Podcasts about Jagged

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Jagged Jungle: Golden Hour with Jayli

Welcome back to Jagged Jungle

Agentic AI is reshaping enterprise software faster than most CIOs, CFOs, and vendors are prepared for. Praveen Akkiraju, Managing Director at Insight Partners, joins Michael Krigsman to examine the state of agentic AI in 2026: what works in production, what remains hype, and how sophisticated enterprises are now running more than 1,000 agents at scale. The conversation covers the engineering that separates reliable agents from unreliable ones, the economics of token consumption, and the build-vs-buy calculus facing enterprise buyer4s.YOU'LL DISCOVER✅ Why Praveen argues "the agent is actually the harness," and what a harness includes: tools, context, memory, and guardrails✅ "Jagged intelligence": why state-of-the-art models still fail on basic prompt variations, and the implications for production deployment✅ How leading enterprises are operating 1,000+ agents and the governance questions that remain unresolved✅ A bounded vs. unbounded framework for deciding where agent autonomy is realistic and where human approval must stay✅ Why "token maxing" is consuming annual AI budgets in 90 days, and what CIOs can do about it✅ How Stampli inserts agentic steps into invoice reconciliation rather than rebuilding the workflow from scratch✅ Build vs. buy: why front-end workflows favor buying and back-end, data-heavy workflows favor building✅ The fractional-FTE pricing model emerging for agentic products, and what it means for software economics⏱️ TIMESTAMPS0:00 Token maxing and the enterprise AI budget problem0:23 Model evolution: reasoning, DeepSeek, and the agentic inflection2:03 What is an agent: models plus harness4:46 Hype versus reality in agentic AI8:31 Where agents deliver measurable value today13:10 Agent negligence, guardrails, and sandboxes16:06 Data access boundaries: APIs, MCP, and policy files20:38 Bolt-on agents versus agent-native software26:53 Human in the loop or autonomous: the operating model question33:49 Fix your data first, or start now?41:54 Will agents replace Salesforce and Workday?47:28 Build vs. buy: front end versus back end50:45 Token costs and the return of variable-cost software54:09 Pricing agents as fractional FTEs

Episode 14 of Jagged Jungle is here, a golden-hour journey through melodic house, tropical grooves, afro rhythms and tribal edits, curated by Jayli. This week opens with the beautiful Lost Frequencies & Nathan Nicholson – So Much Beauty Around Us, before moving into sun-soaked sax energy from York – On The Beach, tropical heat from Palm Monkey & Russi, and a very special Jayli Jungle Edit of Follow Your Sun. Our Treasure Track this week goes back to one of Purple Disco Machine's early records, My House on Off Recordings, before we move into Dean Mickoski – La Trompeta on Stealth Records. For our New Wave Artist, we spotlight Chapter & Verse with Hands Up on Myth of NYX — bringing big club energy and a proper Jagged Jungle connection after playing with us last year. The second half takes us deeper into the jungle with music from Tom Enzy, Astrality & FLORES, Peppe Citarella & Yas Cepeda, SHADU, DJ Hermes, Fly, OR3X, Solander, and a beautiful closing track from Jerro & Benjamin Roustaing – Rush on Thrive Music. Also in this episode: Jagged Jungle event updates, our guest list for The Ned is now closed, with a waiting list open via Instagram, and tickets are still available for Sushi Samba / Samba Room on 8th May, with tables already sold out. Expect warm percussion, sunset melodies, tribal edits, afro house energy and that signature Jagged Jungle sound. Follow Jayli / Jagged Jungle: Instagram: @jaylimusic TikTok: @jaylimusic SoundCloud: Jayli Mixcloud: Jayli

Synopsis: Two decades after Hurricane Katrina ravaged Louisiana, the state is now facing a new kind of storm: the rapid expansion of liquified natural gas facilities that are displacing residents and polluting minority communities. This show is made possible by you! To become a sustaining member go to LauraFlanders.org/donate Description: Hurricane Katrina was one of the deadliest hurricanes ever to strike the United States, killing 1,833 people, displacing hundreds of thousands more and causing more than $100 billion in damage. Louisianans wanted change and climate action, but 20 years on, a state ravaged by climate disasters is now ground zero for a whole new kind of storm: liquified natural gas facilities. The Trump administration okayed several new LNG plants on the Gulf this year, but residents are still picking up the pieces after the first LNG plants entered their neighborhood under Democratic administrations. In this episode, Laura speaks to Louisianans whose lives have been turned upside down by the expansion of LNG exports, and an expert who says minority communities benefit little from the jobs in the petrochemical facilities that surround them, yet suffer disproportionate pollution effects. Their message? Climate refugees exist in the U.S., and there will be more: “Wake up, open your eyes!” “[I'm a] climate refugee, more than once . . . I'm no scientist, but I'm more of an expert than the experts. Living it's a whole different ball game.” - Travis Dardar “[Companies] demand big tax incentives to come here . . . We are last in transportation, last in healthcare, last in education . . . We're almost last in every measurable area because we give tax breaks to the big oil companies and petrochemical companies.” - General Russel L. Honoré “Donald Trump doesn't live next to an oil refinery and he never will.” - Kimberly Terrell Guests: •  Travis Dardar: Commercial Fisherman; Founder, Fishermen Interested In Saving our Heritage (FISH) •  General Russel L. Honoré: Decorated 37-Year Army Veteran; Commander, Joint Task Force Katrina; Founder, GreenARMY •  Kimberly Terrell: Visiting Scientist, Center for Applied Environmental Science (CAES); Former Research Scientist & Director, Community Engagement, Tulane Environmental Law Clinic Additional Crew: for this special report includes Dan T. Peters of Dan T. Peters Media and Calvin Blue Jr..  Special Thanks:  Gina Kim and Anne Rolfes Music credits: Jagged and Thrum of Soil by Blue Dot Sessions and original sound design by Jeannie Hopper   Watch the episode released on YouTube August 1st, 5pm ET; PBS World Channel August 3rd, and on over 300 public stations across the country (check your listings, or search here via zipcode). Listen: Episode airing on community radio (check here to see if your station airs the show) & available as a podcast August 6th. Full Episode Notes are located HERE. -Related Podcast:  Uncut Conversation with General Russel L. Honoré: Decorated 37-Year Army Veteran; Commander, Joint Task Force Katrina; Founder, GreenARMY   RESOURCES: Related Laura Flanders Show Episodes: •  Colette Pichon Battle on Climate Justice Reparations- Watch / Listen:  Episode, Full Conversation •  BIPOC Media Answers the Call: Community Action After Hurricane Helene- Watch / Listen:  Episode, Full Conversation •  Before the Ground Runs Dry: BIPOC Media on the US Water Crisis: Watch / Listen:  Episode Related Articles and Resources: • "Immunity for oil & gas companies are on the horizon if HB804 becomes law in Louisiana:" -  A new bill from State Rep. Geymann would restrict nearly any claims for damages caused by emissions. Environmental reporter Emily Sanders from ExxonKnews explains what's in the bill." by Carolyne Heldman, Behind the Lens Podcast • War in Iran increases demand for U.S. liquified natural gas providers, by Drew Hawkins, March 13, 2026, Morning Edition - NPR  •  Fishfolk are on the frontlines of the gas export boom, Venture Global's Calcasieu Pass 2, or CP2, threatens the way of life on Louisiana's Gulf Coast, January 25, 2025, Southern Environmental Law Center •  The Biden Administration's Next Big Climate Decision.  The liquefied-natural-gas-buildout-and fossil-fuel exports-challenge progress on global warming.  September 22, 2023,  By Bill McKibben, October 31, 2023, The New Yorker •  Pervasive racial and ethnic disparities in the U.S. petrochemical workforce, by Kimberly Terrell, Gianna St. Julien, Michael Ash, September 2025 Science Direct Laura Flanders and Friends Crew: Laura Flanders-Executive Producer, Writer; Sabrina Artel-Supervising Producer; Jeremiah Cothren-Senior Producer; Veronica Delgado-Video Editor, Janet Hernandez-Communications Director; Jeannie Hopper-Audio Director, Podcast & Radio Producer, Audio Editor, Sound Design, Narrator; Sarah Miller-Development Director, Nat Needham-Editor, Graphic Design emeritus; David Neuman-Senior Video Editor, and Rory O'Conner-Senior Consulting Producer. FOLLOW Laura Flanders and FriendsInstagram: https://www.instagram.com/lauraflandersandfriends/Blueky: https://bsky.app/profile/lfandfriends.bsky.socialFacebook: https://www.facebook.com/LauraFlandersAndFriends/Tiktok: https://www.tiktok.com/@lauraflandersandfriendsYouTube: https://www.youtube.com/channel/UCFLRxVeYcB1H7DbuYZQG-lgLinkedin: https://www.linkedin.com/company/lauraflandersandfriendsPatreon: https://www.patreon.com/lauraflandersandfriendsACCESSIBILITY - The broadcast edition of this episode is available with closed captioned by clicking here for our YouTube Channel

Harish Vasudevan deconstructs the complexity of digital marketing, arguing that it is simply "direct marketing on steroids". By focusing on the "Holy Grail" of one-on-one communication and simplifying the customer journey to its basic essence, businesses can stop wasting money on flashy tools.The key is to balance data with human instinct, avoiding the "last-click" trap that ignores the long road a consumer travels before buying.Many marketers are "driving into lakes" by following data blindly. Harish Vasudevan provides a refreshing perspective on metrics, urging non-marketers to start with questions rather than spreadsheets. From the enduring power of email (the "roach" of marketing) to the new "black boxes" of AI search, this conversation is a guide to navigating the digital arc without losing your business intuition.Jagged with Jasravee is facilitated by Jasravee Kaur Chandra. Jasravee has over 25 years experience as a Strategic Brand Builder, Communications Leader and Entrepreneur.

JAGGED JUNGLE – EPISODE 13 This week on Jagged Jungle, we move through a deeper, more reflective journey — blending melodic house, afro influences, and late-night energy with moments that hit a little closer. From the opening energy of AYYBO – Rizz into the warmth of Francis Mercier, Faul & Wad and the African Children's Choir on Sauti, this episode flows between light and shade. We bring in a Jungle Edit a Jayli rework of Lambada and Tove Lo – Habits, flipping two iconic records into one Jagged Jungle moment. This week's New Wave Artist spotlight features MAFRO, alongside rising force TSHA, both shaping the next wave of melodic and percussive electronic music. The Golden Minute transitions beautifully from Edge Of Desire into Monolink – Father Ocean (Ben Böhmer Remix) a reminder that sometimes the most powerful moments aren't the loudest. And for this week's Treasure Track, we revisit a collaboration from three powerhouses Autograf, Klingande, and Dragonette with Hope For Tomorrow (Nico De Andrea Remix). A track that still holds weight years on. Closing out with deeper, hypnotic energy from artists like John Summit, Feid and BØRÅ. This is Jagged Jungle — music to switch off the noise and come back to yourself. — Listen back: SoundCloud / Mixcloud / YouTube: @jaylimusic Upcoming shows: London 08.05 – Samba Rooms in the Sky 16.05 – The Ned (The Vault) Follow for weekly episodes + exclusive Jungle Edits

