Podcasts about knowledge work

On this episode of Christopher Lochhead: Follow Your Different, we welcome back Ray Wang, Chairman and CEO of Constellation Research, and widely regarded as one of the most insightful technology analysts in the world. In a recent conversation with Christopher Lochhead, Ray Wang shared his unfiltered perspective on the biggest developments shaping the technology landscape today. From the historic SpaceX IPO to the transformative acquisition of Cursor, Ray Wang offered sharp analysis that cuts through the noise and gets to what actually matters for businesses and investors navigating an AI-driven world. The conversation covered topics that most analysts are still catching up on, including why knowledge workers need to rethink their value, what Data Inc companies actually are, and why the context layer above large language models may be the most important competitive battleground of the next decade. What makes Ray Wang’s perspective so valuable is not just his breadth of knowledge but his ability to synthesize experience into wisdom, which is precisely the distinction he draws when talking about why AI cannot replace truly seasoned professionals. You're listening to Christopher Lochhead: Follow Your Different. We are the real dialogue podcast for people with a different mind. So get your mind in a different place, and hey ho, let's go.   Ray Wang on AI, Knowledge Work, and the Commoditization of Expertise Ray Wang makes a clear and compelling distinction between knowledge and wisdom. He argues that knowledge has become a commodity, but wisdom, the ability to take insights and turn them into meaningful action, remains deeply human and increasingly valuable. As AI automates deterministic, repetitive tasks, what rises in importance is judgment, the capacity to learn from failure and connect dots in ways that no model trained exclusively on successful outcomes can replicate. This reframing is critical for anyone worried about AI displacing their career. Ray Wang points out that AI systems today learn only from success, with no real failure database informing their outputs. That gap is where experienced professionals earn their keep. Businesses are increasingly paying for people who have lived through cycles of failure and recovery, not simply those who can recite information retrieved from a search index.   The SpaceX IPO and What Ray Wang Says It Means for the Future of Markets Ray Wang describes the SpaceX IPO as a completely new playbook, one that flipped conventional wisdom about how public offerings should be structured. Rather than allocating the vast majority of shares to institutional investors through a traditional roadshow, SpaceX directed somewhere between 20 and 30 percent of the offering toward retail investors. Ray Wang sees this as Elon Musk rewarding the individual investors who stayed loyal through years of volatility, particularly the Tesla shareholders who held on despite relentless short-selling pressure. Beyond the allocation strategy, Ray Wang highlights how Musk essentially told the markets to take it or leave it at a fixed price, bypassing the typical price-discovery process. The Nasdaq inclusion guaranteed a floor without needing the traditional green shoe option to do the heavy lifting. Ray Wang believes this model could influence how future high-profile tech companies, including OpenAI and Anthropic, approach their own public offerings, fundamentally shifting leverage away from Wall Street banks and toward founders and retail participants.   Ray Wang Explains Data Inc Companies and the Context Layer That Defines AI Competitive Advantage Ray Wang has been developing a framework he calls the Data Inc company, a concept centered on the idea that businesses that treat data as their primary asset, combined with strong distribution, will dominate the AI era. According to Ray Wang, unique data sets that no competitor can access or replicate are the foundation of next-generation competitive moats. Companies that fail to own their data and build derivative products from it will find themselves structurally disadvantaged as AI capabilities become more broadly available. Taking that framework one step further, Ray Wang agrees that the real battleground is not the large language model itself but the contextual layer that sits above it. This semantic and contextual wrapper, built from proprietary data and accumulated organizational knowledge, is what gives AI outputs meaning and reduces hallucinations. Swapping out one LLM for another becomes straightforward when this context layer is robust, much like swapping one database for another in a well-architected system. Ray Wang adds one more dimension that elevates the entire conversation: persistent memory. The ability for AI systems to retain learnings across interactions and pass that accumulated intelligence to downstream systems is, in his view, the true home run of enterprise AI. Decision velocity, powered by a rich contextual layer and persistent memory, is what separates companies that merely adopt AI from those that build genuine exponential advantage from it. To hear more from Ray Wang and his thoughts about the Future of Tech, download and listen to this episode.   Bio R “Ray” Wang (pronounced WAHNG) is the Founder, Chairman, and Principal Analyst of Silicon Valley based Constellation Research Inc. He co-hosts DisrupTV, a weekly enterprise tech and leadership webcast that averages 50,000 views per episode and authors a business strategy and technology blog that has received millions of page views per month.  Wang also serves as a non-resident Senior Fellow at The Atlantic Council's GeoTech Center. Since 2003, Ray has delivered thousands of live and virtual keynotes around the world that are inspiring and legendary. Wang has spoken at almost every major tech conference. His ground-breaking bestselling book on digital transformation, Disrupting Digital Business, was published by Harvard Business Review Press in 2015.  Ray's new book about Digital Giants and the future of business titled, Everybody Wants to Rule the World will be released July 2021 by Harper Collins Leadership. Ray Wang is well quoted and frequently interviewed in media outlets such as the Wall Street Journal, Fox Business News, CNBC, Yahoo Finance, Cheddar, CGTN America, Bloomberg, Tech Crunch, ZDNet, Forbes, and Fortune.  He is one of the top technology analysts in the world.   Links Follow Ray Wang! Website | Twitter | LinkedIn | Constellation Research | DisrupTV   We hope you enjoyed this episode of Christopher Lochhead: Follow Your Different™! Christopher loves hearing from his listeners. Feel free to email him, connect on Facebook, X (formerly Twitter), Instagram, and subscribe on Apple Podcast / Spotify!

How do you build AI that actually understands you and the work you do? It all starts with having the right context.  We talk with Dropbox staff product manager Noorain Noorani and principal engineer Sean-Michael Lewis about the art of context engineering and how Dropbox connects to all the tools your team needs for work—so you get AI that works wherever you do.  ~ ~ ~  Working Smarter is brought to you by Dropbox. Find, organize, and share your work—all in one place—with context-aware AI from Dropbox. You can listen to more episodes of Working Smarter on Apple Podcasts, Spotify, YouTube, Amazon Music, or wherever you get your podcasts. To read more stories and past interviews, visit workingsmarter.ai This show would not be possible without the talented team at Cosmic Standard: producer Ben Montoya, sound engineer Aja Simpson, technical director Jacob Winik, and executive producer Eliza Smith. Special thanks to our illustrator Fanny Luor, marketing consultant Meggan Ellingboe, and editorial support from Catie Keck. Our theme song was composed by Doug Stuart.  Working Smarter is hosted by Matthew Braga. Thanks for listening!

This episode explores the rapid evolution of AI and its impact on the job market, particularly for 20-somethings entering the workforce. AI experts Darius Mirshahzadeh of AIifyIt and Jerome Stewart of White Feather Group discuss how artificial intelligence is transforming knowledge work, creating new opportunities for those who adapt quickly while threatening traditional career paths. The conversation covers practical AI tools, automation platforms, and strategic advice for navigating the AI-driven economy. In this episode, Darius will discuss: (00:00) The AI Revolution: A New Era for Knowledge Workers (02:34) Chronological Evolution of AI: Past, Present, and Future (05:41) The Impact of AI on Knowledge Work and Job Security (08:52) Skills for the Future: Preparing for an AI-Driven Economy (11:27) Navigating the Job Market: Opportunities and Challenges for Young Professionals (14:44) The Role of Human Connection in an AI World (17:49) Becoming the Solution: Embracing AI Skills for Career Success (26:24) The Role of AI in Manual Tasks (28:27) The Future of Robotics and AI Integration (30:24) Reassessing Your Tech Stack (34:27) Getting Started with AI for Young Professionals (42:49 The Urgency of Adopting AI in Business Connect with Darius: Website: https://therealdarius.com/ Linkedin: https://www.linkedin.com/in/dariusmirshahzadeh/ Instagram: https://www.instagram.com/imthedarius/ YouTube: https://www.youtube.com/@Thegreatnessmachine  Book: The Core Value Equation https://www.amazon.com/Core-Value-Equation-Framework-Limitless/dp/1544506708 Write a review for The Greatness Machine using this link: https://ratethispodcast.com/spreadinggreatness.  Learn more about your ad choices. Visit megaphone.fm/adchoices

Artificial intelligence is changing how knowledge work gets done, and AI agents may be the next major leap. In this episode of Technoventure, Peter High speaks with Arpan Shah, General Partner at Spark Capital, about how AI is reshaping research, investing, software development, and enterprise productivity. Arpan shares how he uses AI agents to accelerate diligence, synthesize information, and expand his own capacity as an investor, while also exploring the future of AI infrastructure, model competition, security, and stablecoins. Key topics include: How AI agents are transforming knowledge work Why AI demand may outpace compute supply for years The evolution of token economics and enterprise AI adoption Security challenges created by increasingly capable AI systems How stablecoins could reshape global financial infrastructure

