Podcasts about Jevons

Sign up for Practi, a new platform that helps law firms use subscription billing.Here are the top 5 takeaways from this episode:* Lawyers need an AI strategy and policy first. Before adopting any tools, firms must have a written AI policy, even if it simply says no tools are approved yet. Without one, a staff member using an unapproved (non-enterprise) AI tool can cause an ethical breach if client data ends up in model training.* Stick to two AI tools, not a dozen. Jennifer recommends picking one AI within your existing workspace (Copilot if on Microsoft, Gemini if on Google) plus one secondary tool for drafting or checking work. Chasing every new model is counterproductive. Depth beats breadth.* Document infrastructure is the real foundation. Before AI can be useful, a firm's documents need to be organized, accessible, and OCR'd where necessary. Getting documents into a state where an AI can actually “talk” to them is the unglamorous but critical first step.* Claude (especially via Claude Code/Cowork) is the top recommendation for legal writing. For transactional work requiring a long context window, Jennifer sees Claude as unmatched. She's actively installing Claude's Cowork integration for clients, who are amazed at its ability to handle contract redlines directly in their workflow.* AI increases productivity but also workload. Jennifer invokes Jevons' Paradox: AI tools make lawyers faster, but that extra time tends to get filled with more work. The real win is choosing intentionally: take on more clients, deepen client relationships, or bill at a higher rate, rather than just working more hours.__________________________Want your question to be answered on a future show? Fill out this short survey.Have subscription model question? Check out this free resource to ask all of your questions at notebook.practi.ai.Check out Law Tech AI.Sign up for Paxton, my all-in-one AI legal assistant, helping me with legal research, analysis, drafting, and enhancing existing legal work product.Get Connected with SixFifty⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠, a business and employment legal document automation tool.Sign up for ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Gavel⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠, an automation platform for law firms.Visit ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Law Subscribed⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ to subscribe to the weekly newsletter to listen from your web browser.Prefer monthly updates? Sign up for the Law Subscribed Monthly Digest on LinkedIn.Check out ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Mathew Kerbis'⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ law firm ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Subscription Attorney LLC⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠.Want to use the subscription model for your law firm? Click here to sign up for a new platform that helps law firms use subscription billing. Get full access to Law Subscribed at www.lawsubscribed.com/subscribe

Vad ska vi göra när AI har tagit alla jobb? Och vilka nya jobb kommer eventuellt uppstå? Med Hampus, Viktor, Lars och Jacob. TIDSSTÄMPLAR [00:00:00] Intro [00:03:00] USA stänger av Anthropic Fable för utländska användare – "kill switch" i AI-kapprustningen [00:12:00] Historiska jobbomvandlingar: väckaren, stickramen och spinneriet [00:19:00] Kommer AI leda till massarbetslöshet? MIT-studien "Canaries in the Coal Mine" och Jevons-paradoxen [00:25:00] AGI-timing: Dario Amodei, Elon Musk och Marc Andreessen om när superintelligensen kommer [00:31:00] Komparativa fördelar vs AI – och vad IQ-kurvan säger om framtidens arbetsmarknad [00:37:00] Vad skulle du göra om du inte behövde jobba? Lars drömmer om tåg och fotboll [00:44:00] 40-timmarsveckan – historisk relikt eller permanent struktur? [00:48:00] Råd till nyexade: initiativkraft, nyfikenhet och att hålla sig à jour med verktygen [00:52:00] Eric Schmidt utbuad på Harvard – och vad det säger om mänsklighetens förhållande till förändring [00:53:00] AI-attityder: 30% positiva i USA, 70% positiva i Kina – varför är det tvärtom mot vad man tror? [00:57:00] Framtidens yrken OM PODDEN Marknaden är en podd om börs, ekonomi och finans. Vi som gör den är Hampus Brodén, Johan Isaksson, Petter Hjerstedt, Viktor Fritzén, Lars Jörnow och Jacob Bursell. Följ oss på X: https://x.com/marknadspodden Hör av er till oss på jacob@monopolmedia.se

We talk to Michał Zalewski (lcamtuf) about the vulnpocalypse and if we even need fuzzers anymore. This episode may be export controlled at a future date.Watch on YouTube: https://www.youtube.com/watch?v=uI9CSgB4p9oTranscript: https://securitycryptographywhatever.com/2026/06/14/facing-the-vulnpocalypse-with-lcamtufhttps://github.com/google/aflhttps://www.reddit.com/r/claude/comments/1tqtenf/anthropic_said_today_that_mythos_is_coming_to_all/https://github.com/google/clusterfuzzhttps://en.wikipedia.org/wiki/Jevons_paradoxhttps://en.wikipedia.org/wiki/XZ_Utils_backdoorhttps://en.wikipedia.org/wiki/Brighton_hotel_bombinghttps://curl.se/https://ftp.openbsd.org/pub/OpenBSD/patches/7.8/common/025_sack.patch.sighttps://www.wired.com/story/last-pass-vulnerability-password-safe/https://nostarch.com/tangledwebhttps://nostarch.com/silence.htmhttps://nostarch.com/practical-doomsdayhttps://nostarch.com/secret-life-of-circuitshttps://www.youtube.com/c/3blue1brown"Security Cryptography Whatever" is hosted by Deirdre Connolly (@durumcrustulum), Thomas Ptacek (@tqbf), and David Adrian (@dadrian)

Dans cet épisode nous allons nous demander si le paradoxe de Jevons est applicable à l'IA et pourquoi.

00:01 1999 igjen: to skrekkfilm-hiter og «this time it's different»00:04 Rekordbelåning og margin debt på all time high00:05 Opsjonsjaget vi ikke har sett siden 198700:08 Short gamma, marketmakere og spiralen som ga «Red Friday»00:14 Ingenting virket: bare lang volatilitet beskyttet00:17 Laveste korrelasjoner på to år og VIX opp 40 prosent00:18 Bank of America: «here be dragons» og ledighet mot inflasjon00:20 Bilen, AI og Jevons-paradokset00:24 SpaceX som datasenterselskap, ikke rakettselskap00:30 Børsnotering denne uka: 1770 milliarder og Musks absolutte makt00:31 S&P-nekten mot FTSE, Russell og MSCI00:32 Lockup-kalenderen og dagen å frykte: seks måneder og fire dager00:35 Grok mot Groq og «race to zero» i modellene00:40 Midtøsten: Trump mot Netanyahu og oljeprisen00:44 Hva folk ikke ser på nå: bear flattening og carry trades som ryker00:47 Dollar over 161 og japansk intervensjon00:49 Hudson River Trading og datasenteret i Norge00:51 Norge har misforstått seg selv: fisk, olje, rå kraft og nå compute00:53 Å raffinere compute: Skygard, spillvarme og 10X på krafta00:58 Compute som multiplikator: fra 10x-ere til 100x-ere01:00 Budsjettforliket, Mímir Kristjánsson og minstepensjonistene01:05 Å prestere når alt er mulig: fokus, nysgjerrighet og flytskjemaer01:11 Telefonen som heroin: reels, 24-timers reset og hjernen tilbake01:19 Trikkedrapet og situational awareness01:24 Varsler i stedet for å glo på skjermen: gull/sølv og momentum01:35 1998: LTCM, doblede posisjoner og banken som tapte 900 millioner01:45 Andrew Left, Citron og short-saken som ble svindel01:50 Oraclum, superforecasters og nordmannen på topp01:56 Drewry-indeksen, VM-frakt og Fifas fredspris til Trump Hosted on Acast. See acast.com/privacy for more information.

June 2, 2026: Senator Bernie Sanders wants the federal government to own half of OpenAI, Anthropic, and every major AI company in America — and he's framing it as reclaiming stolen public knowledge. We break down exactly how his American AI Sovereign Wealth Fund Act would work, why the Norway comparison falls apart, and what would actually happen to valuations, talent, and American competitiveness if it ever got close to passing. Then: Apollo Global Management's chief economist says there is zero evidence AI is killing jobs — and the data may actually back him up. We look at Jevons paradox, the AI washing phenomenon, and why the aggregate labor market story is more encouraging than the doom headlines suggest. And finally: new Federal Reserve research reveals that 64% of the rise in young worker unemployment since the pandemic traces back to remote work, not AI — and why being willing to go to the office five days a week may be the single best career move a worker in their twenties can make right now.

Most of the AI timeline debate happens in software. Benchmark scores, model releases, the shape of the capability curve. Jon Billow watches a different number for a living: lead times.Billow is on the leadership team at BNS, a firm that manufactures and installs electrical and communication infrastructure. The same critical power equipment his teams put into data centers also goes onto Navy and Coast Guard ships, more than 150 of them. He emailed John Sherman because he thinks the people forecasting AI's arrival are missing what he sees on the construction side every week. The buildout can only move as fast as its slowest part, and right now almost every part is backed up for years.That email is what got him on the show. Here is the heart of what he laid out.The constraint nobody prices inTo bring a large data center online, Billow says, a long list of things has to land at the same time: permitting, grid interconnect, critical power, cooling, and the compute itself. Miss one and the whole project waits. And nearly every item on that list carries a backlog measured in many months, sometimes years.The pinch point he keeps returning to is critical power equipment. According to Billow, the orders all funnel back to roughly five manufacturers, Eaton, ABB, Schneider, GE Vernova among them, and all of them are slammed. He notes that even the US government is having a hard time getting its allocation for ship programs, because it is standing in the same line as every hyperscaler. On top of that, more municipalities are now requiring data centers to bring their own behind-the-meter power generation, which adds another category of equipment backlog and a skill most operators have never needed before. Hooking up to the grid is one thing. Building gas turbines and finding electricians who can parallel generators is another, and the skilled trades are already stretched thin.A factor of five to sevenSherman pushed him to put a number on the gap. If a company says a project lands in a year, how far off is that really?Billow's read: the US has roughly 50 gigawatts of total data center capacity today, with about a quarter of it allocated to AI. Around five gigawatts are under active construction and another seven to twelve sit in backlog. Set that against the order-of-magnitude jumps the labs are talking about and his estimate is blunt. “If I was to be a betting man I would say it's in the order of five to seven years.” Whatever timeline you have been handed, in other words, multiply it.The tells from inside the labsHe pointed to two recent signals that the infrastructure is already the limiting factor. OpenAI walking back a large commitment tied to its Sora video product, which Billow reads as a company looking at finite compute and deciding where to spend it. And Anthropic delaying a model, which he attributes partly to security concerns and partly to the reality of constrained compute capacity. The software keeps leapfrogging. The ground underneath it does not move at the same speed.Why this could be good newsBillow does not frame any of this as a reason to relax. He frames it as time. If the physical buildout runs years behind the hype, that is runway to get governance and alignment right rather than scrambling after the fact. He drew the parallel Sherman's audience knows well, comparing the moment to how the world slowly built doctrine around nuclear risk, and argued the work now is to use the delay deliberately.His closing image stuck with us. He said he wants to tell his grandkids that we were building the car while it was going down the road at 55 miles an hour, but we had the presence of mind to put in seat belts because we knew who was in the back seat.Where they did not agreeThe conversation did not paper over the tension. Sherman described his time in Holly Ridge, Louisiana, a town of about 2,000 mostly elderly people living next to a data center he compared to the size of Manhattan, with construction dust in the air and water residents will not drink. He found it overwhelmingly sad. Billow sees the same structures differently, as a testament to human ingenuity that can be sited and built responsibly if we choose to. Both things sat in the room at once, and the episode is better for letting them.Going deeperWe pulled the headline argument into this piece. The full breakdown for paid subscribers goes into the parts that get more technical and more political:* Compute governance as the most feasible near-term guardrail, including chip tracking and why the industry pushes back hard* The anonymous-compute problem and why “confidential computing” worries safety researchers* China's narrow-AI approach and what it implies about the data center race* Recursive self-improvement, Jevons paradox, and whether you even need new data centers to reach the danger zone* The regulatory carve-out tech enjoys, and the NDA story coming out of LouisianaIf you want that version, upgrade your subscription and it lands in your inbox. This is a public episode. If you'd like to discuss this with other subscribers or get access to bonus episodes, visit theairisknetwork.substack.com/subscribe

