www.linkedin.com/in/geoffreyamoore/recent-activity/articles/—Where to find Lenny:• Newsletter: https://www.lennysnewsletter.com• X: https://twitter.com/lennysan• LinkedIn: https://www.linkedin.com/in/lennyrachitsky/—In this episode, we cover:(00:00) Geoffrey's background(04:03) What people often get wrong about Crossing the Chasm(05:58) Finding your beachhead segment(09:29) The four inflection points of the technology adoption lifestyle(15:45) Geoffrey's bonfire and bowling alley analogies(18:36) Steps to take before trying to cross the chasm(22:19) Signs you're ready to cross the chasm(25:19) Advice for startups on where to start(27:31) Thoughts on venture capital(27:53) A general timeline for crossing the chasm(30:52) What exactly is the “chasm”?(32:35) The difference between visionaries and pragmatists(36:05) Finding the compelling reason to buy(43:45) The Early Market playbook(45:46) The Bowling Alley playbook(48:39) Different sales approaches for early market and bowling alley(51:26) Changing the value state of the company(53:28) The Tornado playbook(57:35) Why combining playbooks doesn't work(59:10) Using generative AI in different market phases(01:03:02) The risks of discounting(01:04:21) Other “deadly sins” of crossing the chasm(01:09:09) Positioning in crossing the chasm(01:10:36) Product-led growth and crossing the chasm(01:13:54) The challenges of software and entrepreneurship(01:16:35) How Geoffrey's thinking has evolved(01:19:30) The importance of entrepreneurship and impact(01:20:42) His book The Infinite Staircase(01:23:58) Connect with Geoffrey Moore—Referenced:• Crossing the Chasm: Marketing and Selling Disruptive Products to Mainstream Customers: https://www.amazon.com/Crossing-Chasm-3rd-Disruptive-Mainstream/dp/0062292986• Oracle: https://www.oracle.com/• Documentum: https://www.opentext.com/products/documentum• Figma: https://www.figma.com/• Notion: https://www.notion.so/• Salesforce: https://www.salesforce.com/• Intel: https://www.intel.com/• Jason Fried challenges your thinking on fundraising, goals, growth, and more: https://www.lennyspodcast.com/jason-fried-challenges-your-thinking-on-fundraising-goals-growth-and-more/• The Mayo Clinic: https://www.mayoclinic.org/• Coda: https://coda.io/• An inside look at how Figma ships product: https://coda.io/@yuhki/figma-product-roadmap• Dylan Field on LinkedIn: https://www.linkedin.com/in/dylanfield/• Regis McKenna on Crunchbase: https://www.crunchbase.com/organization/regis-mckenna-inc• Andrew Grove: https://en.wikipedia.org/wiki/Andrew_Grove• A step-by-step guide to crafting a sales pitch that wins | April Dunford (author of Obviously Awesome and Sales Pitch): https://www.lennyspodcast.com/a-step-by-step-guide-to-crafting-a-sales-pitch-that-wins-april-dunford-author-of-obviously-awesom/• Sales Pitch: How to Craft a Story to Stand Out and Win: https://www.amazon.com/Sales-Pitch-Craft-Story-Stand/dp/1999023021• B2B Go-to-Market Playbooks and the Technology Adoption Life Cycle: https://www.linkedin.com/pulse/b2b-go-to-market-playbooks-technology-adoption-life-cycle-moore/• Juniper: https://www.juniper.net/us/en.html• Sal Khan on LinkedIn: https://www.linkedin.com/in/khanacademy/• Khan Academy: https://www.khanacademy.org/• How the Star Wars Kessel Run Turns Han Solo Into a Time-Traveler: https://www.wired.com/2013/02/kessel-run-12-parsecs/• Atlassian: https://www.atlassian.com/• Martin Casado on LinkedIn: https://www.linkedin.com/in/martincasado/• The Infinite Staircase: What the Universe Tells Us About Life, Ethics, and Mortality: https://www.amazon.com/Infinite-Staircase-Universe-Ethics-Mortality/dp/1950665984—Production and marketing by https://penname.co/. For inquiries about sponsoring the podcast, email podcast@lennyrachitsky.com.—Lenny may be an investor in the companies discussed. Get full access to Lenny's Newsletter at www.lennysnewsletter.com/subscribe

Is it possible to construct a virtual society that authentically replicates human behavior? AI Town, a virtual town experiment where AI residents live, interact, and engage, provides valuable insights into the future of AI's believability and its interaction with humanity.In this panel discussion, Joon Park, the author of 'Generative Agents: Interactive Simulacra of Human Behavior,' and Martin Casado from a16z, discuss  the influence and potential of Generative Agents, exploring their practical applications in the real world.Topics Covered00:00 - Simulating human behaviors04:49 - What are generative agents?07:47 - Simulations, new technology, and LLMs11:45 - The architecture behind simulating human behavior16:37 - Generative agents interactions: observing, planning, and reflecting20:22 - What is the value in advancing generative agents?24:01 - Use cases for simulation behavior technology29:31 - What are the ethical frameworks?33:12 - Q&A from the audience Resources: Find AI Town: https://www.convex.dev/ai-townRead the paper ‘Generative Agents: Interactive Simulacra of Human Behavior': https://arxiv.org/pdf/2304.03442.pdfFind Joon on Twitter: https://twitter.com/joon_s_pkFind Martin on Twitter: https://twitter.com/martin_casadoFind a16z on Twitter: https://twitter.com/a16zFind a16z on LinkedIn: https://www.linkedin.com/company/a16zSubscribe on your favorite podcast app: https://a16z.simplecast.com/Follow our host: https://twitter.com/stephsmithioPlease note that the content here is for informational purposes only; should NOT be taken as legal, business, tax, or investment advice or be used to evaluate any investment or security; and is not directed at any investors or potential investors in any a16z fund. a16z and its affiliates may maintain investments in the companies discussed. For more details please see a16z.com/disclosures.

A16z Podcast Key Takeaways Marc Andreessen's article, “Why AI Will Save the World,” dispels AI hysteria and emphasizes its transformative potentialMarc is worried about the public conversation on AI, which includes a mix of legitimate questions, explanations, and hysterical emotionsHe is also worried about certain individuals or groups trying to exploit the situation by seeking regulatory capture and stifling innovation and startupsMartin asks about the class of problems that AI is now good at compared to the past: Marc points out two key factors: the scale of training data, made possible by internet-scale data collection, and the increase in compute power, particularly with GPUsHe emphasizes the role of quantity in achieving quality in AI systemsMarc emphasizes that although the initial focus of GPT-4 may lean towards leisure and utility uses, he has always believed in the significance of technology being user-friendly and enjoyable“The actual experience of using these systems today is it's actually a lot more like love, right? And I'm not saying that they literally are conscious that they love you, but like, or maybe the analogy would almost be more like a puppy. Like they're like really smart puppies, right?” – Marc AndreessenTraditional adoption pattern: Government -> Big companies -> Small businesses -> IndividualsShift in adoption pattern: Consumers -> Small businesses -> Big companies -> GovernmentBenefits of the current adoption pattern:Faster access to new technologies for everyoneMass market evaluation of technologies before government and big business decisionsIncreased individual autonomy and agency in technology adoptionConcerns and arguments regarding correctness and adoption:Fear of incorrect or unpredictable outputs from AI systems Potential misuse by criminalsTwo biggest commercial opportunities in recent times: “Those are trillion-dollar prizes, right? Whoever figures out how to fix those problems [correctness and security] has the ability potentially to build a company worth a trillion dollars, to make this technology generally useful in a way where it's guaranteed to always be correct or guaranteed to always be secure.” – Marc AndreessenExample of correctness approach using ChatGPT and Wolfram Alpha plugin:Install the Wolfram Alpha plugin to cross-check math and science statementsWolfram Alpha acts as a deterministic calculatorHybrid architecture combining a deterministic calculator with a creative AI systemThere is a misconception of AI replacing top artists or creators; the focus should be on augmenting their abilitiesAddressing concerns about AI replacing human labor:Technological advancements enhance the productivity rateExponential productivity ramp leads to price crash and near-zero cost for products/servicesMarc is dismissive of concerns that AI will eliminate work and worsen human well-beingSocial reform movements have two sides: True believers: represented by the Baptists, they advocate for social improvement by banning alcohol (as in the analogy of prohibition used by Marc to explain the AI reform phenomenon)Opportunistic beneficiaries: represented by bootleggers, they financially benefit from the illegal trade of alcohol and take advantage of the laws and regulations passed by the reform movement to establish their businessesIn modern times, bootleggers are legitimate business people seeking government protection from competition, aiming to form monopolies or cartels and create regulatory structures that prevent new competitionGeopolitical implications of AI and concerns regarding China's ambitions: Focus on the Chinese Communist Party and regime, not the people of ChinaChina's 2025 plan and speeches by Xi Jinping outline their goal of developing AI for population control and surveillanceTwo-stage plan: Implement authoritarian AI control within China, then spread it globallyThe worst-case scenario involves China's vision spreading across Asia, Europe, South America, and potentially the rest of the worldThe doomsday scenarios presented by AI critics are far-fetched and divorced from the reality of AI technologyThe claim that AI will lead to crippling inequality is a misinterpretation of how the economy and self-interest workRead the full notes @ podcastnotes.orgThis week, a16z's own cofounder Marc Andreessen published a nearly 7,000-word article that aimed to dispel fears over AI's risks to our humanity – both real and imagined. Instead, Marc elaborates on how AI can "make everything we care about better." In this timely one-on-one conversation with a16z General Partner Martin Casado, Marc discusses how this technology will maximize human potential, why the future of AI should be decided by the free market, and most importantly, why AI won't destroy the world. In fact, it may save it. Read Marc's full article “Why AI Will Save the World” here: https://a16z.com/2023/06/06/ai-will-save-the-world/ Resources:Marc on Twitter: https://twitter.com/pmarca Marc's Substack: https://pmarca.substack.com/ gptplaysminecraft - Twitch: https://www.twitch.tv/gptplaysminecraftWhy AI Will Save the World: https://a16z.com/2023/06/06/ai-will-save-the-world/Youtube discussion: https://www.youtube.com/watch?v=0wIUK0nsyUg Stay Updated: Find a16z on Twitter: https://twitter.com/a16zFind a16z on LinkedIn: https://www.linkedin.com/company/a16zSubscribe on your favorite podcast app: https://a16z.simplecast.com/Follow our host: https://twitter.com/stephsmithioPlease note that the content here is for informational purposes only; should NOT be taken as legal, business, tax, or investment advice or be used to evaluate any investment or security; and is not directed at any investors or potential investors in any a16z fund. a16z and its affiliates may maintain investments in the companies discussed. For more details please see a16z.com/disclosures.

A16z Podcast Key Takeaways Marc Andreessen's article, “Why AI Will Save the World,” dispels AI hysteria and emphasizes its transformative potentialMarc is worried about the public conversation on AI, which includes a mix of legitimate questions, explanations, and hysterical emotionsHe is also worried about certain individuals or groups trying to exploit the situation by seeking regulatory capture and stifling innovation and startupsMartin asks about the class of problems that AI is now good at compared to the past: Marc points out two key factors: the scale of training data, made possible by internet-scale data collection, and the increase in compute power, particularly with GPUsHe emphasizes the role of quantity in achieving quality in AI systemsMarc emphasizes that although the initial focus of GPT-4 may lean towards leisure and utility uses, he has always believed in the significance of technology being user-friendly and enjoyable“The actual experience of using these systems today is it's actually a lot more like love, right? And I'm not saying that they literally are conscious that they love you, but like, or maybe the analogy would almost be more like a puppy. Like they're like really smart puppies, right?” – Marc AndreessenTraditional adoption pattern: Government -> Big companies -> Small businesses -> IndividualsShift in adoption pattern: Consumers -> Small businesses -> Big companies -> GovernmentBenefits of the current adoption pattern:Faster access to new technologies for everyoneMass market evaluation of technologies before government and big business decisionsIncreased individual autonomy and agency in technology adoptionConcerns and arguments regarding correctness and adoption:Fear of incorrect or unpredictable outputs from AI systems Potential misuse by criminalsTwo biggest commercial opportunities in recent times: “Those are trillion-dollar prizes, right? Whoever figures out how to fix those problems [correctness and security] has the ability potentially to build a company worth a trillion dollars, to make this technology generally useful in a way where it's guaranteed to always be correct or guaranteed to always be secure.” – Marc AndreessenExample of correctness approach using ChatGPT and Wolfram Alpha plugin:Install the Wolfram Alpha plugin to cross-check math and science statementsWolfram Alpha acts as a deterministic calculatorHybrid architecture combining a deterministic calculator with a creative AI systemThere is a misconception of AI replacing top artists or creators; the focus should be on augmenting their abilitiesAddressing concerns about AI replacing human labor:Technological advancements enhance the productivity rateExponential productivity ramp leads to price crash and near-zero cost for products/servicesMarc is dismissive of concerns that AI will eliminate work and worsen human well-beingSocial reform movements have two sides: True believers: represented by the Baptists, they advocate for social improvement by banning alcohol (as in the analogy of prohibition used by Marc to explain the AI reform phenomenon)Opportunistic beneficiaries: represented by bootleggers, they financially benefit from the illegal trade of alcohol and take advantage of the laws and regulations passed by the reform movement to establish their businessesIn modern times, bootleggers are legitimate business people seeking government protection from competition, aiming to form monopolies or cartels and create regulatory structures that prevent new competitionGeopolitical implications of AI and concerns regarding China's ambitions: Focus on the Chinese Communist Party and regime, not the people of ChinaChina's 2025 plan and speeches by Xi Jinping outline their goal of developing AI for population control and surveillanceTwo-stage plan: Implement authoritarian AI control within China, then spread it globallyThe worst-case scenario involves China's vision spreading across Asia, Europe, South America, and potentially the rest of the worldThe doomsday scenarios presented by AI critics are far-fetched and divorced from the reality of AI technologyThe claim that AI will lead to crippling inequality is a misinterpretation of how the economy and self-interest workRead the full notes @ podcastnotes.orgThis week, a16z's own cofounder Marc Andreessen published a nearly 7,000-word article that aimed to dispel fears over AI's risks to our humanity – both real and imagined. Instead, Marc elaborates on how AI can "make everything we care about better." In this timely one-on-one conversation with a16z General Partner Martin Casado, Marc discusses how this technology will maximize human potential, why the future of AI should be decided by the free market, and most importantly, why AI won't destroy the world. In fact, it may save it. Read Marc's full article “Why AI Will Save the World” here: https://a16z.com/2023/06/06/ai-will-save-the-world/ Resources:Marc on Twitter: https://twitter.com/pmarca Marc's Substack: https://pmarca.substack.com/ gptplaysminecraft - Twitch: https://www.twitch.tv/gptplaysminecraftWhy AI Will Save the World: https://a16z.com/2023/06/06/ai-will-save-the-world/Youtube discussion: https://www.youtube.com/watch?v=0wIUK0nsyUg Stay Updated: Find a16z on Twitter: https://twitter.com/a16zFind a16z on LinkedIn: https://www.linkedin.com/company/a16zSubscribe on your favorite podcast app: https://a16z.simplecast.com/Follow our host: https://twitter.com/stephsmithioPlease note that the content here is for informational purposes only; should NOT be taken as legal, business, tax, or investment advice or be used to evaluate any investment or security; and is not directed at any investors or potential investors in any a16z fund. a16z and its affiliates may maintain investments in the companies discussed. For more details please see a16z.com/disclosures.

This week, a16z's own cofounder Marc Andreessen published a nearly 7,000-word article that aimed to dispel fears over AI's risks to our humanity – both real and imagined. Instead, Marc elaborates on how AI can "make everything we care about better." In this timely one-on-one conversation with a16z General Partner Martin Casado, Marc discusses how this technology will maximize human potential, why the future of AI should be decided by the free market, and most importantly, why AI won't destroy the world. In fact, it may save it. Read Marc's full article “Why AI Will Save the World” here: https://a16z.com/2023/06/06/ai-will-save-the-world/ Resources:Marc on Twitter: https://twitter.com/pmarca Marc's Substack: https://pmarca.substack.com/ gptplaysminecraft - Twitch: https://www.twitch.tv/gptplaysminecraftWhy AI Will Save the World: https://a16z.com/2023/06/06/ai-will-save-the-world/Youtube discussion: https://www.youtube.com/watch?v=0wIUK0nsyUg Stay Updated: Find a16z on Twitter: https://twitter.com/a16zFind a16z on LinkedIn: https://www.linkedin.com/company/a16zSubscribe on your favorite podcast app: https://a16z.simplecast.com/Follow our host: https://twitter.com/stephsmithioPlease note that the content here is for informational purposes only; should NOT be taken as legal, business, tax, or investment advice or be used to evaluate any investment or security; and is not directed at any investors or potential investors in any a16z fund. a16z and its affiliates may maintain investments in the companies discussed. For more details please see a16z.com/disclosures.