Jagged Jungle – Episode 12

Fresh off raising a monster $15B, Marc Andreessen has lived through multiple computing platform shifts firsthand, from Mosaic and Netscape to cofounding A16z. In this episode, Marc joins swyx and Alessio in a16z's legendary Sand Hill Road office to argue that AI is not just another hype cycle, but the payoff of an “80-year overnight success”: from neural nets and expert systems to transformers, reasoning models, coding, agents, and recursive self-improvement. He lays out why he thinks this moment is different, why AI is finally escaping the old boom-bust pattern, and why the real bottleneck may be less about models than about the messy institutions, incentives, and social systems that struggle to absorb technological change.This episode was a dream come true for us, and many thanks to Erik Torenberg for the assist in setting this up. Full episode on YouTube!We discuss:* Marc's long view on AI: from the 1980s AI boom and expert systems to AlexNet, transformers, and why he sees today's moment as the culmination of decades of compounding technical progress* Why “this time is different”: the jump from LLMs to reasoning, coding, agents, and recursive self-improvement, and why Marc thinks these breakthroughs make AI real in a way prior cycles were not* AI winters vs. “80-year overnight success”: why the field repeatedly swings between utopianism and doom, and why Marc thinks the underlying researchers were mostly right even when the timelines were wrong* Scaling laws, Moore's Law, and what to build: why he believes AI scaling laws will continue, why the outside world is messier than lab purists assume, and how startups can still create durable value on top of rapidly improving models* The dot-com crash and AI infrastructure risk: Marc's comparison between today's AI capex boom and the fiber/data-center overbuild of 2000, plus why he thinks this cycle is different because the buyers are huge cash-rich incumbents and demand is already here* Why old NVIDIA chips may be getting more valuable: the pace of software progress, chronic capacity shortages, and the idea that even current models are “sandbagged” by supply constraints* Open source, edge inference, and the chip bottleneck: why Marc thinks local models, Apple Silicon, privacy, trust, and economics all point toward a major role for edge AI* American vs. Chinese open source AI: DeepSeek as a “gift to the world,” why open models matter not just because they're free but because they teach the world how things work, and how open source strategies may shift as the market consolidates* Why Pi and OpenClaw matter so much: Marc's claim that the combination of LLM + shell + filesystem + markdown + cron loop is one of the biggest software architecture breakthroughs in decades* Agents as the new “Unix”: how agent state living in files allows portability across models and runtimes, and why self-modifying agents that can extend themselves may redefine what software even is* The future of coding and programming languages: why Marc thinks software becomes abundant, why bots may translate freely across languages, and why “programming language” itself may stop being a salient concept* Browsers, protocols, and human readability: lessons from Mosaic and the web, why text protocols and “view source” mattered, and how similar principles may shape AI-native systems* Real-world OpenClaw use: health dashboards, sleep monitoring, smart homes, rewriting firmware on robot dogs, and why the most aggressive users are discovering both the power and danger of agents first* Proof of human vs. proof of bot: why Marc thinks the internet's bot problem is now unsolvable via detection alone, and why biometric + cryptographic proof of human becomes necessaryTimestamps* 00:00 Marc on AI's “80-Year Overnight Success”* 00:01 A Quick Message From swyx* 01:44 Inside a16z With Marc Andreessen* 02:13 The Truth About a16z's AI Pivot* 03:29 Why This AI Boom Is Not Like 2016* 06:33 Marc on AI Winters, Hype Cycles, and What's Different Now* 10:09 Reasoning, Coding, Agents, and the New AI Breakthroughs* 12:13 What Founders Should Build as Models Keep Improving* 16:33 AI Capex, GPU Shortages, and the Dot-Com Crash Analogy* 24:54 Open Source AI, Edge Inference, and Why It Matters* 33:03 Why OpenClaw and PI Could Change Software Forever* 41:37 Agents, the End of Interfaces, and Software for Bots* 46:47 Do Programming Languages Even Have a Future?* 54:19 AI Agents Need Money: Payments, Crypto, and Stablecoins* 56:59 Proof of Human, Internet Bots, and the Drone Problem* 01:06:12 AI, Management, and the Return of Founder-Led Companies* 01:12:23 Why the Real Economy May Resist AI Longer Than Expected* 01:15:53 Closing ThoughtsTranscriptMarc: Something about AI that causes the people in the field, I would say, to become both excessively utopian and excessively apocalyptic. Having said that, I think what's actually happened is an enormous amount of technical progress that built up over time. And like for, for example, we now know that neural network is the correct architecture.And I, I will tell you like there was a 60 year run where that was like a, you know, or even 70 years where that was controversial. And so, so the way I think about what's happening is basically, I think, I think about basically the, the, the period we're in right now is it's, I call it 80 year overnight success, right?Which is like, it's an overnight success ‘cause it's like bam, you know, chat GPT hits and then, and then oh one hits, and then, you know, open claw hits and like, you know, these are open, these are, these are like overnight, like radical, overnight transformative successes, but they're drawing on an 80 year sort of wellspring backlog, you know, of, of, of, of ideas and thinking it's not just that it's all brand new, it's that it's an unlock of all of these decades of like very serious, hardcore research.If I were 18, like this is a hundred, this is what I would be spending all of my time on. This is like such an incredible conceptual breakthrough.swyx: Before we get into today's episode, I just have a small message for listeners. Thank you. We will not be able to bring you the ai, engineering, science, and entertainment contents that you so clearly want if you didn't choose to also click in and tune into our content.We've been approached by sponsors on an almost daily basis, but fortunately enough of you actually subscribed to us to keep all this sustainable without ads, and we wanna keep it that way. But I just have one favor to ask all of you. The single, most powerful, completely free thing you can do is to click that subscribe button.It's the only thing I'll ever ask of you, and it means absolutely everything to me and my team that works so hard to bring the in space to you each and every week. If you do it, I promise you will never stop working to make the show even better. Now, let's get into it.Alessio: Hey everyone, welcome to the Lidian Space Pockets. This is CIO, founder Kernel Labs, and I'm joined by s Swix, editor of Lidian Space.swyx: Hello. And we're in a 16 Z with a, uh, mark G and welcome.Marc: Yes, yes. A and what, half of 16? Something like that. A one. Exactly,swyx: exactly. Uh, apparently this is the, the final few days in your, your current office.You're moving across the road.Marc: Uh, we're, yeah. We have a, we have some, we have some projects underway, but yeah, this is actually, oh, this is the original. We're in actually the original office. We're in the, we're in the, we're, we're in the whole thing.swyx: It's beautiful. Yeah. Great.Marc: Thank you.swyx: So I have to come out, uh, this is a, you know, I wanted to pick a spicy start in October, 2022.I just made friends with Roone and, uh, I wanted to give him something to sort of be spicy about. And I said, uh. Uh, it'll never not be funny. The A 16 Z was constantly going. The future is where the smart people choose to spend their time and then going deep into crypto and not in ai. And that was in October 22nd, 2022.And Ruen says there was an internal meeting in a 16 Z to reorient around Gen ai. Obviously you have, but was there a meeting? What, what was that?Marc: I mean, I don't, look, I've been doing AI since the late eighties.swyx: Yeah.Marc: So I, I don't know, like all that, as far as I'm concerned, this stuff is all Johnny cum lately.Yeah. You, I mean, look, we've been doing ar entire existence. I mean, we've been doing AI machine learning deep, you know, deeply. We've been doing this stuff way from the beginning. Obviously a AI is just core to computer science. I, I, I actually view them as like quite, uh, quite continuous. Um, you know, Ben and I both have computer science degrees.Um, you know, we, we both, Ben, Ben and I actually both are world enough to remember the actual AI boom in the 1980s. Yeah. There was like a, there was a big AI boom at the time. Um, and there was a, was names like expert systems. Um, and they of like lisp and lisp machines. Uh, I, I coded in lisp. I was coding a lisp in 1989.When that was the, the language of the AI future. Um, yeah. So this is something that we're like completely, you completely comfortable with. I've been doing the whole time and are very enthusiastic aboutswyx: is there a strong, like this time is different because, uh, my closest analog was 20 16 17. It was an AI boom.Mm-hmm. And it petered out very, very quickly. Um, we, it just, it just in terms of investingMarc: sort of, sort of,swyx: yeah. Investment, investment excitement.Marc: Although that's really when the, the, the Nvidia phenomenon really, it was, I would say it was in that period when it was very clear that at, at the time it, the vocabulary was more machine learning, but it, it was very clear at that time that machine learning was hitting some sort of takeoff point.Alessio: Yeah.Marc: Well, and as you guys, you guys have talked about this at length on, on your thing, but, you know, if you really track what happened, I think the real story is, it was, it was the Alex net, uh, basically breakthrough in like 2013. That was the, that was the real knee in the curve. Um, and then it was obviously the transformer breakthrough in 17.Alessio: Yeah.Marc: Um, and then everything that followed. But, but, you know, look, machine learning, you know, there were, you know, look, uh, I mean look, I've been working, you know, I've been working with, uh, one of my, you know, kind of projects working with Facebook since 2004. Um, and on the board since 2007, and of course, you know, they, they started using machine learning very early, um, and, you know, have used it basically, you know, for like 20 years for, you know, content, you know, feed optimization and advertising optimization.And obviously many, you know, financial services. You know, many, many, many companies, many different sectors have been doing this. And so it's like one of these things, it's like, it's not a, it's not a single thing. Like it's, it's like, it's like layers, right? Yeah. Um, and, and the layers arrive at different paces and, but they kind of build up.swyx: Yeah.Marc: Uh, they kind of build up over time and then, and then, yeah. And then look, in retrospect, it was 2017 was kind of the, you know, the key, the key point with the trans transformer and then. And then as you guys know, there was this really weird like four year period where it's like the, the transformer existed and then it was just like,swyx: let's go.Yeah.Marc: Well, but, but it was just, but, but between 2020, but between 2017 and 2021, I mean, that was the era of which like companies like Google had internal chat Botts, but they weren't letting anybody use them.swyx: Yeah.Marc: Right. And then, you know, and then OpenAI developed Chat GT or GPT two, and then they told everybody, this is way too dangerous to deploy.Right. Yeah. You know, we can't possibly let normal people, normal people use this thing. And then you, you guys, I'm sure remember AI Dungeon, um mm-hmm. So the o for, there was like a year where like the only way for a normal person to use GP T three was in, in AI dungeon.Alessio: Yeah.Marc: And so you, you, we would do this, you'd go in there and you'd pretend to play Dungeons and Dragons.In reality, you're just trying to talk to talk to GPT. And so there was this, you know, there was this long, you know, and I, you know, the big, big companies, you know, big companies are cautious and, you know, the big companies were cautious. It, it, by the way, it took open ai. You know, they, they, they talk about this, it took open AI time to actually adjust, you know, kind of re redirect their researchswyx: path.I, I think, uh, let say Rosewood, right? Uh, the, the dinner that founded OpenAI was right there.Marc: Right, right. But that, that dinner would've taken place in 20swyx: 18Marc: 19. The formation of OpenAI Uhhuh as late as 2018.swyx: Uh, uh, sorry. Uh, no, I'm, I'm, I'm, I'm wrong. Probably It should be 20. Yeah. They just celebrated a 10 year anniversary, so it it is 2025.Yeah, so, so 2015?Marc: Yeah. 2015. Yeah. 2015. But then, uh, um, Alec Radford did G PT one in what, probablyswyx: mm-hmm. 17, 18,Marc: yeah. 17, 18. So it, yeah. For, and then, and then they didn't really, and then GPT three was what? 2020? 2020.swyx: 2020.Marc: Because that became copilot immediately. Even open ai, which has been, you know, the leader of, of this thing in the last decade, you know, e even they had to adapt and, and, and lean into the new thing.And so. Um, yeah, I, I think it's just this process of basically sort of wave after wave layer after layer, you know, building on itself. And then you kind of get these catalytic moments where, where the whole thing pops and, and obviously that's what's happening now.swyx: Is it useful to think about will there be any ai, winter?‘cause there's always these patterns. Like, is this, in the summer is something I constantly think about because do I get, do I just like. Just get endlessly hyped and just trust that I will only be early and never wrong or right. Well, are we, will there be a winter?Marc: So there's something about, say the following.There's something about AI that has led to this repeated pattern. Um, and, and, and you guys know this,swyx: it's summer, winter, summer,Marc: winter, summer, winter, summer, winter. And it goes back 80 years. Yeah. 80 years. Uh, so the original neural network paper was 1943. Right. Which is, which is amazing. Uh, that it was, it was far back that long.And then there was you, if you guys have ever talked about this on your show, but there was this, uh, there was a big, uh, there was an a GI conference at Dartmouth University in 1950. 55. 55, yeah. And they got a NSF grant to, uh, for the, all the AI experts at the time to spend the summer together. And they figured if they had 10 weeks together, they could get a GI, uh, at the other end.And they got their, by the way, they got the grant, they got the 10 weeks and then, you know, 1955, you know. No, no. A GI. And like I said, I, I lived through the eighties version of this where there was a big, a big boom and a crash. And so, so there is this thing, and there, there is something about AI that causes the people in the field, I would say, to become both excessively utopian and excessively apocalyptic.Um, and, and it's probably on both sides of like the, the, the boom bus cycle. You, you kind of see that play out. Having said that, I think what's actually happened is like just, and you know, and we now know in retrospect like an enormous amount of technical progress that built up over time. And like for, for example, we now know that neural network is the correct architecture.And I, I will tell you like there was a 60 year run where that was like a, you know, or even 70 years or that was controversial. And, and we now know that that's the case. And so we, we now, you know, everything we're building on today just sort of derives from the original idea in 1943. And so, so in retrospect, we, we now know that like, these, these guys are right.They, they, you know, they would get the timing wrong and they thought, you know, capabilities would arrive faster, or they were, it could be turned into businesses sooner or whatever, but like, they were fundamentally, the, the scientists who worked on this over the course of decades were fundamentally correct about what they were doing.And, and the, and the payoff from, from, from all their work is happening now. And so, so the way I think about what's happening is basically, I think, I think about basically the, the, the period we're in right now is it's, I call it 80 year overnight success, right? Which is like, it's an overnight success.