Ed Zitron, Scott Galloway und Gary Marcus warnen vor dem AI-Crash. Wie ernst muss man sie nehmen? ChatGPT knackt die Milliardenmarke an monatlichen Nutzern, OpenAI Codex meldet 5 Millionen Weekly Active Users mit sechsfachem Wachstum gegenüber Februar. WSJ enthüllt: Auf Sam Altmans Vorschlag erwägt die US-Regierung finanzielle Beteiligungen an den großen KI-Firmen. Anthropic erweitert sein Mythos-Programm auf 150 Organisationen weltweit. FT berichtet, dass die NSA Mythos jetzt offensiv für Hacking nutzt. Meta begrenzt sein Mitarbeiter-Überwachungstool nach Belegschafts-Backlash und launcht zeitgleich AI-Agents für WhatsApp Business. Google kauft heimlich Code von Play-Store-Entwicklern fürs AI-Training. Alibaba Qwen 3.7+ kommt multimodal zu einem Bruchteil der westlichen Preise. S&P 500 hält an Profitabilitätsregeln fest, keine Aufweichung für SpaceX. Morningstar bewertet SpaceX bei nur $780 Mrd., der Hälfte des IPO-Ziels. Alphabet erhöht seine Kapitalmaßnahme auf $85 Mrd., das größte Equity-Offering der Geschichte. Anthropic warnt vor Recursive Self-Improvement. Meta hat heimlich Gesichtserkennung in die Smart Glasses eingebaut. Peter Thiels Founders Fund startet ein YouTube-Format mit Tech-CEOs als Mafia-Spielern. Unterstütze unseren Podcast und entdecke die Angebote unserer Werbepartner auf ⁠⁠⁠⁠⁠⁠doppelgaenger.io/werbung⁠⁠⁠⁠⁠⁠. Vielen Dank!  Philipp Glöckler und Philipp Klöckner sprechen heute über: (00:00:00) AI-Bären-Debatte (00:34:54) ChatGPT 1 Mrd. Nutzer & Codex bei 5 Mio. WAU (00:44:16) US-Regierung will Stake an AI-Firmen (00:47:35) Anthropic dehnt Mythos Access aus (00:49:27) NSA nutzt Anthropic Mythos offensiv für Hacking (00:53:50) Meta limitiert Mitarbeiter-Tracking nach Backlash (00:56:16) Google kauft Play-Store-Code für AI-Training (01:00:40) Alibaba Qwen 3.7+ zum Spotpreis (01:02:07) SpaceX-IPO konkret: $135/Aktie, Trade Republic (01:05:56) S&P 500 bleibt hart, kein Frühzugang für SpaceX (01:08:53) Morningstar halbiert SpaceX auf $780 Mrd. (01:12:24) Alphabet raised $85 Mrd. (Rekord-Equity-Offering) (01:19:01) Anthropic Recursive Self-Improvement (01:24:43) Meta Smart Glasses mit heimlicher Gesichtserkennung (01:26:07) Mafia: The Game von Founders Fund Shownotes Ed Zitron Bloomberg Podcast - youtube.com Ed Zitron: Anthropics Profitability Swindle - wheresyoured.at Scott Galloway: 95% der KI-Investments ohne Return, 50-70% Korrektur in 24 Monaten - the-ai-corner.com ChatGPT-App knackt 1 Mrd. monatliche Nutzer in Rekordzeit - reuters.com OpenAI launcht Codex for Knowledge Work - openai.com US-Regierung diskutiert Beteiligungen an AI-Firmen - wsj.com Anthropic to expand Mythos access - ft.com Uber begrenzt Claude-Code-Nutzung, um Kosten zu sparen - bloomberg.com Snowflake-CIO: Layoffs als Druckmittel, damit Mitarbeiter KI nutzen - theinformation.com Metas AI-Agent für WhatsApp Business weltweit verfügbar - techcrunch.com Meta rollt Mitarbeiter-Tracking-Tool nach Belegschafts-Backlash zurück - theinformation.com US National Security Agency using Anthropic's Mythos for cyber attacks - ft.com Google kauft heimlich Code von Play-Store-Entwicklern fürs KI-Training - 404media.co Alibaba Qwen3.7+: Text, Video, Bilder ab $0,40-$1,60 pro Mio. Token - venturebeat.com SpaceX will $75 Mrd. im Rekord-IPO einsammeln - bloomberg.com Morningstar bewertet SpaceX bei $780 Mrd., nur die Hälfte des IPO-Ziels - reuters.com Wild Twist: SpaceX kommt doch nicht früh in den S&P 500 - marketwatch.com Sitecore übernimmt Scrunch für $225 Mio. - bloomberg.com Alphabet raised $85 Mrd. für AI: größtes Equity-Offering aller Zeiten - thenextweb.com GitLab cuttet 14% der Belegschaft für AI-Workload-Skalierung - techcrunch.com CrowdStrike Q1 2027 Earnings - cnbc.com Anthropic Institute: Recursive Self-Improvement - anthropic.com Anthropic fordert globale KI-Entwicklungspause wegen Self-Improvement-Risiko - wsj.com Meta-Smart-Glasses mit Gesichtserkennung und Nametag - wired.com Tech Celebrities Playing Mafia - newcomer.co

Modern work can be frustrating and chaotic—if you don't have the right tools. From context engineering to multimodal search, go behind the scenes and hear how Dropbox engineers are building AI that actually understands you, so you can focus on the work that matters most. If you're new to Working Smarter, we've travelled from the F1 track to the bottom of a lake, and heard real stories from chefs, doctors, lawyers, and founders about how AI is helping them do more of what they love about their jobs. But in our third season, we're talking to the people behind the tools—the engineers and product leaders building helpful, time-saving AI features into the Dropbox experience you already know and trust. You'll hear all about their work on agents, inference, security, and, of course, how the people building AI use AI themselves. ~ ~ ~  Working Smarter is brought to you by Dropbox. Find, organize, and share your work—all in one place—with context-aware AI from Dropbox. You can listen to more episodes of Working Smarter on Apple Podcasts, Spotify, YouTube, Amazon Music, or wherever you get your podcasts. To read more stories and past interviews, visit workingsmarter.ai This show would not be possible without the talented team at Cosmic Standard: producer Ben Montoya, sound engineer Aja Simpson, technical director Jacob Winik, and executive producer Eliza Smith. Special thanks to our illustrator Fanny Luor, marketing consultant Meggan Ellingboe, and editorial support from Catie Keck.  Our theme song was composed by Doug Stuart.  Working Smarter is hosted by Matthew Braga. Thanks for listening!

In this episode of the Crazy Wisdom Podcast, host Stewart Alsop sits down with returning guest Ekue Kpodar for their third conversation together, covering a wide range of topics at the intersection of technology, geopolitics, and the evolving information age. They dig into Ekue's unconventional setup of running local AI models across roughly 15 computers, the growing case for open source models over closed ones from companies like OpenAI and Anthropic, and how Chinese open source models may be positioned to outcompete Western alternatives on a global scale. The conversation also touches on vibe coding and the democratization of software development, the strategic use of small models for IoT and enterprise applications, the role of Israel and China as dominant players in the information age, and how smaller nations and even individuals may wield outsized power as AI continues to collapse the cost of knowledge work. You can find Ekue Kpodar on X @ekpodar and LinkedIn.Timestamps00:00 Stewart welcomes Ekue for their third episode, diving into vibe coding and AI-driven development changes.05:00 Ekue explains using Claude on Chrome to auto-reply on Skool, burning tokens through screenshots, and Playwright as a more efficient alternative.10:00 Stewart describes his Claude-dependent planning and coding agent system breaking after a model update, prompting him to build his own chatbot.15:00 Small models discussed as critical for IoT, defense, and privacy-focused enterprises building internal APIs instead of routing traffic to OpenAI.20:00 Open source versus closed source debated, with Chinese models gaining global traction while US foundational labs remain expensive and restrictive.25:00 SaaS apocalypse explored as AI commoditizes knowledge work, with Linux and Terraform cited as proof open source still generates wealth.30:00 OpenAI's sci-fi terminator fears explained as the reason they stayed closed source, ultimately handing China a strategic open source advantage.35:00 China's economic dumping strategy applied to AI, potentially displacing US model dominance globally the same way manufacturing was disrupted.40:00 Israel's signals intelligence dominance discussed alongside asymmetric warfare, drones defeating tanks, and information control replacing military muscle.45:00 Global information age rankings debated, Israel leading, US and China tied, France and Poland emerging as sovereign tech players.50:00 Qatar, NVIDIA, and Iran cited as proof that rare resources and technology matter more than population size in the 21st century power landscape.Key Insights1. Running local AI models on a network of affordable computers can be more cost-effective than relying entirely on third-party APIs. By using compressed or smaller open source models locally, developers can handle repetitive or lower-stakes tasks without burning through expensive tokens from providers like Anthropic or OpenAI.2. Small AI models are becoming increasingly important for IoT, defense applications, and companies that do not want to send sensitive data to external providers. Organizations can download open source models, run them on internal servers, and build proprietary APIs around them, creating something like an intranet of specialized small models.3. The value created by AI tools is being redistributed away from traditional SaaS companies toward foundational model providers and individual builders. People are canceling subscriptions to software they once paid hundreds per month for, because AI now allows a single person to build comparable tools themselves.4. Open source technology does not eliminate the ability to profit. Linux and Terraform are both open source yet made their creators wealthy. People will still pay for installation, setup, troubleshooting, and customization even when the underlying software is free.5. China is applying its longstanding manufacturing dumping strategy to artificial intelligence by releasing cheap open source models globally, which threatens to erode US dominance in AI the same way Chinese manufacturing undercut other countries for decades.6. In the information age, the size of a country or institution matters far less than its access to rare resources or advanced technology. Qatar, Israel, and NVIDIA each demonstrate that small populations or headcounts can wield enormous global negotiating power through concentrated technological or resource advantages.7. Asymmetric warfare is redefining military power, with inexpensive drones defeating tanks that cost millions to build. This shifts the advantage toward nations that excel at signals intelligence and information management rather than those with the largest conventional military forces.