Chris Paul and Burning Bright tackle David Ayer's 2014 World War II film Fury, starring Brad Pitt, Shia LaBeouf, Logan Lerman, Jon Bernthal, and Michael Pena. Burning Bright picked it as a Memorial Day rewatch and argues it is one of the most underrated war films of the modern era, deserving way more credit than Saving Private Ryan style lionization tends to allow. The guys dig into the five very different spiritual approaches of the tank crew, the dehumanization of war daddy, bible, gordo, kunas, and the painfully innocent Norman, and why the infamous early execution scene is not the glorification it gets accused of being. They unpack the central biblical passage from First John chapter two, do not love the world or anything in the world, as the real moral spine of the film and the heart of all discernment. From there they go big picture, hitting Jevons paradox and how better military tech just means more efficient mass sacrifice, why World War II had the cleanest cartoon story of any modern war, the controlled opposition Nazi op being run on MAGA right now, narrative shielding through Donald Trump's hyper Zionist posture, and the fiery tank as a birth canal delivering Norman into a second chance.

Jeff Schulze of ClearBridge Investments joins host John Przygocki to assess the health of the US economy. He points to a resilient Q1 GDP reading, strong jobs data and earnings growth in estimating a 30% recession probability. He cites the Jevons paradox to explain why he doesn't fear an AI "job apocalypse." And he remains bullish on US equities despite Middle East uncertainty and inflation worries. 

I detta avsnitt diskuterar vi Jevons paradox och dess relevans i dagens samhälle, särskilt inom AI och energiförbrukning. Vi utforskar hur effektivisering kan leda till ökad efterfrågan snarare än minskad, och hur detta påverkar både företag och individer.

Cuando cada mejora te cuesta más: la trampa de la eficiencia. Para escuchar sobre el tema de System Sprawl al que hago referencia en este episodio, haz clic en este enlace. Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

Será que a Inteligência Artificial vai destruir todos os empregos? Neste vídeo, desmistificamos o alarmismo digital com base na teoria econômica e na história. Entenda o Paradoxo de Jevons , como o Excel revolucionou carreiras e por que a IA é a ferramenta definitiva para aumentar sua produtividade.

In this episode, we break down the Jevons paradox and why AI may not simply replace work but reshape it. As the cost of intelligence falls, demand for analysis, coding, drafting, design, service, and research may rise, shifting how investors think about growth and productivity. To read this week's Sight|Lines, click here. The views expressed in this podcast may not necessarily reflect the views of Stifel Financial Corp. or its affiliates (collectively, Stifel). This communication is provided for information purposes only. Past performance does not guarantee future results. Investing involves risk, including the possible loss of principal. Asset allocation and diversification do not ensure a profit or protect against loss. © Stifel, Nicolaus & Company, Incorporated | Member SIPC & NYSE | www.stifel.com See omnystudio.com/listener for privacy information.

Is the AI job apocalypse a marketing strategy and not an economic forecast?It's nuanced, and today we tap into first wave stats for clarity.Correlation does Not imply Causation. The divergence is real, but timing also coincides with the Fed's aggressive rate hikes and sustained tightening. That said, AI is likely to reshape the labor market—not just in the number of jobs, but in the types of roles that exist - after giants clean up the BLOAT.People think the AI job crisis is about technology, but it's really about wealth inequality. - Scott GallowayPURE FACT. Every generation has its version of this story.The one where machines come for the jobs.Where the future arrives faster than people can adapt.Where the world you knew is about to end.This time around, the story has better PR and a much bigger budget — but underneath, it's the same script.I'm not saying this is nothing to worry about - we all feel the speed. In fact, the current evolution of AI is 300X faster than the Industrial Revolution. So….here's what I keep coming back to so we can understand the middle phase of the tech boom we are living through. The loudest voices warning us about the AI job apocalypse are also the people who profit most when we believe them.Anthropic's CEO says half of all entry-level white-collar jobs will be wiped out in five years.Elon says no job will be needed.Sam Altman wrote, before ChatGPT even launched, that the price of human labor was about to fall toward zero.Notice the pattern?The people predicting an extinction-level event are the same people building the asteroid and selling tickets to watch.We've Been Here BeforeThis panic isn't new.The Nobel-winning economist Robert Shiller has shown that fears about machines replacing humans helped fuel economic downturns in the 1800s.Science fiction later convinced people that automation caused the Great Depression.Computer panic deepened the recession of the early ‘80s.His point was simple.The damage doesn't usually come from the technology itself.It comes from the story we wrap around it.People feel pain from a normal recession, blame the machines, get more pessimistic, pull back further, and the story becomes the thing that creates the outcome it warned us about.That's exactly what I think is happening right now.AI is becoming a convenient cover story for layoffs that are really about over-hiring, inflation, and tariffs.Look at the numbers.U.S. tech employment grew from 8.7 million in 2020 to 9.6 million in 2023, then went flat.Not great.Not the apocalypse either.Meta's 10% cut is just bringing the company back to its 2021 size.Microsoft's 7% cut still leaves it 47% bigger than before the pandemic.Tesla announced it was hiring more, then laid off 10% of its workforce a month later — because of weak sales, not robots.This isn't the prelude to the end of work.It's a low-hire, low-fire labor market.That's it.Three Ways This Resurgence Plays OutScenario one: the bubble pops.The Mag 10 now make up 40% of the S&P.AI stocks have driven the majority of the market's returns since ChatGPT launched.If AI sneezes, the rest of the economy gets the flu.And when that recession comes, we'll blame AI for it — even though, historically, layoffs come in recessionary bursts, not the moment a new technology arrives.Scenario two: AI delivers, just slower than they say.When something gets dramatically cheaper, we don't use less of it.We find a million new uses for it.That's Jevons paradox.When the spreadsheet launched in 1979, everyone said accountants were finished.Instead, the profession quadrupled over the next 40 years.The same pattern shows up everywhere computers got adopted heavily — employment grew faster, not slower.Programmers today are coding less and thinking bigger.They've gone from construction workers to architects.The real question for any knowledge profession isn't “will AI replace this?”It's “is the human demand for analysis, judgment, and oversight elastic?”I think it is.And I think we're about to discover how much demand has been quietly waiting for the cost of execution to drop.Scenario three: the disruption outruns us.This is the scary one.AI hits every sector at once, no policy response, full collapse of the recovery cycle.But here's the part most people miss.Real societal upheaval almost never comes from unemployment.It comes from people who are working hard and still falling behind.From the loss of economic dignity.If that sounds familiar, trust your gut.We're already living in it.What's Really Going OnInside Silicon Valley, the mood is dark.People talk seriously about a “permanent underclass” and a “limited window” to build wealth before robots take over.I think this is a shared hallucination.The same people obsessed with AI's rapid capabilities are ignoring everything else about how economies, labor markets, and human demand actually work.And here's the tell.Only Americans earning over $200,000 a year see AI as a net positive.That's not a fact about AI.That's a fact about who has access to opportunity in this country.The AI jobs panic is just the newest scene in a much older story about wealth inequality.The real disruption isn't going to come from AI.It's going to come from the public finally noticing that the people warning us about the fire are the same ones selling the smoke detectors.The AI job apocalypse isn't an economic forecast.It's a marketing campaign.We're not watching the end of work.We're watching the monetization of fear.Life is so rich. Especially when you realize your inherent creative power and the evolution of our society has bright day's ahead of us. Not the doom - change, and fast? Yes, but the Universal Law of Order is always flowing from chaos to order. Your thoughts? Here's MY thoughts on AI brought to LIFE for REAL SOLUTIONS. How I view AI.....within the SPACE of the LIGHT Between Oracle Healing Journey.“Between stimulus and response there is a space. In that space is our power to choose our response. In our response lies our growth and our freedom.” - Viktor FranklThe Light Between is the conscious, sovereign light that we must maintain between our stimuli and responses. This is the light of discernment, wonder, and creativity - the light where humans truly thrive at our full capacity, rather than merely coping.I'm building a movement to advocate for preserving this vital light. Safeguarding this Light Between will enable the mindful and beneficial integration of AI into our lives.It is the wellspring of our agency, our ability to thoughtfully shape our responses to the world. Protecting and nourishing this Light is paramount as we navigate the increasing presence of artificial intelligence in our lives.In Closing…So if this lit up your heart and minds view of all the bright potential of transforming world of opportunity, then I'd love for you to experience the LIGHT BETWEEN ORACLE JOURNEY + INTUITIVE READINGS. Five Guides and a Five Layer Path…..to accelerate your intuition and problem solving. The Five-Layer Path integrates intention rituals, intuitive card draws, ancient wisdom teachings, somatic practices, and multidimensional exploration to support your journey. With your purchase, you gain access to:* Tailored Guidance: Personalized oracle readings to answer your questions.* Your Place of Power: Tools to discover and transform disempowering states.* Self Hypnosis: Techniques to rewire the subconscious, enhanced by the Neuro-Nature Self Hypnosis App.* Soul Prayer: Contemplative practices to deepen your connection to inner wisdom.* Poetic Insights: A space to save reflections for creative expression and meaning.* Five-Layer Path for Integration: A holistic approach combining intention, intuition, ancient teachings, somatic practices, and multidimensional awakening.Start for FREE and upgrade for deep awakenings and spiritual problem solving that resolves the daily self doubt and uncertainty. This is a public episode. If you'd like to discuss this with other subscribers or get access to bonus episodes, visit thelightbetween.substack.com/subscribe

We're announcing a16z crypto's Fund 5: $2.2B in committed capital to back the startups and founders who are building the next era of crypto. All four GPs sat down to talk through where crypto is right now, what's changed, and where it may be headed next. Chris Dixon, Ali Yahya, Guy Wuollet, and Eddy Lazzarin join Robert Hackett to cover... 00:00 Open  01:31 Why raise Crypto Fund 5 now  02:10 The GENIUS Act and what regulatory clarity unlocks for builders  04:32 Why stablecoins are crypto's WhatsApp moment  08:54 Why the next era of crypto founders will be pragmatic, not ideological  11:49 From cypherpunk revolution to crypto's "collared shirt era"  15:02 Programmable money meets AI  21:15 Onchain capital markets for compute, energy, and credit  25:57 Why finance is the foundation, not the ceiling  28:48 AI agents as first-class economic actors  38:19 Why privacy is the only moat  41:26 Jevons paradox and the future of blockspace demand  43:20 Jolt and the zero-knowledge breakthrough  58:15 Writing the next chapter of Read Write Own Resources:  Chris Dixon: https://x.com/cdixon Ali Yahya: https://x.com/alive_eth Eddy Lazzarin: https://x.com/eddylazzarin Guy Wuollet: https://x.com/guywuolletjr Robert Hackett: https://x.com/rhackett Follow a16z crypto: X: https://x.com/a16zcrypto  LinkedIn: https://www.linkedin.com/showcase/a16zcrypto/posts/  YouTube: https://www.youtube.com/@a16zcrypto Subscribe for more industry reports, trend updates, news analysis, builder guides, and other resources: https://a16zcrypto.substack.com/subscribe/   ***  As always, none of the following should be taken as investment, business, legal, or tax advice. Please see a16z.com/disclosures for more important information, including a link to a list of our investments. Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

The headlines say layoffs. The data says something completely different. National Association of Realtors is forecasting a 14% surge in home sales in 2026—and almost no one is connecting the dots. In this episode, we break down the single most misunderstood economic force shaping real estate right now: the Jevons Paradox. When efficiency increases, demand doesn't shrink—it explodes. And that shift is already showing up across housing, labor, and transaction volume. While many are predicting disruption, the reality is this: the agents who understand what's happening are positioning for one of the biggest opportunities in modern real estate. We cover: • Why the housing crash narrative doesn't match the data • What's really happening to white-collar jobs • Why high-trust, in-person roles are gaining power • How transaction volume is poised to surge • Why the top 20% of agents will dominate the next decade 88% of buyers and 91% of sellers still use an agent. That hasn't changed—and there's a reason. The market isn't collapsing. It's reorganizing. And the agents who adapt now will be the ones running the market by 2030.