‘cause it's like bam, you know, chat, GPT hits and then, and then oh one hits, and then, you know, open claw hits and like, you know, these are open, these are, these are like overnight, like radical, overnight transformative successes, but they're drawing on an 80 year sort of wellspring backlog, you know, of, of, of, of ideas and thinking it's not just that it's all brand new, it's that it's an unlock of all of these decades of like very serious, hardcore research.Um, and thinking, and look, there were AI researchers who spent their entire lives. They got their PhD. They, they worked for, they've researched for 40 years. They retired in a lot of cases, they passed away and they never actually saw it work.swyx: Yeah. It's all sad.Marc: It is. It is sad. It's sad. Knewswyx: Jeff Hinton was like the last guy.Marc: Yeah. Yeah. Well, there were the guys, uh, was a guy, Alan Newell. I mean, there's tons of John McCarthy. You know, John McCarthy was like one of the inventors in the field. He's one of the guys who organized the Dartmouth Conference and you know, he taught at Stanford for 40 years. Wow. And passed, you know, passed away, I don't know, whatever, 10, 10 years ago or something.Never, never actually go. Got to see it happen. But like, it is amazing in retrospect, like, these guys were incredibly smart and they worked really hard and they were correct. So anyway, so then it's like, okay, you know, say history doesn't repeat, but it rhymes. It's like, okay, does that mean that there's gonna be another, like, you know, basically boom buzz cycle.And I, I will tell you, like, let, like in a sense, like yes, everything goes through cycles and, you know, people get overly enthusiastic and overly depressed and there's, there's a time, there's a timelessness to that. Having said that, there's just no question. Um, so the form, the foremost dangerous words in investing this time are, this time is different.Do you know the 12 most dangerous words investing? No. The four most d foremost dangerous words in investing are this time is different. Yeah. Um, the 12 most dangerous words. And so like, I'll tell you what's different. Like now it's working like, like there's just no, I mean, look, there's just no question.And by the way, I, I'll just give you guys my take. Like L LLMs, like from, from basically the Chad G PT moment through to spring of 25. I think you could still, I think well intention, well, and of. Form skeptics could still say, oh, this is just pattern completion. And oh, these things don't really understand what they're doing.And you know, the hall hallucination rates are way too high. And, you know, this is gonna be great for creative writing and creating, you know, Shakespeare and so sonnets and, you know, as, as rap lyrics or whatever, like, it's gonna be great and all that stuff, but we're not gonna be able to harness this to make this relevant in, you know, coding or in medicine or in law or in, you know, you know, kind of feels that, you know, kind of really, really matter.And I think basically it was the reasoning breakthrough. It, it was oh one and then R one that basically answered that question basically said, oh no, we're gonna be able to actually turn this into something that's gonna work in the real world. And, and then obviously the coding breakthrough over the, over basically the coding breakthrough that kind of catalyzed over the holiday break was kind of the third step in that.Mm-hmm. Where you're just like, alright, if, if, you know, if Linus Tova is saying that the AI coding is no better than he is like. Like, that's, that's never happened before. That's theswyx: benchmark.Marc: Yeah. That's never happened before. And so now we know that it's, it's gonna sweep through coding and, and then, and then we, we know, you know, we know that if it's gonna work in coding, it's gonna work in everything else.Right. It's just then, because that's, that's like, that's like, that's like the hardest in many ways. That's the hardest example. And how everything else is gonna be a, a derivative of that. And then on top of that, we just got the agent breakthrough, you know, with Open Claw, which is fantastic. Which is amazing and incredibly powerful.And then we just got the, the, um, the auto research, uh, you know, the, the self-improvement. You know, we're now into the self-improvement breakthrough. And so the, so the way I think about it is we've had four fundamental breakthroughs in functionality, l OMS reasoning, uh, agents, um, and then, uh, and, and then now RSI, um, and, and they're all actually working.Um, and so I'm, I'm just, as you like, you can tell I'm jumping outta my shoes. Like, like this is, like this is it like this, this is the culmination of 80 years worth of worth of work, and this is the time it's becoming real.Alessio: Yeah.Marc: I, I'm completely convinced.Alessio: I think the anxiety that people feel is like during the transistor era, yet Mors law, and it's like, all right, we understand why these things are getting better.We understand the physics of it. Yeah. With ai, it's. It's so jagged in like the jumps where like, like you said, it's like in three months you have like this huge jump like, and people are like, well this can keep happening. Right? But then it keeps happening,Marc: it'll keep happening.Alessio: And so like how do you think about also timelines of like what's we're building?I think we always have this question with guests, which is like, you know, should you spend time building harness for a model versus like the next model just gonna do it one shot in the lead space. Right. And how does that inform, like how you think about the shape of the technology? You know, you talk about how it's a new computing platform.If you have a computing platform, then like every six months it like drastically changes in what it looks like. It's hard to build companies on top of it.Marc: Yeah. So, so a couple things. So one is like, look, the, the Moore's law was what we now call a scaling law. Like Moore's Law was a scaling law and for your younger viewers, more Moore's Law was every chip chip chips either get twice as powerful or twice as cheap every, every 18 months.And that, and that and that, you know, that it's gotten more complicated in the last few years. But like that, that was like the 50 year trajectory of, of, of the computer industry. And then, and then by the way, and that's what took the mainframe computer from a $25 million current dollar thing into, you know, the phone in your pocket being, you know, a million times more powerful than that.Like that, you know, for, for 500 bucks. And so that, that was a scaling law. And then, and then, and then key to any scaling law, including Moore's Law and the AI scaling laws is, you know, they're not really laws, right? They're, they're, they're, they're predictions, but when they work, they become self-fulfilling predictions because they, they, they, they, they set a benchmark and, and then the entire industry, right?All the smart people in the industry kind of work to make sure that, that, that actually happens. And so they, they kind of motivate the breakthroughs that are required to, to keep that going. And, and in and in chips, that was a 50 year, that was a 50 year run. Right. And it, it was amazing. And it's still happening in, in some areas of, of chips.I think the same thing is happening with the, the core scaling laws. The core scaling laws. In, in, in ai, you know, they're, they're not really laws, but like they, they are basically. There are predictions and then they're motivating catalysts for the research work that is required to be. And, and, and, and by the way, also the investment, uh, dollars, um, uh, you know, required to basically keep, you know, keep the curves going and, and look, it, it is, it's gonna be complicated and it's gonna be variable and they're, you know, there're gonna be walls that are gonna look like they're fast approaching, and then they're gonna be, you know, engineers are gonna get to work and they're gonna figure out a way to punch through the walls.And obviously that's, you know, that's been happening a lot, you know, and then look, there's gonna be times when it looks like the walls have, you know, the, the, the laws have petered out and then they're gonna, they're gonna pick up again and surge and then, and then, and then it, it appears what's happening to the eyes is there's not multiple, you know, multiple scaling laws.Um, there's multiple areas of improvement. And, and I think, you know, I don't know how many more there are already yet to be discovered, but there are probably some more that we don't know about yet. You know, they, like, for example, there's probably some scaling law around, um, world models and robotics that we don't fully understand, you know, kind of acquisition of data at scale in the real world that we don't fully understand yet.So that, that, that one will probably kick in at some point here. There's a bunch of really smart people working on that. Um, and so, yeah, I, I think the expectation is that, that, you know, the, the scaling laws generally are gonna continue. Yeah. The, the pace of improvement will continue to move really fast.Um. To your question on like what to build. So, uh, I'm a complete believer the scaling laws are gonna continue. I'm a complete believer the capabilities are gonna keep getting amazing, um, you know, leaps and bounds. Uh, the part where I kind of part ways a little bit with how, what I would describe as the AI purists, um, you know, which is, which I would characterize as like the people who are.In many ways, the smartest people in the field, but also the people who spend their entire life, like at a lab, um, and have, have, I would say, have very little experience in the outside world. Um, the, the, the nuance I would offer is the outside world of 8 billion people and institutions and governments and companies and economic systems and social systems is really complicated.Um, and, um, and doesn't, you know, it it 8 billion people making collective decisions on planet Earth is not a simple process of like, just like you see this happening now. It's like a bunch of AI CEOs have this thing, which is just like, well, there's just this, they just all have this kind of thing when they talk in public where they're just like, well, there's these, these obvious set of things that so society to do.Alessio: Mm-hmm.Marc: And then they're like, society's not doing any of those things. Right. And it's like, how can society not, you know, what, whatever their theory is, how can society not see x, y, Z? Mm-hmm. And the answer is, well, society is number one. There's no single society, it's like 8 billion people. And they like all have a voice, and they all have a vote, like at the end of the day of how they, they react to change.And then, you know, it just like, it's just human reality is just really complicated and messy. Um, and, and, and so the specific answer to your question is like, as usual, it depends. Um, you know, it, it depends. Look, pe there's no question people are gonna, like, there's no question they're gonna be companies.It's already happening. There are companies that think that they're building value on top of the models and then they're just gonna get blissed by the, by the next model. There's no question that's happening. But I think there's no question also that just the process of adaptation of any technology into the real and into the real messy world of humanity is, is just going to be messy and complicated.It's, it's not going to be simple and straightforward. It's gonna be messy and complicated. And there are gonna be a lot of companies and a lot of products, um, uh, and in, in fact entire industries that are gonna get built to, to, to basically actually help all of this technology actually reach real people.Alessio: The amount of capital going into these companies, I mean, Dario talked about it on the Door Cash podcast and Door Cash was like, why don't you just buy 10 x more GPUs? And he is like, because I'm gonna go bankrupt if the model doesn't exactly hit the, the performance level. How do you think about that?Also as a risk on, you know, you guys are investors, open AI and thinking machines and world apps. It seems like we're leveraging the scaling loss at a pretty high rate, right? Like how comfortable, I guess, do you feel with the downside scenario, like, and say like things Peter out, you think you can kind of like restructure uh, these build outs and uh, you know, capital investments.Marc: Yeah. So should start by saying, so I live through the.com crash, um, and I can tell you stories for hours about the.com crash and it was horrible. No, it was awful. It was, it was, it was apocalyptic by the way. The, a lot of the.com crash was actually at the time, it was actually a telecom crash. It was a bandwidth crash.Like the, the thing that actually crashed, that wiped out all the money with the tele, the telecom companies.swyx: GlobalMarc: crossing. Global, global, yeah.swyx: I'm from Singapore and they, they laid so much cable o over over our oceans.Marc: Actually there was a scaling law in the.com. Era. And it was literally the, the US Commerce Department put out a report in 1996 and they said internet traffic was doubling every quarter.Um, and, and actually in 1995 and 1996, internet traffic actually did double every quarter. And so that became the scaling law. And so what all these telecom entrepreneurs did was they went out and they raised money to build fiber, anticipating that the demand for bandwidth is gonna keep doubling every quarter.Doubling every quarter though is like, you know, grains of chess and the chessboard, like at some point the numbers become extremely large. Right. And, and, and it really, and really what happened was the internet. The internet by the way, continuously kept growing basically since inception. And it's, you know, it's, it's continuously grown.It's never shrunk. And it's grown really fast compared to anything else. Mm-hmm. You know, in, in, in human history. But it wasn't doubling every quarter as of 19 98, 19 99. And so there was this gap in the expectation of what they thought was a scaling law versus reality. And that's actually what caused the.com crash, which was the, it they, they way over companies like global crossing way overbuilt fiber, which is sort of the, and by the way, fiber, telecom equipment, you know, so all the, all the networking gear, you know, and then, and then by the way, the actual physical data centers, like that was the beginning of the, of the, of the data center build and then, and the data center overbuild.And so you had that, but it was, it was literally, I think it was like $2 trillion got wiped out, right? It was like Jesus, it was like a big, it was. And by the way, the other, the other subtlety in it was the internet companies themselves never really had any debt. ‘cause tech, tech companies generally don't run on debt, but the telecom companies run on debt.Physical infrastructure companies run on debt. And so the companies like Global Crossing not just raise a lot of equity, they also raise a lot of debt. So they're highly levered. And so then you just do the thing. It's just like, okay, you have a highly levered thing where you're, you're just over, you're overbuilding capacity.Demand is growing, but not as fast as you hoped. And then boom, bankrupt. Right. And, and then it, and then it's like they say about the hotel industry, which is, it's always the third owner of a hotel that makes money. It has to go bankrupt twice, right? You have to wash out all of the over optimistic exuberance before it gets to actually a stable state.And then it makes money. So by the way, all of those data centers and all of those, all the fiber that they're in use, it's all in use today. Yeah. But 25 years later. But it, it, it took, and actually