Generative AI reprices knowledge work by turning tasks that once required costly outsourced labor into low-cost model-driven workflows, reshaping hiring, budgeting, and productivity across industries. That's the key take-away message of this episode of the Wise Decision Maker Show, which discusses how AI reprices knowledge work.This article forms the basis for this episode: https://disasteravoidanceexperts.com/ai-is-twenty-five-times-cheaper-the-number-that-reprices-knowledge-work/

Most organizations think they're doing AI. They've bought the licenses, rolled out the tools, and told the team to start using Copilot. But adding AI on top of a 40-year-old process isn't transformation. It's decoration. Andre Kaminski, Director of Advanced Technology Solutions at WorkSafeBC and author of "The AI-Native Software Development Lifecycle," joins Peter and Dave to talk about what it actually means to rebuild your delivery process around AI, not just bolt it on. They get into why optimizing code generation alone is the wrong focus, what the six phases of an AI-native SDLC look like in practice, and why the biggest challenge isn't the technology at all. It's the identity shift that comes with it. If your organization is asking "which AI tool should we use?" this episode will help you realize that's probably the wrong question.In this episode:Why AI-augmented and AI-native are very different thingsThe compounding learning effect and why early adopters are pulling further ahead every monthWhat prompt architecture actually means and why it matters more than codeHow to think about governance when prompts become your new source of truth Want to keep the conversation going? Drop us a line at feedback@definitelymaybeagile.com or find us at definitelymaybeagile.com. If this episode got you thinking, share it with someone who needs to hear it.

In this episode of Breaking into Cybersecurity, host Christophe sits down with Shan Kulkarni, a security leader focused on the intersection of AI, engineering, and human-centric security practices.They explore the massive shift currently happening in the industry as AI takes over traditional "knowledge work," forcing a move toward higher-level human intuition. Shan introduces the concept of **"Vibe Coding"** and discusses how outcome-driven requirements are changing the types of vulnerabilities we face.Key Discussion Points- The End of Knowledge Work? How AI is automating the repetitive analysis and coding tasks that used to define a career, and why intuition is the new premium skill.- AI in Security: Practical ways to use tools like Claude to automate leadership tasks and reclaim your time.- Vibe Coding & Security: What happens when software is generated based on "vibes" and outcomes rather than line-by-line coding?- Gamifying Vulnerability Fixes: Using scoreboards and competitive metrics to drive engineering engagement and faster remediation.- The Business Language of Security: Why translating technical risk into business value remains the biggest hurdle for security leaders.About the GuestShan Kulkarni is a security leader and strategist known for innovative approaches to automation and gamification. He has a deep background in software engineering, which informs his outcome-driven approach to security.Resources Mentioned- Claude AI (Anthropic)- Vibe Coding (Modern development concept)Connect with Us- Breaking Into Cybersecurity YouTube https://www.youtube.com/@BreakingIntoCybersecurity- Christophe Foulon on LinkedIn https://www.linkedin.com/in/christophefoulon/

What You'll Learn in This Episode:In this episode, Patrick Adams and Shayne Daughenbaugh break down the true meaning of GEMBA and why it's a foundational practice in Lean leadership.You'll learn how going to the “real place” helps leaders move beyond assumptions and understand what's actually happening in their processes. The conversation highlights why many leaders avoid the gemba. Often due to fear, ego, or lack of clarity. Also, how shifting to a mindset of curiosity, humility, and vulnerability can change everything.They also explore how to approach GEMBA in both manufacturing and knowledge work environments, emphasizing the importance of building trust, creating psychological safety, and following up on what you hear.If you've ever struggled to connect with your team, understand your processes, or drive meaningful improvement, this episode gives you a simple, practical way to start.Key Takeaways:GEMBA is about understanding reality—not relying on assumptionsLeaders should approach the gemba with curiosity, not judgmentTrust is built through consistency, follow-up, and psychological safetyStart small—pick one process, observe, listen, and learn before actingLinks: Lean Solutions SummitLean Solutions Website 

What if the biggest threat to your business isn't your competition, but your own reluctance to automate? In this solo episode of The Greatness Machine, Darius shares a raw, urgent wake-up call for entrepreneurs and business owners: AI isn't a technology problem, it's an operations problem. Drawing from his hands-on experience sitting in on live AI builds with his portfolio companies and his role as Chairman of the Board at AIIFYit.com, Darius breaks down what it actually means to "AI-ify" your company and why most businesses are getting it completely wrong. He walks through a real-world case study in the lending industry where a process that took an hour and required offshore employees was reduced to one to two minutes with no human involvement, and explains why that changes everything about cost structures, competitive pricing, and survival in the marketplace. In this episode, Darius will discuss: (00:00) AI: Operations, Not Technology (02:51) The Evolution of AI in Business (06:10) Automating Processes for Unlimited Capacity (09:03) Cultural Friction in AI Implementation (11:52) The Future of Knowledge Work (14:46) The Urgency of AI Adoption (18:10) Out-of-App AI: The Next Frontier Connect with Darius: Website: https://therealdarius.com/ Linkedin: https://www.linkedin.com/in/dariusmirshahzadeh/ Instagram: https://www.instagram.com/imthedarius/ YouTube: https://www.youtube.com/@Thegreatnessmachine  Book: The Core Value Equation https://www.amazon.com/Core-Value-Equation-Framework-Limitless/dp/1544506708 Write a review for The Greatness Machine using this link: https://ratethispodcast.com/spreadinggreatness.  Learn more about your ad choices. Visit megaphone.fm/adchoices

Most organizations think they have a capacity problem. They usually don't.What they have is a work-in-progress problem. And those two things call for very different solutions.In this episode, Peter Maddison and Dave Sharrock dig into one of the most persistent headaches in organizational management: capacity tracking. Why does the instinct to measure utilization backfire? Why does loading people up to 100% actually slow things down? And what should leaders be asking instead?The conversation covers the real cost of context switching, why that "nearly done" project is probably further away than it looks, and how AI is making all of this more urgent, not easier.Three things to take away from this episode:100% utilization is not a goal. It's a warning sign. The right question isn't "how much capacity do we have?" It's "how much work in progress can we actually sustain?AI accelerates your breaking points.If this conversation resonated, there's more where it came from. Peter Maddison and Dave Sharrock explore these kinds of organizational challenges every week on Definitely Maybe Agile - the podcast that gets into the real complexity of modern ways of working, without the buzzwords.Listen wherever you get your podcasts, or visit definitelymaybeagile.com to catch up on past episodes and reach out with your own questions.

On this episode of Christopher Lochhead: Follow Your Different, Christopher Lochhead moves over to the guest chair and answer our questions about AI, Creator Capitalists, and the future of work.  At the AI and Copilot Summit in San Diego, Christopher Lochhead had a conversation that resonated far beyond a typical business keynote. Speaking to hundreds of executives, he challenged the dominant narrative around artificial intelligence. Instead of focusing on fear, disruption, and job loss, he reframed AI as the greatest creative unlock in human history. His message was not about survival in an automated world, but about reinvention. At the heart of his perspective is a shift from knowledge work to creation. As AI makes both knowledge and execution increasingly accessible, the real question is no longer what we know or how efficiently we work. The question becomes what we choose to create and how we differentiate ourselves in a world flooded with sameness. You're listening to Christopher Lochhead: Follow Your Different. We are the real dialogue podcast for people with a different mind. So get your mind in a different place, and hey ho, let's go.   The End of Knowledge Work as We Know It For decades, careers were built on the idea that knowledge is power. Professionals were valued for what they knew and how effectively they could apply that knowledge. This model defined the rise of the knowledge worker, where expertise and execution were the foundation of economic value. AI is dismantling that foundation. With tools that can generate insights and execute tasks instantly, both knowledge and execution are becoming commoditized. As a result, roles centered on repeating known processes are rapidly losing relevance. This shift is not just technological. It is existential, forcing individuals and organizations to rethink what truly creates value in the modern economy.   From Fear to Opportunity in the Age of AI Much of the public conversation around AI is driven by fear, particularly the fear of job loss. Lochhead acknowledges these concerns but argues that they overshadow a more important truth. Every major technological leap has created entirely new categories of work, even as it disrupted old ones. AI is no different, but the pace is unprecedented. Instead of focusing solely on what might disappear, there is a need to explore what becomes possible. The real opportunity lies in recognizing that AI expands human capability. It enables individuals to build, experiment, and innovate at a scale that was previously unimaginable, opening doors for entirely new career paths.   The Rise of the Creator Capitalist In a world where execution is automated and knowledge is abundant, creation becomes the ultimate differentiator. Lochhead introduces the concept of the creator capitalist, someone who leverages their unique perspective, skills, and experiences to produce meaningful value. This is not about following passion alone, but about identifying one's distinct strengths and applying them in ways that matter. The creator capitalist mindset also reframes personal assets. Relationships, reputation, expertise, and financial resources become forms of capital that can be combined and amplified through AI. Those who learn to connect their individuality with scalable tools will define the future of work, while those who cling to outdated models risk being left behind.   Links Want to catch more episode of the AI Agent & Copilot Podcast? You can check them out here: Presented by Cloud Wars | AI Agent and Copilot Podcast | John Siefert LinkedIn | Cloud Wars LinkedIn   We hope you enjoyed this episode of Christopher Lochhead: Follow Your Different™! Christopher loves hearing from his listeners. Feel free to email him, connect on Facebook, X (formerly Twitter), Instagram, and subscribe on Apple Podcast / Spotify!