Martin Casado is a General Partner @ a16z where he focuses on enterprise investing. At a16z, Martin has led investments and serves on the board of dbt Labs, Fivetran, Material Security, Ambient AI and many more incredible companies. Before venture, Martin was previously the Co-Founder and CTO at Nicira, acquired by VMware for $1.26 billion in 2012. While at VMware, Martin served as Senior VP and General Manager of the Networking and Security Business Unit, which he scaled to a $600 million revenue run-rate business. In Today's Episode with Martin Casado We Discuss: 1. From $1.26BN Founder to Leading Enterprise Investing for a16z: How did Martin make his way into the world of VC and come to lead enterprise investing for a16z? What does Martin know now that he wishes he had known when he started investing? What have been some of his biggest investing lessons from Marc and Ben? 2. The VC Model is Broken and Why: Why does Martin believe that the current model for venture is broken? Why does Martin believe that VCs are not oracles and they were not gifted with picking ability? How will asset allocation more broadly fundamentally change over the next decade? Why will Silicon Valley take over and run Wall St? Why does Wall St not care about innovation and true technological development? Who will be the winners and who will be the losers in the next 10 years of venture? 3. Surviving a Crash - What Founders Need To Know: Layoffs: What is Martin's advice to founders on doing layoffs today? How much is the right amount to cut? Should it be done in one go? How should this be communicated to investors and the board? Scenario Planning: What three scenario plans should all founders be creating right now? How should they know which one is the right one to execute against? Comparisons: How should founders use and look to public company performance and market cap to determine which plan they should choose? Hiring Freeze: Why does Martin believe the biggest companies in the world make massive mistakes by freezing hiring? What should they do instead? 4. The Changing Guard at a16z: What have been the single best and worst changes a16z have made over the last 24 months? What are the first things to break when a firm scales as fast as a16z has done? Does Martin agree a16z returns will reduce with the scaling of their funds larger than ever? How does Martin look to train and educate his junior team? How does he advise them on surviving a downturn? What should they do? What should they not do? 5.) The Makings of a Great Board: What are the three types of board members? What is the best? What is the worst? What does Martin believe makes the truly great boards? What is the biggest advice Martin gives to young board members today? How has Martin changed as a board member over time? What does he need to improve? Items Mentioned in Today's Episode: Martin's Fave Book: The Weirdest People in the World: How the West Became Psychologically Peculiar and Particularly Prosperous

Martin Casado is a general partner at Andreessen Horowitz (a16z), a pioneer of software-defined networking, and a co-founder of Nicira Networks. We cover the lessons learnt from Martin's journey as an academic entrepreneur founding Nicira and factors that aspiring entrepreneurs planning to translate their research to products should consider. - Story of an accidental Ph.D., turned into an accidental but very successful entrepreneur - Shares how working with others during grad school helped his entrepreneurial efforts later - Titles don't mean anything- Forget titles and make sure decision makers are responsible for their decisions long term. - Enterprise version of Product market fit means you have to be piped into the product, the market and the tech trends - Discount the advice given by technology advisors who don't understand product market fit. - Academics need to understand how people (customers) do their day to day processes and their current technology before proposing their new technology. - Thoughts about timing and persistence. - Advice on how to hire executives at startups. - Picking board members. - Thoughts on exits and how founders should think about exits - Ph.D.'s can make great CEOs but remember that business problems are harder than technology problems

In this episode from October 2021, Michael Dell, founder and CEO of Dell Technologies and one of the longest serving founder-CEOs in the technology industry, joins a16z general partner Martin Casado, a16z co-founder Marc Andreessen, and host Sonal Choksi on the occasion of Michael's book, Play Nice to Win: A CEO's Journey from Founder to Leader. There are lots of challenges in being public while trying to innovate, and limits to being a private company as well; but it's rare to see a company go public then private then back to public again. As is the case with Dell Technologies, one of the largest tech companies -- which went private 2012-2013 and then also pulled off one of the most epic mergers of all time with Dell + EMC + VMWare 2015-2016 (and which we wrote about here at the time).Is there a method to the madness? How does one not just start, but keep, and transform, their company and business? Michael, Marc, Martin and Sonal debate these questions, as well as the impact of the cloud wars, how innovation happens when a company is private and when its public (something Michael knows well, having taken Dell public to private to back to public again), whether you can actually play nice to win as a leader, and more.

This week we discuss VMware Explore, Snap's move to multi-cloud and the Galaxy Brain take on thought leadership. Plus, Matt Ray's latest Raspberry Pi project is for the birds…? Runner-up Titles Where's my admin? All my children qualify as adults Start by eating their food Put two letters in front of it Where's the grocery store I got that everything bagel spice Is it OK to hang-up on your kids? In the heat of the moment, you can't set policy. The runbook's already written. Spagetti Bowl Tanzu the Shih Tzu A FinOps Type of Motion The opposite of the Sales Kickoff, the Savings Kickoff Growth is best done in the shadows. Wrapping bullshit with bullshit Nopehouse, home of the fast follower The fast followers are just in front of the also-rans Thought-leadership suicide mission Rundown VMware Explore (https://www.vmware.com/explore/us.html) How Snap rebuilt the infrastructure that now supports 347M users (https://www.protocol.com/enterprise/snap-microservices-aws-google-cloud) Screaming in the Cloud with Martin Casado (https://www.lastweekinaws.com/podcast/screaming-in-the-cloud/the-new-cloud-war-with-martin-casado/) Give finops a say over cloud architecture decisions (https://www.infoworld.com/article/3671148/give-finops-a-say-over-cloud-architecture-decisions.html) Business Dudes Need to Stop Talking Like This (https://newsletters.theatlantic.com/galaxy-brain/630ec150bcbd490021b17eab/business-dudes-need-to-stop-talking-like-this/) Relevant to your Interests Amazon tries a new way to excite you about cybersecurity (it's called laughter) (https://www.zdnet.com/article/amazon-tries-a-new-way-to-excite-you-about-cybersecurity-its-called-laughter/) The golden noose around Apple's neck (https://spectatorworld.com/topic/the-golden-noose-around-apples-neck/) Campaign pushes Cloudflare to drop trans hate site (https://www.axios.com/newsletters/axios-login-85e45e2f-8629-43d3-be69-45072a3631f5.html?chunk=0&utm_term=emshare#story0) Mudge at Twitter (https://twitter.com/igb/status/1562427951882199044) Bloomberg takes cut and paste seriously (https://twitter.com/MidwestHedgie/status/1562450905907478531) Notice of Recent Security Incident - The LastPass Blog (https://blog.lastpass.com/2022/08/notice-of-recent-security-incident/) World's Most Popular Password Manager Says It Was Hacked (https://www.bloomberg.com/news/articles/2022-08-25/the-world-s-most-popular-password-manager-says-it-was-hacked) LastPass Says No Passwords Stolen in Data Breach (https://www.cnet.com/tech/services-and-software/lastpass-says-no-passwords-stolen-in-data-breach/) AWS and Kubecost collaborate to deliver cost monitoring for EKS customers | Amazon Web Services (https://aws.amazon.com/blogs/containers/aws-and-kubecost-collaborate-to-deliver-cost-monitoring-for-eks-customers/) Pandas Pivot Table Explained (https://pbpython.com/pandas-pivot-table-explained.html) Charted: Big Tech's bigness (https://www.axios.com/newsletters/axios-login-3db6f78d-4da1-494b-a5d4-04c8984ce0e5.html?chunk=1&utm_term=emshare#story1) UK's Micro Focus shares nearly double after Canada's OpenText agrees $6 bln takeover (https://www.reuters.com/markets/deals/canadas-opentext-buy-software-firm-micro-focus-6-bln-deal-2022-08-25/) Teradata takes on Snowflake and Databricks with cloud-native platform (https://venturebeat.com/data-infrastructure/teradata-makes-database-analytics-cloud-native/) The State of the Mainframe Market - Summer 2022 (https://futurumresearch.com/market-insight-reports/the-state-of-the-mainframe-market-summer-2022/) City2Surf face recognition raises concerns (https://ia.acs.org.au/content/ia/article/2022/city2surf-face-recognition-raises-concerns.html) IBM Watson Health layoffs disguised as staff 'redeployment' (https://www.theregister.com/2022/08/29/ibm_allegedly_hid_watson_health/) David Young on LinkedIn: The metaverse economy is set to boom... gambling will be a significant (https://www.linkedin.com/posts/david-young-b5276523_metaverse-5g-localisation-activity-6966387069338218496-4x5F?utm_source=share&utm_medium=member_desktop) OCI History (https://twitter.com/solomonstre/status/1564499775415676928) VMware CEO bats away Broadcom concerns as 'next transition' (https://www.theregister.com/2022/08/30/vmware_broadcom_/) Heroku to delete inactive accounts, shut down free tier (https://www.theregister.com/2022/08/25/heroku_delete_inactive_free_tier/) Cloudflare Is One of the Companies That Quietly Powers the Internet. Researchers Say It's a Haven for Misinformation (https://time.com/6208828/cloudflare-misinformation-internet-research/) Nonsense Sounds right (https://twitter.com/6thgrade4ever/status/1433519577892327424?s=20&t=o8cx7C7pcCkVR4cTcQbv4g) When the development team meet their first Scrum Master (https://twitter.com/onejasonknight/status/1564287640366628866?s=20&t=y3AIxGPb8kge28aICQ6dFQ) Chart of the year nominee (https://twitter.com/jpwarren/status/1564109454009716736/photo/1) Conferences DevOps Talks Sydney (https://devops.talksplus.com/sydney/devops.html), Sydney, September 6-7, 2022 Sydney Cloud FinOps Meetup (https://events.finops.org/events/details/finops-sydney-cloud-finops-presents-sydney-cloud-finops-meetup/), online, Oct 13, 2022 Matt's presenting Kube (https://events.linuxfoundation.org/kubecon-cloudnativecon-north-america/https://events.linuxfoundation.org/kubecon-cloudnativecon-north-america/)C (https://events.linuxfoundation.org/kubecon-cloudnativecon-north-america/https://events.linuxfoundation.org/kubecon-cloudnativecon-north-america/)o (https://events.linuxfoundation.org/kubecon-cloudnativecon-north-america/https://events.linuxfoundation.org/kubecon-cloudnativecon-north-america/)n North America (https://events.linuxfoundation.org/kubecon-cloudnativecon-north-america/https://events.linuxfoundation.org/kubecon-cloudnativecon-north-america/), Detroit, Oct 24 – 28, 2022 SpringOne Platform (https://springone.io/?utm_source=cote&utm_medium=podcast&utm_content=sdt), SF, December 6–8, 2022 THAT Conference Texas Call For Counselors (https://that.us/call-for-counselors/tx/2023/) Jan 16-19, 2023 Listener Feedback Enlightning (https://tanzu.vmware.com/developer/tv/enlightning/) from Whitney SDT news & hype Join us in Slack (http://www.softwaredefinedtalk.com/slack). Get a SDT Sticker! Send your postal address to stickers@softwaredefinedtalk.com (mailto:stickers@softwaredefinedtalk.com) and we will send you free laptop stickers! Follow us on Twitch (https://www.twitch.tv/sdtpodcast), Twitter (https://twitter.com/softwaredeftalk), Instagram (https://www.instagram.com/softwaredefinedtalk/), LinkedIn (https://www.linkedin.com/company/software-defined-talk/) and YouTube (https://www.youtube.com/channel/UCi3OJPV6h9tp-hbsGBLGsDQ/featured). Use the code SDT to get $20 off Coté's book, (https://leanpub.com/digitalwtf/c/sdt) Digital WTF (https://leanpub.com/digitalwtf/c/sdt), so $5 total. Become a sponsor of Software Defined Talk (https://www.softwaredefinedtalk.com/ads)! Recommendations Brandon: Black Bird (https://www.rottentomatoes.com/tv/black_bird/s01) Matt: BirdNetPi (https://birdnetpi.com/) Festival of Feet Half-Marathon (https://www.westiesjoggers.com/the-georges-river-festival-of-the-feet/) Coté: Spigen ArcDock 120W [GaN III] 4-Port USB C Charging Stantion USB-C PD/USB-A Hub with Spigen USB 4 Cable for Thunderbolt 4 Cable 100W Charging 40Gbps Data Transfer for MacBook Pro Air iPad USB-C Laptop (https://amzn.to/3RqRl7M). C7/C8 coupler cables Photo Credits CoverArt (https://unsplash.com/photos/Ts3yX7wDthw) Banner (https://unsplash.com/photos/hXttDVCwyRA)