the elapsed time was, it took 15 years. It took 15 years from 2000 to 2015 to actually fill, fill up all that capacity.The cautionary warning is the, the overbuild can happen. Um, and, and, and, and, you know, you, you get into this thing where basically everybody, everybody who basically has any sort of institutional capital, it's like, wow. It's just, I, I don't know how to invest in these crazy software things. For sure I can put build data centers and for sure I can buy GPUs that I can deploy, you know, compute grids and, and all these things.Um, and so, you know, if you're a pessimist, you could look at this and you could say, wow, this is like really set up to be able to basically replicate, you know, what we went through, what we went through in 2000. Obviously that would be bad. The counter argument, which is the one I I agree with, which is the counter on, on the other side is a couple things.One is the companies that are investing all the, the companies that are investing the money are like the bluest chip of companies. And so back, back, back in the, in the do, like Global Crossing was like a, it was like an entrepreneur. It was like a, a new venture, but like the money that's being deployed now at scale is Microsoft, and, you know, and Amazon and Google, Facebook and Facebook and Nvidia and, you know, these, these, these, and, and now you know, by the way, open ai philanthropic, which are now at like, you know, really serious size, um, you know, as companies with, you know, very serious revenue.These are very large scale companies with like, lots, lots of cash, lots of debt capacity that they've, they've never used. And so th this is institutional in a way that, that really wasn't at the time. And then the other is, at least for now, every dollar that's being put into anything that results in a running GPU is being turned into revenue right away.Like so, and you guys know this, like everybody's starved for capacity, everybody's starved for compute capacity and then, you know, all the associated things, memory and, and, and interconnected and everything else. Um, data center space. And so e every dollar right now that's being put into the ground is turning into revenue.And, and it, and in fact, I actually think there's an interesting thing happening, which is because everybody starve for capacity, the models that we actually have that we can use today are inferior versions of what we would have if not for the supply constraints. That's true. Um, if Right pose a hypothetical universe in which GPUs were 10 times cheaper and 10 times more plentiful mm-hmm.The models would be much better. ‘cause you would just allocate a lot more money to training and you'd just build better models and they would be better. Um, and so we're, we're actually getting the sandbag version of the technology.swyx: Yeah. No. Everything we use is quantized because the, the labs have to keep the, the full versions,Marc: right?swyx: LikeMarc: we're not even getting the good stuff.swyx: Yeah.Marc: But, but getting the good stuff, it's, it's just, even if technical progress stops. Once there's like a much bigger build of like GPU manufacturing capacity and memory, you know, all, all the things that have to happen in the course of the next five or 10 years.Once it happens, even the current technology is gonna get, gonna get much better. And then as you know, like there's just like a million ways to use this stuff. Like there's just like a million use cases for this. Mm-hmm. Like, it, it, you know, this isn't just sending packets across a, a thing, whatever, and hoping that people find something to do with it.This is just like, oh, we apply intelligence into every domain of human activity. And then it works like incredibly well. Yeah. Um. Here's what I know, here's what I know. Um, in the next three or four year, it's like somewhere between three or four years out, basically everything is selling out. So like the, the entire supply chain is, is, is, is sold out or, or, or selling out.And so there, there's no, like, we're just gonna have like chronic supply shortage for, you know, for years to come. Um, there's going to be a response from the market that's gonna result in an enormous, you know, it's happening now. An enormous flood of investment in a new fab capacity and ev you know, every, everything else to be able to do that, at some point the supply chain constraints will unlock, you know, at least to some degree that will be another accelerant to industry growth when that happens.‘cause the products will get better and everything will get cheaper. Um, and so, so I know that's gonna happen. I know that, you know, the deployments, you know, the, the actual use cases are like really compelling. And then, like I said, you know, with reasoning and agents and so forth, like, I know they're just gonna get like much, much better from here.And so I, I, I know the capabilities are like really real and serious. I also know that the technical progress is not going to stop. It. It, it is excel. It is, is accelerating. Like the, the breakthroughs are are tremendous. I mean, even just month over month, the breakthroughs are really dramatic. And so, you know, I think if you were a cynic and there, there are cynics, you can look at 2000, you can find echoes.But I can't even imagine betting it that this is gonna like somehow disappoint and, you know, at least for years to come, I think it would be essentially suicidal to make that bet. Yeah. Um, it was that Michael Burry, uh, uh, that'sswyx: anMarc: interesting guy, huh? We'll pick on a guy. We'll pick, let's pick on one guy.We'll pick. Well ‘cause he did, he he came out with, it was, it was the, heswyx: doesn't mind.Marc: It was the Nvidia short. Right. He came with the Nvidia short. And then if you guys probably talked about this, which is the, the analysis now that like the current models are getting better faster at such a rate that if you are running an Nvidia, if you're running an Nvidia inference chip today, that's three years old, you're making more money on it today than you did three years ago because the pace of improvement of the software is, is faster than the, the, the depreciation cycle, the chip.And then my understanding is Google is running. I don't if they've, I don't know exactly what, uh, these are rumors that I've heard or maybe it's public, but, um, I think Google's running very old TPUs, very profitably. Ference. Yeah. And very profit and very profitably. Yeah. Um, and so, so it actually turns out, as far as I can tell, it's actually the opposite of the Beery thesis is actually.He was actually 180 degrees wrong. It's actually the, the, the, the old Nvidia chips are getting more valuable, which is something that's like literally never happened before. Like it's never been the case that you have an older model chip that becomes more valuable, not less valuable. And that, and again, that's an expression of the just ferocious pace of software progress.Ferocious pace of capability payoff. Yeah. Uh, that you're getting on the other side of this. And so I just, the idea of betting against that, like.swyx: Yeah. Yeah. Well, one ofMarc: my, it seems like an invitation to get your face ripped up.swyx: One of my early hits was like modeling the lifespan of the H 100 and h two hundreds and, and going like, you know, usually they advise like four to seven years and it was, you know, maybe you sort of realistically haircut cut it down to two to three.Yeah. But actually it's going up and not down. Yeah. And, and uh, that's, I mean that's, I think that's the dream. Uh, we are finding utilization and I think utilization solves all problems. Like, you can, you can find use, use cases for even like the poor, like even memory, we're having a shortage. Right. And, and even like the, the shittier versions of, of memory that we do have, we are finding use cases for it.So like That's great.Marc: Yeah.Alessio: How, how important is open source AI and kinda like edge inference in a world in which you have three years of supply crunch. Like, do you think in the, like, you know, if you fast forward like five years, like how do you think about inference, uh, in the data center versus at the edge?Marc: Well, so just to start, yeah. So I think, I think open source is very important for a bunch of reasons. I think edge, edge inference is very important for a bunch of reasons. I, I think just practically speaking, if we're just gonna have fundamental construc, supply crunches for the next, I mean, you, you guys know if you just project forward demand over the next three years, right?Yeah. Relative to supply, one of the, its main predictions you can do is what's gonna, what, what's gonna happen to the cost of, of inference in the core, uh, over the next three years? And like, it may rise dramatically, right? Like, so, so what is, and then is, is, you know, like the, the, the big model competition are subsidizing heavily right now.Right? Right. And so, so what's the, what will be the average person's, you know, per day, per month token cost, you know, three years from now to do all the things that they want to do. And I, I don't know, it's gonna. I mean, I have, you guys probably have friends, I have friends today who are paying a thousand dollars a day for open claw, for claw tokens to run open claw.Right? And so, okay. $30,000 a month. Right? And, and by the way, those, those friends have like a thousand more ideas of the things that they want their claw to do, right? Yeah. And so you, you could imagine there, there's like latent demand of up to, I don't know, five or $10,000 a day of, of, of tokens for a fully deployed, you know, per personal agent.Uh, and obviously consumers can't pay that, right? And so, so, but it gives you a sense of the fu of the fu of the future scope of demand, right? And so, so even, even if there's a 10 x improvement in price performance, that still, you know, goes to a hundred dollars a day, which is still way beyond what people can pay.Mm-hmm. So there's just gonna be like. Ferocious to me, by the way. The agent thing, the other interesting thing is I think the agent thing, so up until now, a lot of the constraints of GGPU constraints, I think the agent thing now also translates into CPU constraints. Mm-hmm. Right?swyx: CPU memory.Marc: Yes. CPU memory, right?And so, like the entire chip ecosystem is just gonna get wait,swyx: wait for network constraints, that that will be the killer.Marc: It's all bottleneck potentially for years. And so, so I, I think that Brad, and, and I think it's actually possible, I mean, generally inference costs are gonna keep coming down, but I think the, let's put it this way, the rate of decline, I think may level out here for a bit because of these supply constraints.And then at some point, maybe the lab stops subsidizing so much and that, that, that again, will be, be an issue. And so there's just gonna be so much more demand for inference than, than can be satisfied. Um, you know, kind of with the centralized model. And then, and then, you know, you guys know this, but like all the, just the dramatic, I mean just the dramatic innovations that have happened in the Apple silicon to be able to do, uh, inferences, it's quite amazing the level of effort being put.Like the open source guys are putting incredible effort into getting, you know, this recurring pattern where the big model will never run on a pc, and then six months later mm-hmm. Oh, it runs in a pc, right? It's like amazing. And there's very smart people working on that. So there's all that. And then look, there's also, you know.There's also like other, there's other motivators. There's other motivators which is just like, okay, how much trust are the big centralized model providers? You know, how much trust are they building in the market versus, you know, how much are, you know, at least for, in certain cases with some people, for certain use cases, people being like, well, I'm not willing to just like, turn everything over.So there, there, there's all the trust issues. Um, by the way, there's also just like straight up price optimization. There's many uses of AI where you don't need Einstein in the cloud. You just need like a, a a, a smart local model. There's also performance issues where you want, you know, you want, you know, you're gonna want your doorknob to have an AI model in it.Right. You know, to be able to, you know, do, um, you know, to be able to do access control. Um, obviously like everything with a chip is gonna have an AI model in it. Mm-hmm. And it, a lot of those are gonna be local. Um, and so, yeah. No, like I think, I think you're gonna have ti and then you're gonna, by the way, also wearable devices, you know, you don't wanna do a complete round trip.You want, you know, you, whatever your smart devices are, you want it to be like super low latency. Yeah.swyx: The question, do we care who makes it? Yeah. One of the biggest news this week was the collapse of AI two, the Allen Institute. Mm-hmm. One of the actual American open source model labs. Yeah. Um, and, uh, I'm not that optimistic on, on American open source.Yeah. Like you, you guys invested in MIS trial and MIS trial's doing extremely well outside of China. That's about it.Marc: Yeah. We'll see. We'll see. I look, I, number one, I do think we care. Uh, I do think we, I do think we care who makes it. Um, I would say this, the, the, the, the previous presidential administration wanted to kill it in the us Oh yeah.They wanted to drown in the bathtub. Um, and so they wanted to kill it. So at least we have a government now that actually like, actually wants it wants it to happen. And youswyx: earned to councilMarc: and Yeah. And the new and the P pcast. Yeah. So the, the, you know, this admin for whatever other political issues people have, which are many, you know, this administration has, I think a very enlightened view and in particular an enlightened view on AI and in particular on open source ai.Uh, and so they're very supportive. Um, my read is the Chi. The Chinese have a very, the various Chinese companies have a very specific reason to do open source, which is, they, they, they don't fundamentally, they don't think they can sell commercial, uh, AI outside of China right now. And or at least specifically not, not in the US for a combination of reasons.And so they, they kind of view, I think, open source AI as a bit of a loss leader against basically domestic, uh, you know, paid, paid services. And then kind of an, you know, kind of an ancillary products. You know, they're, they're very excited about it, by the way. I think it's great. I think it's great that they're doing it.Um, you know, I think Deeps seek was like a gift to the world. Um, I think. The great thing about open source, open source, the, the, the impact of open source is felt two ways. One is you, you get the software for free, but the other is you get to learn how it works, right? And so like the paper, the paper, the paper and, and the code, right?And the code. And so, like, for example, I thought this was amazing. So open comes out with L one and it's an amazing technical breakthrough, and it's just like, absolutely fantastic. But of course they don't explain how it works in detail. And then of course they hide the, they hide the reasoning traces, right?And, and then, and then, and then everybody's like, okay, this is great, but like, who's gonna be able to replicate this? Are other people gonna be able to do this? You know, is their secret sauce in there? And then our one comes out and it's just like, there's the code and there's the paper, and now the whole world knows how to do it.And then, you know, three months later, every other AI model is, is adding reasoning. And so, so you get this kind of double, like even if the Chinese models themselves are not the models that get used, the education that's taken place to the rest of the world, the information diffusion, you know, is incredibly powerful.So that happens and then, I don't know. We'll, we'll see. You know, there are a bunch of American, you know, open source, you know, ai, uh, model companies. I mean, look, there's gonna be tremendous, you know, there already is. There's, you know, there's gonna be tre there's tremendous competition, uh, among