SECURE YOUR SPOT FOR THE AGENTIC AI COURSE: https://services.multiplai.ai/agentic-courseAre you already falling behind in the AI race—without even realizing it?AI isn't just evolving—it's accelerating at a pace that's rewriting how businesses operate, compete, and grow. The real shift isn't coming someday… it's already here.In this episode, you'll discover how today's most advanced AI tools are enabling individuals to build full-scale business systems from their phone—and why the real limitation is no longer the technology, but how effectively you use it.If you want to stay relevant, the solution is clear: learn how to think, build, and operate alongside AI—or risk being outpaced by those who do.In this session, you'll discover: How Anthropic is shipping AI updates at an unprecedented pace—and why it matters  What “AI psychosis” is and why even top experts feel they're falling behind  A real-world example of building a fully automated YouTube growth engine in days  The rise of autonomous AI agents that can execute business tasks end-to-end  Why humans—not AI—are now the biggest bottleneck  The 3 critical skills you need to succeed in the AI-driven future  What major shifts at OpenAI signal about where the market is heading  The growing impact of AI on jobs, hiring, and business structure  Why unconventional thinkers and skilled trades may dominate the future workforce  The emerging risks, opportunities, and ethical questions shaping AI adoptionAbout Leveraging AIThe Ultimate AI Course for Business People: https://multiplai.ai/ai-course/YouTube Full Episodes: https://www.youtube.com/@Multiplai_AI/Connect with Isar Meitis: https://www.linkedin.com/in/isarmeitis/ Join our Live Sessions, AI Hangouts and newsletter: https://services.multiplai.ai/eventsIf you've enjoyed or benefited from some of the insights of this episode, leave us a five-star review on your favorite podcast platform, and let us know what you learned, found helpful, or liked most about this show!

Spencer Penn, Co founder and CEO of LightSource, joins The Tech Trek for a sharp conversation on AI native procurement, agentic workflows, and what actually happens to knowledge work as automation gets better. This episode is worth your time because it moves past lazy takes about AI replacing jobs and gets into something more useful, how work changes, where human value holds, and why procurement may be more strategic than most companies treat it.This conversation starts with procurement, but it quickly expands into a bigger discussion about role design, change management, and the pace of AI adoption inside real companies. Spencer breaks down why some jobs get redesigned while others disappear, how AI can elevate overlooked functions, and what people should do right now if their company is behind.In this episodeWhy procurement is a strong fit for AI, especially where teams are buried in tedious process workThe difference between job automation and job eliminationSpencer's idea of role plasticity, and why it matters more than most AI debatesWhy procurement teams may become more valuable, not less, as AI improvesPractical ways professionals can start using AI before their company rolls out a formal strategyTimestamped highlights00:37 What LightSource does and why direct material sourcing is a high stakes AI use case01:51 Why procurement teams spend too much time on transactional work06:47 Which jobs get enhanced by AI, which ones get eliminated, and Spencer's framework for role plasticity13:44 What the next few years could look like for procurement professionals26:18 Where to start if your company has not adopted an AI native workflow yet30:07 How to learn more about LightSource and connect with Spencer“AI will not replace your job. Someone who knows how to use AI will.”A practical thread running through this episode is simple. Start using the tools now. Use foundation models for secondary work, reporting, summaries, and internal communication. Build familiarity before the workflow shift gets forced on you.If you are interested in AI, procurement, operations, supply chain, or the future of knowledge work, follow The Tech Trek for more conversations like this.

What happens when AI stops helping with work—and starts doing the work itself?This episode connects a set of developments that business leaders should not ignore. From Sequoia's thesis that AI is replacing services, not just software, to Anthropic's findings that AI adoption is still far behind AI capability, the message is clear: the bottleneck is no longer technology. It is implementation.The bigger takeaway is even more important. Google, Microsoft, and Anthropic all released capabilities this week that make autonomous, business-ready AI workflows far more practical than they were even a few months ago. For leaders, that means the window to experiment is still open—but it may not stay open for long.In this session, you'll discover:Why AI is increasingly targeting work itself rather than the software layer around itThe difference between intelligence work and judgment work, and why that matters for business leadersWhat Anthropic's Claude usage data reveals about the gap between AI capability and actual adoptionWhy friction—not technical limitations—is slowing AI transformation inside companiesHow Google's new Workspace CLI expands agent access across Gmail, Drive, Docs, Sheets, and moreWhat Microsoft Copilot Cowork could mean for enterprise automation inside Microsoft 365Why AI review systems will become essential as AI-generated output scales across functionsHow autonomous agent loops could reshape software, marketing, sales, customer service, and product developmentWhat recent layoffs at Meta and Atlassian suggest about the future of knowledge workThe legal battles emerging around AI, from copyright to legal advice to data privacyAbout Leveraging AI The Ultimate AI Course for Business People: https://multiplai.ai/ai-course/ YouTube Full Episodes: https://www.youtube.com/@Multiplai_AI/ Connect with Isar Meitis: https://www.linkedin.com/in/isarmeitis/ Join our Live Sessions, AI Hangouts and newsletter: https://services.multiplai.ai/events If you've enjoyed or benefited from some of the insights of this episode, leave us a five-star review on your favorite podcast platform, and let us know what you learned, found helpful, or liked most about this show!

Welcome to Exponential View, the show where I explore how exponential technologies such as AI are reshaping our future. I've been studying AI and exponential technologies at the frontier for over ten years. Each week, I share some of my analysis or speak with an expert guest to make light of a particular topic. To keep up with the Exponential transition, subscribe to this channel or to my newsletter: https://www.exponentialview.co/ ----- AI has become so embedded in how I work that I can no longer cleanly separate it from my thinking. That raises a question I find genuinely unsettling: is intensive AI use making me a sharper thinker, or quietly doing the opposite? In this episode I pull back the curtain on my full research and writing process — the custom tools, the friction points, and the places where I'm still not sure I've got it right. For Ezra Klein, having AI summarize material is a disaster for original thought. But my AI systems are designed to protect the cognitive work that has to stay human, while they handle everything else. Knowing where to draw that line turns out to be the hardest and most important question. I covered: 00:00 - Is AI worsening our thinking? 02:35 - Ezra Klein on AI and the death of original thought 04:02 - Cognitive offloading vs cognitive surrender 09:20 - Signal detection at scale 11:06 - Why I use several AI personas to scan for different insights 13:37 - AI tells me what NOT to think about 16:25 - The value of quietness 19:07 - Small notebooks, small ideas 20:01 - Writing reveals what you don't yet know 23:24 - The golden thread 25:20 - Speaking drafts aloud 28:05 - How I stress-test my arguments before publishing 29:35 - Using AI to stress-test my own house views 31:44 - Stylometer: my AI style and grammar tool 33:10 - Did AI make the thinking better? For more on this week's topics, subscribe to my newsletter https://www.exponentialview.co/ ----- Where to find me: Exponential View newsletter: https://www.exponentialview.co/ Website: https://www.azeemazhar.com/ LinkedIn: https://www.linkedin.com/in/azhar/ Twitter/X: https://x.com/azeem Production by EPIIPLUS1 Production and research: Baba Films, Chantal Smith, Marija Gavrilov. Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

OpenAI dropped GPT-5.4 Thinking and Pro.

Welcome to Exponential View, the show where I explore how exponential technologies such as AI are reshaping our future. I've been studying AI and exponential technologies at the frontier for over ten years. Each week, I share some of my analysis or speak with an expert guest to make light of a particular topic. To keep up with the Exponential transition, subscribe to this channel or to my newsletter: https://www.exponentialview.co/ ----- Meet R Mini Arnold - my OpenClaw chief of staff, which manages the equivalent of a ten-person team from a Mac mini in my garden studio. While I slept, that AI team debugged its own code at 3am, researched a trending Substack essay using five parallel investigators, and wrote a 4,600-word script for this very episode in 40 minutes. The gap between people who've started building this way and those who haven't is widening every week.  I covered: 00:51 Introducing my OpenClaw agent “R Mini Arnold” 03:59 What my AI chief of staff actually does 07:58 The hardware and software stack 10:38 A morning brief before you wake up 12:05 Overnight agents: research and code 15:00 How I communicate with my agent 18:56 Example 1: the sovereign wealth fund 22:41 Example 2: how this video was written 26:34 What it costs 29:22 The soul.md personality spec 32:39 Am I losing the judgment muscle? 35:46 Individuals vs. Fortune 500s 38:25 What to try this week ----- Where to find me: Exponential View newsletter: https://www.exponentialview.co/ Website: https://www.azeemazhar.com/ LinkedIn: https://www.linkedin.com/in/azhar/ Twitter/X: https://x.com/azeem Production by EPIIPLUS1 Production and research: Baba Films, Chantal Smith, Marija Gavrilov. Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

Is your job safe if it happens on a screen?In the past few weeks, AI hasn't just improved, it has crossed a line. From writing production-ready code to building full applications autonomously, the shift is no longer theoretical. It's operational.The reality? AI is moving from assistant to operator, faster than most leaders are prepared for.In this episode, we break down what's really happening behind the headlines, why this moment feels eerily similar to early 2020, and what business leaders must do now to avoid being caught off guard.If you lead people, manage budgets, or make strategic decisions, this conversation is not optional.In this session, you'll discover:Why a viral article comparing AI to early COVID signals a bigger structural shiftHow Claude 4.6 and GPT 5.3 are moving from “helpful tool” to “finished output”The real reason AI labs targeted software engineers firstWhy “anything that can be done on a computer” is now vulnerableHow AI built a full multi-agent production pipeline in 48 hoursWhat Gemini 3.1 Pro's benchmark leap actually meansWhy Accenture now ties promotions to AI usageHow AI insurance is removing enterprise adoption barriersWhat the India AI Summit revealed about global governance tensionsWhy OpenAI's $100B raise is both brilliant and dangerously high-stakesHow robotics is quietly moving from factory floors into daily lifeWhy hybrid human-AI workflows are temporary by designThe coming economic disruption — and where opportunity hides inside itAbout Leveraging AI The Ultimate AI Course for Business People: https://multiplai.ai/ai-course/ YouTube Full Episodes: https://www.youtube.com/@Multiplai_AI/ Connect with Isar Meitis: https://www.linkedin.com/in/isarmeitis/ Join our Live Sessions, AI Hangouts and newsletter: https://services.multiplai.ai/events If you've enjoyed or benefited from some of the insights of this episode, leave us a five-star review on your favorite podcast platform, and let us know what you learned, found helpful, or liked most about this show!