Uma garrafa de champanhe vendida por 2 mil reais não custou nem perto disso para ser produzida. Marx e Adam Smith achavam que o valor vinha do trabalho. Estavam errados.No século XIX, um economista britânico chamado William Jevons mudou para sempre a forma como entendemos o valor das coisas — e, de quebra, como entendemos nossas próprias decisões.A ideia dele, a "utilidade marginal", é uma das mais poderosas da história da economia.Neste episódio da série A História do Dinheiro, a gente explica como Jevons e Alfred Marshall construíram o modelo que domina a economia até hoje: oferta, demanda, concorrência perfeita e o famoso "homem econômico racional". Uma teoria elegante, poderosa — e que alguns consideram perigosamente simplificada.

This week's Frankly is the second in a three-part series on the role oil plays in modern civilization, prompted by the recent flow disruptions and geopolitical conflict surrounding the Strait of Hormuz. This installment explores how modern society has been built on the assumption of cheap and abundant energy, and what happens when that assumption breaks down. Nate describes the ways our built systems, including food production, water treatment, manufacturing, and global trade, are calibrated to cheap energy inputs, and how processes that look economically efficient are often deeply inefficient in physical terms. He walks through the staggering degree to which the modern food system runs on fossil hydrocarbons, noting that roughly ten calories of fossil energy now go into every calorie of food on the plate, and that the Haber-Bosch process for synthetic fertilizer is what allows the planet to feed roughly half of its current population. Nate then traces the accelerating depletion of conventional oil fields and the turn towards shale, which behaves as a fundamentally different resource than the conventional wells it has been masking. He considers the alternatives often proposed as replacements, highlighting why energy quality matters as much as energy quantity, and why solar and wind are better described as 'rebuildable' rather than 'renewable.' The episode closes with Jevons paradox and the historical pattern that humans have never actually transitioned off an energy source, only ever adding new ones on top of the old.  Why can't we simply swap in alternative technologies for fossil hydrocarbons? What does the turn toward shale mean for systems built around cheap and stable energy inputs? And how might oil supply disruptions reshape the things you do, consume, and think about in your daily life? (Recorded March 31st, 2026)   Show Notes and More   Watch this video episode on YouTube   Want to learn the broad overview of The Great Simplification in 30 minutes? Watch our Animated Movie.   ---   Support The Institute for the Study of Energy and Our Future   Join our Substack newsletter   Join our Hylo channel and connect with other listeners

Il vero costo del tuo prodotto digitale non si misura solo in server e codice.Si misura in litri d'acqua e tonnellate di CO2.In questo episodio Marco Imperato intervista Costanza Mosi, Head of Product di @Treedom, per svelare l'impatto reale (e devastante) di app e siti web sul nostro pianeta, e come ridurlo senza distruggere le conversioni.Oggi il rischio non è solo avere un prodotto lento.È essere complici di un'obesità digitale insostenibile.

In this episode, Mauricio sits down with Andreas Steno Larsen to discuss his upbringing in a family influenced by macroeconomics and markets, shaped by his father's role as a chief economist. Andreas explains his liquidity-centric global macro framework, emphasizing how global liquidity—driven by central banks, treasuries, and commercial banks—serves as the primary force behind asset prices, operating in extended cycles likely peaking around Q3 or Q4 of 2026 amid midterm elections. He explores the interplay of politics, low interest rates, and abundant liquidity leading to potential inflation in 2027, while addressing Bitcoin's resilient yet dislocated price action amid geopolitical tensions and AI disruptions, viewing it as infrastructure rather than mere software. Andreas rebuts doomsday AI theses by invoking the Jevons paradox, predicting productivity gains and increased demand rather than mass unemployment, and highlights catalysts like stablecoin adoption for an agentic economy. The conversation also covers geopolitical hedges, with oil, natural gas, and gold outperforming silver, and touches on central banks' potential Bitcoin adoption.

Vad händer i barns hjärna när de scrollar TikTok varje dag – och vem bär egentligen ansvaret? I detta avsnitt djupdyker vi i en av vår tids mest laddade frågor: barns skärmtid och sociala medier. Vi går igenom forskningen, rättsprocessen mot Meta och Google i Kalifornien, de beroendeskapande mekanismerna bakom algoritmerna – och vad som faktiskt kan göras åt det. I veckans avsnitt medverkar: Jacob Bursell – Monopol MediaLars Jörnow – Medgrundare, EQT VenturesViktor Fritzén – Styrelseproffs, f.d. CFO Leo VegasHelena Frielingsdorf – Psykiater & utredare, Folkhälsomyndigheten TIDSSTÄMPLAR 00:00:00 – Intro: Välkommen tillbaka efter sportlovet 00:02:00 – Jack Dorsey säger upp 4 000 på Block – är det AI-revolutionens startskott? 00:07:00 – Citrine-rapporten: Dystopisk framtid eller Jevons-paradoxen? 00:10:00 – Klipp från CNBC: Rättegången mot Meta och Google i Kalifornien 00:12:00 – Helena presenterar Folkhälsomyndighetens rekommendationer 00:14:00 – Skärmtidsregler per ålder: Vad säger forskningen? 00:16:00 – FOMO och sociala medier vs. TV och spel – vad är skillnaden? 00:17:00 – Viktor: Min nioåring lärde sig lösa Rubik's cube via Youtube 00:22:00 – De allvarligaste riskerna: Grooming, mobbning och skeva skönhetsideal 00:26:00 – Lars: Tio år av Slack-missbruk – och vad han lärde sig av det 00:28:00 – Hjärnans utveckling och koncentrationsförmågan hos barn 00:31:00 – Hönan eller ägget: Är skärmtiden orsak eller symptom? 00:33:00 – Föräldrar som dåliga förebilder – äter vi godis samtidigt? 00:36:00 – Skärmen som barnvakt: Den lätta genvägen och de dolda kostnaderna 00:40:00 – Intermittent belöning: Enarmade banditer i barnens fickor 00:43:00 – Autoplay, infinite scroll och push-notiser – designat för beroende 00:44:00 – Vad rättegången i USA egentligen handlar om: Visste bolagen? 00:46:00 – Tobaksindustrins cykel: Tog 40 år från vetenskap till åldersgräns 00:47:00 – Australien, Frankrike, Polen: Hur definierar man "sociala medier" i lag? 00:51:00 – EU:s Digital Services Act – varför har den inte fungerat? 00:53:00 – Race to the bottom: Reglering och den svarta marknaden 00:58:00 – Lars: Spelindustrins perspektiv – vem har det holistiska ansvaret? 01:00:00 – Borde Apple och Google bära det verkliga distributörsansvaret? 01:03:00 – FT och Economist mot förbud: Barnen kringgår ändå åldersgränserna 01:07:00 – Säkerhetsbälte-analogin: Normerande lagstiftning fungerar ändå 01:08:00 – Vad tycker barnen själva? Äldre tonåringar: "Vänta så länge ni kan" 01:10:00 – Producent, distributör, konsument – var ska ansvaret ligga? 01:11:00 – Anthropic vs OpenAI och Pentagon: Race to the bottom i AI också 01:17:00 – Kasinoregleringen som backfired – kan samma sak hända här? 01:18:00 – Utredningen om åldersgränser: Vad lämnar Sverige fram i november? 01:21:00 – AI-companions: Filmen Her blir verklighet – hur reglerar man det? 01:23:00 – Bris: AI-kompisar som säljer läppstift till deprimerade barn 01:26:00 – Har fokus på föräldrar räckt? Och vad händer när kulturen vänder? 01:27:00 – Smartphone Free Childhood: Klassrumsinitiativ som faktiskt fungerar 01:29:00 – Avslutning: Helena återkommer när utredningen är klar i november ÄMNEN SOM DISKUTERAS • Rättegången mot Meta och Google – Visste bolagen om de skadliga effekterna? • Beroendeskapande design – Intermittent belöning, infinite scroll och push-notiser • Folkhälsomyndighetens rekommendationer – Vad forskningen faktiskt säger om skärmtid • Åldersgränser i världen – Australien, Frankrike och Sverige utreder nu • Tobaksanalogien – 40 år från vetenskaplig konsensus till lag • Distributörsansvaret – Borde Apple och Google vara den primära regleringsytan? • AI-companions för barn – Nästa stora utmaning som vi inte är redo för • Föräldrarollen – Hur sätter man gränser när man själv sitter med telefonen? • Jevons-paradoxen och AI – Skapas fler jobb eller börjar snöbollen rulla? • Jack Dorsey och Block – Är 4 000 uppsägningar AI-revolutionens startskott? • Speldesign och beroende – Lars berättar om Kings affärsmodell inifrån • Smartphone Free Childhood – Kulturell förändring nerifrån och upp OM PODDEN Marknaden består av Jacob Bursell, Hampus Brodén, Viktor Fritzén, Johan Isaksson, Lars Jörnow och Petter Hjertstedt. Nu också på Youtube! Twitter: https://x.com/Marknaden_podd Kommentera och ge feedback – vi vill höra vad ni tycker! Mejla: jacob@monopolmedia.se #skärmtid #socialamedier #barnochungdomar #folkhälsa #techjättar #meta #google #tiktok #beroende #föräldrar #ai #aicompanion #reglering #australien #marknaden #podcast #svenska