the primary model companies.You know, there's, depending on how you count, there's like four or five, you know, big co model companies now that are, you know, kind of neck and neck, uh, in different ways. Um, uh, you know, and, and, and, um, you know, and then obviously Bo Bo both X and then MetAware involved are, you know, both have huge, you know, huge attempts to, you know, kind of, to kind of leapfrog underway.And then you've got, you know, a whole fleet of startups, new companies, including a whole bunch that we're backing, that are, you know, trying to come out with different approaches. And then you've got whatever it is. I don't know how, how many, how many, like main line foundation model companies are there in China at this point?It's probably six. It'sswyx: five Tigers is what they call it. Yeah. Uh, Quinn is in questionable because there's change in leadership,Marc: right?swyx: Yeah.Marc: But that, does that include, that includes like Moonshot,swyx: yes. Can deep seek, uh, uh, ZI, um, Quinn oh one is in there.Marc: Right. And then, um, and by dance and, and then you see,swyx: ance would be like the next tier ance.They weren't as prominent. They weren't, didn't haveMarc: a leading. Yeah. But they, you at least, you know, ance is very inspiring and presumably they have more stuff coming and Tencent probably has more stuff coming and, and so forth. And so, so, so like, look, here, here would be a thing you can anticipate, which is there are not these markets, there are not going to be between the US and China right now, there's like a dozen primary foundation model companies that are like at scale, at, at some level of a critical mass.It's not gonna be a dozen in three years, right? Like, it just because these industries don't bear a dozen, it's, it's gonna be three or you know, there's gonna be three or four big winners or maybe one or two big winners. And so there's gonna be like a whole bunch of those guys that are gonna have to figure out alternate strategies.Um, and I think like open source is one of those strategies. And so I, I think you could see like a whole, i, I, I think the questions like, who's gonna do open source? I think that could change really fast. I, I think that, that, that's a very dynamic thing. I think it's very hard to predict what happens. And, and I think it's very important.swyx: NVIDIA's doing a lot.Marc: Well, I was gonna say. Well, exactly. And then you're got Nvidia and then, and then, you know, just to, again, indu, there's an old thing in business strategy, which is called, uh, commoditize Compliments. Commoditize the compliment. That's right. And so if your Jensen is just kind of obvious, of course, you wanna commoditize the software.Yeah. And he's, and to his enormous credit, he's putting enormous resources behind that. And so maybe it, maybe it's literally Nvidia and I think that would be great.Alessio: Yeah. Uh, narrative violation to European projects, uh, in the, uh, damn.swyx: I'm hosting my, uh, Europe, uh, conference soon. And I got both of them.Alessio: They got us.They got us. MarkMarc: finished. They got us, us. Well, wait a minute. Where was Peter? So where was Steinberger when he did? In AustriaAlessio: was, yeah, yeah, yeah.Marc: He was in what? He was in Vienna. Oh, he was in Vienna. And then where is he now?swyx: Uh, he's moving to sf.Marc: Okay. Okay. Alright. Okay, there we go. And then, yeah, the PI guy, right?The PI guys are European.swyx: Yeah, they're also, they're buddies inAlessio: Australia. Mario's also there. Yeah.Marc: Right. And are they, yeah, they haven't announced yet. Any sort of change changed or have theyAlessio: No, they're, they have a company there.Marc: Okay. Got, okay. Good.Alessio: Good, good,good.Alessio: Um,Marc: yeah, good.swyx: Anyways, I think pie and open cloud very important software things and, and I just wanted you to just go off on what you think.Marc: Yeah. So I think in co the, the combination of the two of them I think is one of the 10 most important softwares. Openswyx: Claw got all the attention, but Right. Talk about pie,Marc: pi pie's, kind of the Yeah. PI's, PI's kind of the architectural breakthrough for those of us who are older. There was this whole thing that was very important in the world of software basically from like 1970 to, I don't know, it still is very important, but like 19, from 1973 to like basically the creation of Linux, which is basically this, this thing used to call like the Unix mindset.Like so, so, ‘cause there were all these different, you know, theories. There are all these different operating systems and mainframes and, and then you know, all these windows and Mac and all these things. And then there was this, but kind of behind it all was this idea of kind of the Unix mindset. And the Unix mindset was this thing where basically you don't have these, like, like in the old days, like, like the operating system that like made the computer industry really work, like in the 1960s mm-hmm.Was this thing called o os 360, which was this big operating system that IBM developed that was supposed to basically run everything. And it was this like giant monolithic architecture in the sky. It was like a, you know, it was like a giant castle. Um, of software. And, and by the way, it worked really well and they were very successful with it.But like, it was this huge castle in the sky, but it was this thing, it was almost unapproachable, which is like, you had to be kind of inside IBM or very close to IBM. And you had to really understand every aspect, how the system worked. And then the, the Unix sky is originally out of at and t and then out out of Berkeley, um, you know, came out and they said, no, let's have a completely different architecture.And the way architecture's gonna work is we're gonna have, we're gonna have a, a prompt and, and a, and a shell. And then, and then we're gonna, all, all the functionality is gonna be in the form of these discreet modules, and then you're gonna be able to chain the modules together. Mm-hmm. Yeah. And so like the, the, the op, it's almost like the operating, operating system itself is gonna be a programming language.Um, and then that led led to the, the, the sort of centrality of the shell. Um, and then that led to sort of, uh, you know, basically chaining together Unix tools. And then that led to the emergence of these, these scripting languages like Pearl, where you, you could basically kind of very easily do this, and then the shells got more sophisticated and then, and then, and then look like, you know, that, that, that number one, that worked and that, that was the world I grew up in.Like I was, I was a Unix guy. You know, sort of from, call it 1988 to, you know, kind of all, all the way through my work and it worked really well. It, it's in the background, um, you know, nor normal people don't need to, didn't need to necessarily know about it, but like, if you were doing like system architecture, application development, you, you, you knew all about it.Um, and then, you know, it's been in the background ever since. And, you know, look, your Mac still has a Unix shell, you know, kind of in there, and your iPhone still has a Unix shell kind of buried in there somewhere. So they're kind of in there. And then, you know, the Windows shell is kind of a, you know, sort of a weird derivative of that.But, um, you know, but look, the inter, the internet runs on Unix, um, and that smartphones, actually, both iOS and Android are Unix derivatives. And so, you know, kind of Unix did end up winning. But, but anyway, and then we just started taking that for granted. And then, and then so, so basically the, the way I think about what happened with Pie and then with Open Claw is basically what those guys figured out is, I always say the, the great breakthroughs are obvious in retrospect, right?Which is the best kind, the best kind. They weren't obvious at the time or somebody else would've done them already. Um, and so there is a, like a real conceptual leap, but then you look at it sort of the backwards looking and you're just like, oh, of course. Mm-hmm. Like the, the, to me those are always the best breakthroughs.Well, actually language models themselves are like that. It's just like, oh, next token completion. Oh, of course.swyx: Yeah. What other objective mattered?Marc: Yeah, exactly. But, but like it, right. But she's even saying it wasn't obvious until somebody actually did it. Right. And so the conceptual breakthrough is real and deep and powerful and, and very important.And so the way I think about pie and olaw is it's basically marrying the, the language model mindset to the un to the Unix, basically shell prompt mindset. And so it's, it's basically this idea that what, what, so what is an agent, right? And as, as, and as you know, like many smart people who have been trying to figure out what an agent is for, for, for decades, and they've had many architectures to build agents and the whole thing.And it turns out what is an agent. So it turns out what we now know is an agent is the following. It's, so it's a language model. And then above that, it's a ba, it's a bash shell. Um, so it's a, it's a Unix shell, and then it's, and then the agent has access, uh, has access to, to the shell. And, you know, hopeful, hopefully in a sandbox, maybe in, maybe in a sandbox.So it's, it's the model. Um, it's the shell. Um, and then it's a fi, it's a file system. Um, and then the state is stored in files. And then, you know, there's the markdown format for the, you know, for, for the files themselves. And then, and then there's basically what in Unix is called Aron job. There's a loop and then there's a heartbeat for the, there's heartbeat and, and the thing basically Wake Wakes up.Wakes up. So it's basically LLM plus shell, plus file system, plus markdown, plus kron. And it turns out that's an agent. And, and, and every part of that, other than the model is something that we already completely know and understand. And in fact, it turns out that like the latent power of the Unix shell is like extraordinary because basically like all, like, there's just like an, there's just enormous latent power in the shell.There's enormous numbers of Unix commands, there's enormous number of command line interfaces into all kinds of things already in the, you know, your entire, I mean your entire, just to start with, your computer runs on a shell. If you're running a Mac or a, or, or a phone, your computer, your computer's running on a shell, uh, already.And so like the full power of your computer is available at the command line level. Um, and then it turns out it's really easy to expose other functions as a command line interface. And so like this whole idea where we need like MCP and these like product mm-hmm. Fancy protocols, whatever, it's like, no, we don't, we just need like a command, command line thing.So that's the architecture. And then it turns out what is your agent? Your agent has a bunch of files starting a file system. And then there's the thing that just like completely blew my mind when I write my head around it as a result of this, which is like, okay. This means your agent is now actually independent of the model that it's running on.Because you can actually swap out a different LLM underneath your agent and your, your agent will change personality somewhat. ‘cause the model is different, but all of the state stored in the files will be retained.swyx: Yeah. Different instruction set, but you just compiledit.Marc: Right, exactly. And it's all right.It's like right. Swapping out a ship and recompiling, but it's, it's still, it's still your agent with all of its memories. Um, and with all of its capabilities. And then by the way, you can also swap out the shell, uh, so you can move it to a different execution environment that is also, is also a b shell, by the way, you can also switch out the file system, right.Uh, and you can, and you can, and you can swap out the, the, the heartbeat for the, the crown framework, the, the loop that the agent framework itself. And so your agent basically is ba basically at the end of the day, it's just. It's just, its files. Um, and then, and then there's of course it a openswyx: call.Marc: Yeah, it's, it's basically, it's, it's just the files.Um, and then by the way, as a consequence of that, the agent and then the agent itself, it turns out a couple important things. So one is it, it's, it, it can migrate itself, right? And so you're, you can instruct your agent, migrate yourself to a different, uh, runtime environment, migrate yourself to a different file system, migrate yourself to a different, you know, swap out the language model.Your agent will do all that stuff for you. And then there's the final thing, which is just amazing, which is the agent is the agent actually has full introspection. It actually, it actually knows about its own files and it could rewrite its own files. Right. Which by the way, is basically no widely deployed software system in history where the, the, the thing that you're using actually has full introspective knowledge of how it itself works and is able to modify itself.Like that, that, I mean, there have been toy systems that have had that, but there, there's never been a widely deployed system that has that capability and then that leads you to the capability. That just like completely blew my mind when I wrap my head around it, which is you can tell the agent to add new functions and features to itself and it can do that.Extend yourself. Yeah. Right? Extend, extend yourself. Like extend yourself. Give yourself a new capability. Right? And so, and so literally it's just like you run into somebody at a party and they're like, oh, I have my open claw, do whatever, connect to my eat, sleep bed, and it gives me better advice and sleep.And you go home at night and you tell your claw, or if they're at the party, by the way, you tell your claw, oh, add this capability to yourself. And your claw will say, oh, okay, no problem. And it'll go out on the internet and it'll figure out whatever it needs and then it'll go out to claw code or whatever.It'll write whatever it needs. And then the next thing you know, it has this new capability. And so you don't even have to, like, you can have it upgrade itself without even having to, without having to do anything other than tell it that you want it to do that. And so anyway, so the, the combination of all this is just, I mean, this is just like a massive, incredible, I mean, it's just incredible.Like if I, if I were, if I were 18, like this is a hundred, this is what I would be spending all of my time on. This is like such an incredible conceptual breakthrough. Yeah. And again, pe people are gonna look at it and they already get this response. People are gonna look at it and they're gonna say, oh, well, where's the breakthrough?‘cause these, the, all of these components were already known before. Mm-hmm. But, but this is the key, the key to the breakthrough was by using all these components that were known before, you get all of the underlying capability of that's buried in there. And so all, and so for example, computer use all of a sudden just kind of falls, trivi, trivial.Of course it's gonna be able to use your computer. It has full access to the shell. Right. And then, and then you just, you, you give it access to a browser, and then you've got the computer and the browser and, and often away it goes. And, and then you've got all the abilities of the browser also. Um, yeah.And so, and so the capability unlock here is profound. My friends who are, you know, deepest into this, are having their claw do like a, like, literally like a thousand things in their lives. They have new ideas every day. They're just like constantly throwing new challenges at the thing. And by the way, it's early and, you know, these are, you know, these are prototypes and there are, you know, as you guys know, there's security issues.Yeah. And, and so, you know, there's a bunch of stuff to be ironed out, but the, the unlock of capability is just incredible.swyx: Yeah.Marc: And I, I have absolutely no doubt that everybody in the world is gonna, is gonna have at least, you know, an agent like this, if not an entire family of agents. And w