What if months of work could be done in a single day? In this solo episode of The Greatness Machine, host Darius Mirshahzadeh delivers a blunt, eye-opening reality check on how AI is permanently reshaping work and business. Darius shares how tools like Claude.ai helped him unlock what he estimates as 80x productivity, collapsing months of effort into a single day while building his new private equity firm. From playbooks and investment materials to inbox zero and app creation, the results left him stunned. He challenges CEOs, founders, knowledge workers, and students to rethink their roles now, making it clear that AI is no longer “tech,” it is operations. The future, he argues, belongs to those who can build workflows, deploy agents, and leverage automation tools like n8n. In this episode, Darius will discuss: (00:00) The AI Revolution Begins (02:33) Harnessing AI for Productivity (05:48) Transforming Workflows with AI (08:16) The Future of Knowledge Work (11:28) Preparing for an AI-Driven World (14:16) The New Era of Business Operations Connect with Darius: Website: https://therealdarius.com/ Linkedin: https://www.linkedin.com/in/dariusmirshahzadeh/ Instagram: https://www.instagram.com/imthedarius/ YouTube: https://www.youtube.com/@Thegreatnessmachine  Book: The Core Value Equation https://www.amazon.com/Core-Value-Equation-Framework-Limitless/dp/1544506708 Write a review for The Greatness Machine using this link: https://ratethispodcast.com/spreadinggreatness.  Learn more about your ad choices. Visit megaphone.fm/adchoices

How to design meetings with purpose so they actually move work forward.Meetings are a necessary part of work. But for many people, they're also a major source of frustration. According to Rebecca Hinds, meetings don't have to feel like a drain—better meetings start when we stop treating them as a default and start designing them with intention.Hinds is the author of Your Best Meeting Ever: Seven Principles for Designing Meetings That Get Things Done, and a future-of-work expert who founded the Work Innovation Lab at Asana and the Work AI Institute at Glean. She argues that the problem isn't meetings themselves, but the sheer number of poorly designed ones, and by being more thoughtful about what actually deserves synchronous time, teams can redesign how they communicate in the workplace “Meetings are the most important product in our entire organization, and yet they're also the least optimized,” she says. “The first step is recognizing we need to be much more intentional about how we're designing meetings.”In this episode of Think Fast, Talk Smart, Hinds and host Matt Abrahams discuss why meetings so often go wrong—and what it takes to make them work. Whether you're leading a team, trying to protect focus time, or simply hoping to spend less of your week in calendar invites, Hinds offers practical frameworks for designing meetings with purpose so they become a tool people actually value.To listen to the extended Deep Thinks version of this episode, please visit FasterSmarter.io/premium.Episode Reference Links:Rebecca HindsRebecca's Book: Your Best Meeting EverEp.124 Making Meetings Meaningful Pt. 1: How to Structure and Organize More Effective Gatherings Ep.125 Making Meetings Meaningful Pt. 2: Key Ingredients for Effective Meetings Connect:Premium Signup >>>> Think Fast Talk Smart PremiumEmail Questions & Feedback >>> hello@fastersmarter.ioEpisode Transcripts >>> Think Fast Talk Smart WebsiteNewsletter Signup + English Language Learning >>> FasterSmarter.ioThink Fast Talk Smart >>> LinkedIn, Instagram, YouTubeMatt Abrahams >>> LinkedInChapters:(00:00) - Introduction (01:42) - Why Meetings Feel Broken (02:57) - The Default-To-Meeting Problem (03:50) - Treat Meetings Like A Product (05:10) - Meeting Doomsday Reset (06:40) - The 4-DCEO Test (08:43) - Designing Better Meetings (10:05) - Creating a Meeting Agenda (12:58) - Context And Meeting Fatigue (14:06) - Memo-First Meetings (16:11) - The Final Three Questions (21:02) - Conclusion ********Thank you to our sponsors.  These partnerships support the ongoing production of the podcast, allowing us to bring it to you at no cost.This episode is sponsored by Strawberry.me. Get 50% off your first coaching session today at Strawberry.me/tftsJoin our Think Fast Talk Smart Learning Community and become the communicator you want to be.

Jonathan Siddharth is the founder and CEO of Turing, a $2.2 billion AI company that provides coding and reasoning data to train frontier models for OpenAI, Google, Meta, Anthropic and more. Turing's mission is to accelerate superintelligence to drive economic growth. In this episode of World of DaaS, Jonathan and Auren discuss:How Turing creates expert data for frontier modelsWhy SaaS is dying in the age of AI agentsDisrupting the $30 trillion market for digital knowledge workBuilding a stage five company cultureYou can find Auren Hoffman on X at @auren and Jonathan Siddharth on X at @jonsidd.Editing and post-production work for this episode was provided by The Podcast Consultant (https://thepodcastconsultant.com)

The best way to build a horrible search product? Don't ever measure anything against what a user wants.Search veterans Doug Turnbull (Led Search at Reddit + Shopify; Wrote Relevant Search + AI Powered Search) and John Berryman (Early Engineer on Github Copilot; Author of Relevant Search + Prompt Engineering for LLMs), join Hugo to talk about how to build Agentic Search Applications.We Discuss:* The evolution of information retrieval as it moves from traditional keyword search toward “agentic search“ and what this means for builders.* John's five-level maturity model (you can prototype today!) for AI adoption, moving from Trad Search to conversational AI to asynchronous research assistants that reason about result quality.* The Agentic Search Builders Playbook, including why and how you should “hand-roll” your own agentic loops to maintain control;* The importance of “revealed preferences” that LLM-judges often miss (evaluations must use real clickstream data to capture “revealed preferences” that semantic relevance alone cannot infer)* Patterns and Anti-Patterns for Agentic Search Applications* Learning and teaching Search in the Age of AgentsYou can find the full episode on Spotify, Apple Podcasts, and YouTube.You can also interact directly with the transcript here in NotebookLM: If you do so, let us know anything you find in the comments!

▶️ Connect with Richard on LinkedIn: https://www.linkedin.com/in/richardatherton-firsthuman/   Is AI about to take over knowledge work? And what does that mean for the rest of us?   In this episode of Being Human, I speak with Alastair Moore, AI strategist and co-founder of ventures helping organisations navigate the machine intelligence revolution. Alastair argues that we've already crossed a threshold: AI isn't just assisting knowledge workers — it's now performing tasks at the frontier of research, science, and complex problem-solving.   We explore how large models are reshaping entire categories of white-collar work, why organisations are unprepared for the acceleration curve, and what skills will matter in a world where cognition becomes a shared capability between humans and machines. This is a grounded, practical, and sometimes unsettling conversation about the next decade of work.   We discuss: AI at the scientific frontier Automation of knowledge work Human–machine complementarities Skills for the post-GPT economy Links: DeepFlow - the company co-founded by Alastair

On the 61st episode of Enterprise AI Innovators, hosts Evan Reiser (CEO and co-founder, Abnormal AI) and Saam Motamedi (Greylock Partners) talk with Allen Fazio, CIO at Houlihan Lokey. Allen lays out how a global mid-cap M&A leader is rethinking investment banking as a professional service powered by AI. By putting a single orchestration layer at the center and starting with “100-level” use cases for analysts and interns, he is building an innovation engine that protects regulatory exposure while transforming how human bankers research, model, and execute deals.Quick hits from Allen:On orchestration and data advantage: “We've been looking for almost three years for what I'll call the orchestration layer. What do we put in the middle of the picture?”On analyst-first AI adoption: “So for us, our focus is going to be on the lookout level, right. Let's start with the analysts, associates, and interns. And let's really focus on their capabilities, where I think some of our peers are. I'm not saying they're wrong, but where they're spending more time than I'm going to spend is on these high-end use cases.”On culture over tools: “You're building out an innovation culture, not deploying a technology or a toolset.”Recent Book Recommendation: Snow Crash by Neal Stephenson --Like what you hear? Leave us a review and subscribe to the show on Apple, Google, Spotify, Stitcher, or wherever you listen to podcasts.Enterprise AI Innovators is a show where top technology executives share how AI is transforming the enterprise. Find more great lessons from tech leaders and enterprise software experts at https://www.enterprisesoftware.blog/ Enterprise AI Innovators is produced by Abnormal Studios.