¿Qué ocurre cuando las profecías tecnológicas más audaces chocan frontalmente con la tozuda realidad de los hospitales y los mercados? En 2016, Geoffrey Hinton sentenció que debíamos dejar de formar radiólogos, asumiendo que el reconocimiento de patrones por IA los haría obsoletos en un suspiro. Sin embargo, casi una década después, el «canario» que debía alertarnos del colapso del empleo humano no solo sigue vivo, sino que canta con más fuerza que nunca. En este episodio exploramos cómo la paradoja de Jevons y la lógica de la Reina Roja nos mantienen corriendo a toda velocidad solo para permanecer en el mismo sitio. Y nos preguntamos si la verdadera victoria de la IA no será la ejecución de tareas, sino la oportunidad de recuperar la dirección y el sentido de nuestro propio florecimiento humano. Bienvenidos al 2-5-0. Para seguir conectando puntos: Why AI isn't replacing radiologists Este análisis profundiza en los motivos técnicos y estructurales que explican por qué la IA no ha logrado desplazar a los especialistas, destacando la enorme brecha que existe entre el rendimiento de un algoritmo en un entorno controlado y el caos del día a día hospitalario. Nos sirve para entender que la radiología es mucho más que identificar manchas en una imagen; es un proceso complejo de contexto, responsabilidad legal y juicio clínico que las «islas de automatización» actuales aún no pueden replicar. https://www.worksinprogress.news/p/why-ai-isnt-replacing-radiologists El empleo de los radiólogos ante la IA (Informe Vanguard) Este artículo contrasta la teoría del reemplazo con los datos reales del mercado laboral, donde el aumento de la eficiencia ha disparado paradójicamente la demanda de pruebas y, por extensión, de profesionales para supervisarlas. Es la constatación empírica de cómo el sistema coevoluciona para escalar la complejidad en lugar de reducir el esfuerzo, validando que el futuro del trabajo sanitario pasa por la integración y no por la sustitución pura. https://www.elconfidencial.com/tecnologia/2026-01-03/empleo-radiologos-inteligencia-artificial-informe-vanguard-salarios-4276082 Jevons Paradox: A Personal Perspective (Tina He en Fakepixels) Esta pieza nos invita a reflexionar sobre la cara B de la productividad personal y cómo la hiperoptimización suele derivar en una «cinta sin fin» donde acabamos más agotados que antes de automatizar nuestras tareas. Compartimos la visión de la autora sobre la necesidad de desplazar el foco desde la ejecución mecánica hacia la dirección estratégica, cuestionando si el éxito debe medirse por el volumen de lo que hacemos o por la profundidad y el bienestar que generamos. https://fakepixels.substack.com/p/jevons-paradox-a-personal-perspective A New Evolutionary Law (Leigh Van Valen) Recuperamos este concepto clásico de la biología evolutiva para explicar por qué, a pesar de los avances en IA, sentimos que el trabajo nunca disminuye. Al igual que las especies en un ecosistema, nos vemos obligados a correr cada vez más rápido solo para mantener nuestra posición relativa en un mercado hipereficaz. Es una lectura esencial para comprender la trampa de la productividad infinita y por qué la tecnología, por sí sola, no nos sacará de la carrera. https://www.pnas.org/doi/10.1073/pnas.1525395113 La jaula de hierro (Max Weber) Mencionamos la metáfora de Weber para advertir sobre el peligro de convertir los medios tecnológicos en fines en sí mismos. En este episodio, conectamos esta visión con la «jaula algorítmica» que nos rodea: un entorno donde la racionalización extrema y la supervisión digital pueden terminar asfixiando nuestra libertad y creatividad si no somos conscientes de sus barrotes invisibles. https://conectandopuntos.es/episodio-249-la-jaula-de-hierro-algoritmica/ Wellbeing Budget (The Treasury New Zealand) Frente al dictamen del crecimiento económico ciego, nos fijamos en modelos que priorizan el florecimiento humano y la salud integral. Exploramos cómo algunos gobiernos están empezando a medir el éxito no solo por lo que producimos, sino por el bienestar real de la población, ofreciéndonos una brújula distinta para navegar la era de la IA y redirigir sus frutos hacia lo que verdaderamente importa. https://www.treasury.govt.nz/publications/wellbeing-budget/wellbeing-budget-2021-securing-our-recovery Conecta, conectante Para contactar con nosotros, podéis utilizar nuestra cuenta de twitter (@conectantes), Instagram (conectandopuntos) o el formulario de contacto de nuestra web conectandopuntos.es. Nos podéis escuchar en iVoox, en iTunes o en Spotify (busca por nuestro nombre, es fácil). Damos crédito, porque nos parece imoportante Intro: Stefan Kanterberg ‘By by baby‘ (licencia CC Atribución). Cierre: Stefan Kanterberg ‘Guitalele's Happy Place‘ (licencia CC Atribución). Foto: Creada con IA Gemini ¿Quieres patrocinar este podcast? Usamos los patrocinios para cosas como mejorar nuestros materiales de grabación y aumentar nuestra visibilidad, porque sabemos que ahí fuera existen muchos más puntos con los que conectar Si quieres ayudarnos con un patrocinio, puedes hacerlo a través de este enlace La entrada Episodio 250: El canario que seguía cantando en la mina de la IA se publicó primero en Conectando Puntos.

Are self-driving databases the Waymos of the future? In Episode 35 of Talking Postgres, Luigi Nardi—founder and CEO of DBtune and Stanford researcher—joins Claire Giordano to explore his journey from academic research to Level 5 autonomous database tuning. We dig into Luigi's early days with a Commodore 64, how he began his PhD in Paris before he had learned to speak French, and how "professor privilege" in Sweden helped him bootstrap his startup. You'll learn why the DBtune team chose database tuning and Postgres as their focus, what the Jevons paradox means for the future of developers, and how the “Level 5” vision fuels the DBtune team's work toward a truly self-driving system. Previously on Talking Postgres:Talking Postgres Ep30: AI for data engineers with Simon WillisonTalking Postgres Ep23: How I got started as a developer & in Postgres with Daniel GustafssonLinks mentioned in this episode:CFP: POSETTE: An Event for Postgres 2026's CFP closes on Sun Feb 1, 2026 @ 11:59pm PSTVideo of POSETTE 2024 talk: Autotuning PostgreSQL on Azure Flexible Server, by Luigi NardiVideo of PGConf India 2025 talk: ML for Systems and Systems for ML, by Luigi NardiPGConf India 2025: Round Table Discussion about AIOxide and Friends podcast: Engineering Rigor in the LLM AgeWikipedia: Jevons paradoxWikipedia: Neuro-symbolic AIConference: PGDay Lowlands (Boriss Mejías calls it the second-best Postgres conference in Europe)Calendar invite: LIVE recording of Ep36 of Talking Postgres to happen on Wed Feb 18, 2026

My guests today are Animesh Koratana and Jamin Ball. Animesh is the founder and CEO of our portfolio company PlayerZero, which is building AI production engineers that operate complex enterprise software autonomously - resolving production incidents, catching defects before release, and building durable models of how systems actually behave.Jamin is a partner at Altimeter Capital and the writer behind Clouded Judgement, a Substack where he analyzes emerging trends in enterprise software. Jamin recently sparked a debate with an essay titled “Long Live Systems of Record.” His core argument is that while agents are changing how software is used and where value accrues, they still depend on ground truth. Systems of record won't disappear so much as get pushed down the stack as new agent-native interfaces emerge on top.My partner Jaya and I felt compelled to respond, with Animesh contributing insights based on what he's seeing on the ground as he builds PlayerZero. From our perspective, the missing layer is what happens inside the workflow itself: the judgment, exceptions, and reasoning that agents and humans apply as work gets done. We call these decision traces, and we believe the context graph they form over time will become the most valuable asset for companies building and deploying AI systems.It's a genuine debate - and one that's only going to matter more as agents move from demos to production.Looking forward to keeping the conversation going!Chapters00:00 Why Jamin's essay sparked debate00:35 Jamin's thesis: why agents need ground truth02:00 Animesh on why context graphs become the new source of leverage07:58 What current systems of record miss08:28 PlayerZero's perspective: context graphs in practice10:00 How context graphs could change org structures11:10 How to capture decision traces without forcing humans to log it?14:35 Which systems of record are most at risk17:04 Two workflows ripe for disruption: GTM and software development22:31 Animesh on where context graphs can add most value 28:50 Why context graphs create durability vs short-lived point solutions30:00 Will context graphs be verticalized or universal?34:00 Bear case: do context graphs fail like semantic layers?43:27 2026 predictions: big AI IPOs, world models, enterprise agent adoption45:00 Hot takes: point solutions die; AI job-loss discourse hits a fever pitch47:30 Jevons paradox: why agents create more work, not less

Mainstream economists and environmentalists share something in common. Both tend to tout efficiency -- think better light bulbs -- as the solution to climate change and all our other environmental problems. But the little-understood Jevons Paradox intervenes to overwhelm any progress that comes from improved efficiency. We skewer the efficiency gains of electric vehicles, lighting, and plenty of other sectors, and we cover ideas for avoiding the efficiency trap, including unveiling our new political platform, which is sure to take the country by storm.Sources/Links/Notes:Jason Barlow, "EVs Have Gotten Too Powerful," Wired, September 19, 2025.Russ Heaps, "Heaviest Electric Vehicles of 2025," Kelley Blue Book, April 7, 2025.Wikipedia article on energy efficiency in transport that includes a table that compares many modes of transportWilliam Stanley Jevons, The Coal Question: An Inquiry concerning the Progress of the Nation, and the Probable Exhaustion of our Coal-mines (London: Macmillan and Co., 1866). 2nd edition, revised.Tomas Kloucek, "Darkness as an Endangered Species: Why Light Pollution Matters," Earth Bridge, June 11, 2025.Scenic America, "Billboards in the Sky: The Hidden Culprit Behind Light Pollution," July 30, 2025.Prepared Mind, "Welcome to the Great Unraveling (Tapestry Cloud Style Reweaving Polycrisis into Polyopportunity," June 20, 2025.2,000 Watt SocietyCalculate your ecological footprint.Related episode(s) of Crazy Town:Episode 3, "One Point Twenty-One Jigawatts"Episode 19, "I Can't Drive...