About MartinMartin Casado is a general partner at the venture capital firm Andreessen Horowitz where he focuses on enterprise investing. He was previously the cofounder and chief technology officer at Nicira, which was acquired by VMware for $1.26 billion in 2012. While at VMware, Martin was a fellow, and served as senior vice president and general manager of the Networking and Security Business Unit, which he scaled to a $600 million run-rate business by the time he left VMware in 2016.Martin started his career at Lawrence Livermore National Laboratory where he worked on large-scale simulations for the Department of Defense before moving over to work with the intelligence community on networking and cybersecurity. These experiences inspired his work at Stanford where he created the software-defined networking (SDN) movement, leading to a new paradigm of network virtualization. While at Stanford he also cofounded Illuminics Systems, an IP analytics company, which was acquired by Quova Inc. in 2006.For his work, Martin was awarded both the ACM Grace Murray Hopper award and the NEC C&C award, and he's an inductee of the Lawrence Livermore Lab's Entrepreneur's Hall of Fame. He holds both a PhD and Masters degree in Computer Science from Stanford University.Martin serves on the board of ActionIQ, Ambient.ai, Astranis, dbt Labs, Fivetran, Imply, Isovalent, Kong, Material Security, Netlify, Orbit, Pindrop Security, Preset, RapidAPI, Rasa, Tackle, Tecton, and Yubico.Links: Yet Another Infra Group Discord Server: https://discord.gg/f3xnJzwbeQ “The Cost of Cloud, a Trillion Dollar Paradox” - https://a16z.com/2021/05/27/cost-of-cloud-paradox-market-cap-cloud-lifecycle-scale-growth-repatriation-optimization/ TranscriptAnnouncer: Hello, and welcome to Screaming in the Cloud with your host, Chief Cloud Economist at The Duckbill Group, Corey Quinn. This weekly show features conversations with people doing interesting work in the world of cloud, thoughtful commentary on the state of the technical world, and ridiculous titles for which Corey refuses to apologize. This is Screaming in the Cloud.Corey: This episode is sponsored in part by Honeycomb. When production is running slow, it's hard to know where problems originate. Is it your application code, users, or the underlying systems? I've got five bucks on DNS, personally. Why scroll through endless dashboards while dealing with alert floods, going from tool to tool to tool that you employ, guessing at which puzzle pieces matter? Context switching and tool sprawl are slowly killing both your team and your business. You should care more about one of those than the other; which one is up to you. Drop the separate pillars and enter a world of getting one unified understanding of the one thing driving your business: production. With Honeycomb, you guess less and know more. Try it for free at honeycomb.io/screaminginthecloud. Observability: it's more than just hipster monitoring.Corey: This episode is sponsored in part by our friends at Sysdig. Sysdig secures your cloud from source to run. They believe, as do I, that DevOps and security are inextricably linked. If you wanna learn more about how they view this, check out their blog, it's definitely worth the read. To learn more about how they are absolutely getting it right from where I sit, visit Sysdig.com and tell them that I sent you. That's S Y S D I G.com. And my thanks to them for their continued support of this ridiculous nonsense.Corey: Welcome to Screaming in the Cloud. I'm Corey Quinn. I'm joined today by someone who has taken a slightly different approach to being—well, we'll call it cloud skepticism here. Martin Casado is a general partner at Andreessen Horowitz and has been on my radar starting a while back, based upon a piece that he wrote focusing on the costs of cloud and how repatriation is going to grow. You wrote that in conjunction with your colleague, Sarah Wang. Martin, thank you so much for joining me. What got you onto that path?Martin: So, I want to be very clear, just to start with is, I think cloud is the biggest innovation that we've seen in infrastructure, probably ever. It's a core part of the industry. I think it's very important, I think every company's going to be using cloud, so I'm very pro-cloud. I just think the nature of how you use clouds is shifting. And that was the focus.Corey: When you first put out your article in conjunction with your colleague as well, like, I saw it and I have to say that this was the first time I'd really come across any of your work previously. And I have my own biases that I started from, so my opening position on reading it was this is just some jerk who's trying to say something controversial and edgy to get attention. That's my frickin job. Excuse me, sir. And who is this clown?So, I started digging, and what I found really changed my perspective because as mentioned at the start of the show, you are a general partner at Andreessen Horowitz, which means you are a VC. You are definitionally almost the archetype of a VC in that sense. And to me, being a venture capitalist means the most interesting thing about you is that you write a large check consisting of someone else's money. And that's never been particularly interesting.Martin: [laugh].Corey: You kind of cut against that grain and that narrative. You have a master's and a PhD in computer science from Stanford; you started your career at one of the national labs—Laurence Livermore, if memory serves—you wound up starting a business, Nicira, if I'm pronouncing that correctly—Martin: Yeah, yeah, yeah.Corey: That you then sold to VMware in 2012, back at a time when that was a noble outcome, rather than a state of failure because VMware is not exactly what it once was. You ran a $600 million a year business while you were there. Basically, the list of boards that you're on is lengthy enough and notable enough that it sounds almost like you're professionally bored, so I don't—Martin: [laugh].Corey: So, looking at this, it's okay, this is someone who actually knows what he is talking about, not just, “Well, I talked to three people in pitch meetings and I now think I know what is going on in this broader industry.” You pay attention, and you're connected, disturbingly well, to what's going on, to the point where if you see something, it is almost certainly rooted in something that is happening. And it's a big enough market that I don't think any one person can keep their finger on the pulse of everything. So, that's when I started really digging into it, paying attention, and more or less took a lot of what you wrote as there are some theses in here that I want to prove or disprove. And I spent a fair bit of time basically threatening, swindling, and bribing people with infinite cups of coffee in order to start figuring out what is going on.And I am begrudgingly left with no better conclusion than you have a series of points in here that are very challenging to disprove. So, where do you stand today, now that, I guess, the whole rise and fall of the hype around your article on cloud repatriation—which yes, yes, we'll put a link to it in the show notes if people want to go there—but you've talked about this in a lot of different contexts. Having had the conversations that you've had, and I'm sure some very salty arguments with people who have a certain vested interest in you being wrong, do you wind up continuing to stand by the baseline positions that you've laid out, or have they evolved into something more nuanced?Martin: So yeah, I definitely want to point out, so this was work done with Sarah Wang was also at Andreessen Horowitz; she's also a GP. She actually did the majority of the analysis and she's way smarter than I am. [laugh]. And so, I'm just very—feel very lucky to work with her on this. And I want to make sure she gets due credit on this.So, let's talk about the furor. So like, I actually thought that this was kind of interesting and it started a good discussion, but instead, like, [laugh] the amount of, like, response pieces and, like, angry emails I got, and [laugh] like, I mean it just—and I kind of thought to myself, like, “Why are people so upset?” I think there's three reasons. I'm going to go through them very quickly because they're interesting.So, the first one is, like, you're right, like, I'm a VC. I think people see a VC and they're like, oh, lack of credibility, lack of accountability, [laugh], you know, doesn't know what they're doing, broad pattern matcher. And, like, I will say, like, I did not necessarily write this as a VC; I wrote this as somebody that's, like, listen, my PhD is an infrastructure; my company was an infrastructure. It's all data center stuff. I had a $600 million a year data center business that sold infrastructure into data centers. I've worked with all of the above. Like, I've worked with Amazon, I've—Corey: So, you sold three Cisco switches?Martin: [laugh]. That's right.Corey: I remember those days. Those were awesome, but not inexpensive.Martin: [laugh]. That's right. Yeah, so like, you know, I had 15 years. It's kind of a culmination of that experience. So, that was one; I just think that people see VC and they have a reaction.The second one is, I think people still have the first cloud wars fresh in their memories and so they just don't know how to think outside of that. So, a lot of the rebuttals were first cloud war rebuttals. Like, “Well, but internal IT is slow and you can't have the expertise.” But like, they just don't apply to the new world, right? Like, listen, if you're Cloudflare, to say that you can't run, like, a large operation is just silly. If you went to Cloudflare and you're like, “Listen, you can't run your own infrastructure,” like, they'd take out your sucker and pat you on the head. [laugh].Corey: And not for nothing, if you try to run what they're doing on other cloud providers from a pure bandwidth perspective, you don't have a company anymore, regardless of how well funded you are. It's a never-full money pit that just sucks all of the money. And I've talked to a number of very early idea stage companies that aren't really founded yet about trying to do things like CDN-style work or streaming video, and a lot of those questions start off with well, we did some back-of-the-envelope math around AWS data transfer pricing, and if our numbers are right, when we scale, we'll be spending $65,000 on data transfer every minute. What did we get wrong?And it's like, “Oh, yeah, you realize that one thing is per hour not per minute, so slight difference there. But no, you're basically correct. Don't do it.” And yeah, no one pays retail price at that volume, but they're not going to give you a 99.999% discount on these things, so come up with a better plan. Cloudflare's business will not work on AWS, full stop.Martin: Yep, yep. So, I legitimately know, basically, household name public companies that are software companies that anybody listening to this knows the name of these companies, who have product lines who have 0% margins because they're [laugh] basically, like, for every dollar they make, they pay a dollar to Amazon. Like, this is a very real thing, right? And if you go to these companies, these are software infrastructure companies; they've got very talented teams, they know how to build, like, infrastructure. To tell them that like, “Well, you know, you can't build your own infrastructure,” or something is, I mean, it's like telling, like, an expert in the business, they can't do what they do; this is what they do. So, I just think that part of the furor, part of the uproar, was like, I just think people were stuck in this cloud war 1.0 mindset.I think the third thing is, listen, we've got an oligopoly, and they employ a bunch of people, and they've convinced a bunch of people they're right, and it's always hard to change that. And I also think there's just a knee-jerk reaction to these big macro shifts. And it was the same thing we did to software-defined networking. You know, like, my grad school work was trying to change networking to go from hardware to software. I remember giving a talk at Cisco, and I was, like, this kind of like a naive grad student, and they literally yelled at me out of the room. They're like, it'll never work.Corey: They tried to burn you as a witch, as I recall.Martin: [laugh]. And so, your specific question is, like, have our views evolved? But the first one is, I think that this macro downturn really kind of makes the problem more acute. And so, I think the problem is very, very real. And so, I think the question is, “Okay, so what happens?”So, let's say if you're building a new software company, and you have a choice of using, like, one of the Big Three public clouds, but it impacts your margins so much that it depresses your share price, what do you do? And I think that we thought a lot more about what the answers there are. And the ones that I think that we're seeing is, some actually are; companies are building their own infrastructure. Like, very famously MosaicML is building their own infrastructure. Fly.io, -building their own infrastructure.Mighty—you know, Suhail's company—building his own infrastructure. Cloudflare has their own infrastructure. So, I think if you're an infrastructure provider, a very reasonable thing to do is to build your own infrastructure. If you're not a core infrastructure provider, you're not; you can still use somebody's infrastructure that's built at a better cost point.So, for example, if I'm looking at a CDN tier, I'm going to use Fly.io, right? I mean, it's like, it's way cheaper, the multi-region is way better, and so, like, I do think that we're seeing, like, almost verticalized clouds getting built out that address this price point and, like, these new use cases. And I think this is going to start happening more and more now. And we're going to see basically almost the delamination of the cloud into these verticalized clouds.Corey: I think there's also a question of scale, where if you're starting out in the evening tonight, to—I want to build, I don't know Excel as a service or something. Great. You're pretty silly if you're not going to start off with a cloud provider, just because you can get instant access to resources, and if your product catches on, you scale out without having to ever go back and build it as quote-unquote “Enterprise grade,” as opposed to having building it on cheap servers or Raspberry Pis or something floating around. By the time that costs hit a certain point—and what that point is going to depend on your stage of company and lifecycle—you're remiss if you don't at least do an analysis on is this the path we want to continue on for the service that we're offering?And to be clear, the answer to this is almost entirely going to be bounded by the context of your business. I don't believe that companies as a general rule, make ill-reasoned decisions. I think that when we see a decision a company makes, by and large, there's context or constraints that we don't see that inform that. I know, it's fun to dunk on some of the large companies' seemingly inscrutable decisions, but I will say, having had the privilege to talk to an awful lot of execs in an awful lot of places—particularly on this show—I don't find myself encountering a whole lot of people in those roles who I come away with thinking that they're a few fries short of a Happy Meal. They generally are very well reasoned in why they do what they do. It's just a question of where we think the future is going on some level.Martin: Yep. So, I think that's absolutely right. So, to be a little bit more clear on what I think is happening with the cloud, which is I think every company that gets created in tech is going to use the cloud for something, right? They'll use it for development, the website, test, et cetera. And many will have everything in the cloud, right?So, the cloud is here to stay, it's going to continue to grow, it's a very important piece of the ecosystem, it's very important piece of IT. I'm very, very pro cloud; there's a lot of value. But the one area that's under pressure is if your product is SaaS if your product is selling Software as a Service, so then your product is basically infrastructure, now you've got a product cost model that includes the infrastructure itself, right? And if you reduce that, that's going to increase your margin. And so, every company that's doing that should ask the question, like, A, is the Big Three the right one for me?Maybe a verticalized cloud—like for example, whatever Fly or Mosaic or whatever is better because the cost is better. And I know how to, you know, write software and run these things, so I'll use that. They'll make that decision or maybe they'll build their own infrastructure. And I think we're going to see that decision happening more and more, exactly because now software is being offered as a service and they can do that. And I just want to make the point, just because I think it's so important, that the clouds did exactly this to the hardware providers. So, I just want to tell a quick story, just because for me, it's just so interesting. So—Corey: No, please, I was only really paying attention to this market from 2016 or so. There was a lot of the early days that I was using as a customer, but I wasn't paying attention to the overall industry trends. Please, storytime. This is how I learned things. I hang out with smart people and I come away a little bit smarter than when I started.Martin: [laugh]. This is, like, literally my fa—this is why this is one of my favorite topics is what I'm about to tell you, which is, so the clouds have always had this argument, right? The big clouds, three clouds, they're like, “Listen, why would you build your own cloud? Because, like, you don't have the expertise, and it's hard and you don't have economies of scale.” Right?And the answer is you wouldn't unless it impacts your share price, right? If it impacts your share price, then of course you would because it makes economic sense. So, the clouds had that exact same dilemma in 2005, right? So, in 2005, Google and Amazon and Microsoft, they looked at their COGS, they looked like, “Okay, I'm offering a cloud. If I look at the COGS, who am I paying?”And it turns out, there was a bunch of hardware providers that had 30% margins or 70% margins. They're like, “Why am I paying Cisco these big margins? Why am I paying Dell these big margins?” Right? So, they had the exact same dilemma.And all of the arguments that they use now applied then, right? So, the exact same arguments, for example, “AWS, you know nothing about hardware. Why would you build hardware? You don't have the expertise. These guys sell to everybody in the world, you don't have the economies of scale.”So, all of the same arguments applied to them. And yet… and yes because it was part of COGS] that it impacted the share price, they can make the economic argument to actually build hardware teams and build chips. And so, they verticalized, right? And so, it just turns out if the infrastructure becomes parts of COGS, it makes sense to optimize that infrastructure. And I would say, the Big Three's foray into OEMs and hardware is a much, much, much bigger leap than an infrastructure company foraying into building their own infrastructure.Corey: There's a certain startup cost inherent to all these things. And the small version of that we had in every company that we started in a pre-cloud era: renting virtual computers from vendors was a thing, but it was still fraught and challenging and things that we use, then, like, GoGrid no longer exist, for good reason. But the alternative was, “Great, I'm going to start building and seeing if this thing has any traction.” Well, you need to go lease a rack somewhere and buy servers from Dell, and they're going to do the fast expedited option, which means only six short weeks until they show up in the data center and then gets sent away because they weren't expecting to receive them. And you wind up with this entire universe of hell between cross-connects and all the rest.And that's before you can ever get anything in front of customers or users to see what happens. Now, it's a swipe of a credit card away and your evening's experiments round up to 25 cents. That was significant. Having to make these significant tens of thousands of dollars of investment just to launch is no longer true. And I feel like that was a great equalizer in some respects.Martin: Yeah, I think that—Corey: And that cost has been borne by the astonishing level of investment that the cloud providers themselves have made. And that basically means that we don't have to. But it does come at a cost.Martin: I think it's also worth pointing out that it's much easier to stand up your own infrastructure now than it has been in the past, too. And so, I think that there's a gradient here, right? So, if you're building a SaaS app, [laugh] you would be crazy not to use the cloud, you just be absolutely insane, right? Like, what do you know about core infrastructure? You know, what do you know about building a back-end? Like, what do you know about operating these things? Go focus on your SaaS app.Corey: The calluses I used to have from crimping my own Ethernet patch cables in data centers have faded by now. I don't want them to come back. Yeah, we used to know how to do these things. Now, most people in most companies do not have that baseline of experience, for excellent reasons. And I wouldn't wish that on the current generation of engineers, except for the ones I dislike.Martin: However, that is if you're building an application. Almost all of my investments are people that are building infrastructure. [laugh]. They're already doing these hardcore backend things; that's what they do: they sell infrastructure. Would you think, like, someone, like, at Databricks doesn't understand how to run infr—of course it does. I mean, like, or Snowflake or whatever, right?And so, this is a gradient. On the extreme app end, you shouldn't be thinking about infrastructure; just use the cloud. Somewhere in the middle, maybe you start on the cloud, maybe you don't. As you get closer to being a cloud service, of course you're going to build your own infrastructure.Like, for example—listen, I mean, I've been mentioning Fly; I just think it's a great example. I mean, Fly is a next-generation CDN, that you can run compute on, where they build their own infrastructure—it's a great developer experience—and they would just be silly. Like, they couldn't even make the cost model work if they did it on the cloud. So clearly, there's a gradient here, and I just think that you would be remiss and probably negligent if you're selling software not to have this conversation, or at least do the analysis.Corey: This episode is sponsored in part by our friend EnterpriseDB. EnterpriseDB has been powering enterprise applications with PostgreSQL for 15 years. And now EnterpriseDB has you covered wherever you deploy PostgreSQL on-premises, private cloud, and they just announced a fully-managed service on AWS and Azure called BigAnimal, all one word. Don't leave managing your database to your cloud vendor because they're too busy launching another half-dozen managed databases to focus on any one of them that they didn't build themselves. Instead, work with the experts over at EnterpriseDB. They can save you time and money, they can even help you migrate legacy applications—including Oracle—to the cloud. To learn more, try BigAnimal for free. Go to biganimal.com/snark, and tell them Corey sent you.Corey: I think there's also a philosophical shift, where a lot of the customers that I talk to about their AWS bills want to believe something that is often not true. And what they want to believe is that their AWS bill is a function of how many customers they have.Martin: Oh yeah.Corey: In practice, it is much more closely correlated with how many engineers they've hired. And it sounds like a joke, except that it's not. The challenge that you have when you choose to build in a data center is that you have bounds around your growth because there are capacity concerns. You are going to run out of power, cooling, and space to wind up having additional servers installed. In cloud, you have an unbounded growth problem.S3 is infinite storage, and the reason I'm comfortable saying that is that they can add hard drives faster than you can fill them. For all effective purposes, it is infinite amounts of storage. There is no forcing function that forces you to get rid of things. You spin up an instance, the natural state of it in a data center as a virtual machine or a virtual instance, is that it's going to stop working two to three years left on maintain when a raccoon hauls it off into the woods to make a nest or whatever the hell raccoons do. In cloud, you will retire before that instance does is it gets migrated to different underlying hosts, continuing to cost you however many cents per hour every hour until the earth crashes into the sun, or Amazon goes bankrupt.That is the trade-off you're making. There is no forcing function. And it's only money, which is a weird thing to say, but the failure mode of turning something off mistakenly that takes things down, well that's disastrous to your brand and your company. Just leaving it up, well, it's only money. It's never a top-of-mind priority, so it continues to build and continues to build and continues to build until you're really forced to reckon with a much larger problem.It is a form of technical debt, where you've kicked the can down the road until you can no longer kick that can. Then your options are either go ahead and fix it or go back and talk to you folks, and it's time for more money.Martin: Yeah. Or talk to you. [laugh].Corey: There is that.Martin: No seriously, I think everybody should, honestly. I think this is a board-level concern for every compa—I sit on a lot of boards; I see this. And this has organically become a board-level concern. I think it should become a conscious board-level concern of, you know, cloud costs, impact COGS. Any software company has it; it always becomes an issue, and so it should be treated as a first-class problem.And if you're not thinking through your options—and I think by the way, your company is a great option—but if you're not thinking to the options, then you're almost fiduciarily negligent. I think the vast, vast majority of people and vast majority of companies are going to stay on the cloud and just do some basic cost controls and some just basic hygiene and they're fine and, like, this doesn't touch them. But there are a set of companies, particularly those that sell infrastructure, where they may have to get more aggressive. And that ecosystem is now very vibrant, and there's a lot of shifts in it, and I think it's the most exciting place [laugh] in all of IT, like, personally in the industry.Corey: One question I have for you is where do you draw the line around infrastructure companies. I tend to have an evolving view of it myself, where things that are hard and difficult do not become harder with time. It used to require a deep-level engineer with a week to kill to wind up compiling and building a web server. Now, it is evolved and evolved and evolved; it is check a box on a webpage somewhere and you're serving a static website. Managed databases, I used to think, were something that were higher up the stack and not infrastructure. Today, I'd call them pretty clearly infrastructure.Things seem to be continually, I guess, a slipping beneath the waves to borrow an iceberg analogy. And it's only the stuff that you can see that is interesting and differentiated, on some level. I don't know where the industry is going at all, but I continue to think of infrastructure companies as being increasingly broad.Martin: Yeah, yeah, yeah. This is my favorite question. [laugh]. I'm so glad you asked. [laugh].Corey: This was not planned to be clear.Martin: No, no, no. Listen, I am such an infrastructure maximalist. And I've changed my opinion on this so much in the last three years. So, it used to be the case—and infrastructure has a long history of, like, calling the end of infrastructure. Like, every decade has been the end of infrastructure. It's like, you build the primitives and then everything else becomes an app problem, you know?Like, you build a cloud, and then we're done, you know? You build the PC and then we're done. And so, they are even very famous talks where people talk about the end of systems when we've be built everything right then. And I've totally changed my view. So, here's my current view.My current view is, infrastructure is the only, really, differentiation in systems, in all IT, in all software. It's just infrastructure. And the app layer is very important for the business, but the app layer always sits on infrastructure. And the differentiations in app is provided by the infrastructure. And so, the start of value is basically infrastructure.And the design space is so huge, so huge, right? I mean, we've moved from, like, PCs to cloud to data. Now, the cloud is decoupling and moving to the CDN tier. I mean, like, the front-end developers are building stuff in the browser. Like, there's just so much stuff to do that I think the value is always going to accrue to infrastructure.So, in my view, anybody that's improving the app accuracy or performance or correctness with technology is an infrastructure company, right? And the more of that you do, [laugh] the more infrastructure you are. And I think, you know, in 30 years, you and I are going to be old, and we're going to go back on this podcast. We're going to talk and there's going to be a whole bunch of infrastructure companies that are being created that have accrued a lot of value. I'm going to say one more thing, which is so—okay, this is a sneak preview for the people listening to this that nobody else has heard before.So Sarah, and I are back at it again, and—the brilliant Sarah, who did the first piece—and we're doing another study. And the study is if you look at public companies and you look at ones that are app companies versus infrastructure companies, where does the value accrue? And there's way, way more app companies; there's a ton of app companies, but it turns out that infrastructure companies have higher multiples and accrue more value. And that's actually a counter-narrative because people think that the business is the apps, but it just turns out that's where the differentiation is. So, I'm just an infra maximalist. I think you could be an infra person your entire career and it's the place to be. [laugh].Corey: And this is the real value that I see of looking at AWS bills. And our narrative is oh, we come in and we fix the horrifying AWS bill. And the naive pass is, “Oh, you cut the bill and make it lower?” Not always. Our primary focus has been on understanding it because you get a phone-number-looking bill from AWS. Great, you look at it, what's driving the cost? Storage.Okay, great. That doesn't mean anything to the company. They want to know what teams are doing this. What's it going to cost for them to add another thousand monthly active users? What is the increase in cost? How do they wind up identifying their bottlenecks? How do they track and assign portions of their COGS to different aspects of their service? How do they trace the flow of capital for their organization as they're serving their customers?And understanding the bill and knowing what to optimize and what not to becomes increasingly strategic business concern.Martin: Yeah.Corey: That's the fun part. That's the stuff I don't see that software has a good way of answering, just because there's no way to use an API to gain that kind of business context. When I started this place, I thought I was going to be building software. It turns out, there's so many conversations that have to happen as a part of this that cannot be replicated by software. I mean, honestly, my biggest competitor for all this stuff is Microsoft Excel because people want to try and do it themselves internally. And sometimes they do a great job, sometimes they don't, but it's understanding their drivers behind their cost. And I think that is what was often getting lost because the cloud obscures an awful lot of that.Martin: Yeah. I think even just summarize this whole thing pretty quickly, which is, like, I do think that organically, like, cloud cost has become a board-level issue. And I think that the shift that founders and execs should make is to just, like, treat it like a first-class problem upfront. So, what does that mean? Minimally, it means understanding how these things break down—A, to your point—B, there's a number of tools that actually help with onboarding of this stuff. Like, Vantage is one that I'm a fan of; it just provides some visibility.And then the third one is if you're selling Software as a Service, that's your core product or software, and particularly it's a infrastructure, if you don't actually do the analysis on, like, how this impacts your share price for different cloud costs, if you don't do that analysis, I would say your fiduciarily negligent, just because the impact would be so high, especially in this market. And so, I think, listen, these three things are pretty straightforward and I think anybody listening to this should consider them if you're running a company, or you're an executive company.Corey: Let's be clear, this is also the kind of problem that when you're sitting there trying to come up with an idea for a business that you can put on slide decks and then present to people like you, these sounds like the paradise of problems to have. Like, “Wow, we're successful and our business is so complex and scaled out that we don't know where exactly a lot of these cost drivers are coming from.” It's, “Yeah, that sounds amazing.” Like, I remember those early days, back when all I was able to do and spend time on and energy on was just down to the idea of, ohh, I'm getting business cards. That's awesome. That means I've made it as a business person.Spoiler: it did not. Having an aggressive Twitter presence, that's what made me as a business person. But then there's this next step and this next step and this next step and this next step, and eventually, you look around and realize just how overwrought everything you've built is and how untangling it just becomes a bit of a challenge and a hell of a mess. Now, the good part is at that point of success, you can bring people in, like, a CFO and a finance team who can do some deep-level analysis to help identify what COGS is—or in some cases, have some founders, explain what COGS is to you—and understand those structures and how you think about that. But it always feels like it's a trailing problem, not an early problem that people focus on.Martin: I'll tell you the reason. The reason is because this is a very new phenomenon that it's part of COGS. It's literally five years new. And so, we're just catching up. Even now, this discussion isn't what it was when we first wrote the post.Like, now people are pretty educated on, like, “Oh yeah, like, this is really an issue. Oh, yeah. It contributes to COGS. Oh, yeah. Like, our stock price gets hit.” Like, it's so funny to watch, like, the industry mature in real-time. And I think, like, going forward, it's just going to be obvious that this is a board-level issue; it's going to be obvious this is, like, a first-class consideration. But I agree with you. It's like, listen, like, the industry wasn't ready for it because we didn't have public companies. A lot of public companies, like, this is a real issue. I mean really we're talking about the last five, seven years.Corey: It really is neat, just in real time watching how you come up with something that sounds borderline heretical, and in a relatively short period of time, becomes accepted as a large-scale problem, and now it's now it is fallen off of the hype train into, “Yeah, this is something to be aware of.” And people's attention spans have already jumped to the next level and next generation of problem. It feels like this used to take way longer for these cycles, and now everything is so rapid that I almost worry that between the time we're recording this and the time that it publishes in a few weeks, what is going to have happened that makes this conversation irrelevant? I didn't used to have to think like that. Now, I do.Martin: Yeah, yeah, yeah, for sure. Well, just a couple of things. I want to talk about, like, one of the reasons that accelerated this, and then when I think is going forward. So, one of the reasons this was accelerated was just the macro downturn. Like, when we wrote the post, you could make the argument that nobody cares about margins because it's all about growth, right?And so, like—and even then, it still saved a bunch of money, but like, a lot of people were like, “Listen, the only thing that matters is growth.” Now, that's absolutely not the case if you look at public market valuations. I mean, people really care about free cash flow, they really care about profitability, and they really care about margins. And so, it's just really forced the issue. And it also, like, you know, made kind of what we were saying very, very clear.I would say, you know, as far as shifts that are going, I think one of the biggest shifts is for every back-end developer, there's, like, a hundred front-end developers. It's just crazy. And those front-end developers—Corey: A third of a DevOps engineer.Martin: [laugh]. True. I think those front-end developers are getting, like, better tools to build complete apps, right? Like, totally complete apps, right? Like they've got great JavaScript frameworks that coming out all the time.And so, you could argue that actually a secular technology change—which is that developers are now rebuilding apps as kind of front-end applications—is going to pull compute away from the clouds anyways, right? Like if instead of, like, the app being some back-end thing running in AWS, but instead is a front-end thing, you know, running in a browser at the CDN tier, while you're still using the Big Three clouds, it's being used in a very different way. And we may have to think about it again differently. Now, this, again, is a five-year going forward problem, but I do feel like there are big shifts that are even changing the way that we currently think about cloud now. And we'll see.Corey: And if those providers don't keep up and start matching those paradigms, there's going to be an intermediary shim layer of companies that wind up converting their resources and infrastructure into things that suit this new dynamic, and effectively, they're going to become the next version of, I don't know, Level 3, one of those big underlying infrastructure companies that most people have never heard of or have to think about because they're not doing anything that's perceived as interesting.Martin: Yeah, I agree. And I honestly think this is why Cloudflare and Cloudflare work is very interesting. This is why Fly is very interesting. It's a set of companies that are, like, “Hey, listen, like, workloads are moving to the front-end and, you know, you need compute closer to the user and multi-region is really important, et cetera.” So, even as we speak, we're seeing kind of shifts to the way the cloud is moving, which is just exciting. This is why it's, like, listen, infrastructure is everything. And, like, you and I like if we live to be 200, we can do [laugh] a great infrastructure work every year.Corey: I'm terrified, on some level, that I'll still be doing the exact same type of thing in 20 years.Martin: [laugh].Corey: I like solving different problems as we go. I really want to thank you for spending so much time talking to me today. If people want to learn more about what you're up to, slash beg you for other people's money or whatnot, where's the best place for them to find you?Martin: You know, we've got this amazing infrastructure Discord channel. [laugh].Corey: Really? I did not know that.Martin: I love it. It's, like, the best. Yeah, my favorite thing to do is drink coffee and talk about infrastructure. And like, I posted this on Twitter and we've got, like, 600 people. And it's just the best thing. So, that's honestly the best way to have these discussions. Maybe can you put, like, the link in, like, the show notes?Corey: Oh, absolutely. It is already there in the show notes. Check the show notes. Feel free to join the infrastructure Discord. I will be there waiting for you.Martin: Yeah, yeah, yeah. That'll be fantastic.Corey: Thank you so much for being so generous with your time. I appreciate it.Martin: This was great. Likewise, Corey. You're always a class act and I really appreciate that about you.Corey: I do my best. Martin Casado, general partner at Andreessen Horowitz. I'm Cloud Economist Corey Quinn, and this is Screaming in the Cloud. If you've enjoyed this podcast, please leave a five-star review on your podcast platform of choice, whereas if you've hated this podcast, please leave a five-star review on your podcast platform of choice along with an angry comment telling me that I got it completely wrong and what check you wrote makes you the most interesting.Announcer: The content here is for informational purposes only and should not be taken as legal, business, tax, or investment advice, or be used to evaluate any investment or security and is not directed at any investors or potential investors in any a16z fund. For more details, please see a16z.com/disclosures.Corey: If your AWS bill keeps rising and your blood pressure is doing the same, then you need The Duckbill Group. We help companies fix their AWS bill by making it smaller and less horrifying. The Duckbill Group works for you, not AWS. We tailor recommendations to your business and we get to the point. Visit duckbillgroup.com to get started.Announcer: This has been a HumblePod production. Stay humble.