At 22, Brendan Foody is both the youngest Conversations with Tyler guest ever and the youngest unicorn founder on record. His company Mercor hires the experts who train frontier AI models—from poets grading verse to economists building evaluation frameworks—and has become one of the fastest-growing startups in history. Tyler and Brendan discuss why Mercor pays poets $150 an hour, why AI labs need rubrics more than raw text, whether we should enshrine the aesthetic standards of past eras rather than current ones, how quickly models are improving at economically valuable tasks, how long until AI can stump Cass Sunstein, the coming shift toward knowledge workers building RL environments instead of doing repetitive analysis, how to interview without falling for vibes, why nepotism might make a comeback as AI optimizes everyone's cover letters, scaling the Thiel Fellowship 100,000X, what his 8th-grade donut empire taught him about driving out competition, the link between dyslexia and entrepreneurship, dining out and dating in San Francisco, Mercor's next steps, and more. Read a full transcript enhanced with helpful links, or watch the full video on the new dedicated Conversations with Tyler channel. Recorded October 16th, 2025. Other ways to connect Follow us on X and Instagram Follow Tyler on X Follow Brendan on X Sign up for our newsletter Join our Discord Email us: cowenconvos@mercatus.gmu.edu Learn more about Conversations with Tyler and other Mercatus Center podcasts here. Timestamps 00:00:00 - Hiring poets to teach AI 00:05:29 - Measuring real-world AI progress  00:13:25 - Why rubrics are the new oil  00:18:44 - Enshrining taste in LLMs 00:22:38 - Turning society into one giant RL machine 00:26:37 - When AI will stump experts 00:30:46 - AI and employment 00:35:05 - Why vibes-based hiring fails 00:39:55 - Solving labor market matching problems  00:45:01 - Scaling the Thiel Fellowship  00:48:11 - A hypothetical gap year 00:50:31 - Donuts, debates, and dyslexia 00:56:15 - Dating and dining out 00:59:01 - Mercor's next steps

Get access to metatrends 10+ years before anyone else - https://qr.diamandis.com/metatrends   Emad Mostaque is the founder of Intelligent Internet ( https://www.ii.inc )  Read Emad's Book: https://thelasteconomy.com Salim Ismail is the founder of OpenExO Dave Blundin is the founder & GP of Link Ventures Dr. Alexander Wissner-Gross is a computer scientist and founder of Reified – My companies: Apply to Dave's and my new fund:https://qr.diamandis.com/linkventureslanding      Go to Blitzy to book a free demo and start building today: https://qr.diamandis.com/blitzy   Grab dinner with MOONSHOT listeners: https://moonshots.dnnr.io/ _ Connect with Peter: X Instagram Connect with Emad:  Read Emad's Book  X  Learn about Intelligent Internet Connect with Dave: X LinkedIn Connect with Salim: X Join Salim's Workshop to build your ExO  Connect with Alex Website LinkedIn X Email Listen to MOONSHOTS: Apple YouTube – *Recorded on December 18th, 2025 *The views expressed by me and all guests are personal opinions and do not constitute Financial, Medical, or Legal advice. Learn more about your ad choices. Visit megaphone.fm/adchoices

Join Conor Grennan and Jaeden as they dive into the latest release of GPT 5.2. Discover how this new model is revolutionizing knowledge work, outperforming industry professionals, and what it means for the future of AI. From personal anecdotes to industry benchmarks, this episode covers it all. Tune in to learn more about the incremental updates and their impact on technology and productivityGet the top 40+ AI Models for $20 at AI Box: ⁠⁠https://aibox.aiConor's AI Course: https://www.ai-mindset.ai/coursesConor's AI Newsletter: https://www.ai-mindset.ai/Jaeden's AI Hustle Community: https://www.skool.com/aihustleSee Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

Don Kieffer has spent more than fifty years redesigning how real work gets done. In this episode, he explains why so many improvement efforts stall—and how Dynamic Work Design offers a clearer, more practical way forward. Episode page with video, transcript, and more Don traces his path from machinist to Vice President of Operational Excellence at Harley-Davidson and senior lecturer at MIT Sloan. He shares what he learned working with Toyota legend Hajime Oba, including the moment he realized that copying Toyota's rituals was the wrong goal. The real power, he argues, lies in understanding the thinking behind great work design. We break down the five principles of Dynamic Work Design—solving the right problem, structuring for discovery, connecting the human chain, regulating flow, and making work visible—and discuss how they apply far beyond the factory floor. Don explains why intellectual work is “almost infinitely compressible,” why executives misdiagnose morale problems, and why most leaders can draw their org chart but not the actual flow of work. Along the way, he shares stories from Harley, MIT, and client organizations that learned to shift from firefighting to flow. His message is consistent: when you redesign the work, you change the culture. Engagement follows the system, not the other way around. This episode pairs well with Episode 538 with Nelson Repenning and is essential listening for leaders trying to improve performance, reduce frustration, and create environments where people can do their best work. Key ideas • Copying Toyota's practices isn't the same as understanding Toyota's thinking • Why Dynamic Work Design starts with a specific problem—not a program • How to create real-time management systems in knowledge-work environments • Why most dysfunction is a work-design issue, not a people issue • How better work design restores flow, learning, and joy in the work Representative Quotes “Five percent of the problem is people. Ninety-five percent is bad work design.” “Most executives can draw the org chart, but not the work.” “Intellectual work is almost infinitely compressible.” “Culture emerges from how the work is designed—not from what leaders say.”

Jonathan Siddharth is Founder and CEO of Turing, one of the fastest-growing AI companies advancing frontier models. Jonathan has led the company to an astonishing $350M ARR with just $225M raised and a profitable company. A Stanford-trained AI scientist, Jonathan previously helped pioneer natural language search at Powerset, which was acquired by Microsoft. AGENDA: 03:35 Data, Compute, Algorithms: What is Most Abundant? What is Lacking Most? 09:18 What Does No One Know About AI's Data Requirements That Everyone Should? 17:05 The Biggest Challenges Enterprises Have with AI Adoption 20:38 Why Will 99% of Knowledge Work Will be Gone in 10 Years 27:12 How Will Data-Driven Feedback Loops Replace Technology as the Moat 36:08 Who Wins the Data Labelling Market? Who Loses? 38:23 Is Revenue BS in Data Labelling? Are Players Calling GMV Revenue?  45:20 Why is SaaS Dead in a World of AI? 51:23 Will the Phone be the Primary User Interface to an AI World? 57:07 Quickfire Round    

The world record for fastest pit stop—a mere 1.8 seconds—was set by the McLaren F1 Team at the Qatar Grand Prix in 2023. It's an incredible feat of speed and choreography; a pit stop that fast can't happen without a team of people operating at peak human performance. But as Dan Keyworth explains, AI plays a crucial role, too. As the Director of Business Technology at McLaren Racing, Dan is responsible for helping the whole team perform at their best—and that starts with having the right tools. Whether it's the firehose of sensor data coming off a race car, video analysis of the pit crew in action, or marketing analytics for the next Grand Prix, AI helps the McLaren F1 Team make the right decisions—and make them fast.On this episode, Dan talks about the importance of getting simple answers from complex data, how they use Dropbox Dash, and why we shouldn't think of AI as labor replacement so much as laborious replacement.You can learn more about the McLaren F1 Team at mclaren.com/racing/formula-1. And if you haven't already seen it, be sure to watch their world record pit stop at youtube.com/watch?v=tRBOiq-Q6_s. Seriously, it's blink-and-you'll-miss-it fast.~ ~ ~Working Smarter is brought to you by Dropbox Dash—the AI universal search and knowledge management tool from Dropbox. Learn more at workingsmarter.ai/dashYou can listen to more episodes of Working Smarter on Apple Podcasts, Spotify, YouTube Music, Amazon Music, or wherever you get your podcasts. To read more stories and past interviews, visit workingsmarter.aiThis show would not be possible without the talented team at Cosmic Standard: producer Dominic Girard, sound engineer Aja Simpson, technical director Jacob Winik, and executive producer Eliza Smith. Special thanks to our illustrators Justin Tran and Fanny Luor, marketing consultant Meggan Ellingboe, and editorial support from Catie Keck. Our theme song was composed by Doug Stuart. Working Smarter is hosted by Matthew Braga. Thanks for listening!

Cal Newport unpacks his framework for Slow Productivity, built on three core principles: doing fewer things, working at a natural pace, and obsessing over quality. He introduces "pseudo productivity"—the toxic heuristic that emerged in mid-20th century knowledge work when visible activity became a proxy for useful effort because traditional productivity metrics (Model Ts per hour, bushels per acre) no longer applied. Newport argues that pseudo productivity was tolerable until the digital office revolution—email, Slack, mobile computing—enabled visible activity to be demonstrated at incredibly high frequency, anywhere, anytime, creating a performance theater that drains actual productive capacity. The conversation explores how to build custom AI systems for daily planning (using GPT models trained on transcripts and book notes), the three levels of working with large language models (training from scratch, fine-tuning, and software intermediaries), and why specialized vertical AI will dominate the next wave of innovation. Newport makes the case for abandoning industrial-era proxies and reclaiming knowledge work as a craft that requires depth, patience, and quality over constant performative busyness. Hosted on Acast. See acast.com/privacy for more information.

In this episode of The Digital Executive, host Brian Thomas welcomes Alberto Rizzoli, serial entrepreneur and CEO of V7, a UK-based company pioneering AI systems to automate knowledge work across industries like healthcare, finance, and insurance.Alberto shares his journey from creating AI Poly, a groundbreaking app that empowered the visually impaired, to leading V7, where AI agents now handle complex, document-heavy workflows with accuracy, traceability, and compliance at scale. He explains how V7 blends human expertise with AI, allowing organizations to design reliable automations that learn step by step and always ground decisions in documented evidence—ensuring trustworthy, transparent AI operations.Looking ahead, Alberto envisions a world where AI eliminates administrative burdens, reduces bureaucracy, and empowers a new generation of AI workflow designers—transforming how we define knowledge work itself.Whether you're an AI innovator, enterprise leader, or future-focused technologist, this episode offers a bold perspective on how human creativity and machine intelligence will coexist to reshape the modern workplace.If you liked what you heard today, please leave us a review - Apple or Spotify. See Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

Iain Thomas is a poet, author, and the Chief Innovation Officer at Sounds Fun—an advertising and creative agency that he co-founded with the belief that human creativity could be enhanced, rather than diminished, with the help of AI. It's a realization that actually began to dawn on Iain a few years prior, after his mother died. He wasn't sure how to explain death to his children, so he turned to an early version of ChatGPT for help—and was so impressed by the poetry of its responses that he came away convinced of AI's immense potential as a thought partner for his creative work. On this episode, Iain talks about using AI to make more space for the creative parts of your work, and why, in a world where everyone has access to the same tools, it's never been more important to lean into the skills, context, and experiences that make each of us most unique—and most human.Learn more about Sounds Fun soundsfun.co~ ~ ~Working Smarter is brought to you by Dropbox Dash—the AI universal search and knowledge management tool from Dropbox. Learn more at workingsmarter.ai/dashYou can listen to more episodes of Working Smarter on Apple Podcasts, Spotify, YouTube Music, Amazon Music, or wherever you get your podcasts. To read more stories and past interviews, visit workingsmarter.aiThis show would not be possible without the talented team at Cosmic Standard: producer Dominic Girard, sound engineer Aja Simpson, technical director Jacob Winik, and executive producer Eliza Smith. Special thanks to our illustrators Justin Tran and Fanny Luor, marketing consultant Meggan Ellingboe, and editorial support from Catie Keck. Our theme song was composed by Doug Stuart. Working Smarter is hosted by Matthew Braga. Thanks for listening!