With developments in generative AI progressing at such a furious pace, how can investors cut through the noise to identify the companies that will really matter? Baillie Gifford's Kyle McEnery shares his approach to meeting the entrepreneurs building the future – including his encounters with AppLovin, Anthropic, NVIDIA, Roblox and Reddit. Background:Kyle McEnery is an investment manager in our Long Term Global Growth Team (LTGG) and previously led Baillie Gifford's Artificial Intelligence Research Project. In this conversation, he tells host Leo Kelion why AI's ever-increasing capabilities make this one of the most exciting times to be a growth investor, and how leadership and culture act as signals in the noise to help identify companies with the greatest long-term growth potential. In addition to discussing which of the firms enabling and using today's language-based ‘frontier' AI models are leading the pack, he explains how efforts to understand and simulate real-world physics could unlock further progress. Portfolio companies discussed include:Anthropic – developer of the Claude AI models, which excel at coding, among other tasks.NVIDIA – the semiconductors firm whose accelerator chips are powering many of the advances in generative AI.Roblox – the video games platform whose Cube 3D technology allows creators to build objects and environments out of text-based descriptions.AppLovin – the ad-tech company whose AI-first strategy keeps the business lean and nimble.Reddit – the online discussion forum, whose authentic human conversations are gaining in value as a counterpoint to AI-generated output. Resources:AI and the future of everything: a long-term perspectiveAnthropic: why we are backing the AI frontrunnerLong Term Global Growth Strategy (institutional investors only)LTGG philosophy and process (institutional investors only)Private companies: from Anthropic to ZetwerkShort Briefings on Long Term Thinking hub Companies mentioned include:Alphabet/GoogleAmazonAnthropicAppLovinHorizon RoboticsNVIDIARedditRobloxTesla  Timecodes:00:00  Introduction – Dartmouth College's artificial intelligence workshop01:50   From quantum to AI via asset management02:50  Creating and then culling a machine-learning initiative08:05  ChatGPT's wake-up call10:35   Exceptional companies at the dawn of generative AI12:10   Anthropic's appeal to business customers14:55   A winner-takes-all opportunity?17:05   Dario Amodei and the scaling laws19:10   NVIDIA's foundational role in neural networks22:55  Making video game items in Roblox with AI25:00  AppLovin – a company built for the next era26:55  Reddit's valuable conversational communities29:35  World models, spatial AI and the physical world32:35  Staying open-minded and humble33:35  Book choice  Glossary of terms (in order of mention): Generative AI: AI systems that create new content such as text, images or code rather than just analysing data.Machine learning: AI techniques where systems learn patterns from data rather than being explicitly programmed.End-to-end, systematic (investment strategy): Fully automated, with decisions made by predefined rules rather than human judgement.Agentic AI: AI systems that can plan and carry out tasks autonomously rather than just responding to prompts.R&D: Research and development.GPT: OpenAI's models, which power its ChatGPT chatbot.Natural language processing: AI that enables computers to understand and generate human language.Token: A chunk of text, such as a word or part of a word, used by language models.Foundation models: Large AI models that can handle a wide variety of tasks.Know your customer (KYC): Financial checks used by banks to verify customers' identities and risks.Scaling laws: The idea that AI performance improves predictably as models, data and computing power increase.Compute: The processing power required to train and run AI models.Jevons' paradox: The counterintuitive idea that efficiency gains can increase, rather than reduce, overall usage.CUDA: NVIDIA's software platform for programming its chips for high-performance computing.Jensen: Jensen Huang, NVIDIA's co-founder and chief executive.Metaverse: Shared virtual worlds where people interact, create and play online.Large language models (LLMs): AI systems trained on vast amounts of text to understand and generate language.Multimodal models: AI systems that can process multiple types of data, such as text, images and video.World models: AI systems that learn how the physical world works in order to predict and simulate it.Embodied AI: AI that learns through physical interaction with the real world, such as robots or vehicles.Imitation learning: Training AI by having it copy actions demonstrated by humans.

Send us a textIn this episode, we sit down with designer Josh Jevons to discuss what it actually looks like to build a sustainable creative career without burning out, cold-pitching nonstop, or doing everything yourself.We also get into real-world outreach strategies, including walking trade shows, pitching without being salesy, and why face-to-face connections still matter. Along the way, we talk packaging, brand strategy, work-life balance, and designing systems that allow you to grow without burning out.If you're a designer who wants better clients, better collaboration, and a career that supports your life–not the other way around–this one's for you.All that and more when you listen to this episode:Making the shift from agency work to independent freelancingWhy complementary skill sets matter more than hiring “another you”Building a flexible, collaborative, creative teamThe role of brand strategy in effective (not just beautiful) designPricing, budgets, and scaling process without cutting value What designers don't learn in school, but learn fast on the jobOutreach strategies that actually feel humanHow to talk to potential clients without feeling awkward or salesyConnect with Joshua JevonsWebsite: https://www.jevonsdesign.com/ Instagram: https://www.instagram.com/joshuajevons_design/ Yeah Brother's Instagram: https://www.instagram.com/yeahbrother.co/ Mentioned in this episode:Rochester Institute of Technology https://www.rit.edu/ Yeah Brother https://yeahbrother.co/ Adobe MAX https://www.adobe.com/max.html AIGA https://www.aiga.org/ Connect with Katie & Ilana from Goodtype Goodtype Website Goodtype on Instagram Goodtype on Youtube Love The Typecast and free stuff? Leave a review, and send a screenshot of it to us on Slack. Each month we pick a random reviewer to win a Goodtype Goodie! Goodies include merch, courses and Kernference tickets! Leave us a review on Apple PodcastsSubscribe to the showTag us on Instagram @GoodtypeFollow us on Tiktok @lovegoodtypeLearn from Katie and IlanaGrab your tea, coffee, or drink of choice, kick back, and let's get down to business!

Why does adding more lanes to a highway actually make traffic jams get even worse? How did the machine meant to end slavery accidentally make it ten times more profitable? Why did the invention of the ATM lead to more bank tellers instead of replacing them? Is your "eco-friendly" car actually causing you to burn more fuel than your old one? Why does being the most efficient worker in the office always result in being given more work? ... we explain like I'm five Thank you to the r/explainlikeimfive community and in particular the following users whose questions and comments formed the basis of this discussion: environmental_bus507, sharp_simple_2764, zem, m1ss1ontomars2k4, nowhereman136 and mammoth-mud-9609 To the ELI5 community that has supported us so far, thanks for all your feedback and comments. Join us on Twitter: https://www.twitter.com/eli5ThePodcast/ or send us an e-mail: ELI5ThePodcast@gmail.com

Time for the annual predictions episode! Bryan and Adam were joined by frequent future-ologists Simon Willison, Steve Klabnik, and Ian Grunert to review past predictions and peer into the future. If any of these predictions come to fruition, it's going to be an interest 1, 3, or 6 years!In addition to Bryan Cantrill and Adam Leventhal, speakers included Simon Willison, Steve Klabnik, and Ian Grunert.Previously on Oxide and Friends:OxF s04e02 – Open Source LLMs with Simon WillisonOxF s02e23 – Predictions 2022OxF s03e20 – Predictions 2023!OxF s04e01 – Predictions 2024!OxF s05e01 – Predictions 2025Predictions during the show:Adam1 year: AI companies go on an acquisition binge (especially for anything that smells like data)3 year: Crisis of AI slop open source (both projects and contributions)6 year: Jensen hands over the reins at Nvidia6 year: Tesla is out of the consumer car business6 year: With the iPhone market shrinking, Apple has several new attempts at the next potential flagship productBryan1 year: "Vibe coding" is out of the lexicon -- or used strictly pejoratively it becomes a named condition (for which Adam -- in an act of nomenclature genius rivaling The Leventhal Conundrum -- suggested "Deep Blue")1 year: A frontier model company has a prominent whitepaper making the case that AI will lead to broad-based prosperity rather than job loss1 year: Harvey.ai becomes the pets.com of the AI boom -- and a harbinger of the coming bust (which becomes known as a Correction-like euphemism)1 year: A prominent S1 has revalations of economic behavior that has an effect beyond the company's IPO3 year: Frontier models treat AGI as "already done" -- and ASI as a non-goal3 year: Custom-written software thrives in lieu of SaaS6 year: DSM adds LLMs as a substance that can induce psychosis6 year: $NVDA not beyond its November 2025 peakSimon1 year: The AI for programming holdouts are going to have a nasty shock1 year: We're going to solve sandboxing1 year: Our own challenger disaster with respect to coding agent security - see the Normalization of Deviance in AI by Johann Rehberger3 year: Something that seems impossible for a coding agent to build today - like a full working web browser - won't just be built by coding agents, it will be unsurprising3 year: We will find out if the Jevons paradox saves our careers as software engineers or not6 year: The number of people employed to type code into computers will drop to almost nothing - it will be like punch card operators. Those of us who write code today will have very different jobs that still build software and take advantage of our previous coding experience.Steve1 year: Agent Orchestration will still be a hot topic. It'll be partially, but not entirely, solved. Updated with some more rigour: We won't have a "kubernetes for agents" just yet.3 year: Using AI tools when writing software professionally will be considered something closer to using autocomplete or syntax highlighting than something controversial or exceptional.6 year: AI will not have caused the total collapse of our economic and governmental systems.If we got something wrong or missed something, please file a PR! Our next show will likely be on Monday at 5p Pacific Time on our Discord server; stay tuned to our Mastodon feeds for details, or subscribe to this calendar. We'd love to have you join us, as we always love to hear from new speakers

Topics covered in this episode: Has the cost of building software just dropped 90%? More on Deprecation Warnings How FOSS Won and Why It Matters Should I be looking for a GitHub alternative? Extras Joke Watch on YouTube About the show Sponsored by us! Support our work through: Our courses at Talk Python Training The Complete pytest Course Patreon Supporters Connect with the hosts Michael: @mkennedy@fosstodon.org / @mkennedy.codes (bsky) Brian: @brianokken@fosstodon.org / @brianokken.bsky.social Show: @pythonbytes@fosstodon.org / @pythonbytes.fm (bsky) Join us on YouTube at pythonbytes.fm/live to be part of the audience. Usually Monday at 10am PT. Older video versions available there too. Finally, if you want an artisanal, hand-crafted digest of every week of the show notes in email form? Add your name and email to our friends of the show list, we'll never share it. HEADS UP: We are taking next week off, happy holiday everyone. Michael #1: Has the cost of building software just dropped 90%? by Martin Alderson Agentic coding tools are collapsing “implementation time,” so the cost curve of shipping software may be shifting sharply Recent programming advancements haven't been that great of a true benefit: Cloud, TDD, microservices, complex frontends, Kubernetes, etc. Agentic AI's big savings are not just code generation, but coordination overhead reduction (fewer handoffs, fewer meetings, fewer blocks). Thinking, product clarity, and domain decisions stay hard, while typing and scaffolding get cheap. Is it the end of software dev? Not really, see Jevons paradox: when production gets cheaper, total demand can rise rather than spending simply falling. (Historically: the efficiency of coal use led to the increased consumption of coal) Pushes back on “only good for greenfield” by arguing agents also help with legacy code comprehension and bug-fixing. I 100% agree. #Legacy code for the win. Brian #2: More on Deprecation Warnings How are people ignoring them? yep, it's right in the Python docs: -W ignore::DeprecationWarning Don't do that! Perhaps the docs should give the example of emitting them only once -W once::::DeprecationWarning See also -X dev mode , which sets -W default and some other runtime checks Don't use warn, use the @warnings.deprecated decorator instead Thanks John Hagen for pointing this out Emits a warning It's understood by type checkers, so editors visually warn you You can pass in your own custom UserWarning with category mypy also has a command line option and setting for this --enable-error-code deprecated or in [tool.mypy] enable_error_code = ["deprecated"] My recommendation Use @deprecated with your own custom warning and test with pytest -W error Michael #3: How FOSS Won and Why It Matters by Thomas Depierre Companies are not cheap, companies optimize cost control. They do this by making purchasing slow and painful. FOSS is/was a major unlock hack to skip procurement, legal, etc. Example is months to start using a paid “Add to calendar” widget! It “works both ways”: the same bypass lowers the barrier for maintainers too, no need for a legal entity, lawyers, liability insurance, or sales motion. Proposals that “fix FOSS” by reintroducing supply-chain style controls (he name-checks SBOMs and mandated processes) risk being rejected or gamed, because they restore the very friction FOSS sidesteps. Brian #4: Should I be looking for a GitHub alternative? Pricing changes for GitHub Actions The self-hosted runner pricing change caused a kerfuffle. It's has been postponed But… if you were to look around, maybe pay attention to These 4 GitHub alternatives are just as good—or better Codeburg, BitBucket, GitLab, Gitea And a new-ish entry, Tangled Extras Brian: End of year sale for The Complete pytest Course Use code XMAS2025 for 50% off before Dec 31 Writing work on Lean TDD book on hold for holidays Will pick up again in January Michael: PyCharm has better Ruff support now out of the box, via Daniel Molnar This is from the release notes of 2025.3: "PyCharm 2025.3 expands its LSP integration with support for Ruff, ty, Pyright, and Pyrefly.” If you check out the LSP section it will land you on this page and you can go to Ruff. The Ruff doc site was also updated. Previously it was only available external tools and a third party plugin, this feels like a big step. Fun quote I saw on ExTwitter: May your bug tracker be forever empty. Joke: Try/Catch/Stack Overflow Create a super annoying linkedin profile - From Tim Kellogg, submitted by archtoad