Jagged Jungle – The Golden Hour | Episode 10 Welcome back to Jagged Jungle: The Golden Hour - a feel-good melodic journey packed with tropical grooves, deep rhythms and global energy. This one marks Episode 10, and I'm taking it back to one of my favourite shows from the series so far. Expect sunshine-infused house, melodic moments, and the kind of music that feels like summer wherever you are. Also, a little update from the Jungle. we've got two huge events coming up in May. Catch Jagged Jungle live at Sushi Samba / Samba Room RIO AFTER DARK on 8th May, followed by a very exclusive party at The Ned on 16th May. Two massive dates, two completely unforgettable vibes. From the airwaves to the dancefloor, Jagged Jungle is all about bringing together sounds from around the world -different cultures, different energies, one feel-good connection through music. Lock in, turn it up, and come with me for the next hour. Tickets / event info: https://www.sevenrooms.com/events/sushisambalondon Follow Jayli / Jagged Jungle: Instagram: instagram.com/jaylimusic TikTok: tiktok.com/jaylimusic

Jagged Jungle Radio – Episode 7

Jagged Jungle - Episode 6 - Mixed by Jayli This week's Jagged Jungle drifts from sunrise emotion into deeper, late-night grooves -blending melodic house, underground classics and global textures into one seamless journey. We open in Anjunadeep territory with CRi & Nicky Elisabeth, before sliding into lush remixes from Klangkarussell, Ucha (Bias Beach Records) and a dreamy New Wave moment with Redfield's poolside take on Kenya Grace. The journey dips into timeless territory with Maya Jane Coles -What They Say, followed by deeper energy from Haddadi Von Engst (Kings Dead) and a signature Jayli Jungle Edit mashup bringing unexpected nostalgia to the dancefloor. Later, we move through Crosstown Rebels magic with Bonafique, into warm textures from Barry Can't Swim and Ben Böhmer (Ninja Tune), before closing on deeper Afro and melodic club heat from Frank Delour (Afro Tech Muzik) and Argy & Omiki. Expect melodic storytelling, underground classics, and Jagged Jungle energy from start to finish.

Jagged Jungle - Mixed by Jayli A sunrise-to-midnight journey through melodic, deep and emotionally charged house. This week's Jagged Jungle weaves hypnotic atmospheres with dancefloor energy, moving from Ben Böhmer's cinematic soundscapes on Ninja Tune into club-rooted grooves from Hot Since 82 & Kuuda (Bedrock), Roland Clark (Get Physical) and CamelPhat (Insomniac/Interstellar). Expect sultry, late-night moments from Bonafique (Crosstown Rebels), a timeless throwback with Henry Krinkle's Stay (Justin Martin Remix) via Ultra Records, and peak-time heat from Vintage Culture (AFFAIRS) and Frank Delour (Afro Tech Muzik). Featuring Jayli's Jungle Edit — ‘Come With Me', blending nostalgia with fresh, tropical-leaning energy. If you love melodic house with soul, groove, this one's for you.

Chapter 680 - "The Power Of Chasing Creativity" ...as read by Jake Woodruff of Jagged City/DefeaterToday we welcome Defeater guitarist Jake Woodruff to the podcast! Jake has a new project called Jagged City and they released their debut EP, There Are More Of Us, Always, last Friday with Pelagic Records! Jake talks about his early days touring, joining Defeater, the inspiration behind Jagged City, connecting with Robin and Pelagic Records, and more.https://jaggedcity.bandcamp.com/album/there-are-more-of-us-alwayshttps://defeaterhc.com/February Sponsor - Tapehead City https://tapeheadcity.com/DiscordPatreonSubstackEmail: asthestorygrows@gmail.comChapter 680 Music:Jagged City - "Imaginary Lines"Defeater - "Unanswered"Jagged City - "Ocean East, Ocean West"Jagged City - "Deluge In A Paper Cup"

Episode 4 of the Golden Hour era of Jagged Jungle is all about slowing the pace, stepping outside, and letting inspiration meet you when you least expect it - soundtracked by warm melodies, soulful vocals, and sunset-ready grooves. This week's journey moves from emotional openers into confident dancefloor energy, featuring music from Cover Girls, Juany Bravo, Mydoz, ASHER SWISSA, Omer Keinan, Duke Dumont, Empire of the Sun (STEIN Remix), BUNT., Nate Traveller, PAAX (Tulum), Mark Knight, Pietro, Rome Fort, House Gospel Choir, LP Giobbi, Simone Vitullo, Joezi, Monkey Safari and more. The Treasure Track comes from Duke Dumont - The Giver, a timeless record packed with emotion and late-night nostalgia, while the Jungle Edit features Jayli's own rework of “Africa”, blending familiar energy with fresh movement. You'll also hear Jayli's Golden Minute, a short reflective pause about getting off your phone, stepping into the real world, and finding creativity in the everyday moments where your mind finally slows down. Warm-up, wind-down, or dance it out - this one's built for those golden moments where the day turns into night. Welcome to Episode 4 of Jagged Jungle: Golden Hour.

Jagged edge type music (05:00)Sports reference (7:00)Father parent teacher conference (9:50)Unsatisfactory (15:45)Druski skit (25:36)Idolize the pastors ?? (32:50)Good Ole Boy (46.00)The 2 wardrobe (54:00)Socials Twitter@THDLongviewWoo@Deshawn_903TikTok @Deshawn__903@LakeportWooWordpress@woonation.wordpress.com

Jagged Jungle: Golden Hour: Episode 3 with Jayli Episode 3 of the Golden Hour era of Jagged Jungle is all about sun-soaked melodies, emotional builds, and late-afternoon grooves that carry you from golden light into full dancefloor energy. This week's journey moves through melodic and tropical flavours with music from Thomas Jack, Pocket, Monkey Safari, BUNT, Sam Feldt, JP Chronic, Cedric Gervais, HUGEL, Disco Lines, Tinashe, Galantis, Ellie Sax, Ian Asher, CamelPhat and more — blending feel-good euphoria with deeper, driving moments as the energy lifts. You'll also hear a special Jungle Edit from Jayli, plus a Golden Minute moment — a short pause for reflection before diving back into the rhythm. Whether you're driving into the sunset, working out, cooking, or just escaping for an hour, this one's built to lift your mood and keep you moving. Welcome to Episode 3 of Jagged Jungle: Golden Hour.

Alanis Morissette and Taylor Swift are being inducted into the Songwriters Hall of Fame. Speaking of Taylor Swift… I guess we can read her text messages now. Bob tries to summarize the latest on the Blake Lively and Justin Baldoni case. Pokemon is big money, apparently. This story isn't how you want to bring a child into the world, so let's just play When Did That Happen?

Episode two of Jagged Jungle: Golden Hour with Jayli flows from melodic sunrise energy through nostalgic moments like Robin Schulz's Sun Goes Down, into a Jungle Edit from Jayli's own studio vault and a Golden Minute pause for reflection on the choices we make Expect feel-good global grooves from artists like Halsey, Jerro, REX STAX, Wakyin and SUNANA & Basax before sliding into an uplifting Sunset Stretch Designed for long drives, workouts and golden-hour escapes — welcome back to the jungle.

At 15 years old, Taylor Swift understood something most brands still miss. "Half your time writing material. Half your time talking to fans."She spent 10-15 years doing this EVERY night. On MySpace. On Bebo. On Tumblr. Replying to fans. Showing her world. Building connection. The result? A brand so powerful that fans get her lyrics tattooed on their bodies."Taylor Swift doesn't sell music. She sells belonging," explains behavioral scientist Ken Hughes.Your brand doesn't need better product. It needs better connection. In this podcast Ken Hughes talks about his book "TAYLORMAKING", a strategic playbook for building customer loyalty, brand intimacy, and emotional resonance.Jagged with Jasravee is facilitated by Jasravee Kaur Chandra. Jasravee has over 25 years experience as a Strategic Brand Builder, Communications Leader and Entrepreneur. Please visit Jasravee at https://jasravee.com/Connect with Jasravee on Linkedin at https://www.linkedin.com/in/jasravee/ Email Jasravee at jasravee@gmail.com

A new era of Jagged Jungle with Jayli. Sun-drenched melodic house, emotional grooves, exclusive Jungle Edits and a Golden Minute moment of reflection all designed for your drive, your workout, or your late-night escape. Welcome to Golden Hour.