In this episode of the Digital HR Leaders Podcast, host David Green is joined once again by Mikael Wornoo, Co-Founder of TechWolf - a company at the forefront of skills intelligence. Bringing fresh insights from the frontlines of AI and workforce strategy, together they explore where leading companies are heading, and what HR needs to do to stay ahead of the curve. From adoption challenges to ethical concerns, in this episode, you can expect to learn more about: How the conversation around AI and skills is shifting—and what's driving the change Why skills-based workforce planning is becoming a business-critical priority The human side of AI: navigating adoption, mindset shifts, and ethical concerns The data and insights HR needs to lead meaningful transformation How to build a fair, skills-powered future—and avoid a “winner-takes-all” dynamic This episode is sponsored by TechWolf. TechWolf helps enterprises get fast, accurate, and actionable skills data—without surveys. From identifying the skills your workforce has to mapping what they need, TechWolf's AI integrates seamlessly with your existing systems to turn messy data into strategic advantage. Learn more at techwolf.com Hosted on Acast. See acast.com/privacy for more information.

Software development and software engineering could be the first major economically valuable capability that closes the gap between humans and AI, says Eiso Kant, the CTO of frontier AI company poolside. He shares what these changes mean for technology and the sector, and for knowledge work generally. Eiso stays cautious about tech forecasts and predictions, but breaks down how worry and fear can be a motivator to drive true learning and understanding in a fast-moving era, sharing and questions we should ask and mindsets we should apply to understand how we can uniquely contribute to societies and economies in the years ahead as technologies reshape human roles. This interview was recorded in January 2025 at the World Economic Forum Annual Meeting in Davos, Switzerland. About this episode: https://poolside.ai/ Related report: Future of Jobs 2025: https://www.weforum.org/publications/the-future-of-jobs-report-2025/ Related episodes: Radio Davos: Do you need an AI mentor? This tech entrepreneur thinks so Watch here: https://www.youtube.com/watch?v=-I0CNHlS7f4 Read here: https://tinyurl.com/28z7cmtt Listen here: https://tinyurl.com/y7yshdad Meet The Leader: This company launched with $600 a decade ago. How it's using data and AI to boost yields for millions of small-scale farmers Watch here: https://www.youtube.com/watch?v=IkOu9As6J60 Read here: https://tinyurl.com/bdz69j65Listen here: https://tinyurl.com/bcmj6572

Bespoken Spirits isn't your typical whiskey distillery. Yes, they're based in the American bourbon heartland of Lexington, Kentucky, and yes, they often make private label whiskeys for clients. But everything from how Bespoken Spirits distills their whiskey to how they market it is done with the help of AI. Jordan Spitzer, their head of flavor, can finish a whiskey in days instead of years—while precisely crafting its taste—using their machine-learning backed approach. And Wane Lindsey, their director of marketing, credits AI tools with helping his tiny team punch way above their weight.The result is a whiskey that may not be traditional, but still tastes great—and in a fraction of the time it would otherwise take. That's time they can spend on the creative side of their craft and the work that has the most meaning: building brands and bespoke spirits that people will want to drink.On this episode, Jordan and Wane share how AI has helped them explore creative new ways to make and market whiskey—and why, no matter how smart our tools get, there's still no substitute for human taste.You can learn more about Bespoken Spirits at bespokenspirits.com~ ~ ~Working Smarter is brought to you by Dropbox Dash—the AI universal search and knowledge management tool from Dropbox. Learn more at workingsmarter.ai/dashYou can listen to more episodes of Working Smarter on Apple Podcasts, Spotify, YouTube Music, Amazon Music, or wherever you get your podcasts. To read more stories and past interviews, visit workingsmarter.aiThis show would not be possible without the talented team at Cosmic Standard: producer Dominic Girard, sound engineer Aja Simpson, technical director Jacob Winik, and executive producer Eliza Smith. Special thanks to our illustrators Justin Tran and Fanny Luor, marketing consultant Meggan Ellingboe, and editorial support from Catie Keck. Our theme song was composed by Doug Stuart. Working Smarter is hosted by Matthew Braga. Thanks for listening!

Amanda Cupido doesn't speak Spanish or French. But using AI, she and her team helped a global nonprofit make their internal podcast more accessible to as many employees as possible. Amanda is an audio producer and the founder of a production company called Lead Podcasting. One of her clients is a global nonprofit with over 35,000 employees—and not all of them speak English. So she made them a pitch: what if they added AI into the mix? They would make the podcast in English, and then use generative AI voice tools to translate it into Spanish and French—with a lot of human oversight, of course. Driven by a desire to use these tools for good, the goal was never to replace people, but to reach more people, and it worked.On this episode, Amanda shows what it's like—and what it sounds like—to make a podcast with AI that's still human at its core.You can learn more about Lead Podcasting at leadpodcasting.com~ ~ ~Working Smarter is brought to you by Dropbox Dash—the AI universal search and knowledge management tool from Dropbox. Learn more at workingsmarter.ai/dashYou can listen to more episodes of Working Smarter on Apple Podcasts, Spotify, YouTube Music, Amazon Music, or wherever you get your podcasts. To read more stories and past interviews, visit workingsmarter.aiThis show would not be possible without the talented team at Cosmic Standard: producer Dominic Girard, sound engineer Aja Simpson, technical director Jacob Winik, and executive producer Eliza Smith. Special thanks to our illustrators Justin Tran and Fanny Luor, marketing consultant Meggan Ellingboe, and editorial support from Catie Keck. Our theme song was composed by Doug Stuart. Working Smarter is hosted by Matthew Braga. Thanks for listening!

What if biotech teams could automate the most information-intensive parts of bringing a drug to market? In this episode of Data in Biotech, host Ross Katz speaks with Convoke co-founders Alex Telford and Maged Ahmed about building an AI-native knowledge acquisition and curation system for biopharma. Learn how they're transforming clinical research, regulatory writing, and competitive intelligence using LLMs, semantic search, and scalable data infrastructure. ​​What You'll Learn in This Episode: >> How Convoke unifies public and private biotech data into a single workspace for smarter decision-making >> Why structured outputs and semantic layers are key to high-quality AI-driven insights >> Real-world use cases including clinical trial design, competitive landscape analysis, and regulatory documentation >> How feedback loops and model evaluations drive product reliability and user trust >> The future of AI in biotech: continuous decision-making and multimodal intelligence Meet Our Guests Alex Telford is Co-Founder and CEO of Convoke, an AI-native OS transforming drug development workflows. His background in life sciences consulting drives his mission to unify data and streamline outputs like clinical documents and regulatory submissions. Maged Ahmed is Co-Founder of Convoke and a former AI lead at Applied Intuition. He brings deep data infrastructure expertise to biotech, aiming to reduce friction in regulated environments by automating knowledge generation. About The Host Ross Katz is Principal and Data Science Lead at CorrDyn. Ross specializes in building intelligent data systems that empower biotech and healthcare organizations to extract insights and drive innovation. Connect with Our Guest: Sponsor: CorrDyn, a data consultancyConnect with Alex Telford  on LinkedIn Connect with Maged Ahmed on LinkedIn Connect with Us: Follow the podcast for more insightful discussions on the latest in biotech and data science.Subscribe and leave a review if you enjoyed this episode!Connect with Ross Katz on LinkedIn Sponsored by… This episode is brought to you by CorrDyn, the leader in data-driven solutions for biotech and healthcare. Discover how CorrDyn is helping organizations turn data into breakthroughs at CorrDyn.

Very few people get paid to visit shipwrecks—but for Stephanie Gandulla, it's all part of the job. Stephanie is a scuba diver, maritime archeologist, and resource protection coordinator for the Thunder Bay National Marine Sanctuary. The agency safeguards Lake Huron's historic shipwrecks, many of which have yet to be discovered. That's where Katie Skinner comes in. She's an assistant professor at the University of Michigan and the director of the school's Field Robotics Group. Skinner and her team have been developing autonomous underwater vehicles that can find new shipwreck sites, all on their own. For humans, a search is costly, time-consuming, manual work. But for AI? Skinner thinks it could help us find answers in a snap. On this episode, Stephanie and Katie talk about using AI to find shipwrecks in a literal lake of data, so that they can spend less time searching and more time exploring—as only humans can do.You can learn more about some of the people and projects featured in this episode, including… The Thunder Bay National Marine Sanctuary at thunderbay.noaa.govKatie Skinner and the University of Michigan's Field Robotics Group at fieldrobotics.engin.umich.eduPrevious efforts to autonomously map Thunder Bay's historical shipwrecks at theverge.com/2020/3/5/21157791/drone-autonomous-boat-ben-shipwreck-alley-unh-noaa-great-lakes-thunder-bay~ ~ ~Working Smarter is brought to you by Dropbox Dash—the AI universal search and knowledge management tool from Dropbox. Learn more at workingsmarter.ai/dashYou can listen to more episodes of Working Smarter on Apple Podcasts, Spotify, YouTube Music, Amazon Music, or wherever you get your podcasts. To read more stories and past interviews, visit workingsmarter.aiThis show would not be possible without the talented team at Cosmic Standard: producer Dominic Girard, sound engineer Aja Simpson, technical director Jacob Winik, and executive producer Eliza Smith. Special thanks to our illustrators Justin Tran and Fanny Luor, marketing consultant Meggan Ellingboe, and editorial support from Catie Keck. Our theme song was composed by Doug Stuart. Working Smarter is hosted by Matthew Braga. Thanks for listening!