Should you fire all your engineers and replace them with AI? That's what Squirrel pitches to Gene Kim, our guest, when he returns for the second of a three part series exploring the themes of his new book Vibe Coding. Tune in to discover how you can transform your organisation with Vibe Coding and the power of AI assistance. - Vibe Coding book: https://itrevolution.com/product/vibe-coding-book/ - Dr. Pal: https://www.linkedin.com/in/tapabratapal - Jevon's Paradox: https://en.wikipedia.org/wiki/Jevons_paradox - Reinertsen, Principles of Product Development Flow: http://lpd2.com/ - DORA report 2025: https://dora.dev/research/2025/dora-report/ - MIT beer game: https://en.wikipedia.org/wiki/Beer_distribution_game -------------------------------------------------- You'll find free videos and practice material, plus our book Agile Conversations, at agileconversations.com And we'd love to hear any thoughts, ideas, or feedback you have about the show: email us at info@agileconversations.com -------------------------------------------------- About Your Hosts Douglas Squirrel and Jeffrey Fredrick joined forces at TIM Group in 2013, where they studied and practised the art of management through difficult conversations. Over a decade later, they remain united in their passion for growing profitable organisations through better communication. Squirrel is an advisor, author, keynote speaker, coach, and consultant, and he's helped over 300 companies of all sizes make huge, profitable improvements in their culture, skills, and processes. You can find out more about his work here: douglassquirrel.com/index.html Jeffrey is Vice President of Engineering at ION Analytics, Organiser at CITCON, the Continuous Integration and Testing Conference, and is an accomplished author and speaker. You can connect with him here: www.linkedin.com/in/jfredrick/

Dylan Field is co-founder and CEO of Figma, a beloved tool used by every modern product team. Founded in 2012, Figma has expanded from a single design tool to a comprehensive platform including FigJam, Slides, Dev Mode, and, most recently, Figma Make. After a $20 billion acquisition by Adobe fell through due to regulatory pushback, Dylan led the company to a successful IPO in 2025.What you'll learn:• How Dylan kept internal morale up after the Adobe acquisition fell through• His approach to maintaining pace and a sense of urgency 13 years in• How to systematically develop taste• How Figma decides which product lines to add• Why Dylan obsesses over “time to value”• How AI is making design more valuable—Brought to you by:Stripe—Helping companies of all sizes grow revenue—Transcript: ⁠https://www.lennysnewsletter.com/p/why-ai-makes-design-craft-and-quality-the-new-moat⁠—My biggest takeaways (for paid newsletter subscribers): ⁠https://www.lennysnewsletter.com/i/175569466/my-biggest-takeaways-from-this-conversation⁠—Where to find Dylan Field:• X: https://x.com/zoink• LinkedIn: https://www.linkedin.com/in/dylanfield/—Where to find Lenny:• Newsletter: https://www.lennysnewsletter.com• X: https://twitter.com/lennysan• LinkedIn: https://www.linkedin.com/in/lennyrachitsky/—In this episode, we cover:(00:00) Introduction to Dylan Field(03:58) The Adobe deal fallout(05:50) Maintaining team morale post-deal(09:13) Strategies for sustaining high performance(13:37) Maintaining Figma's unique company culture(16:22) Dylan's leadership evolution(21:03) How to improve clarity as a leader(24:40) The controversy behind FigJam(31:06) Lessons from expanding Figma's core product line(39:32) Time-to-value(45:14) Introduction to Figma Make(48:26) AI app prototyping and the future of Figma Make(53:38) Lessons from Figma's AI product launch(57:47) The importance of craft(59:54) Developing good taste(01:05:35) The future of product development(01:10:32) Why AI won't steal your job(01:14:37) AI corner(01:18:32) Lightning round and final thoughts—Referenced:• Dylan Field live at Config: Intuition, simplicity, and the future of design: https://www.lennysnewsletter.com/p/dylan-field-live-at-config• Figma: https://www.figma.com/• Adobe: https://www.adobe.com/• Vision, conviction, and hype: How to build 0 to 1 inside a company | Mihika Kapoor (Product at Figma): https://www.lennysnewsletter.com/p/vision-conviction-hype-mihika-kapoor• Notion's lost years, its near collapse during Covid, staying small to move fast, the joy and suffering of building horizontal, more | Ivan Zhao (CEO and co-founder): https://www.lennysnewsletter.com/p/inside-notion-ivan-zhao• $46B of hard truths from Ben Horowitz: Why founders fail and why you need to run toward fear (a16z co-founder): https://www.lennysnewsletter.com/p/46b-of-hard-truths-from-ben-horowitz• FigJam: https://www.figma.com/figjam/• Cursor chat: https://help.figma.com/hc/en-us/articles/4403130802199-Use-cursor-chat-in-Figma-Design• Figma Slides: https://www.figma.com/slides/• Figma Sites: https://www.figma.com/sites/• Figma Buzz: https://www.figma.com/buzz/• Figma Draw: https://www.figma.com/draw/• Figma Design: https://www.figma.com/design/• Dev Mode: https://www.figma.com/dev-mode/• Figma Make: https://www.figma.com/make/• Zach Lloyd on X: https://x.com/zachlloydtweets• Warp: https://www.warp.dev/• Dylan's post on X about Figma on an AI product leaderboard: https://x.com/zoink/status/1968588014935801884• Kurt Cobain: https://en.wikipedia.org/wiki/Kurt_Cobain• Damien Correll on LinkedIn: https://www.linkedin.com/in/damiencorrell/• Marcin Wichary on LinkedIn: https://www.linkedin.com/in/mwichary/• Loredana Crisan on LinkedIn: https://www.linkedin.com/in/loredanacrisan/• Amber Bravo on LinkedIn: https://www.linkedin.com/in/amberbravo/• Figma's 2025 AI report: Perspectives from designers and developers: https://www.figma.com/blog/figma-2025-ai-report-perspectives/• Jevons paradox: https://en.wikipedia.org/wiki/Jevons_paradox#Energy_conservation_policy• AI prompt engineering in 2025: What works and what doesn't | Sander Schulhoff (Learn Prompting, HackAPrompt): https://www.lennysnewsletter.com/p/ai-prompt-engineering-in-2025-sander-schulhoff• Pantheon: https://www.imdb.com/title/tt11680642/• Retro: https://retro.app/• Thiel Fellowship: https://thielfellowship.org/—Recommended books:• Understanding Comics: The Invisible Art: https://www.amazon.com/Understanding-Comics-Invisible-Scott-McCloud/dp/006097625X• The Spy and the Traitor: The Greatest Espionage Story of the Cold War: https://www.amazon.com/Spy-Traitor-Greatest-Espionage-Story/dp/1101904216• Codex Seraphinianus: https://www.amazon.com/Codex-Seraphinianus-Anniversary-Luigi-Serafini/dp/0847871045Production and marketing by https://penname.co/. For inquiries about sponsoring the podcast, email podcast@lennyrachitsky.com.—Lenny may be an investor in the companies discussed.My biggest takeaways from this conversation: To hear more, visit www.lennysnewsletter.com

https://a16z.com/the-techno-optimist-manifesto/ " Techno-optimism is the belief that rapid technological progress is the main driver of human prosperity and should be pursued as a moral imperative. It argues that: Growth = Good: Innovation creates abundance, longer lives, and better living standards. Barriers = Bad: Regulation, caution, and pessimism slow down progress and should be resisted. Technology as Solution: Challenges like poverty, disease, and climate change are best solved by accelerating science and technology rather than restricting them. In short: Techno-optimism sees faster innovation as the surest path to human flourishing — and treats resistance to technological progress as harmful. " Here's a structured overview of the major schools of economic thought, mapped across time, followed by an estimate of which views dominate public and policy thinking today.

Abi Noda from DX is back to share some cold, hard data on just how productive AI coding tools are actually making developers. Teaser: the productivity increase isn't as high as we expected. We also discuss Jevons paradox, AI agents as extensions of humans, which tools are winning in the enterprise, how development budgets are changing, and more.

With so many great reader emails recently Jeffrey and I haven't got around to discussing CitCon on the podcast yet! This week we do just that, with Jeffrey's reflections from discussions on the evolving role of AI in coding including Steve Yegge's new article which revisits whether the ‘death' of the junior developer will ultimately be a ‘revenge.' Links: - Steve Yegge article: https://sourcegraph.com/blog/revenge-of-the-junior-developer - Jevon's Paradox: https://en.wikipedia.org/wiki/Jevons_paradox -------------------------------------------------- You'll find free videos and practice material, plus our book Agile Conversations, at agileconversations.com And we'd love to hear any thoughts, ideas, or feedback you have about the show: email us at info@agileconversations.com -------------------------------------------------- About Your Hosts Douglas Squirrel and Jeffrey Fredrick joined forces at TIM Group in 2013, where they studied and practised the art of management through difficult conversations. Over a decade later, they remain united in their passion for growing profitable organisations through better communication. Squirrel is an advisor, author, keynote speaker, coach, and consultant, and he's helped over 300 companies of all sizes make huge, profitable improvements in their culture, skills, and processes. You can find out more about his work here: douglassquirrel.com/index.html Jeffrey is Vice President of Engineering at ION Analytics, Organiser at CITCON, the Continuous Integration and Testing Conference, and is an accomplished author and speaker. You can connect with him here: www.linkedin.com/in/jfredrick/

durée : 00:59:24 - Entendez-vous l'éco ? - par : Aliette Hovine, Bruno Baradat - W.S. Jevons est un économiste anglais de l'époque victorienne, connu pour avoir établi le concept d'utilité marginale et la théorie économique qui en découle. Il a également marqué la littérature par ses travaux précurseurs sur les conséquences de l'épuisement des ressources fossiles en Angleterre. - réalisation : Françoise Le Floch - invités : Antoine Missemer Economiste, chargé de recherche CNRS, membre du Centre International de Recherche sur l'Environnement et le Développement (CIRED); Nicolas Chaigneau Professeur d'économie à l'Université Lumière Lyon II