In this episode from December 2018, Hennessy, currently the chairman of Alphabet as well as Turing Award-winning computer scientist, joins a16z co-founder Marc Andreessen, a16z general partner Martin Casado, and host Sonal Choksi for a wide-ranging conversation about moving from academia to startups, the history of Silicon Valley, the “Stanford model”, how to build enduring organizations, and more.Hennessy also co-founded startups, including one based on pioneering microprocessor architecture used in 99% of devices today (for which he and his collaborator won the prestigious Turing Award)... so what did it take to go from research/idea to industry/implementation? And  how has the overall relationship and "divide" between academia and industry shifted, especially as the tech industry itself has changed? Finally, in his book, Leading Matters, Hennessy shares some of the leadership principles he's learned, offering nuanced takes on topics like humility (needs ambition), empathy (without contravening fairness and reason), and others. What does it take to build not just tech, but a successful organization?

Welcome to the ninth episode of The Better Podcast! We're your co-hosts CHIN Hui Leong and CHONG Ser Jing. In The Better Podcast, we want you to get better at this game called life, together with us. This podcast is designed to share what we've learnt about life, business, investing, and so much more.If you prefer videos of our conversations, we have a Youtube channel too, which you can find here!For our ninth episode, we discussed a whole bunch of things, including:The history of Visa (and the creation of its network effect), from its earliest days as a card scheme created by Bank of America, to how it became adopted by banks all across the USAThe brilliance of Dee Hock, one of Visa's early leaders, in setting the stage for the company's future growth by (1) running Visa in a decentralised manner, and (2) creating important constraints for banks who were using the card scheme, that ended up being de-constraining (throwback to Episode 8!)The importance of Bank of America spinning out Visa as an independent entity, and how Amazon could potentially make its cloud-computing arm, AWS (Amazon Web Services), an even more valuable entity by allowing it become a stand-alone companyHow innovation in organisations could better flourish if individuals were given greater autonomy and freedom to explore in a decentralised wayThe idea that as markets become larger, individual units within the market can become sizeable businesses - for example, an early Ford Motors factory had to bring in rubber, coal, metals, etc; in contrast, a modern automobile factory would have specialised suppliersWhy Michelin, a tire manufacturer, ended up recommending restaurantsA funny anecdote on how traditional financial institutions in Indonesia still cannot handle digitalisation todayNothing on this show should be taken as investment advice. It is purely for informational and entertainment purposes only. All opinions expressed in this show by us and our guests are solely our own opinions. We and our guests may hold positions in the financial assets discussed in the show. These holdings are subject to change at any time.We value your feedback, so let us know your thoughts! Contact us at thebetterpodcaster@gmail.comShow NotesArticle on Visa's history by Fast Company: LinkPodcast featuring Kenneth Stanley that describes how companies should handle innovation for better results: LinkPodcast featuring Martin Casado that features the idea of how markets become granularized over time as they become larger: Link This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit thebetterpodcast.substack.com

Matt Bornstein and Jennifer Li (and their co-author Martin Casado) of a16z have compiled arguably the most nuanced diagram of the data ecosystem ever made.  They recently refreshed their classic 2020 post, "Emerging Architectures for Modern Data Infrastructure" and in this conversation, Tristan attempts to pin down: what does all of this innovation in tooling mean for data people + the work we're capable of doing? When will the glorious future come to our laptops? For full show notes and to read 6+ years of back issues of the podcast's companion newsletter, head to https://roundup.getdbt.com.  The Analytics Engineering Podcast is sponsored by dbt Labs.

My guest today is Martin Casado. Martin is a general partner at Andreessen Horowitz where he focuses on digital infrastructure. Before joining a16z, Martin pioneered software-defined networking and co-founded Nicira, which was bought by VMware for $1.3 billion in 2012. Martin has studied, built, and invested in digital infrastructure his whole career and is the perfect person to discuss the most interesting aspects of the industry. Please enjoy this great conversation with Martin Casado.   For the full show notes, transcript, and links to mentioned content, check out the episode page here.   -----   This episode is brought to you by Tegus. Tegus streamlines the investment research process so you can get up to speed and find answers to critical questions on companies faster and more efficiently. The Tegus platform surfaces the hard-to-get qualitative insights, gives instant access to critical public financial data through BamSEC, and helps you set up customized expert calls. It's all done on a single, modern SaaS platform that offers 360-degree insight into any public or private company. As a listener, you can take Tegus for a free test drive by visiting tegus.co/patrick. And until 2023 every Tegus license comes with complimentary access to BamSec by Tegus.   -----   Today's episode is brought to you by Brex, the integrated financial platform trusted by the world's most innovative entrepreneurs and fastest-growing companies. With Brex, you can move money fast for instant impact with high-limit corporate cards, payments, venture debt, and spend management software all in one place. Ready to accelerate your business? Learn more at brex.com/best.   -----   Invest Like the Best is a property of Colossus, LLC. For more episodes of Invest Like the Best, visit joincolossus.com/episodes.    Past guests include Tobi Lutke, Kevin Systrom, Mike Krieger, John Collison, Kat Cole, Marc Andreessen, Matthew Ball, Bill Gurley, Anu Hariharan, Ben Thompson, and many more.   Stay up to date on all our podcasts by signing up to Colossus Weekly, our quick dive every Sunday highlighting the top business and investing concepts from our podcasts and the best of what we read that week. Sign up here.   Follow us on Twitter: @patrick_oshag | @JoinColossus   Show Notes [00:02:43] - [First question] - The state of the digital infrastructure industry today  [00:04:02] - The major stages and eras of cloud technology  [00:06:30] - Overview of Dropbox's story and the two major trends at the time of its emergence [00:10:12] - Lost margin and lost market cap from big users of the public cloud  [00:12:14] - Whether or not there is a headwind coming for public cloud providers [00:14:07] - The base level primitives of the digital world and innovation within those areas [00:17:33] - How entrepreneurs might go after the biggest public cloud providers [00:19:37] - His view on API first companies and granular monetizable units in growing markets [00:23:20] - Developer facing tools and what works well when going to market  [00:25:34] - Lessons learned about successfully building relationships between a company and developers as a buying class  [00:27:12] - The difference between a front-end and back-end developer and what is changing in their responsibilities  [00:28:45] - What he looks for as an investor when he's processing a new API first company [00:30:31] - Common redflags and disqualifying observations for an API first company  [00:31:59] - Pricing usage and building a revenue model around one of these businesses [00:33:49] - Reasons why this proliferation is happening and important parts of the data stack [00:36:35] - Frank Slootman Episode; Snowflake's offering for their users, their explosive growth, and primitives in their sector [00:39:06] - The history of digital security and potential opportunities as an investor [00:40:19] - How digital infrastructure intersects with the real world and hardware world [00:42:14] - What he's most excited about that digital infrastructure might unlock in the future [00:43:33] - How to screen out people for their potential to deliver transformative technology [00:45:38] - What he'd like to know about the future that he isn't sure of yet  [00:47:45] - Things he's most intrigued about by cryptocurrencies as an infrastructure person [00:51:36] - Where he's most bullish and bearish relative to his peers in digital infrastructure [00:52:49] - The kindest thing anyone has ever done for him

Gross margins–which are essentially a company's revenue from products and services minus the costs to deliver those products and services to customers–are one of the most important financial metrics for any startup and growing business. And yet, figuring out what goes into the “cost” for delivering products and services is not as simple as it may sound, particularly for high-growth software businesses that might use emerging business models or be leveraging new technology. In this episode from June 2020, a16z general partners Martin Casado, David George, and Sarah Wang talk all things gross margins, from early to late stage. Why do gross margins matter? When do they matter during a company's growth? And how do you use them to plan for the future? The conversation ranges from the nuances of and strategy for calculating margins with things like cloud costs, freemium users, or implementation costs, to the impact margins can have on valuations.