Phyl Coe Mysteries 1937-11-23 Jagged Rock Mystery

This is the final Jagged Jungle show of the year A non-stop journey through melodic, tropical and emotive house to close out what's been a huge chapter. As we land between Christmas and the New Year, this mix is about reflection, release, and new beginnings. The moments that stayed with us. The sounds that carried us. And the energy we're taking forward. This show also marks the last episode before Jagged Jungle returns live and I honestly cannot wait to be back in the studio with you. I'm looking to evolve the show in the new year, so I'd love to hear from you: What were your favourite moments this year? The Melodic Map journeys? The Tropical Transitions? Or discovering a New Wave Artist here first? Drop me a message or leave a comment Until then, turn it up, lock in, and let the music do the talking. ✨ Jayli The only home in the UK for melodic house music

Welcome to Jagged Jungle We've got one more show after this before the year wraps up and what a year it's been. As we head into next year, I'm looking at evolving the show a little, and I'd love your input. So tell me — what hit for you this year? Was it the Melodic Map, taking you somewhere new? The Tropical Transition, when the energy shifted? Or discovering fresh sounds through the New Wave Artist? Drop me a message on SoundCloud or Instagram instagram.com/@jaylimusic. Two more shows till I'm back live… But right now, we're locking into a non-stop Jagged Jungle. Turn it up. Lock it in. This is Jayli, the only home in the UK for melodic house music.

Did 2025 mark the formal end of the neoliberal age? Gary Gerstle, author of The Rise and Fall of the Neoliberal Order, has already written neoliberalism's official obituary, so he's quite comfortable with a post neoliberal world. But Trump 2.0, Gerstle suggests, marks the formal beginning of America's place in this new cracked, jagged and leaderless world. What most defines it, Gerstle suggests, is its absence of “flatness” - Tom Friedman's term to describe a world simultaneously “flat” and yet dominated by singularly American ideas, economics and power. The ironic thing about Trump 2.0 is that, for all his bluster, his America is just another player in this post Pax Americana economic and political system. His “place in the history books is secure,” Gerstle says about Trump. But it may not exactly be the place that the MAGA leader wants to be. Keen On America is a reader-supported publication. To receive new posts and support my work, consider becoming a free or paid subscriber. This is a public episode. If you'd like to discuss this with other subscribers or get access to bonus episodes, visit keenon.substack.com/subscribe

Jagged Jungle Radio – Episode 28 (Non-Stop Mix) Episode 28 of Jagged Jungle Radio is a pure, uninterrupted journey, no mic, no chatter, just music doing what it does best. I'm officially stepping away for a short holiday break, but the Jagged Jungle never sleeps… so the grooves keep rolling while I recharge the soul and top up the tan ☀️ While I'll be back with fresh episodes in the second week of January, consider this mix your bridge between now and then timeless, flowing, and intentionally hands-free. No segments. No interruptions. Just vibes. Jagged Jungle has always been about movement, emotion, and escape and this episode leans fully into that ethos. Think less “radio show,” more soundtrack to your life while I'm briefly horizontal somewhere. Thank you for riding with me this year. Your support means everything and trust me, 2026 is loading…

In this deep, insight-packed conversation with Roger Hurni, we explore behavioural marketing, consumer psychology, and how human decision-making really works—through real-world stories from brands like Nike, DoubleTree, Four Seasons, Apple Pay etc.From the legendary DoubleTree cookie strategy to AI-driven personalization, this episode breaks down:Jagged with Jasravee is facilitated by Jasravee Kaur Chandra. Jasravee has over 25 years experience as a Strategic Brand Builder, Communications Leader and Entrepreneur. Please visit Jasravee at https://jasravee.com/Connect with Jasravee on Linkedin at https://www.linkedin.com/in/jasravee/ Email Jasravee at jasravee@gmail.com

Today's show leans into artists like Jerro, and Ben Bohmer, Promesses by dimmi which captious Barack Obama's Victory Speech, Music that feels aspirational, that opens the sky a little, that reminds you there's more ahead than behind. 
This episode is all about elevating you, carrying you out of the day-to-day noise, even just for an hour. Because life can be tough.
Life can be heavy.
But we all deserve moments of light and that's exactly what Jagged Jungle is here to give you today. Tracklist: 00:00:00 Jerro, Otherwish - For You (Original Mix) THRIVE MUSIC 00:05:01 Nora En Pure - Watermark (Extended Mix) Enormous Tunes 00:10:28 Klangkarussell, Senes, GIVVEN - Sun Went Down, Sky Went Dark (Extended Mix) Bias Beach Records 00:17:38 Monolink - Father Ocean (Ben Böhmer Remix) Embassy One 00:24:49 Ben Böhmer - Begin Again (Original Mix) Anjunadeep 00:27:07 Coach Harrison x A.M.R (DE) - Come For Me Bamboo Artists 00:32:01 Bakermat - 900 Miles ft. Barbara Dane (Extended) Big Top Amsterdam 00:35:33 - Promesses - DIMMI feat B Lacoste ( FLO.motion Extended ) 00:40:24 Romain Garcia - White Flag (Extended Mix) Ton Töpferei 00:44:37 Joris Delacroix - Aiguilhe (Original Mix) Cercle Records 00:48:39 Marsh, Nox Vahn - Come Together (Extended Mix) Anjunadeep 00:55:37 - Manifest everything

Jagged Jungle Radio Show – 6-Month Flashback Special A one-hour escape from the city… back to where it all began. We've officially hit the half-year mark 25 weeks of sunrise grooves, treasure tracks, tropical transitions, melodic maps, and sunset stretches. To celebrate six months of the Jagged Jungle journey, we're rewinding the clock and bringing you a special Flashback Episode: the very first show we ever aired on Distorted. This debut episode was the blueprint the moment the sound, the vibe, and the vision all clicked. From the silky Sunrise Set with Jerro, Sophia Bel, Sigala, and Chris Malinchak… to the tribal pulse of Bakermat, Kaleta & Robert PM, and the hypnotic energy of Rafa Barrios… this was where the story started. ✨ The OG Segments That Started It All: Sunrise Set: Smooth, tribal grooves to set the tone (Jerro, Sigala) Treasure Track: Chris Malinchak – So Good To Me (a timeless anthem) Energy Builder: Feel-good heat with Bakermat, Kaleta, Rafa Barrios New Wave: DJ YUKI's remix of Show Me Love + her first JJ appearance Tropical Transmission: A then-and-now look at David Guetta — from the Avicii era influence to his collab with HUGEL Melodic Map: Destination — Puglia, Italy (Cala Maka) Sunset Stretch: Euphoric coastal closer with Les Bisous & Samuele Sartini Six months later… the jungle's bigger, brighter, and bolder — and it's all thanks to you. Whether you've been here since Episode 1 or only just joined the tribe, I'm grateful for every listen, every share, every message. Hit play and step back into the beginning paradise is still just a button away.

Episode 24 is a little love letter. A rewind. A reflection. A journey through the tracks that built the sound of Jagged Jungle from the very beginning. This week, I pulled together all my favourite songs that shaped this show, the ones I've played on long drives, airport runs, and those quiet moments where music hits deeper than usual. We're going from the OG tropical era with Faul & Wad's Changes all the way to their brand-new release Everybody, plus emotional cuts from aname, Oskar med K, Forrester, LP Giobbi, Jerro, Nora En Pure and more… including my own track Come With Me to close it out. If you've been with Jagged Jungle from day one or you've just joined the family, this one is for you. It's nostalgic, melodic, euphoric… and honestly, it feels like a warm hug. Press play and escape with me.

Taking a deep dive with Selena Fragassi, author of the book "Alanis: Thirty Years of Jagged Little Pill," which explores the 30th anniversary of Alanis Morissette's landmark album.

Send us a textBig Rich sits down with Jagged X Off-Road founder Bill Schueler to trace the journey from a Phoenix garage to the front lines of UTV racing and aftermarket innovation. Bill shares how his sons Justin and Brandon turned a high school hobby into Jagged X, the early Rhino craze, and the fateful call from Polaris that put them on the map—leading to the first-ever desert race for the Polaris RZR.Highlights: - Chicago roots to Arizona life: construction, dispatching, and launching a successful transportation brokerage. - The backyard beginnings of Jagged X: lifted golf carts, early Yamaha Rhinos, and magazine features. - Polaris partnership: becoming an aftermarket development partner and fielding one of the first RZR race cars. Support the show

This week's show takes you on a melodic journey from sunrise to sunset, a lush blend of tropical house, deep grooves, and emotional electronica that'll lift your mood and move your body. Our Treasure Track is the timeless “Younger (Kygo Remix)” by Seinabo Sey, released back in 2013, a record that helped shape the birth of tropical house and still hits with that golden-hour magic. Our New Wave Artist spotlight shines on N2N, part of the rising U.S. tech-house scene, bringing groove, melody, and undeniable warmth to the mix. In the Tropical Transition, we dive deep with RÜFÜS DU SOL, the masters of desert-meets-ocean emotion, before heading to India on this week's Melodic Map, where Jerro will perform at MERÇII on December 6th. Expect an unforgettable closing stretch on the Sunset Strip, Press play and escape the noise — from the city to the tropics.

JAGGED JUNGLE RADIO – EPISODE 22 Hosted by Jayli This week we're going full journey mode from sunrise melodies to late-night club energy, with a few stories from the road along the way. We open with a brand-new track from The Chainsmokers' new album Breathe, roll into fresh heat from Jerro, Kid Cudi, RÜFÜS DU SOL, CamelPhat & Cristoph, and spotlight our New Wave Artist of the week: AMOG (FR) one to watch in the melodic house world. Our Treasure Track digs back into Ninetoes – Finder, the 2013 Ibiza anthem that became the most Shazamed track on the island that year. This week's Tropical Transition is a special one , a vocal journey through the rise of Jem Cooke, from her early releases to global club classic Breathe and her brand-new Toolroom single Good To Go. Then we jump to New York City for the Melodic Map, reliving Halloween at Brooklyn's high-fidelity club Public Records, where Jayli saw house legend Dennis Ferrer shut the room down. Expect deep, emotional club cuts and a whole lot of groove. Finally, we land in the Sunset Strip, cinematic, warm, end-of-the-night energy.

JAGGED JUNGLE RADIO SHOW – EPISODE 21: HALLOWEEN SPECIAL This week's episode of Jagged Jungle Radio takes you on a full-scale Halloween journey — from the glow of sunrise right through to the dark pulse of midnight. Expect a mix of new wave house, tropical grooves, melodic techno, and Halloween-ready remixes stitched together in true Jagged Jungle style. Featuring fresh cuts from Ricky Pellegrino, ESSENN, John Summit, Anyma, CamelPhat, Yes Boone, and more — plus a few special moments including:


Jagged Jungle 19 with Jayli Welcome to Jagged Jungle 19, a jewel of an episode carved from tribal roots, melodic highs, and global club grooves. This edition features a Tropical Transition courtesy of Calvin Harris, a spotlight on rising New Wave artist MÖM, and a sonic passport stop on our Melodic Map with Leandro Da Silva, the Italo-Brazilian producer channeling Florence's Bamboo Lounge heat.

This week Lauren deep dives the newish jukebox musical, Jagged Little Pill. This show has everything! Drugs! Gender Identity! SA! Cheating! And more! If there is a societal issue, it's in this musical! Get in touch! @downstageleftpc downstageleftpc@gmail.com downstageleftpodcast.com

Send us a textFaith & Doubt 03 — God as Mosaic, Faith as a CreedWhen you stay in the tradition long enough, you realize something unsettling: God doesn't hold still. The moment you think you've got God figured out—a verse, a doctrine, a tidy metaphor—life shifts. A diagnosis, a betrayal, a miracle, a silence. Suddenly, God looks different again.That's what this episode is about. The idea that God is not static. The story of Scripture is a moving picture—God in gardens, God in deserts, God in exile, God in flesh. From Genesis to Revelation, the divine keeps showing up in new and surprising forms. The faithful are always being asked to reorient, to find holiness inside the disorientation.In this third piece of the Faith & Doubt series, I explore how faith was never meant to be a posture of certainty, but of fidelity. Faith as showing up. Faith as staying loyal even when the picture blurs. Because maybe what God wants from us isn't perfect answers—but steady presence.I talk about the danger of cherry-picking only the comforting images of God—the gentle shepherd, the loving father, the still small voice—while ignoring the wilder parts: the fire, the storm, the silence that won't speak. What if the truest picture of God is a mosaic? Jagged, colorful, and whole only when we hold all the pieces together.“If God is a moving target, maybe faith is the willingness to keep aiming.”That's the center of this reflection. That faith is less about having answers and more about staying in the questions. That doubt doesn't make you faithless—it makes you honest. God isn't afraid of your questions; God is in them.If this episode speaks to you, you can read the full essay here on Text & Rock and check out the rest of the Faith & Doubt series for more reflections on belief, deconstruction, and becoming whole again.For Text and Rock Poetry, Podcasts, and Video Content or to contact Mark and Eric, visit us at www.textandrock.com. You can find all of social handles here: TEXT AND ROCK SOCIALS.Want to support the show, experience our best creative work, buy one of our books or give an uncommonly better gift or art and heart? Ha! Head to the TEXT AND ROCK DIGITAL PRESS.