Scott Wu is the co-founder and CEO of Cognition, the company behind Devin—the world's first autonomous AI software engineer. Unlike other AI coding tools, Devin works like an autonomous engineer that you can interact with through Slack, Linear, and GitHub, just like with a remote engineer. With Scott's background in competitive programming and a previous AI-powered startup, Lunchclub, teaching AI to code has become his ultimate passion.What you'll learn:1. How a team of “Devins” are already producing 25% of Cognition's pull requests, and they are on track to hit 50% by year's end2. How each engineer on Cognition's 15-person engineering team works with about five Devins each3. How Devin has evolved from a “high school CS student” to a “junior engineer” over the past year4. Why engineering will shift from “bricklayers” to “architects”5. Why AI tools will lead to more engineering jobs rather than fewer6. How Devin creates its own wiki to understand and document complex codebases7. The eight pivots Cognition went through before landing on their current approach8. The cultural shifts required to successfully adopt AI engineers—Brought to you by:Enterpret—Transform customer feedback into product growthParagon—Ship every SaaS integration your customers wantAttio—The powerful, flexible CRM for fast-growing startups—Where to find Scott Wu:• X: https://x.com/scottwu46• LinkedIn: https://www.linkedin.com/in/scott-wu-8b94ab96/—Where to find Lenny:• Newsletter: https://www.lennysnewsletter.com• X: https://twitter.com/lennysan• LinkedIn: https://www.linkedin.com/in/lennyrachitsky/—In this episode, we cover:(00:00) Introduction to Scott Wu and Devin(09:13) Scaling and future prospects(10:23) Devin's origin story(17:26) The idea of Devin as a person(22:19) How a team of “Devins” are already producing 25% of Cognition's pull requests(25:17) Important skills in the AI era(30:21) How Cognition's engineering team works with Devin's(34:37) Live demo(42:20) Devin's codebase integration(44:50) Automation with Linear(46:53) What Devin does best(52:56) The future of AI in software engineering(57:13) Moats and stickiness in AI(01:01:57) The tech that enables Devin(01:04:14) AI will be the biggest technology shift of our lives(01:07:25) Adopting Devin in your company(01:15:13) Startup wisdom and hiring practices(01:22:32) Lightning round and final thoughts—Referenced:• Devin: https://devin.ai/• GitHub: https://github.com/• Linear: https://linear.app/• Waymo: https://waymo.com/• GitHub Copilot: https://github.com/features/copilot• Cursor: https://www.cursor.com/• Anysphere: https://anysphere.inc/• Bolt: https://bolt.new/• StackBlitz: https://stackblitz.com/• Cognition: https://cognition.ai/• v0: https://v0.dev/• Vercel: https://vercel.com/• Everyone's an engineer now: Inside v0's mission to create a hundred million builders | Guillermo Rauch (founder and CEO of Vercel, creators of v0 and Next.js): https://www.lennysnewsletter.com/p/everyones-an-engineer-now-guillermo-rauch• Inside Bolt: From near-death to ~$40m ARR in 5 months—one of the fastest-growing products in history | Eric Simons (founder and CEO of StackBlitz): https://www.lennysnewsletter.com/p/inside-bolt-eric-simons• Assembly: https://en.wikipedia.org/wiki/Assembly_language• Pascal: https://en.wikipedia.org/wiki/Pascal_(programming_language)• Python: https://www.python.org/• Jevons paradox: https://en.wikipedia.org/wiki/Jevons_paradox• Datadog: https://www.datadoghq.com/• Bending the universe in your favor | Claire Vo (LaunchDarkly, Color, Optimizely, ChatPRD): https://www.lennysnewsletter.com/p/bending-the-universe-in-your-favor• OpenAI's CPO on how AI changes must-have skills, moats, coding, startup playbooks, more | Kevin Weil (CPO at OpenAI, ex-Instagram, Twitter): https://www.lennysnewsletter.com/p/kevin-weil-open-ai• Behind the product: Replit | Amjad Masad (co-founder and CEO): https://www.lennysnewsletter.com/p/behind-the-product-replit-amjad-masad• Windsurf: https://windsurf.com/• COBOL: https://en.wikipedia.org/wiki/COBOL• Fortran: https://en.wikipedia.org/wiki/Fortran• Magic the Gathering: https://magic.wizards.com/en• Aura frames: https://auraframes.com/• AirPods: https://www.apple.com/airpods/• Steven Hao on LinkedIn: https://www.linkedin.com/in/steven-hao-160b9638/• Walden Yan on LinkedIn: https://www.linkedin.com/in/waldenyan/—Recommended books:• How to Win Friends & Influence People: https://www.amazon.com/How-Win-Friends-Influence-People/dp/0671027034• The Power Law: Venture Capital and the Making of the New Future: https://www.amazon.com/Power-Law-Venture-Capital-Making/dp/052555999X• The Great Gatsby: https://www.amazon.com/Great-Gatsby-F-Scott-Fitzgerald/dp/0743273567—Production and marketing by https://penname.co/. For inquiries about sponsoring the podcast, email podcast@lennyrachitsky.com.—Lenny may be an investor in the companies discussed. Get full access to Lenny's Newsletter at www.lennysnewsletter.com/subscribe

Our Chief Fixed Income Strategist Vishy Tirupattur thinks that efficiency gains from Chinese AI startup DeepSeek may drive incremental demand for AI.----- Listener Survey -----Complete a short listener survey at http://www.morganstanley.com/podcast-survey and help us make the podcast even more valuable for you. For every survey completed, Morgan Stanley will donate $25 to the Feeding America® organization to support their important work.© 2025 Morgan Stanley. All Rights Reserved. CRC#4174856 02/2025----- Transcript -----Hi, I'm Michael Zezas, Global Head of Fixed Income research & Public Policy Strategy at Morgan Stanley. Before we get into today's episode … the team behind Thoughts on the Market wants your thoughts and your input. Fill out our listener survey and help us make this podcast even more valuable for you. The link is in the show notes, and you'll hear it at the end of the episode. Plus, help us help the Feeding America organization. For every survey completed, Morgan Stanley will donate $25 toward their important work.Thanks for your time and support. On to the show…Welcome to Thoughts on the Market. I'm Vishy Tirupattur, Morgan Stanley's Chief Fixed Income Strategist. Today I'll be talking about the macro implications of the DeepSeek development.It's Friday February 7th at 9 am, and I'm on the road in Riyadh, Saudi Arabia.Recently we learned that DeepSeek, a Chinese AI startup, has developed two open-source large language models – LLMs – that can perform at levels comparable to models from American counterparts at a substantially lower cost. This news set off shockwaves in the equity markets that wiped out nearly a trillion dollars in the market cap of listed US technology companies on January 27. While the market has recouped some of these losses, their magnitude raises questions for investors about AI. My equity research colleagues have addressed a range of stock-specific issues in their work. Today we step back and consider the broader implications for the economy in terms of productivity growth and investment spending on AI infrastructure.First thing. While this is an important milestone and a significant development in the evolution of LLMs, it doesn't come entirely as a shock. The history of computing is replete with examples of dramatic efficiency gains. The DeepSeek development is precisely that – a dramatic efficiency improvement which, in our view, drives incremental demand for AI. Rapid declines in the cost of computing during the 1990s provide a useful parallel to what we are seeing now. As Michael Gapen, our US chief economist, has noted, the investment boom during the 1990s was really driven by the pace at which firms replaced depreciated capital and a sharp and persistent decline in the price of computing capital relative to the price of output. If efficiency gains from DeepSeek reflect a similar phenomenon, we may be seeing early signs [that] the cost of AI capital is coming down – and coming down rapidly. In turn, that should support the outlook for business spending pertaining to AI.In the last few weeks, we have heard a lot of reference to the Jevons paradox – which really dates from 1865 – and it states that as technological advancements reduce the cost of using a resource, the overall demand for the resource increases, causing the total resource consumption to rise. In other words, cheaper and more ubiquitous technology will increase its consumption. This enables AI to transition from innovators to more generalized adoption and opens the door for faster LLM-enabled product innovation. That means wider and faster consumer and enterprise adoption. Over time, this should result in greater increases in productivity and faster realization of AI's transformational promise.From a micro perspective, our equity research colleagues, who are experts in covering stocks in these sectors, come to a very similar conclusion. They think it's unlikely that the DeepSeek development will meaningfully reduce CapEx related to AI infrastructure. From a macroeconomic perspective, there is a good case to be made for higher business spending related to AI, as well as productivity growth from AI.Obviously, it is still early days, and we will see leaders and laggards at the stock level. But the economy as a whole we think will emerge as a winner. DeepSeek illustrates the potential for efficiency gains, which in turn foster greater competition and drive wider adoption of AI. With that premise, we remain constructive on AI's transformational promise.Thanks for listening. If you enjoy the podcast, help us make it even more valuable to you. Share your feedback on the show at morganstanley.com/podcast-survey or head to the episode notes for the survey link.In the last few weeks… (Laughs) It's almost like the birds are waiting for me to start speaking.The proceeding content is informational only and based on information available when created. It is not an offer or a solicitation nor is it tax or legal advice. It does not consider your financial circumstances and objectives and may not be suitable for you.

Replit's new AI agent can turn a simple prompt into a working app straight from your phone. Is this the end of traditional software development, or are we entering a new phase where anyone can build? This episode examines AI powered coding, how low code tools change software creation, and what happens when intelligence becomes widely accessible. Brought to you by: KPMG – Go to ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠www.kpmg.us/ai⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ to learn more about how KPMG can help you drive value with our AI solutions. Vanta - Simplify compliance - ⁠⁠⁠⁠⁠⁠⁠https://vanta.com/nlw The Agent Readiness Audit from Superintelligent - Go to https://besuper.ai/ to request your company's agent readiness score. The AI Daily Brief helps you understand the most important news and discussions in AI. Subscribe to the podcast version of The AI Daily Brief wherever you listen: https://pod.link/1680633614 Subscribe to the newsletter: https://aidailybrief.beehiiv.com/ Join our Discord: https://bit.ly/aibreakdown

This week: The Trump administration offered a resignation deal to millions of federal employees. Felix Salmon, Emily Peck, and Elizabeth Spiers discuss why this plan seems like a bad idea – for everyone. Then, Invidia's stock dropped this week when Deepseek proved AI can be done cheaper. But is this just steam engines and Jevons paradox all over again? Finally, the bookstore is back. The hosts discuss the recent success of Barnes & Noble and why they, and other bookstores, are the unexpected winners of the digital media age.In the Slate Plus episode: CVS has a new way of locking up their stuff.Want to hear that discussion and hear more Slate Money? Join Slate Plus to unlock weekly bonus episodes. Plus, you'll access ad-free listening across all your favorite Slate podcasts. You can subscribe directly from the Slate Money show page on Apple Podcasts and Spotify. Or, visit slate.com/moneyplus to get access wherever you listen.Podcast production by Jessamine Molli. Hosted on Acast. See acast.com/privacy for more information.

This week: The Trump administration offered a resignation deal to millions of federal employees. Felix Salmon, Emily Peck, and Elizabeth Spiers discuss why this plan seems like a bad idea – for everyone. Then, Invidia's stock dropped this week when Deepseek proved AI can be done cheaper. But is this just steam engines and Jevons paradox all over again? Finally, the bookstore is back. The hosts discuss the recent success of Barnes & Noble and why they, and other bookstores, are the unexpected winners of the digital media age. In the Slate Plus episode: CVS has a new way of locking up their stuff. Want to hear that discussion and hear more Slate Money? Join Slate Plus to unlock weekly bonus episodes. Plus, you'll access ad-free listening across all your favorite Slate podcasts. You can subscribe directly from the Slate Money show page on Apple Podcasts and Spotify. Or, visit slate.com/moneyplus to get access wherever you listen. Podcast production by Jessamine Molli. Learn more about your ad choices. Visit megaphone.fm/adchoices

This week: The Trump administration offered a resignation deal to millions of federal employees. Felix Salmon, Emily Peck, and Elizabeth Spiers discuss why this plan seems like a bad idea – for everyone. Then, Invidia's stock dropped this week when Deepseek proved AI can be done cheaper. But is this just steam engines and Jevons paradox all over again? Finally, the bookstore is back. The hosts discuss the recent success of Barnes & Noble and why they, and other bookstores, are the unexpected winners of the digital media age.In the Slate Plus episode: CVS has a new way of locking up their stuff.Want to hear that discussion and hear more Slate Money? Join Slate Plus to unlock weekly bonus episodes. Plus, you'll access ad-free listening across all your favorite Slate podcasts. You can subscribe directly from the Slate Money show page on Apple Podcasts and Spotify. Or, visit slate.com/moneyplus to get access wherever you listen.Podcast production by Jessamine Molli. Hosted on Acast. See acast.com/privacy for more information.