Over a decade after the idea of “big data'' was first born, data has become the central nervous system for decision-making in organizations of all sizes. But the modern data stack is evolving and which infrastructure trends and technologies will ultimately win out remains to be decided.In this podcast, originally recorded as part of Fivetran's Modern Data Stack conference, five leaders in data infrastructure debate that question: a16z general partner and pioneer of software defined networking Martin Casado, former CEO of Snowflake Bob Muglia; Michelle Ufford, founder and CEO of Noteable; Tristan Handy, founder of Fishtown Analytics and leader of the open source project dbt; and Fivetran founder George Fraser.The conversation covers the future of data lakes, the new use cases for the modern data stack, data mesh and whether decentralization of teams and tools is the future, and how low we actually need to go with latency. And while the topic of debate is the modern data stack, the themes and differing perspectives strike at the heart of an even bigger: how does technology evolve in complex enterprise environments? We're re-running this episode as part of a special report on Future.com, the Data50: the World's Top Data Startups, which covers the bellwether private companies across the most exciting categories in data, from AI/ML to observability and more. 

Martin Casado is a general partner at Andreessen Horowitz (a16z), a pioneer of software-defined networking, and a co-founder of Nicira Networks. We cover the lessons learnt from Martin's journey as an academic entrepreneur founding Nicira and factors that aspiring entrepreneurs planning to translate their research to products should consider. - Story of an accidental Ph.D., turned into an accidental but very successful entrepreneur - Shares how working with others during grad school helped his entrepreneurial efforts later - Titles don't mean anything- Forget titles and make sure decision makers are responsible for their decisions long term. - Enterprise version of Product market fit means you have to be piped into the product, the market and the tech trends - Discount the advice given by technology advisors who don't understand product market fit. - Academics need to understand how people (customers) do their day to day processes and their current technology before proposing their new technology. - Thoughts about timing and persistence. - Advice on how to hire executives at startups. - Picking board members. - Thoughts on exits and how founders should think about exits - Ph.D.'s can make great CEOs but remember that business problems are harder than technology problems

This episode is in partnership with Ran Tavory's REVERSIM podcast - and we could not be more excited. This session hosts Martin Casado as we discuss a topic we have covered more than once:  “The Trillion Dollar Paradox” article by Martin and Sarah Wang.

Martin joins The Net crew to discuss his career from physicist to VC and all the networking in between

AI is meant to help us expedite processes and get to the conclusions quicker. But, what happens when the process that AI takes to get to the end goal is erroneous? In this episode we discuss how you can prevent your AI from cheating and define what it means to be a successful AI company in today's tech-saturated world. Specification Gaming: The Flip Side of AI Ingenuity (DeepMind Blog)The New Business of AI (and How It's Different From Traditional Software) by Martin Casado and Matt Bornstein (Adreessen Horowitz)