Bulwark Capital  https://KnowYourRiskPodcast.comHear directly from Zach Abraham as he shares insights in this FREE “Back To Basics” Webinar, THIS THURSDAY at 3:30 Pacific.  Register now at Know Your Risk Podcast dot com. Bizable https://GoBizable.comUntie your business exposure from your personal exposure with BiZABLE.  Schedule your FREE consultation at GoBizAble.com today. Renue Healthcare https://Renue.Healthcare/ToddYour journey to a better life starts at Renue Healthcare. Visit https://Renue.Healthcare/Todd Alan's Soaps https://www.AlansArtisanSoaps.comUse coupon code TODD to save an additional 10% off the bundle price.Bonefrog https://BonefrogCoffee.com/toddThe new GOLDEN AGE is here!  Use code TODD at checkout to receive 10% off your first purchase and 15% on subscriptions.LISTEN and SUBSCRIBE at:The Todd Herman Show - Podcast - Apple PodcastsThe Todd Herman Show | Podcast on SpotifyWATCH and SUBSCRIBE at: Todd Herman - The Todd Herman Show - YouTubeThere is a problem with Democrat women in leadership. They're gross. So what do we do with this information?
Episode Links:Hillary Clinton continues to demonize white Christian men.KAMALA: “We have to remember nobody gives us our light. It's ours … Don't let them extinguish our light.”Emma Watson finally breaks her silence and shares her truth about the rift with JK Rowling. Spoiler alert- You may need some vinaigrette to consume this.Emma Watson is struggling with her cognitive dissonance. She knows JK Rowling is speaking the truth but wants to cling onto the lies of trans ideology regardless.If only there was someone who could have warned Emma Watson that nothing short of total & absolute surrendering to trans ideology is enough for them.NEW: Serena Williams speaks out against a cotton decoration at a New York City hotel, says it doesn't make her "feel great." -- "Personally, for me, it doesn't feel great," she said on IGThis woman is baffled because she found out a person she works with is conservativeWhat Does God's Word Say?Acts 16:16-20 Paul and Silas in Prison16 Once when we were going to the place of prayer, we were met by a female slave who had a spirit by which she predicted the future. She earned a great deal of money for her owners by fortune-telling. 17 She followed Paul and the rest of us, shouting, “These men are servants of the Most High God, who are telling you the way to be saved.” 18 She kept this up for many days. Finally Paul became so annoyed that he turned around and said to the spirit, “In the name of Jesus Christ I command you to come out of her!” At that moment the spirit left her.

“Moms buy everything.” From Gatorade to SUVs, they drive 85% of purchases. Time for marketers to wake up. Maria Bailey has built a powerful career at the intersection of media, business, and marketing. Recognized as the foremost authority on marketing to moms, she is also a leading voice in influencer engagement. Named by Ad Age as “One of the Must-Follow Women on Social Media,” she is an award-winning author, talk show host, international keynote speaker, and CEO of BSM Media. Jagged with Jasravee is facilitated by Jasravee Kaur Chandra. Jasravee has over 25 years experience as a Strategic Brand Builder, Communications Leader and Entrepreneur. Please visit Jasravee at https://jasravee.com/Email Jasravee at jasravee@gmail.com

France is slipping through her fingers. With the kingdom on the brink of collapse, Queen Isabeau of Bavaria makes a desperate move: she offers her daughter's hand to England's King Henry V. It's a bold bid for peace—but peace comes at a price. As the English celebrate their triumph, they soon discover that ruling a broken kingdom is far more costly than conquering it. This is a tale of uneasy alliances, royal ambition, and the brutal cost of diplomacy. Listen back to season six, episode twelve for the last time France was under English control.  Find all of that and more on our Patreon, where you can also vote on future episodes, share some spicy court gossip with fellow subscribers, and hear from Danièle and the rest of the royal council.  Become one of our royal favourites: patreon.com/thisishistory  A Sony Music Entertainment production.  Find more great podcasts from Sony Music Entertainment at sonymusic.com/podcasts  To bring your brand to life in this podcast, email podcastadsales@sonymusic.com  Learn more about your ad choices.  Visit megaphone.fm/adchoices  Presented by Dan Jones Producer - Alan Weedon  Senior Producer - Dominic Tyerman Executive Producer - Simon Poole Production Manager - Jen Mistri  Production coordinator - Eric Ryan  Sound Design and Mixing - Amber Devereux Head of content - Chris Skinner Learn more about your ad choices. Visit podcastchoices.com/adchoices

Jagged, urgent, experimental - the 1998 album Sand On Seven by Not From There is an inventive debut that effectively blends post-punk, slowcore, and noise rock. The Australian trio incorporate German-language vocals on several tracks, giving the album an otherworldly edge to pair with angular guitars, throbbing basslines, and restless rhythms giving 90s indie rock a uniquely disorienting twist. Songs move between abrasive noise and moody atmosphere, reflecting both tension and restraint. Though it didn't reach massive commercial heights, Sand On Seven became a cult favorite in alternative circles and won the ARIA Award for Best Alternative Release in 1999.   Songs In This Episode Intro - Sich Öffnen 10:57 - Hurricane Charlie 14:57 - Neurons 16:57 - Juanita's Cocktail Party 19:52 - The Orb of Discomfort 26:18 - Abgedroschen Outro - What Is Better Now   Support the podcast, join the DMO UNION at Patreon. Listen to the episode archive at DigMeOutPodcast.com.

Synopsis: Two decades after Hurricane Katrina ravaged Louisiana, the state is now facing a new kind of storm: the rapid expansion of liquified natural gas facilities that are displacing residents and polluting minority communities.This show is made possible by you! To become a sustaining member go to LauraFlanders.org/donateDescription: Hurricane Katrina was one of the deadliest hurricanes ever to strike the United States, killing 1,833 people, displacing hundreds of thousands more and causing more than $100 billion in damage. Louisianans wanted change and climate action, but 20 years on, a state ravaged by climate disasters is now ground zero for a whole new kind of storm: liquified natural gas facilities. The Trump administration okayed several new LNG plants on the Gulf this year, but residents are still picking up the pieces after the first LNG plants entered their neighborhood under Democratic administrations. In this episode, Laura speaks to Louisianans whose lives have been turned upside down by the expansion of LNG exports, and an expert who says minority communities benefit little from the jobs in the petrochemical facilities that surround them, yet suffer disproportionate pollution effects. Their message? Climate refugees exist in the U.S., and there will be more: “Wake up, open your eyes!”“[I'm a] climate refugee, more than once . . . I'm no scientist, but I'm more of an expert than the experts. Living it's a whole different ball game.” - Travis Dardar“[Companies] demand big tax incentives to come here . . . We are last in transportation, last in healthcare, last in education . . . We're almost last in every measurable area because we give tax breaks to the big oil companies and petrochemical companies.” - General Russel L. Honoré“Donald Trump doesn't live next to an oil refinery and he never will.” - Kimberly TerrellGuests:•  Travis Dardar: Commercial Fisherman; Founder, Fishermen Interested In Saving our Heritage (FISH)•  General Russel L. Honoré: Decorated 37-Year Army Veteran; Commander, Joint Task Force Katrina; Founder, GreenARMY•  Kimberly Terrell: Visiting Scientist, Center for Applied Environmental Science (CAES); Former Research Scientist & Director, Community Engagement, Tulane Environmental Law ClinicAdditional Crew: for this special report includes Dan T. Peters of Dan T. Peters Media and Calvin Blue Jr..  Special Thanks:  Gina Kim and Anne RolfesMusic credits: Jagged and Thrum of Soil by Blue Dot Sessions and original sound design by Jeannie Hopper Watch the episode released on YouTube August 1st, 5pm ET; PBS World Channel August 3rd, and on over 300 public stations across the country (check your listings, or search here via zipcode). Listen: Episode airing on community radio (check here to see if your station airs the show) & available as a podcast August 6th.Full Episode Notes are located HERE.-Related Podcast:  Uncut Conversation with General Russel L. Honoré: Decorated 37-Year Army Veteran; Commander, Joint Task Force Katrina; Founder, GreenARMY RESOURCES:Related Laura Flanders Show Episodes:•  Colette Pichon Battle on Climate Justice Reparations- Watch / Listen:  Episode, Full Conversation•  BIPOC Media Answers the Call: Community Action After Hurricane Helene- Watch / Listen:  Episode, Full Conversation•  Before the Ground Runs Dry: BIPOC Media on the US Water Crisis: Watch / Listen:  EpisodeRelated Articles and Resources:•  Fishfolk are on the frontlines of the gas export boom, Venture Global's Calcasieu Pass 2, or CP2, threatens the way of life on Louisiana's Gulf Coast, January 25, 2025, Southern Environmental Law Center•  The Biden Administration's Next Big Climate Decision.  The liquefied-natural-gas-buildout-and fossil-fuel exports-challenge progress on global warming.  September 22, 2023,  By Bill McKibben, October 31, 2023, The New Yorker•  Pervasive racial and ethnic disparities in the U.S. petrochemical workforce, by Kimberly Terrell, Gianna St. Julien, Michael Ash, September 2025 Science Direct Laura Flanders and Friends Crew: Laura Flanders, along with Sabrina Artel, Jeremiah Cothren, Veronica Delgado, Janet Hernandez, Jeannie Hopper, Gina Kim, Sarah Miller, Nat Needham, David Neuman, and Rory O'Conner. FOLLOW Laura Flanders and FriendsInstagram: https://www.instagram.com/lauraflandersandfriends/Blueky: https://bsky.app/profile/lfandfriends.bsky.socialFacebook: https://www.facebook.com/LauraFlandersAndFriends/Tiktok: https://www.tiktok.com/@lauraflandersandfriendsYouTube: https://www.youtube.com/channel/UCFLRxVeYcB1H7DbuYZQG-lgLinkedin: https://www.linkedin.com/company/lauraflandersandfriendsPatreon: https://www.patreon.com/lauraflandersandfriendsACCESSIBILITY - The broadcast edition of this episode is available with closed captioned by clicking here for our YouTube Channel

Returning guest Tim Hinely (Dagger Zine, Where The Wild Gigs Were) brings us Dallas, TX band Old 97's and their 1997 breakout release 'Too Far To Care'. Coming up during the alt-country boom of the 90s that also included bands like Wilco and Son Volt, their love of both Hank Williams AND punk rock shines through on this fine collection of tunes. Songs discussed in this episode: Iron Road - Old 97's and Waylon Jennings; New Madrid - Uncle Tupelo; Drown - Son Volt; Timebomb, Barrier Reef, Broadway, Salome, W. TX. Teardrops - Old 97's; City Of Wet Angels - Funland; Melt Show, Streets Of Where I'm From, Jagged, Big Brown Eyes, Just Like California, Curtain Calls, Niteclub, House That Used To Be - Old 97's; The World's A Mess, It's In My Kiss - X; Four Leaf Clover, Rocks Off (Rolling Stones cover) - Old 97's

It’s an Alanis Morissette and Carole King mashup episode! Rachel and Kurt are not on the same page, Becky has a new boyfriend everyone is concerned about, and Brittana takes their relationship to the next level! Kevin and Jenna have a lot of thoughts, including being underwhelmed by one of the storylines, the scene that ticked off Kevin, and the scene that still has them laughing uncontrollably!Plus, the inside scoop on Santana’s brutal Kurt takedown, and Kevin's reflection on the show’s decision to have Coach Beiste transition and how timely and topical it is today.For fun, exclusive content, and behind-the-scenes clips, be sure to follow us on Instagram @andthatswhatyoureallymissedpod!See omnystudio.com/listener for privacy information.