This week: The Trump administration offered a resignation deal to millions of federal employees. Felix Salmon, Emily Peck, and Elizabeth Spiers discuss why this plan seems like a bad idea – for everyone. Then, Invidia's stock dropped this week when Deepseek proved AI can be done cheaper. But is this just steam engines and Jevons paradox all over again? Finally, the bookstore is back. The hosts discuss the recent success of Barnes & Noble and why they, and other bookstores, are the unexpected winners of the digital media age. In the Slate Plus episode: CVS has a new way of locking up their stuff. Want to hear that discussion and hear more Slate Money? Join Slate Plus to unlock weekly bonus episodes. Plus, you'll access ad-free listening across all your favorite Slate podcasts. You can subscribe directly from the Slate Money show page on Apple Podcasts and Spotify. Or, visit slate.com/moneyplus to get access wherever you listen. Podcast production by Jessamine Molli. Learn more about your ad choices. Visit megaphone.fm/adchoices

This week: The Trump administration offered a resignation deal to millions of federal employees. Felix Salmon, Emily Peck, and Elizabeth Spiers discuss why this plan seems like a bad idea – for everyone. Then, Invidia's stock dropped this week when Deepseek proved AI can be done cheaper. But is this just steam engines and Jevons paradox all over again? Finally, the bookstore is back. The hosts discuss the recent success of Barnes & Noble and why they, and other bookstores, are the unexpected winners of the digital media age.In the Slate Plus episode: CVS has a new way of locking up their stuff.Want to hear that discussion and hear more Slate Money? Join Slate Plus to unlock weekly bonus episodes. Plus, you'll access ad-free listening across all your favorite Slate podcasts. You can subscribe directly from the Slate Money show page on Apple Podcasts and Spotify. Or, visit slate.com/moneyplus to get access wherever you listen.Podcast production by Jessamine Molli. Hosted on Acast. See acast.com/privacy for more information.

This week: The Trump administration offered a resignation deal to millions of federal employees. Felix Salmon, Emily Peck, and Elizabeth Spiers discuss why this plan seems like a bad idea – for everyone. Then, Invidia's stock dropped this week when Deepseek proved AI can be done cheaper. But is this just steam engines and Jevons paradox all over again? Finally, the bookstore is back. The hosts discuss the recent success of Barnes & Noble and why they, and other bookstores, are the unexpected winners of the digital media age. In the Slate Plus episode: CVS has a new way of locking up their stuff. Want to hear that discussion and hear more Slate Money? Join Slate Plus to unlock weekly bonus episodes. Plus, you'll access ad-free listening across all your favorite Slate podcasts. You can subscribe directly from the Slate Money show page on Apple Podcasts and Spotify. Or, visit slate.com/moneyplus to get access wherever you listen. Podcast production by Jessamine Molli. Learn more about your ad choices. Visit megaphone.fm/adchoices

This week: The Trump administration offered a resignation deal to millions of federal employees. Felix Salmon, Emily Peck, and Elizabeth Spiers discuss why this plan seems like a bad idea – for everyone. Then, Invidia's stock dropped this week when Deepseek proved AI can be done cheaper. But is this just steam engines and Jevons paradox all over again? Finally, the bookstore is back. The hosts discuss the recent success of Barnes & Noble and why they, and other bookstores, are the unexpected winners of the digital media age. In the Slate Plus episode: CVS has a new way of locking up their stuff. Want to hear that discussion and hear more Slate Money? Join Slate Plus to unlock weekly bonus episodes. Plus, you'll access ad-free listening across all your favorite Slate podcasts. You can subscribe directly from the Slate Money show page on Apple Podcasts and Spotify. Or, visit slate.com/moneyplus to get access wherever you listen. Podcast production by Jessamine Molli. Learn more about your ad choices. Visit megaphone.fm/adchoices

(0:00) The Besties intro Travis Kalanick! (2:11) Travis breaks down the future of food and the state of CloudKitchens (13:34) Sacks breaks in! (15:38) DeepSeek panic: What's real, training innovation, China, impact on markets and the AI industry (50:14) US vs China in AI, the Singapore backdoor (1:01:51) OpenAI reportedly in talks to raise ~$40B with Masa as the lead investor (1:10:37) DOGE's first 10 days (1:25:13) Future of Self Driving: Uber, Waymo, Tesla (1:38:04) Fed holds rates steady, how DOGE can impact rate cuts (1:44:17) Fatal DC plane crash Follow Travis: https://x.com/travisk Follow the besties: https://x.com/chamath https://x.com/Jason https://x.com/DavidSacks https://x.com/friedberg Follow on X: https://x.com/theallinpod Follow on Instagram: https://www.instagram.com/theallinpod Follow on TikTok: https://www.tiktok.com/@theallinpod Follow on LinkedIn: https://www.linkedin.com/company/allinpod Intro Music Credit: https://rb.gy/tppkzl https://x.com/yung_spielburg Intro Video Credit: https://x.com/TheZachEffect Referenced in the show: https://github.com/deepseek-ai/DeepSeek-R1/blob/main/DeepSeek_R1.pdf https://www.tomshardware.com/tech-industry/artificial-intelligence/chinese-company-trained-gpt-4-rival-with-just-2-000-gpus-01-ai-spent-usd3m-compared-to-openais-usd80m-to-usd100m https://www.cnbc.com/2025/01/27/nvidia-sheds-almost-600-billion-in-market-cap-biggest-drop-ever.html https://x.com/shrihacker/status/1884414667503853749 https://x.com/balajis/status/1884975064283812270 https://www.fool.com/earnings/call-transcripts/2025/01/29/meta-platforms-meta-q4-2024 earnings-call-transcri https://x.com/mrexits/status/1885017400308806121 https://www.wsj.com/livecoverage/stock-market-today-dow-sp500-nasdaq-live-01-28-2025/card/deepseek-s-ai-learned-from-chatgpt-trump-s-ai-czar-says-LoCYvz2Lm0riS0AuEoB5 https://www.wsj.com/tech/ai/why-distillation-has-become-the-scariest-wordfor-ai-companies-aa146ae3 https://techcrunch.com/2024/12/27/why-deepseeks-new-ai-model-thinks-its-chatgpt https://x.com/rauchg/status/1875627666113740892 https://www.ft.com/content/a0dfedd1-5255-4fa9-8ccc-1fe01de87ea6 https://x.com/satyanadella/status/1883753899255046301 https://en.m.wikipedia.org/wiki/Jevons_paradox https://x.com/pitdesi/status/1883192498274873513 https://x.com/rihardjarc/status/1884263865703358726 https://x.com/austen/status/1884444298130674000 https://www.cnbc.com/2025/01/30/openai-in-talks-to-raise-up-to-40-billion-at-340-billion-valuation.html https://x.com/america/status/1884372526144598056 https://x.com/DOGE/status/1884396041786524032 https://fred.stlouisfed.org/series/FYFSD https://www.whitehouse.gov/presidential-actions/2025/01/establishing-and-implementing-the-presidents-department-of-government-efficiency https://x.com/Jason/status/1884671945800573018 https://abcnews.go.com/538/trump-starts-term-weak-approval-rating/story?id=118146633 https://www.cnbc.com/2025/01/15/cpi-inflation-december-2024-.html https://x.com/chamath/status/1885068981905875241

Ejaaz and David reunite to unpack the DeepSeek shockwave: how a mere $6M open-source AI model rattled OpenAI's dominance, nudged Nvidia's stock, and sparked a fresh “arms race” in crypto AI. Meanwhile, Trump's massive AI funding pledge and Solana's record DEX volumes signal that the space might be heading for its biggest bull run yet. On the builder side, ARC's rust-based agents partner with the Solana Foundation, AI16Z launches a $10M fund, and Virtuals teases multi-chain expansions that could redefine how agent tokens earn revenue. Between China's fast breakthroughs and America's big AI bets, the race to integrate AI and crypto has never been hotter. Buckle up, anon. ------

Today's show: A $6M open-source AI model from China, DeepSeek, sends shockwaves through Wall Street, wiping billions off NVIDIA's market cap and forcing a rethink on AI infrastructure spending. We explore the 25% surge in startup shutdowns, the lessons from leaner teams, and why some companies just couldn't make the runway. Plus, SailPoint returns to the public markets saddled with $1.6B in debt—what does this say about private equity's “buy, fix, and flip” strategy? Don't miss this deep dive into the latest tech and startup news! * Timestamps: (0:00) Jason and Alex kick off the show. (1:58) DeepSeek's market impact and Project Stargate (4:18) Innovation, H100 GPUs, and open-source AI models (8:41) Jevons paradox, Pat Gelsinger's analogy, and AI efficiency (10:03) Northwest Registered Agent. For just $39 plus state fees, Northwest will handle your complete business identity. Visit https://www.northwestregisteredagent.com/twist today. (13:25) AI's benefits for startups and privacy concerns (19:32) Squarespace. TWiST listeners: use code TWIST to save 10% off your first purchase of a website or domain: https://www.Squarespace.com/TWIST (19:51) AI optimization vs. hardware consumption (22:20) OpenAI's revenue, valuation, and NVIDIA's market value (30:13) LinkedIn Jobs. Post your first job for free at https://www.linkedin.com/twist (33:21) Unified AI digital assistants and DeepSeq's new model (35:01) AI's role in venture capital and team size reduction (41:04) China's influence and DeepSeek's market impact (43:22) Startup shutdowns and potential for increased M&A activity (53:02) Nvidia's historical analysis, risks of leverage, and SailPoint's IPO * Subscribe to the TWiST500 newsletter: https://ticker.thisweekinstartups.com Check out the TWIST500: https://www.twist500.com Subscribe to This Week in Startups on Apple: https://rb.gy/v19fcp * Follow Alex: X: https://x.com/alex LinkedIn: ⁠https://www.linkedin.com/in/alexwilhelm * Follow Jason: X: https://twitter.com/Jason LinkedIn: https://www.linkedin.com/in/jasoncalacanis * Thank you to our partners: (10:03) Northwest Registered Agent. For just $39 plus state fees, Northwest will handle your complete business identity. Visit https://www.northwestregisteredagent.com/twist today. (19:32) Squarespace. TWiST listeners: use code TWIST to save 10% off your first purchase of a website or domain: https://www.Squarespace.com/TWIST (30:13) LinkedIn Jobs. Post your first job for free at https://www.linkedin.com/twist * Great TWIST interviews: Will Guidara, Eoghan McCabe, Steve Huffman, Brian Chesky, Bob Moesta, Aaron Levie, Sophia Amoruso, Reid Hoffman, Frank Slootman, Billy McFarland * Check out Jason's suite of newsletters: https://substack.com/@calacanis * Follow TWiST: Twitter: https://twitter.com/TWiStartups YouTube: https://www.youtube.com/thisweekin Instagram: https://www.instagram.com/thisweekinstartups TikTok: https://www.tiktok.com/@thisweekinstartups Substack: https://twistartups.substack.com * Subscribe to the Founder University Podcast: https://www.youtube.com/@founderuniversity1916