There are two words that get the blame more often than not when a problem cannot be rooted: the network! Today, along with special guest, Scott Lowe, we try to dig into what the network actually means. We discover, through our discussion that the network is, in fact, a distributed system. This means that each component of the network has a degree of independence and the complexity of them makes it difficult to understand the true state of the network. We also look at some of the fascinating parallels between networks and other systems, such as the configuration patterns for distributed systems. A large portion of the show deals with infrastructure and networks, but we also look at how developers understand networks. In a changing space, despite self-service becoming more common, there is still generally a poor understanding of networks from the developers’ vantage point. We also cover other network-related topics, such as the future of the network engineer’s role, transferability of their skills and other similarities between network problem-solving and development problem-solving. Tune in today! Follow us: https://twitter.com/thepodlets Website: https://thepodlets.io Feeback: info@thepodlets.io https://github.com/vmware-tanzu/thepodlets/issues Hosts: Duffie Cooley Nicholas Lane Josh Rosso Key Points From This Episode: • The network is often confused with the server or other elements when there is a problem.• People forget that the network is a distributed system, which has independent routers.• The distributed pieces that make up a network could be standalone computers.• The parallels between routing protocols and configuration patterns for distributed systems.• There is not a model for eventually achieving consistent networks, particularly if they are old.• Most routing patterns have a time-sensitive mechanism where traffic can be re-dispersed.• Understanding a network is a distributed system gives insights into other ones, like Kubernetes.• Even from a developers’ perspective, there is a limited understanding of the network.• There are many overlaps between developers and infrastructural thinking about systems.• How can network engineers apply their skills across different systems?• As the future changes, understanding the systems and theories is crucial for network engineers.• There is a chasm between networking and development.• The same ‘primitive’ tools are still being used for software application layers.• An explanation of CSMACD, collisions and their applicability. • Examples of cloud native applications where the network does not work at all.• How Spanning Tree works and the problems that it solves.• The relationship between software-defined networking and the adoption of cloud native technologies.• Software-defined networking increases the ability to self-service.• With self-service on-prem solutions, there is still not a great deal of self-service. Quotes: “In reality, what we have are 10 or hundreds of devices with the state of the network as a system, distributed in little bitty pieces across all of these devices.” — @scott_lowe [0:03:11] “If you understand how a network is a distributed system and how these theories apply to a network, then you can extrapolate those concepts and apply them to something like Kubernetes or other distributed systems.” — @scott_lowe [0:14:05] “A lot of these software defined networking concepts are still seeing use in the modern clouds these days” — @scott_lowe [0:44:38] “The problems that we are trying to solve in networking are not different than the problems that you are trying to solve in applications.” — @mauilion [0:51:55] Links Mentioned in Today’s Episode: Scott Lowe on LinkedIn — https://www.linkedin.com/in/scottslowe/ Scott Lowe’s blog — https://blog.scottlowe.org/ Kafka — https://kafka.apache.org/ Redis — https://redis.io/ Raft — https://raft.github.io/ Packet Pushers — https://packetpushers.net/ AWS — https://aws.amazon.com/ Azure — https://azure.microsoft.com/en-us/ Martin Casado — http://yuba.stanford.edu/~casado/ Transcript: EPISODE 15 [INTRODUCTION] [0:00:08.7] ANNOUNCER: Welcome to The Podlets Podcast, a weekly show that explores Cloud Native one buzzword at a time. Each week, experts in the field will discuss and contrast distributed systems concepts, practices, tradeoffs and lessons learned to help you on your cloud native journey. This space moves fast and we shouldn’t reinvent the wheel. If you’re an engineer, operator or technically minded decision maker, this podcast is for you. [EPISODE] [0:00:41.4] DC: Good afternoon everybody. In this episode, we’re going to talk about the network. My name is Duffie Cooley and I’ll be the lead of this episode and with me, I have Nick. [0:00:49.0] NL: Hey, what’s up everyone. [0:00:51.5] DC: And Josh. [0:00:52.5] JS: Hi. [0:00:53.6] DC: And Mr. Scott Lowe joining us as a guest speaker. [0:00:56.2] SL: Hey everyone. [0:00:57.6] DC: Welcome, Scott. [0:00:58.6] SL: Thank you. [0:01:00.5] DC: In this discussion, we’re going to try and stay away, like we do always, we’re going to try and stay away from particular products or solutions that are related to the problem. The goal of it is to really kind of dig in to like what the network means when we refer to it as it relates to like cloud native applications or just application design in general. One of the things that I’ve noticed over time and I’m curious, what you all think but like, one of the things I’ve done over time is that people are kind of the mind that if it can’t root cause a particular issue that they run into, they’re like, “That was the network.” Have you all seen that kind of stuff out there? [0:01:31.4] NL: Yes, absolutely. In my previous life, before being a Kubernetes architect, I actually used my networking and engineering degree to be a network administrator for the Boeing Company, under the Boeing Corporation. Time and time again, someone would come to me and say, “This isn’t working. The network is down.” And I’m like, “Is the network down or is the server down?” Because those are different things. Turns out it was usually the server. [0:01:58.5] SL: I used to tell my kids that they would come to me and they would say, the Internet is down and I would say, “Well, you know. I don’t think the entire Internet is down, I think it’s just our connection to the Internet.” [0:02:10.1] DC: Exactly. [0:02:11.7] JS: Dad, the entire global economy is just taking a total hit. [0:02:15.8] SL: Exactly, right. [0:02:17.2] DC: I frequently tell people that my first distributed system that I ever had a real understanding of was the network, you know? It’s interesting because it kind of like, relies on the premises that I think a good distributed system should in that there is some autonomy to each of the systems, right? They are dependent on each other or even are inter communicate with each other but fundamentally, like when you look at routers and things like that, they are autonomous in their own way. There’s work that they do exclusive to the work that others do and exclusive to their dependencies which I think is very interesting. [0:02:50.6] SL: I think the fact that the network is a distributed system and I’m glad you said that Duffie, I think the fact the network is a distributed system is what most people overlook when they start sort of blaming the network, right? Let’s face it, in the diagrams, right, the network’s always just this blob, right? Here’s the network, right? It’s this thing, this one singular thing. When in reality, what we have are like 10 or hundreds of devices with the state of the network as a system, distributed in little bitty pieces across all of these devices. And no way, aside from logging in to each one of these devices are we able to assemble what the overall state is, right? Even routing protocols mean, their entire purpose is to assemble some sort of common understanding of what the state of the network is. Melding together, not just IP addresses which are these abstract concept but physical addresses and physical connections. And trying to reason to make decisions about them, how we center across and it’s far more complex and a lot of people understand, I think that’s why it’s just like the network is down, right? When reality, it’s probably something else entirely. [0:03:58.1] DC: Yeah, absolutely. Another good point to bring up is that each of these distributed pieces of this distributed system are in themselves like basically like just a computer. A lot of times, I’ve talked to people and they were like, “Well, the router is something special.” And I’m like, “Not really. Technically, a Linux box could just be a router if you have enough ports that you plug into it. Or it could be a switch if you needed to, just plug in ports.” [0:04:24.4] NL: Another good interesting parallel there is like when we talk about like routing protocols which are a way of – a way that allow configuration changes to particular components within that distributed system to be known about by other components within that distributed system. I think there’s an interesting parallel here between the way that works and the way that configuration patterns that we have for distributed systems work, right? If you wanted to make a configuration only change to a set of applications that make up some distributed system, you might go about like leveraging Ansible or one of the many other configuration models for this. I think it’s interesting because it represents sort of an evolution of that same idea in that you’re making it so that each of the components is responsible for informing the other components of the change, rather than taking the outside approach of my job is to actually push a change that should be known about by all of these concepts, down to them. Really, it’s an interesting parallel. What do you all think of that? [0:05:22.2] SL: I don’t know, I’m not sure. I’d have to process that for a bit. But I mean, are you saying like the interesting thought here is that in contrast to typical systems management where we push configuration out to something, using a tool like an Ansible, whatever, these things are talking amongst themselves to determine state? [0:05:41.4] DC: Yeah, it’s like, there are patterns for this like inside of distributed systems today, things like Kafka and you know, Kafka and Gossip protocol, stuff like this actually allows all of the components of a particular distributed system to understand the common state or things that would be shared across them and if you think about them, they’re not all that different from a routing protocol, right? Like the goal being that you give the systems the ability to inform the other systems in some distributed system of the changes that they may have to react to. Another good example of this one, which I think is interesting is like, what they call – when you have a feature behind a flag, right? You might have some distributed configuration model, like a Redis cache or database somewhere that you’ve actually – that you’ve held the running configuration of this distributed system. And when you want to turn on this particular feature flag, you want all of the components that are associated with that feature flag to enable that new capability. Some of the patterns for that are pretty darn close to the way that routing protocol models work. [0:06:44.6] SL: Yeah, I see what you're saying. Actually, that’ makes a lot of sense. I mean, if we think about things like Gossip protocols or even consensus protocols like Raft, right? They are similar to routing protocols in that they are responsible for distributing state and then coming to an agreement on what that state is across the entire system. And we even apply terms like convergence to both environments like we talk about how long it takes routing protocol to converge. And we might also talk about how long it takes for and ETCD cluster to converge after changing the number of members in the cluster of that nature. The point at which everybody in that distributed system, whether it be the network ETCD or some other system comes to the same understanding of what that shared state is. [0:07:33.1] DC: Yeah, I think that’s a perfect breakdown, honestly. Pretty much every routing technology that’s out there. You know, if you’re taking that – the computer of the network, you know, it takes a while but eventually, everyone will reconcile the fact that, “Yeah, that node is gone now.” [0:07:47.5] NL: I think one thing that’s interesting and I don’t know how much of a parallel there is in this one but like as we consider these systems like with modern systems that we’re building at scale, frequently we can make use of things like eventual consistency in which it’s not required per se for a transaction to be persisted across all of the components that it would affect immediately. Just that they eventually converge, right? Whereas with the network, not so much, right? The network needs to be right now and every time and there’s not really a model for eventually consistent networks, right? [0:08:19.9] SL: I don’t know. I would contend that there is a model for eventually consistent networks, right? Certainly not on you know, most organizations, relatively simple, local area networks, right? But even if we were to take it and look at something like a Clos fabric, right, where we have top of rack switches and this is getting too deep for none networking blokes that we know, right? Where you take top of rack switches that are talking layer to the servers below them or the end point below them. And they’re talking layer three across a multi-link piece up to the top, right? To the spine switches, so you have leaf switches, talking up spine switches, they’re going to have multiple uplinks. If one of those uplinks goes down, it doesn’t really matter if the rest off that fabric knows that that link is down because we have the SQL cost multi pathing going across that one, right? In a situation like that, that fabric is eventually consistent in that it’s okay if you know, knee dropping link number one of leaf A up to spine A is down and the rest of the system doesn’t know about that yet. But, on the other hand, if you are looking at network designs where convergence is being handled on active standby links or something of that nature or there aren’t enough paths to get from point A to point B until convergence happens then yes, you’re right. I think it kind of comes down to network design and the underlying architecture and there are so many factors that affect that and so many designs over the years that it’s hard to – I would agree and from the perspective of like if you have an older network and it’s been around for some period of time, right? You probably have one that is not going to be tolerant, a link being down like it will cause problems. [0:09:58.4] NL: Adds another really great parallel in software development, I think. Another great example of that, right? If we consider for a minute like the circuit breaking pattern or even like you know, most load balancer patterns, right? In which you have some way of understanding a list of healthy end points behind the load balancer and were able to react when certain end points are no longer available. I don’t consider that a pattern that I would relate to specifically if they consent to eventual consistency. I feel like that still has to be immediate, right? We have to be able to not send the new transaction to the dead thing. That has to stop immediately, right? It does in most routing patterns that are described by multi path, there is a very time sensitive mechanism that allows for the re-dispersal of that traffic across known paths that are still good. And the work, the amazing amount of work that protocol architects and network engineers go through to understand just exactly how the behavior of those systems will work. Such that we don’t see traffic. Black hole in the network for a period of time, right? If we don’t send traffic to the trash when we know or we have for a period of time, while things converge is really has a lot going for it. [0:11:07.0] SL: Yeah, I would agree. I think the interesting thing about discussing eventual consistency with regards to the networking is that even if we take a relatively simple model like the DOD model where we only have four layers to contend with, right? We don’t have to go all the way to this seven-layer OSI model. But even if we take a simple layer like the DOD four-layer model, we could be talking about the rapid response of a device connected at layer two but the less than rapid response of something operating at layer three or layer four, right? In the case of a network where we have these discreet layers that are intentionally loosely coupled which is another topic, we could talk about from a distribution perspective, right? We have these layers that are intentionally loosely coupled, we might even see consistency and the application of the cap theorem, behave differently at different layers of their model. [0:12:04.4] DC: That’s right. I think it’s fascinating like how much parallel there is here. As you get into like you know, deep architectures around software, you’re thinking of these things as it relates to like these distributed systems, especially as you’re moving toward more cloud native systems in which you start employing things like control theory and thinking about the behaviours of those systems both in aggregate like you know, some component of my application, can I scale this particular component horizontally or can I not, how am I handling state. So many of those things have parallels to the network that I feel like it kind of highlights I’m sure what everybody has heard a million times, you know, that there’s nothing new under the sun. There’s million things that we could learn from things that we’ve done in the past. [0:12:47.0] NL: Yeah, totally agree. I recently have been getting more and more development practice and something that I do sometimes is like draw out like how all of my functions and my methods, and take that in rack with each other across a consisting code base and lo and behold when I draw everything out, it sure does look a lot like a network diagram. All these things have to flow together in a very specific way and you expect the kind of returns that you’re looking for. It looks exactly the same, it’s kind of the – you know, how an atom kind of looks like a galaxy from our diagram? All these things are extrapolated across like – [0:13:23.4] SL: Yeah, totally. [0:13:24.3] NL: Different models. Or an atom looks like a solar system which looks like a galaxy. [0:13:28.8] SL: Nicholas, you said your network administrator at Boeing? [0:13:30.9] NL: I was, I was a network engineer at Boeing. [0:13:34.0] SL: You know, as you were sitting there talking, Duffie, so, I thought back to you Nick, I think all the times, I have a personal passion for helping people continue to grow and evolve in their career and not being stuck. I talk to a lot of networking folks, probably dating because of my involvement, back in the NSX team, right? But folks being like, “I’m just a network engineer, there’s so much for me to learn if I have to go learn Kubernetes, I wouldn’t even know where to start.” This discussion to me underscores the fact that if you understand how a network is a distributed system and how these theories apply to a network, then you can extrapolate those concepts and apply them to something like Kubernetes or other distributed systems, right? Immediately begin to understand, okay. Well, you know, this is how these pieces talk to each other, this is how they come, the consensus, this is where the state is stored, this is how they understand and exchange date, I got this. [0:14:33.9] NL: if you want to go down that that path, the controlled plane of your cluster is just like your central routing back bone and then the kublets themselves are just your edge switches going to each of your individual smaller network and then the pods themselves have been nodes inside of the network, right? You can easily – look at that, holy crap, it looks exactly the same. [0:14:54.5] SL: Yeah, that’s a good point. [0:14:55.1] DC: I mean, another interesting part, when you think about how we characterize systems, like where we learn that, where that skillset comes from. You raise a very good point. I think it’s an easier – maybe slightly easier thing to learn inside of networking, how to characterize that particular distributed system because of the way the components themselves are laid out and in such a common way. Where when we start looking at different applications, we find a myriad of different patterns with particular components that may behave slightly differently depending, right? Like there are different patterns within software like almost on per application bases whereas like with networks, they’re pretty consistently applied, right? Every once in a while, they’ll be kind of like a new pattern that emerges, that it just changes the behavior a little bit, right? Or changes the behavior like a lot but at the same time, consistently across all of those things that we call data center networks or what have you. To learn to troubleshoot though, I think the key part of this is to be able to spend the time and the effort to actually understand that system and you know, whether you light that fire with networking or whether you light that fire with like just understanding how to operationalize applications or even just developing and architecting them, all of those things come into play I think. [0:16:08.2] NL: I agree. I’m actually kind of curious, the three of us have been talking quite a bit about networking from the perspective that we have which is more infrastructure focused. But Josh, you have more of a developer focused background, what’s your interaction and understanding of the network and how it plays? [0:16:24.1] JS: Yeah, I’ve always been a consumer of the network. It’s something that is sat behind an API and some library, right? I call out to something that makes a TCP connection or an http interaction and then things just happen. I think what’s really interesting hearing talk and especially the point about network engineers getting into thee distributed system space is that I really think that as we started to put infrastructure behind API’s and made it more and more accessible to people like myself, app developers and programmers, we started – by we, you know, I’m obviously generalizing here. But we started owning more and more of the infrastructure. When I go into teams that are doing big Kubernetes deployments, it’s pretty rare, that’s the conventional infrastructure and networking teams that are standing up distributed systems, Kubernetes or not, right? It's a lot of times, a bunch of app developers who have maybe what we call dev-ops, whatever that means but they have an application development background, they understand how they interact with API’s, how to write code that respects or interacts with their infrastructure and they’re standing up these systems and I think one of the gaps of that really creates is a lot of people including myself just hearing you all talk, we don’t understand networking at that level. When stuff falls over and it’s either truly the network or it’s getting blamed on the network, it’s often times, just because we truly don’t understand a lot of these things, right? Encapsulation, meshes, whatever it might be, we just don’t understand these concepts at a deep level and I think if we had a lot more people with network engineering backgrounds, shifting into the distributed system space. It would alleviate a bit of that, right? Bringing more understanding into the space that we work in nowadays. [0:18:05.4] DC: I wonder if maybe it also would be a benefit to have like more cross discussions like this one between developers and infrastructure kind of focused people, because we’re starting to see like as we’re crossing boundaries, we see that the same things that we’re doing on the infrastructure side, you’re also doing in the developer side. Like cap theorem as Scott mention which is the idea that you can have two out of three of consistency, availability and partitioning. That also applies to networking in a lot of ways. You can only have a network that is either like consistent or available but it can’t handle partitioning. It can be a consistent to handle partitioning but it’s not always going to be available, that sort of thing. These things that apply in from the software perspective also apply to us but we think about them as being so completely different. [0:18:52.5] JS: Yeah, I totally agree. I really think like on the app side, a couple of years ago, you know, I really just didn’t care anything outside of the JVM like my stuff on the JVM and if it got out to the network layer of the host like just didn’t care, know, need to know about that at all. But ever since cloud computing and distributed systems and everything became more prevalent, the overlap has become extremely obvious, right? In all these different concepts and it’s been really interesting to try to ramp up on that. [0:19:19.6]:19.3] NNL: Yeah, I think you know Scott and I both do this. I think as I imagine, actually, this is true of all four of us to be honest. But I think that it’s really interesting when you are out there talking to people who do feel like they’re stuck in some particular role like they’re specialists in some particular area and we end up having the same discussion with them over and over again. You know, like, “Look, that may pay the bills right now but it’s not going to pay the bills in the future.” And so you know, the question becomes, how can you, as a network engineer take your skills forward and not feel as though you’re just going to have to like learn everything all over again. I think that one of the things that network engineers are pretty decent at is characterizing those systems and being able to troubleshoot them and being able to do it right now and being able to like firefight those capabilities and those skills are incredibly valuable in the software development and in operationalizing applications and in SRE models. I mean, all of those skills transfer, you know? If you’re out there and you’re listening and you feel like I will always be a network engineer, consider that you could actually take those skills forward into some other role if you chose to. [0:20:25.1] JS: Yeah, totally agree. I mean, look at me, the lofty career that I’ve been come to. [0:20:31.4] SL: You know, I would also say that the fascinating thing to me and one of the reasons I launched, I don’t say this to like try and plug it but just as a way of talking about the reason I launched my own podcast which is now part of packet pushers, was exploring this very space and that is like we’ve got folks like Josh who comes from the application development spacing is now being, you know, in a way, forced to own and understand more infrastructure and we’ve got the infrastructure folks who now in a way, whether it be through the rise of cloud computing and abstractions away from visible items are being forced kind of up the stack and so they’re coming together and this idea of what does the future of the folks that are kind of like in our space, what does that look like? How much longer does a network engineer really need to be deeply versed in all the different layers? Because everything’s been abstracted away by some other type of thing whether it’s VPC’s or Azure V Nets or whatever the case is, right? I mean, you’ve got companies bringing the VPC model to on premises networks, right? As API’s become more prevalent, as everything gets sort of abstracted away, what does the future look like, what are the most important skills and it seems to me that it’s these concepts that we’re talking about, right? This idea of distributed systems and how distributed systems behave and how the components react to one another and understanding things like the cap theorem that are going to be most applicable rather than the details of trouble shooting VGP or understanding AWS VPC’s or whatever the case may be. [0:22:08.5] NL: I think there is always going to be a place for the people who know how things are running under the hood from like a physical layer perspective, that sort of thing, there’s always going to be the need for the grave beards, right? Even in software development, we still have the people who are slinging kernel code in C. And you know, they’re the best, we salute you but that is not something that I’m interested in it for sure. We always need someone there to pick up the pieces as it were. I think that yeah, having just being like, I’m a Cisco guy, I’m a Juniper guy, you know? I know how to pawn that or RSH into the switch and execute these commands and suddenly I’ve got this port is now you know, trunk to this V neck crap, I was like, Nick, remember your training, you know? How to issue those commands, I wonder, I think that that isn’t necessarily going away but it will be less in demand in the future. [0:22:08.5] SL: I’m curious to hear Josh’s perspective as like having to own more and more of the infrastructure underneath like what seems to be the right path forward for those folks? [0:23:08.7] JS: Yeah, I mean, unfortunately, I feel like a lot of times, it just ends up being trial by fire and it probably shouldn’t be that. But the amount of times that I have seen a deployment of some technology fall over because we overlapped the site range or something like that is crazy. Because we just didn’t think about it or really understand it that well. You know, like using one protocol, you just described BGP. I never ever dreamt of what BGP was until I started using attributed systems, right? Started using BGP as a way to communicate routes and the amount off times that I’ve messed up that connection because I don’t have a background in how to set that up appropriately, it’s been rough. I guess my perspective is that the technology has gotten better overall and I’m mostly obviously in the Kubernetes space, speaking to the technologies around a lot of the container networking solutions but I’m sure this is true overall. It seems like a lot of the sharp edges have been buffed out quite a bit and I have less of an opportunity to do things terribly wrong. I’ve also noticed for what it’s worth, a lot of folks that have my kind of background or going out to like the AWS is the Azure’s of the world. They’re using all these like, abstracted networking technologies that allow t hem to do really cool stuff without really having to understand how it works and they’re often times going back to their networking team on prem when they have on prem requirements and being like it should be this easy or XY and Z and they’re almost like pushing the networking team to modernize that and make things simpler. Based on experiences they’re having with these cloud providers. [0:24:44.2] DC: Yeah, what do you mean I can’t create a load balancer that crosses between these two disparate data centers as it easily is. Just issuing a single command. Doesn’t this just exist from a networking standpoint? Even just the idea that you can issue an API command and get a load balancer, just that idea alone, the thousands of times I have heard that request in my career. [0:25:08.8] JS: And like the actual work under the hood to get that to work properly is it’s a lot, there’s a lot of stuff going on. [0:25:16.5] SL: Absolutely, yeah, [0:25:17.5] DC: Especially when you’re into plumbing, you know? If you’re going to create a load balancer with API, well then, what API does the load balancer use to understand where to send that traffic when it’s being balanced. How do you handle discovery, how do you hit like – obviously, yeah, there’s no shortage on the amount of work there. [0:25:36.0] JS: Yeah. [0:25:36.3] DC: That’s a really good point, I mean, I think sometimes it’s easy for me to think about some of these API driven networking models and the cost that come with them, the hidden cost that come with them. An example of this is, if you’re in AWS and you have a connectivity between wo availability, actually could be any cloud, it doesn’t have to be an AWS, right? If you have connectivity between two different availability zones and you’re relying on that to be reliable and consistent and definitely not to experience, what tools do you have at your disposal, what guarantees do you have that that network has even operating in a way that is responsive, right? And in a way, this is kind of taking us towards the observability conversation that I think we’ve talked a little bit about the past. Because I think it highlights the same set of problems again, right? You have to understand, you have to be able to provide the consumers of any service, whether that service is plumbing, whether it’s networking, whether it’s your application that you’ve developed that represents a set of micro service. You have to provide everybody a way or you know, have to provide the people who are going to answer the phone at two in the morning. Or even the robots that are going to answer the phone at two in the morning. I have to provide them some mechanism by which to observe those systems as they are in use. [0:26:51.7] JS: I’m not convinced that very many of the cloud providers do that terribly well today, you know? I feel like I’ve been burned in the past without actually having an understanding of the state that we’re in and so it is interesting maybe the software development team can actually start pushing that down toward the networking vendors out there out in the world. [0:27:09.9] NL: Yeah that would be great. I mean I have been recently using a managed Kubernetes service. I have been kicking the tires on it a little bit. And yeah there has been a couple of times where I had just been got by networking issues. I am not going to get into what I have seen in a container network interface or any of the technologies around that. We are going to talk about that another time. But the CNI that I am using in this managed service was just so wonky and weird. And it was failing from a network standpoint. The actual network was failing in a sense because the IP addresses for the nodes themselves or the pods wasn’t being released properly and because of our bag. And so, the rules associated with my account could not remove IP addresses from a node in the network because it wasn’t allowed to and so from a network, I ran out of IP addresses in my very small site there. [0:28:02.1] SL: And this could happen in database, right? This could happen in a cache of information, this could happen in pretty much the same pattern that you are describing is absolutely relevant in both of these fields, right? And that is a fascinating thing about this is that you know we talk about the network generally in these nebulous terms and that it is like a black box and I don’t want them to know anything about it. I want to learn about it, I don’t want to understand it. I just want to be able to consume it via an API and I want to have the expectation that everything will work the way it is supposed to. I think it is fascinating that on the other side of that API are people maybe just like you who are doing their level best to provide, to chase the cap theorum into it’s happy end and figure out how to actually give you what you need out of that service, you know? So, empathy I think is important. [0:28:50.4] NL: Absolutely, to bring that to an interesting thought that I just had where on both sides of this chasm or whatever it is between networking and develop, the same principles exists like we have been saying but just to elicited on it a little bit more, it’s like on one side you have like I need to make sure that these ETCD nodes communicate with each other and that the data is consistent across the other ones. So, we use a protocol called RAFT, right? And so that’s eventually existent tool then that information is sent onto a network, which is probably using OSPF, which is “open shortest path first” routing protocol to become eventually consistent on the data getting from one point to the other by opening the shortest path possible. And so these two things are very similar. They are both these communication protocols, which is I mean that is what protocol means, right? The center for communication but they’re just so many different layers. Obviously of the OSI model but people don’t put them together but they really are and we keep coming back to that where it is all the same thing but we think about it so differently. And I am actually really appreciating this conversation because now I am having a galaxy brain moment like boo. [0:30:01.1] SL: Another really interesting one like another galaxy moment, I think that is interesting is if you think about – so let us break them down like TCP and UTP. These are interesting patterns that actually do totally relate again just in software patterns, right? In TCP the guarantee is that every data gram, if you didn’t get the entire data gram you will understand that you are missing data and you will request a new version of that same packet. And so, you can provide consistency in the form of retries or repeats if things don’t work, right? Not dissimilar from the ability to understand like that whether you chuck some in data across the network or like in a particular data base, if you make a query for a bunch of information you have to have some way of understanding that you got the most recent version of it, right? Or ETCD supports us by using the revision by understanding what revision you received last or whether that is the most recent one. And other software patterns kind of follow the same model and I think that is also kind of interesting. Like we are still using the same primitive tools to solve the same problems whether we are doing it at a software application layer or whether we are doing it down in the plumbing at the network there, these tools are still very similar. Another example is like UTP where it is basically there are no repeats. You either got the packet or you didn’t, which sounds a lot like an event stream to me in some ways, right? Like it is very interesting, you just figured out like I put in on the line, you didn’t get it? It is okay, I will put another line here in a minute you can react to that one, right? It is an interesting overlap. [0:31:30.6] NL: Yeah, totally. [0:31:32.9] JS: Yeah, the comparison to event streams or message queues, right? There is an interesting one that I hadn’t considered before but yeah, there are certainly parallels between saying, “Okay I am going to put this on the message queue,” and wait for the acknowledgement that somebody has taken it and taken ownership of it as oppose to an event stream where it is like this happened. I admit this event. If you get it and you do something with it, great. If you don’t get it then you don’t do something with it, great because another event is going to come along soon. So, there you go. [0:32:02.1] DC: Yep, I am going to go down a weird topic associated with what we are just talking about. But I am going to get a little bit more into the weeds of networking and this is actually directed into us in a way. So, talking about the kind of parallels between networking and development, in networking at least with TCP and networking, there is something called CSMACD, which is “carry your sense multi,” oh I can’t remember what the A stands for and the CD. [0:32:29.2] SL: Access. [0:32:29.8] DC: Multi access and then CD is collision detection and so basically what that means is whenever you sent out a packet on the network, the network device itself is listening on the network for any collisions and if it detects a collision it will refuse to send a packet until a certain period of time and they will do a retry to make sure that these packets are getting sent as efficiently as possible. There is an alternative to that called CMSCA, which was used by Mac before they switched over to using a Linux based operating system. And then putting a fancy UI in front of it, which collision avoidance would listen and try and – I can’t remember exactly, it would time it differently so that it would totally just avoid any chance that there could be collision. It would make sure that no packets were being sent right then and then send it back up. And so I was wondering if something like that exists in the realm between the communication path between applications. [0:33:22.5] JS: Is it collision two of the same packets being sent or what exactly is that? [0:33:26.9] DC: With the packets so basically any data going back and forth. [0:33:29.7] JS: What makes it a collision? [0:33:32.0] SL: It is the idea that you can only transmit one message at a time because if they both populate the same media it is trash, both of them are trash. [0:33:39.2] JS: And how do you qualify that. Do you receive an ac from the system or? [0:33:42.8] NL: No there is just nothing returned essentially so it is like literally like the electrical signals going down the wire. They physically collide with each other and then the signal breaks. [0:33:56.9] JS: Oh, I see, yeah, I am not sure. I think there is some parallels to that maybe with like queuing technologies and things like that but can’t think of anything on like direct app dev side. [0:34:08.6] DC: Okay, anyway sorry for that tangent. I just wanted to go down that little rabbit-hole a little bit. It was like while we are talking about networking, I was like, “Oh yeah, I wanted to see how deep down we can make this parallel going?” so that was the direction I went. [0:34:20.5] SL: Like where is that that CSMACD, a piece is like seriously old school, right? Because it only applied to half duplex Ethernet and as soon as we went to full duplex Ethernet it didn’t matter anymore. [0:34:33.7] DC: That is true. I totally forgot about that. [0:34:33.8] JS: It applied the satellite with all of these as well. [0:34:35.9] DC: Yeah, I totally forgot about that. Yeah and with full duplex, we totally just space on that. This is – damn Scott, way to make me feel old. [0:34:45.9] SL: Well I mean satellite stuff, too, right? I mean it is actually any shared media upon which you have to – where if this stuff goes and overlap there, you are not going to be able to make it work right? And so, I mean it is interesting. It is actually an interesting PNL. I am struggling to think of an example of this as well. I mean my brain is going towards circuit breaking but I don’t think that that is quite the same thing. It is sort the same thing that in a circuit breaking pattern, the application that is making the request has the ability obviously because it is the thing making the request to understand that the target it is trying to connect to is not working correctly. And so, it is able to make an almost instantaneous decision or at least a very shortly, a very timely decision about what to do when it detects that state. And so that’s a little similar and that you can and from the requester side you can do things if you see things going awry. And really and in reality, in the circuit breaking pattern we are making the assumption that only the application making the request will ever get that information fast enough to react to it. [0:35:51.8] JS: Yeah where my head was kind of going with it but I think it is pretty off is like on a low level piece of code like it is maybe something you write in C where you implement your own queue in that area and then multiple threads are firing off the same time and there is no block system or mechanism if two threads contend to put something in the same memory space that that queue represents. That is really going down the rabbit hole. I can’t even speak to what degree that is possible in modern programming but that is where my head was. [0:36:20.3] NL: Yeah that is a good point. [0:36:21.4] SL: Yeah, I think that is actually a pretty good analogy because the key commonality here is some sort of shared access, right? Multiple threads accessing the same stack or memory buffer. The other thing that came to mind to me was like some sort of session multiplexing, right? Where you are running multiple application layer sessions inside a single sort of network connection and those network sessions getting comingled in some fashion. Whether through identifiers or sequence number or something else of that nature and therefore, you know garbling the ultimate communication that is trying to be sent. [0:36:59.2] DC: Yeah, locks are exactly the right direction, I think. [0:37:03.6] NL: That is a very good point. [0:37:05.2] DC: Yeah, I think that makes perfect sense. Good, all right. Yes, we nailed it. [0:37:09.7] SL: Good job. [0:37:10.8] DC: Can anybody here think of a software pattern that maybe doesn’t come across that way? When you are thinking about some of the patterns that you see today in cloud native applications, is there a counter example, something that the network does not do at all? [0:37:24.1] NL: That is interesting. I am trying to think where event streams. No, that is just straight up packets. [0:37:30.7] JS: I feel like we should open up one of those old school Java books of like 9,000 design patterns you need to know and we should go one by one and be like, “What about this” you know? There is probably something I can’t think of it off the top of my head. [0:37:43.6] DC: Yeah me neither. I was trying to think of it. I mean like I can think of a myriad of things that do cross over even the idea of only locally relevant state, right? That is like a cam table on a switch that is only locally relevant because once you get outside of that switching domain it doesn’t matter anymore and it is like there is a ton of those things that totally do relate, you know? But I am really struggling to come up with one that doesn’t – One thing that is actually interesting is I was going to bring up – we mentioned the cap theorem and it is an interesting one that you can only pick like two and three of consistency availability and partition tolerance. And I think you know, when I think about the way that networks solve or try to address this problem, they do it in some pretty interesting way. It’s like if you were to consider like Spanning Tree, right? The idea that there can really only be one path through a series of broadcast domains. Because we have multiple paths then obviously we are going to get duplicity and the things are going to get bad because they are going to have packets that are addressed the same things across and you are going to have all kinds of bad behaviors, switching loops and broadcast storms and all kinds of stuff like that and so Spanning Tree came along and Spanning Tree was invented by an amazing woman engineer who created it to basically ensure that there was only one path through a set of broadcast domains. And in a way, this solved that camp through them because you are getting to the point where you said like since I understand that for availability purpose, I only need one path through the whole thing and so to ensure consistency, I am going to turn off the other paths and to allow for partition tolerance, I am going to enable the system to learn when one of those paths is no longer viable so that it can re-enable one of the other paths. Now the challenge of course is there is a transition period in which we lose traffic because we haven’t been able to open one of those other paths fast enough, right? And so, it is interesting to think about how the network is trying to solve with the part that same set of problems that is described by the cap theorem that we see people trying to solve with software routine. [0:39:44.9] SL: No man I totally agree. In a case like Spanning Tree, you are sacrificing availability essentially for consistency and partition tolerance when the network achieves consistency then availability will be restored and there is other ways to doing that. So as we move into systems like I mentioned clos fabrics earlier, you know a cost fabric is a different way of establishing a solution to that and that is saying I’d later too. I will have multiple connections. I will wait those connections using the higher-level protocol and I will sacrifice consistency in terms of how the routes are exchanged to get across that fabric in exchange for availability and partition columns. So, it is a different way of solving the same problem and using a different set of tools to do that, right? [0:40:34.7] DC: I personally find it funny that in the cap theorem there is at no point do we mention complexity, right? We are just trying to get all three and we don’t care if it’s complex. But at the same time, as a consumer of all of these systems, you care a lot about the complexity. I hear it all the time. Whether that complexity is in a way that the API itself works or whether even in this episode we are talking about like I maybe don’t want to learn how to make the network work. I am busy trying to figure out how to make my application work, right? Like cognitive load is a thing. I can only really focus on so many things at a time where am I going to spend my time? Am I going to spend it learning how to do plumbing or am I going to spend it actually trying the right application that solves my business problem, right? It is an interesting thing. [0:41:17.7] NL: So, with the rise of software defined networking, how did that play into the adoption of cloud native technologies? [0:41:27.9] DC: I think it is actually one of the more interesting overlaps in the space because I think to Josh’s point again. his is where we were taking I mean I work for a company called [inaudible 0:41:37], in which we were virtualizing the network and this is fascinating because effectively we are looking at this as a software service that we had to bring up and build and build reliably and scalable. Reliably and consistently and scalable. We want to create this all while we are solving problems. But we need it to do within an API. It is like we couldn’t make the assumption with the way that networks were being defined today like going to each component and configuring them or using protocols was actually going to work in this new model of software confined networking. And so, we had an incredible amount of engineers who were really focused from a computer science perspective on how to effectively reinvent network as a software solution. And I do think that there is a huge amount of cross over here like this is actually where I think the waters meet between the way the developers think about the problems and the way that network engineers think about the problem but it has been a rough road I will say. I will say that STN I think is actually has definitely thrown a lot of network engineers under their heels because they’re like, “Wait, wait but that is not a network,” you know? Because I can’t actually look at it and characterize it in the way that I am accustomed to looking at characterizing the other networks that I play with. And then from the software side, you’re like, “Well maybe that is okay” right? Maybe that is enough, it is really interesting. [0:42:57.5] SL: You know I don’t know enough about the details of how AWS or Azure or Google are actually doing their networking like and I don’t even know and maybe you guys all do know – but I don’t even know that aside from a few tidbits here and there that AWS is going to even divulge the details of how things work under the covers for VPC’s right? But I can’t imagine that any modern cloud networking solution whether it would be VBPC’s or VNET’s or whatever doesn’t have a significant software to find aspect to it. You know, we don’t need to get into the definitions of what STN is or isn’t. That was a big discussion Duffie and I had six years ago, right? But there has to be some part of it that is taking and using the concepts that are common in STN right? And applying that. Just as the same way as the cloud vendors are using the concepts from compute virtualization to enable what they are doing. I mean like the reality is that you know the work that was done by the Cambridge folks on Zen was a massive enabler trade for AWS, right? The word done on KVM also a massive enabler for lots of people. I think GCP is KBM based and V Sphere where VM Ware data as well. I mean all of this stuff was a massive enablers for what we do with compute virtualization in the cloud. I have to think that whether it is – even if it wasn’t necessarily directly stemming out of Martin Casado’s open flow work at Stanford, right? That a lot of these software define networking concepts are still seeing use in the modern clouds these days and that is what enables us to do things like issue an API call and have an isolated network space with its own address space and its own routing and satiated in some way and managed. [0:44:56.4] JS: Yeah and on that latter point, you know as a consumer of this new software defined nature of networking, it is amazing the amount of I don’t know, I started using like a blanket marketing term here but agility that it is added, right? Because it has turned all of these constructs that I used to file a ticket and follow up with people into self-service things that when I need to poke holes in the network, hopefully the rights are locked down, so I just can’t open it all up. Assuming I know what I am doing and the rights are correct it is totally self-service for me. I go into AWS, I change the security group roll and boom, the ports have changed and it never looked like that prior to this full takeover of what I believe is STN almost end to end in the case of AWS and so on. So, it is really just not only has it made people like myself have to understand more about networking but it has allowed us to self-service a lot of the things. That I would imagine most network engineers were probably tired of doing anyways, right? How many times do you want to go to that firewall and open up that port? Are you really that excited about that? I would imagine not so. [0:45:57.1] NL: Well I can only speak from experience and I think a lot of network engineers kind of get into that field because it really love control. And so, they want to know what these ports are that are opening and it is scary to be like this person has opened up these ports, “Wait what?” Like without them even totally knowing. I mean I was generalizing, I was more so speaking to myself as being self-deprecating. It doesn’t apply to you listener. [0:46:22.9] JS: I mean it is a really interesting point though. I mean do you think it makes the networking people or network engineers maybe a little bit more into the realm of observability and like knowing when to trigger when something has gone wrong? Does it make them more reactive in their role I guess. Or maybe self-service is not as common as I think it is. It is just from my point of view, it seems like with STN’s the ability to modify the network more power has been put into the developers’ hands is how I look at it, you know? [0:46:50.7] DC: I definitely agree with that. It is interesting like if we go back a few years there was a time when all of us in the room here I think are employed by VMware. So, there was a time where VMware’s thing was like the real value or one of the key values that VMware brought to the table was the idea that a developer come and say “Give me 10 servers.” And you could just call an API or make it or you could quickly provision those 10 servers on behalf of that developer and hand them right back. You wouldn’t have to go out and get 10 new machines and put them into a rack, power them and provision them and go through that whole process that you could actually just stamp those things out, right? And that is absolutely parallel to the network piece as well. I mean if there is nothing else that SPN did bring to the fore is that, right? That you can get that same capability of just stamping up virtual machines but with networks that the API is important in almost everything we do. Whether it is a service that you were developing, whether it is a network itself, whether it is the firewall that we need to do these things programmatically. [0:47:53.7] SL: I agree with you Duffie. Although I would contend that the one area that and I will call it on premises STN shall we say right? Which is the people putting on STN solutions. I’d say the one area at least in my observation that they haven’t done well is that self-service model. Like in the cloud, self-service is paramount to Josh’s point. They can go out there, they can create their own BPC’s, create their own sub nets, create their own NAT gateways, Internet gateways to run security groups. Load balancers, blah-blah, all of that right? But it still seems to me that even though we are probably 90, 95% of the way there, maybe farther in terms of on premise STN solutions right that you still typically don’t see self-service being pushed out in the same way you would in the public cloud, right? That is almost the final piece that is needed to bring that cloud experience to the on-premises environment. [0:48:52.6] DC: That is an interesting point. I think from an infrastructure as a service perspective, it falls into that realm. It is a problem to solve in that space, right? So when you look at things like OpenStack and things like AWS and things like JKE or not JKE but GCE and areas like that, it is a requirement that if you are going to provide infrastructure as a service that you provide some capability around networking but at the same time, if we look at some of the platforms that are used for things like cloud native applications. Things like Kubernetes, what is fascinating about that is that we have agreed on a least come – we agreed on abstraction of networking that is maybe I don’t know, maybe a little more precooked you know what I mean? In the assumption within like most of the platforms as a service that I have seen, the assumption is that when I deploy a container or I deploy a pod or I deploy some function as a service or any of these things that the networking is going to be handled for me. I shouldn’t have to think about whether it is being routed to the Internet or not or routed back and forth between these domains. I should if anything only have to actually give you intent, be able to describe to you the intent of what could be connected to this and what ports I am actually going to be exposing and that the platform actually hides all of the complexity of that network away from me, which is an interesting round to strike. [0:50:16.3] SL: So, this is one of my favorite things, one of my favorite distinctions to make, right? And that is this is the two worlds that we have been talking about, applications and infrastructure and the perfect example of these different perspectives and you even said it or you talked there Duffie like from an IS perspective it is considered a given that you have to be able to say I want a network, right? But when you come at this from the application perspective, you don’t care about a network. You just want network connectivity, right? And so, when you look at the abstractions that IS vendors and solutions or products have created then they are IS centric but when you look at the abstractions that have been created in the cloud data space like within Kubernetes, they are application centric, right? And so, we are talking about infrastructure artifacts versus application artifacts and they end up meeting but they are coming at this from two different very different perspectives. [0:51:18.5] DC: Yeah. [0:51:19.4] NL: Yeah, I agree. [0:51:21.2] DC: All right, well that was a great discussion. I imagine that we are probably get into – at least I have a couple of different networking discussions that I wanted to dig into and this conversation I hope that we’ve helped draw some parallels back and forth between the way – I mean there is both some empathy to spend here, right? I mean the people who are providing the service of networking to you in your cloud environments and your data centers are solving almost exactly the same sorts of availability problems and capabilities that you are trying to solve with your own software. And I think in itself is a really interesting takeaway. Another one is that again there is nothing new under the sun. The problems that we are trying to solve in networking are not different than the problems that you are trying to solve in applications. We have far fewer tools and we generally network engineers are focused on specific changes that happen in the industry rather than looking at a breathe of industries like I mean as Josh pointed out, you could break open a Java book. And see 8,000 patterns for how to do Java and this is true, every programming language that I am aware of I mean if you look at Go and see a bunch of different patterns there and we have talked about different patterns for just developing cloud native aware applications as well, right? I mean there is so many options in the software versus what we can do and what are available to us within networks. And so I think I am rambling a little bit but I think that is the takeaway from this session. Is that there is a lot of overlap and there is a lot of really great stuff out there. So, this is Duffie, thank you for tuning in and I look forward to the next episode. [0:52:49.9] NL: Yep and I think we can all agree that Token Ring should have won. [0:52:53.4] DC: Thank you Josh and thank you Scott. [0:52:55.8] JS: Thanks. [0:52:57.0] SL: Thanks guys, this was a blast. [END OF EPISODE] [0:52:59.4] ANNOUNCER: Thank you for listening to The Podlets Cloud Native Podcast. Find us on Twitter at https://twitter.com/ThePodlets and on the http://thepodlets.io/ website, where you'll find transcripts and show notes. We'll be back next week. Stay tuned by subscribing. [END]See omnystudio.com/listener for privacy information.

Fivetran, a startup that helps companies move data from disparate repositories to data warehouses, announced $44 million Series B financing today, less than a year after collecting a $15 million Series A round. Andreessen Horowitz (A16Z) led the round with participation from existing investors Matrix Partners and CEAS Investments. As part of the deal, Martin Casado from A16Z will join the Fivetran board.

What happens when monolithic architectures are broken down into containers and microservices (or when things are broken down into smaller units, not just in infrastructure but perhaps even in company structure too)? From building more dynamic websites to monitoring the enterprise cloud to elastically scaling applications, where are developers in the enterprise going now and next? This episode of the a16z Podcast, based on a panel by and for developers recorded at the a16z Summit in November 2017 and moderated by general partner Martin Casado, features Matt Billmann, CEO and co-founder of Netlify; Florian Leibert, CEO and co-founder of Mesophere; and Karthik Rau, CEO and co-founder of SignalFX. The views expressed here are those of the individual AH Capital Management, L.L.C. (“a16z”) personnel quoted and are not the views of a16z or its affiliates. Certain information contained in here has been obtained from third-party sources, including from portfolio companies of funds managed by a16z. While taken from sources believed to be reliable, a16z has not independently verified such information and makes no representations about the enduring accuracy of the information or its appropriateness for a given situation. This content is provided for informational purposes only, and should not be relied upon as legal, business, investment, or tax advice. You should consult your own advisers as to those matters. References to any securities or digital assets are for illustrative purposes only, and do not constitute an investment recommendation or offer to provide investment advisory services. Furthermore, this content is not directed at nor intended for use by any investors or prospective investors, and may not under any circumstances be relied upon when making a decision to invest in any fund managed by a16z. (An offering to invest in an a16z fund will be made only by the private placement memorandum, subscription agreement, and other relevant documentation of any such fund and should be read in their entirety.) Any investments or portfolio companies mentioned, referred to, or described are not representative of all investments in vehicles managed by a16z, and there can be no assurance that the investments will be profitable or that other investments made in the future will have similar characteristics or results. A list of investments made by funds managed by Andreessen Horowitz (excluding investments and certain publicly traded cryptocurrencies/ digital assets for which the issuer has not provided permission for a16z to disclose publicly) is available at https://a16z.com/investments/. Charts and graphs provided within are for informational purposes solely and should not be relied upon when making any investment decision. Past performance is not indicative of future results. The content speaks only as of the date indicated. Any projections, estimates, forecasts, targets, prospects, and/or opinions expressed in these materials are subject to change without notice and may differ or be contrary to opinions expressed by others. Please see https://a16z.com/disclosures for additional important information.

When most people think of space, they think of outer space: Mars, billionaires with rockets, and the “final frontier”. But space innovation is actually playing out right now -- in an immediate and more accessible way, thanks to techonologies getting smaller, faster, and cheaper -- through micro satellites that do everything from map terrain, to telecommunications that can provide connectivity even in remote areas. This episode of the a16z Podcast -- based on an November 2017 a16z Summit conversation moderated by general partner Martin Casado with Dan Berkenstock, founding CEO of Skybox Imaging; John Gedmark, CEO and co-founder of Astranis; and Steve Smith, former astronaut from NASA -- covers how this trend of small satellites is developing, as well as what existing applications it will change to what new business opportunities it presents. The views expressed here are those of the individual AH Capital Management, L.L.C. (“a16z”) personnel quoted and are not the views of a16z or its affiliates. Certain information contained in here has been obtained from third-party sources, including from portfolio companies of funds managed by a16z. While taken from sources believed to be reliable, a16z has not independently verified such information and makes no representations about the enduring accuracy of the information or its appropriateness for a given situation. This content is provided for informational purposes only, and should not be relied upon as legal, business, investment, or tax advice. You should consult your own advisers as to those matters. References to any securities or digital assets are for illustrative purposes only, and do not constitute an investment recommendation or offer to provide investment advisory services. Furthermore, this content is not directed at nor intended for use by any investors or prospective investors, and may not under any circumstances be relied upon when making a decision to invest in any fund managed by a16z. (An offering to invest in an a16z fund will be made only by the private placement memorandum, subscription agreement, and other relevant documentation of any such fund and should be read in their entirety.) Any investments or portfolio companies mentioned, referred to, or described are not representative of all investments in vehicles managed by a16z, and there can be no assurance that the investments will be profitable or that other investments made in the future will have similar characteristics or results. A list of investments made by funds managed by Andreessen Horowitz (excluding investments and certain publicly traded cryptocurrencies/ digital assets for which the issuer has not provided permission for a16z to disclose publicly) is available at https://a16z.com/investments/. Charts and graphs provided within are for informational purposes solely and should not be relied upon when making any investment decision. Past performance is not indicative of future results. The content speaks only as of the date indicated. Any projections, estimates, forecasts, targets, prospects, and/or opinions expressed in these materials are subject to change without notice and may differ or be contrary to opinions expressed by others. Please see https://a16z.com/disclosures for additional important information.

with Joel de la Garza, Stina Ehrensvärd, Niels Provos, and Martin Casado Given the heated discussions around security and the c-word (“cyber”), it's hard to figure out what the actual state of the industry is. And clearly it's not just an academic exercise — it is a matter of both business survival and personal safety. As cyber, physical, and national security become one and the same, how does that make us rethink how businesses address the problem, from software to hardware? And where do consumers come in? This episode of the a16z Podcast — based on a conversation recorded at our Summit event in November 2017 — features Stina Ehrensvärd, founder and CEO, of Yubico; Joel de la Garza, CISO of Box; and Niels Provos, distinguished engineer at Google, moderated by a16z general partner Martin Casado. ––– The views expressed here are those of the individual AH Capital Management, L.L.C. (“a16z”) personnel quoted and are not the views of a16z or its affiliates. Certain information contained in here has been obtained from third-party sources, including from portfolio companies of funds managed by a16z. While taken from sources believed to be reliable, a16z has not independently verified such information and makes no representations about the enduring accuracy of the information or its appropriateness for a given situation. This content is provided for informational purposes only, and should not be relied upon as legal, business, investment, or tax advice. You should consult your own advisers as to those matters. References to any securities or digital assets are for illustrative purposes only, and do not constitute an investment recommendation or offer to provide investment advisory services. Furthermore, this content is not directed at nor intended for use by any investors or prospective investors, and may not under any circumstances be relied upon when making a decision to invest in any fund managed by a16z. (An offering to invest in an a16z fund will be made only by the private placement memorandum, subscription agreement, and other relevant documentation of any such fund and should be read in their entirety.) Any investments or portfolio companies mentioned, referred to, or described are not representative of all investments in vehicles managed by a16z, and there can be no assurance that the investments will be profitable or that other investments made in the future will have similar characteristics or results. A list of investments made by funds managed by Andreessen Horowitz (excluding investments and certain publicly traded cryptocurrencies/ digital assets for which the issuer has not provided permission for a16z to disclose publicly) is available at https://a16z.com/investments/. Charts and graphs provided within are for informational purposes solely and should not be relied upon when making any investment decision. Past performance is not indicative of future results. The content speaks only as of the date indicated. Any projections, estimates, forecasts, targets, prospects, and/or opinions expressed in these materials are subject to change without notice and may differ or be contrary to opinions expressed by others. Please see https://a16z.com/disclosures for additional important information.

with Martin Casado (@martin_casado), Michel Feaster (@michelfeaster) and Sonal Chokshi (@smc90) The purpose of category creation, argue the guests in this episode of the podcast, isn't just about making a dent in the way companies work and changing what people do every day... it's about setting the price. And with that, comes creating the concept in people's heads, defining the value, and setting the rules of the game. But when you're going for a big change, you have to play by the current rules of the game, too. And to make things even more complicated, theories about how "IT is dead" -- or the conviction that companies and departments beyond IT will become empowered through software -- are still very much in transition. Somehow we don't talk about that enough. That means startups need to do everything in two phases: for the now, and for the later and towards two constituencies: both direct lines of businesses and IT. So what does that mean for startups trying to navigate a complex enterprise, including internal debates around build vs. buy? How do you move beyond a few internal champions only? And just how long can a company cash out on founder charisma? In fact, all of these things can give entrepreneurs very confusing, mixed signals about whether or not they have product-market fit yet. So what patterns reveal that it's working? In this episode of the a16z Podcast, general partner Martin Casado -- who helped create the category of "software-defined networking" in the enterprise through Nicira and then VMware (and has also written about the mixed messages involved in going to market when no market exists) -- and Michel Feaster, CEO and co-founder of Usermind, and who previously (as VP of products at Apptio) also defined the category and discipline of "technology business management" -- share their insights, in conversation with Sonal Chokshi. It's a long game, but if you can tease apart the signals, and nail some key moves early... you can win.

When you have “a really hot, frothy space” like AI, even the most basic questions — like what is it good for, how do you make sure your data is in shape, and so on — aren't answered. This is just as true for the companies eager to adopt the technology and get into the space, as it is for those building companies around that space, observes Joe Spisak, Head of Partnerships at Amazon Web Services. “People treat it like magic,” adds a16z general partner Martin Casado. This magical realism is especially true of AI, because by definition — i.e., machines learning — there is a bit of a “black box” between what you put in and what you get out of it. Which may be fine… Except when you have to completely change the data being fed into that black box, or you're shooting for a completely different target to come out of it. That's why, observes Scott Clark, CEO and co-founder of SigOpt, “an untuned, sophisticated system will underperform a tuned simple system” almost every time. So what does this mean for organizations going from so-called “toy” problems in R&D to real business results tied to KPIs and ROI? In this episode of the a16z Podcast, Casado, Clark, and Spisak (in conversation with Sonal Chokshi) share their thoughts on what's happening and what's needed for AI in practice, given their vantage points working with both large companies and AI startups. What does it mean for data scientists and domain experts? For differentiation and advantage? Because even though we finally have widely available building blocks for AI, we need the scaffolding too… and only then can we build something powerful on top of it.

Hiring a VP of Product -- especially as the founder of the company -- can almost feel like handing over your baby to someone else to hold, observes a16z executive talent team partner Caroline Horn, who hosted an event on this topic earlier this year (which this podcast is based on). Featuring Vijay Balasubramaniyan, founder/CEO of Pindrop; Shishir Mehrotra, founder and CEO of Coda; Gokul Rajaram, Production Engineering Lead at Square; and Alan Schaaf, founder/CEO of Imgur -- and moderated by general partner Martin Casado -- the discussion covers everything from what the VP of Product role really is to how to hire and integrate it into your company. Because if you're going to be handing your "baby" over... how can you avoid common pitfalls? And know that you pick the right person for the job?

When individuals gain the abilities that only nation states once had, how do we put cyber threats in perspective for policymakers -- without unduly "inflating" the threats? As it is, security is an intense and important topic, so our job is to be scared -- and prepared -- but what's the scope of the actual threats, how do we talk about them, and what are the best analogies even? For example, we tend to think about "getting inside" as the big problem -- but in fact, the steady, "low-grade" degradation of trust and constant exposure is much more common and where we should be focusing holistically.  The guests in this episode of the a16z Podcast discuss all this in a conversation (with a16z's Matt Spence) recorded as part of our Tech Policy Summit in Washington D.C.: a16z general partner Martin Casado; Head of Cybersecurity Strategy at Illumio Nathaniel Gleicher; and former Director of the National Counterterrorism Center and former General Counsel for the NSA Matthew Olsen.

Nearly every cybersecurity discussion/presentation follows this formula: We don't know what we're doing; the bad guys are getting smarter; our defenses are getting worse; everything's more connected than ever; we're heading towards a digital . But even though security itself has obviously changed in many ways and not in others, we — as an industry — have actually gotten pretty good at doing our jobs, argues a16z general partner Martin Casado in this segment excerpted from a talk he gave at our recent Tech Policy Summit in Washington, D.C. That's not to minimize the seriousness or cost of cyber attacks! It's just that changing the conversation here will let us pay attention to the fact that “cybersecurity” these days is really… “security”. Because we shouldn't isolate the “cyber”; we need to always think of digital assets, physical assets, and human assets together. Especially as cyber — or rather, just security — has become more physical than ever (and not in the obvious Internet of Things sense).

Here's what we know about open source: Developers are the new buyers. Community matters. And there will never be another Red Hat (i.e., a successful “open core” business model … nor do we necessarily think there should be). Yet open source is real, and it's here to stay. So how then do companies build a viable business model on top of open source? And not only make money, but become a huge business, like the IBMs, Microsofts, Oracles, and SAPs of the world? The answer, argues James Watters, has more to do with good software strategy and smart enterprise sales/procurement tactics (including design and a service-like experience) than with open source per se — from riding a huge trend or architectural shift, to being less transactional and more an extension of your customer's team. Watters, who is the SVP of Product at Pivotal (part of VMWare and therefore also Dell-EMC), is a veteran of monetizing open source — from OpenSolaris (at Sun Microsystems) to Springsource (acquired by VMWare) to Pivotal Cloud Foundry — with plenty of failures, and successes, along the way. He shares those lessons learned in this episode of the a16z Podcast with Sonal Chokshi and general partner Martin Casado (who was co-founder and CTO of Nicira, later part of VMWare before joining Andreessen Horowitz). These lessons matter, especially as open source has become more of a requirement — and how large enterprises bet on big new trends.

"Incremental change may be good theory, but in practice you have to have a big enough stick to hit everybody with to make everything move at once". So shares Adrian Cockcroft, who helped lead Netflix's migration from datacenter to the cloud -- and from monolithic to microservices architecture -- when their streaming business (the "stick"!) was exploding. So how did they -- and how can other companies -- make such big, bet-the-company kind of moves, without getting mired in fanatical internal debates? Does organizational structure need to change, especially if moving from a more product-, than project-based, approach? What happens to security? And finally, what happens to the role of CIOs; what can/should they do? Most interestingly: How will the entire industry be affected as companies not only adopt, but essentially offer, microservices or narrow cloud APIs? How do the trends of microservices, containers, devops, cloud, as-a-service/ on-demand, serverless -- all moves towards more and more ephemerality -- change the future of computing and even work? Cockcroft (who is now a technology fellow at Battery Ventures) joins this episode of the a16z Podcast, in conversation with Frank Chen and Martin Casado (and Sonal Chokshi) to discuss these shifts and more. The views expressed here are those of the individual AH Capital Management, L.L.C. (“a16z”) personnel quoted and are not the views of a16z or its affiliates. Certain information contained in here has been obtained from third-party sources, including from portfolio companies of funds managed by a16z. While taken from sources believed to be reliable, a16z has not independently verified such information and makes no representations about the enduring accuracy of the information or its appropriateness for a given situation. This content is provided for informational purposes only, and should not be relied upon as legal, business, investment, or tax advice. You should consult your own advisers as to those matters. References to any securities or digital assets are for illustrative purposes only, and do not constitute an investment recommendation or offer to provide investment advisory services. Furthermore, this content is not directed at nor intended for use by any investors or prospective investors, and may not under any circumstances be relied upon when making a decision to invest in any fund managed by a16z. (An offering to invest in an a16z fund will be made only by the private placement memorandum, subscription agreement, and other relevant documentation of any such fund and should be read in their entirety.) Any investments or portfolio companies mentioned, referred to, or described are not representative of all investments in vehicles managed by a16z, and there can be no assurance that the investments will be profitable or that other investments made in the future will have similar characteristics or results. A list of investments made by funds managed by Andreessen Horowitz (excluding investments and certain publicly traded cryptocurrencies/ digital assets for which the issuer has not provided permission for a16z to disclose publicly) is available at https://a16z.com/investments/. Charts and graphs provided within are for informational purposes solely and should not be relied upon when making any investment decision. Past performance is not indicative of future results. The content speaks only as of the date indicated. Any projections, estimates, forecasts, targets, prospects, and/or opinions expressed in these materials are subject to change without notice and may differ or be contrary to opinions expressed by others. Please see https://a16z.com/disclosures for additional important information.

Now that we know to price and plan early, price high -- especially for category-creating or "pre-chasm" businesses -- how do we handle freemium models? While free to premium is a great way to get bottoms-up, often viral traction in an enterprise, the challenge is figuring out just where and how to "draw the line" between where free ends and paid begins. Especially for open source, which while not necessarily free/mium, is also affected by these questions. And in that case, how does one balance the developer community and desire to "spread the religion" within and beyond the enterprise? All this and more in this episode of the a16z Podcast with Andreessen Horowitz general partners (who cover all things infrastructure) Martin Casado and Peter Levine and Go-to-Market and EBC operating head Mark Cranney. The trick, they tells us, involves layering ... like layers in a cake.

"Raise prices." Regular listeners of our podcast have heard this advice more than once. But why is this so key and yet so hard for many technical founders? And how should startups go about raising prices -- or more specifically, creating value -- for their products? In this episode of the a16z Podcast, former sales VP Mark Cranney (and head of a16z's EBC and go-to-market practice for startups) and former startup founder (and general partner focused on all things infrastructure) Martin Casado talk to managing partner Scott Kupor about pricing for startups ... especially for category-creating businesses. It's not all "pricing, pricing, pricing" though -- there's another important "p" in there too!

Developers are more than just influencers inside the enterprise -- they're now buyers, too. That's a huge shift from before, when only IT and other departments had that kind of purchasing power. (It's not just a Silicon Valley thing, either, as every company becomes a software company.) So what's different then about selling and marketing to developers? One key is open source. But offering products and services built on top of open source brings up a whole slew of other questions: What are viable business models, how do you monetize? Especially since (as Peter Levine has argued before) there will never be another Red Hat a.k.a. a successful "open core" business model. a16z partners Levine and Martin Casado offer their observations and advice about selling to developers and open source business models in this episode of the podcast. The answers affect everything from sales -- yes, you still need sales even when selling to developers! -- to product management (what features to withhold, who builds them) and go to market plan. The views expressed here are those of the individual AH Capital Management, L.L.C. (“a16z”) personnel quoted and are not the views of a16z or its affiliates. Certain information contained in here has been obtained from third-party sources, including from portfolio companies of funds managed by a16z. While taken from sources believed to be reliable, a16z has not independently verified such information and makes no representations about the enduring accuracy of the information or its appropriateness for a given situation. This content is provided for informational purposes only, and should not be relied upon as legal, business, investment, or tax advice. You should consult your own advisers as to those matters. References to any securities or digital assets are for illustrative purposes only, and do not constitute an investment recommendation or offer to provide investment advisory services. Furthermore, this content is not directed at nor intended for use by any investors or prospective investors, and may not under any circumstances be relied upon when making a decision to invest in any fund managed by a16z. (An offering to invest in an a16z fund will be made only by the private placement memorandum, subscription agreement, and other relevant documentation of any such fund and should be read in their entirety.) Any investments or portfolio companies mentioned, referred to, or described are not representative of all investments in vehicles managed by a16z, and there can be no assurance that the investments will be profitable or that other investments made in the future will have similar characteristics or results. A list of investments made by funds managed by Andreessen Horowitz (excluding investments and certain publicly traded cryptocurrencies/ digital assets for which the issuer has not provided permission for a16z to disclose publicly) is available at https://a16z.com/investments/. Charts and graphs provided within are for informational purposes solely and should not be relied upon when making any investment decision. Past performance is not indicative of future results. The content speaks only as of the date indicated. Any projections, estimates, forecasts, targets, prospects, and/or opinions expressed in these materials are subject to change without notice and may differ or be contrary to opinions expressed by others. Please see https://a16z.com/disclosures for additional important information.

Infrastructure. It powers everything from cities to computing, yet is sometimes considered "boring" because it is so invisible to so many of us. But as software continues to eat the world, infrastructure has come to the forefront. And some of the most exciting technology innovations are now happening at the infrastructure level: It's changing everything, observes a16z's newest general partner Martin Casado -- from how new tech is created to how new tech is sold. Casado -- one of the pioneers of "software-defined networking" -- joins this episode of the a16z Podcast with Sonal Chokshi and Michael Copeland to share his journey from Lawrence Livermore National Laboratory to Stanford to Nicira Networks to VMware to a16z. He also discusses the tradeoffs in theoretical v. applied computer "science", including lessons learned as a PhD and technologist who then had to run a startup through hard times. Finally, Casado shares what he thinks are the key vectors and trends in networking, what's coming next, how the "as-a-service"(ification) of infrastructure is creating entirely new patterns of buying tech, and how selling to developers is so different (hint: open source is a lot more important than you might think!).