Welcome to episode #1000 of Six Pixels of Separation - The ThinkersOne Podcast. Patrick Tanguay is a self-described generalist, synthesist and curator whose lifelong curiosity and love of reading have led him across multiple careers, and now shape one of the most thoughtful newsletters in the futures-thinking space. As the creator of Sentiers, a weekly “futures thinking observatory” (and one of my most favorite reads), Patrick spotlights signals of change across technology, society, and culture. He helps readers trace emergent paths instead of prescribing them. Alongside his writing, he designed and launched Station C, one of the first co-working spaces, co-founded the print magazine, The Alpine Review, and seeded communities like Creative Mornings and some of the earlier community get-togethers for the digital enthusiasts. For episode #1000, Patrick guides us through how he curates global currents of change, explores how platform design, sense-making systems and personal knowledge management influence our capacity to understand the future, and why the skills of generalists matter now more than ever. He walks us through why Sentiers became such a respected newsletter and how its architecture reinforces and expands his handwritten trail of ideas. Across the show we consider how to build a personal “observatory,” not just follow feed algorithms, how to connect seemingly disparate signals from AI to city futures, and why being able to notice what's happening before everyone else is becoming more crucial... and more rare. This is an episode for curious minds, digital gardeners and anyone searching for clarity amid chaos. I hope that you will also take a couple of moments to listen to my opening monologue about my reflections on the past 1000 episodes (nearly 20 years), and what the future will hold for this show starting next week. Enjoy the conversation… Running time: 1:28:08. Hello from beautiful Montreal. Listen and subscribe over at Apple Podcasts. Listen and subscribe over at Spotify. Please visit and leave comments on the blog - Six Pixels of Separation. Feel free to connect to me directly on Facebook here: Mitch Joel on Facebook. Check out ThinkersOne. or you can connect on LinkedIn. ...or on X. Here is my conversation with Patrick Tanguay. Sentiers. The Alpine Review. Follow Patrick on LinkedIn. Chapters: (00:00) - The Evolution of Six Pixels of Separation. (04:14) - Introducing Patrick Tanguay. (05:31) - The Art of Thinking and Curating. (20:56) - Foresight and Future Thinking. (29:54) - Navigating the World of AI. (41:41) - The Role of Reading in Deep Thinking. (01:00:08) - The Future of Knowledge Work. (01:10:04) - The Intersection of AI and Human Purpose.

Ian Ramirez has spent his career finding innovative ways to make mouth-watering meals for clients—and one of his latest ingredients is artificial intelligence. As a chef, culinary consultant, and co-founder of Mad Honey Culinary Studio and Goods, he's the guy that brands hire to get their product on restaurant menus, and make it look and taste good—whether it's a sauce, syrup, spread, or spice. Ian uses AI to tackle the repetitive, time-consuming parts of menu planning for commercial kitchens, and help clients visualize new concepts before anything gets sliced or diced. It's a tool that augments his creativity, he says, and makes prep less of a grind. On this episode, Ian talks about how AI is helping him and his team spend more time doing what they love: cooking and getting creative in the kitchen.Learn more about Mad Honey Culinary Studio and Goods at madhoneyculinary.comLearn more about Dropbox Dash—the AI universal search and knowledge management tool from Dropbox—at workingsmarter.ai/dash~ ~ ~Working Smarter is brought to you by Dropbox Dash—the AI universal search and knowledge management tool from Dropbox. Learn more at workingsmarter.ai/dashYou can listen to more episodes of Working Smarter on Apple Podcasts, Spotify, YouTube Music, Amazon Music, or wherever you get your podcasts. To read more stories and past interviews, visit workingsmarter.aiThis show would not be possible without the talented team at Cosmic Standard: producer Dominic Girard, sound engineer Aja Simpson, technical director Jacob Winik, and executive producer Eliza Smith. Special thanks to our illustrators Justin Tran and Fanny Luor, marketing consultant Meggan Ellingboe, and editorial support from Catie Keck. Our theme song was composed by Doug Stuart. Working Smarter is hosted by Matthew Braga. Thanks for listening!

Working Smarter is back for season two! Starting September 3, we're going beyond the hype and headlines to bring you stories about real people using AI to do more of what they love about their jobs. From the F1 track to the kitchen—and even the bottom of a lake—learn how new tools are helping creatives, makers, visionaries, and their teams think big, move faster, and focus on the work that matters most.~ ~ ~Working Smarter is brought to you by Dropbox Dash—the AI universal search and knowledge management tool from Dropbox. Learn more at workingsmarter.ai/dashYou can listen to more episodes of Working Smarter on Apple Podcasts, Spotify, YouTube Music, Amazon Music, or wherever you get your podcasts. To read more stories and past interviews, visit workingsmarter.aiThis show would not be possible without the talented team at Cosmic Standard: producer Dominic Girard, sound engineer Aja Simpson, technical director Jacob Winik, and executive producer Eliza Smith. Special thanks to our illustrators Justin Tran and Fanny Luor, marketing consultant Meggan Ellingboe, and editorial support from Catie Keck. Our theme song was composed by Doug Stuart. Working Smarter is hosted by Matthew Braga. Thanks for listening!

Welcome to episode #995 of Six Pixels of Separation - The ThinkersOne Podcast. Nelson Repenning has built his career at MIT Sloan and Shift Gear by asking a simple but haunting question: why do so many smart, capable organizations fail to get the right work done? In his new book, There's Got to Be a Better Way, Nelson (along with his co-author, Don Kieffer) introduces dynamic work design: a practical framework that helps leaders move beyond broken systems and toward better execution. In this conversation, we explore the five principles behind this approach: solving the right problem, structuring for discovery, connecting the human chain, regulating for flow and visualizing the work. We talk about how businesses become addicted to heroics and strategic ambiguity, and how this culture often traps people in cycles of fire-fighting and busywork that look productive but deliver little. Nelson shares stories from his experience applying these principles in casinos, hospitals, biotech labs, and even homeless shelters (environments where urgency is real, resources are stretched and clarity can make or break outcomes). We also discuss how leadership often overcomplicates productivity with reorgs and top-down mandates, instead of fixing the structural design flaws that block meaningful progress. Nelson is quick to point out that the work isn't just about doing more: it's about doing it better… and that better means aligning actual workflow with the outcomes organizations care about. He reflects on his early days as a student at MIT and why dynamic work design is less a management fad and more a necessary shift in how modern teams operate. If you're tired of watching your best people get burned out chasing KPIs while nothing fundamental improves, this episode offers a clearer path. We also get into the tension between change management and change design, and why the latter matters more in a world flooded with noise, complexity and well-intentioned but ineffective solutions. This is a sharp and focused take on work culture from someone who's spent a lifetime challenging the systems beneath it. Enjoy the conversation… Running time: 1:00:22. Hello from beautiful Montreal. Listen and subscribe over at Apple Podcasts. Listen and subscribe over at Spotify. Please visit and leave comments on the blog - Six Pixels of Separation. Feel free to connect to me directly on Facebook here: Mitch Joel on Facebook. Check out ThinkersOne. or you can connect on LinkedIn. ...or on X. Here is my conversation with Nelson Repenning. There's Got to Be a Better Way. Shift Gear. MIT Sloan. Follow Nelson on LinkedIn. Chapters: (00:00) - Introduction to Nelson Repenning. (02:55) - The Journey to System Dynamics. (05:55) - Bridging Theory and Practice in Organizations. (09:14) - The Challenge of Success and Anomalies. (11:54) - Dynamic Work Design: From Manufacturing to Knowledge Work. (15:06) - The Role of AI in Knowledge Work. (18:12) - Manufacturing's Future and National Security. (20:58) - The Integration of Design and Manufacturing. (32:01) - The Complexity of Manufacturing and Supply Chains. (33:14) - Dynamic Work Design: A New Approach. (35:34) - Identifying and Solving the Right Problems. (39:28) - The Disconnect Between Management and Ground Realities. (42:14) - Adapting Management Practices for Hybrid Work. (45:33) - Visual Management in Knowledge Work. (52:44) - Regulating Flow to Prevent Overload. (58:41) - The Psychological Hurdles of Change.

You won't lose your job to AI.You'll lose it to someone who knows how to use it.Neil Twa sits down with John Gargiulo, AI entrepreneur and founder of AirPost, to unpack how AI is transforming video marketing, content creation, and business at scale. From gigawatt data centers to ugly ads that convert, they explore what's real, what's hype, and how you can actually use AI to grow your brand without losing authenticity.In This Episode, We Cover:✅ Why AI is replacing knowledge workers first✅ What industries will be hit hardest and fastest✅ The future of video ad creation using AI + humans Chapters: [00:01:00] Why AI Feels Like the Internet in 1994[00:03:00] The Death of Knowledge Work as We Know It[00:08:40] AI in Marketing: From Ad Targeting to Creative[00:14:20] Human + AI = The Future of Video Ad Creation[00:17:00] The Content Bottleneck Every Brand Faces[00:18:25] Ugly Ads, Real People, and What Actually Converts[00:20:00] How to Use AI to Scale Your Brand's Storytelling

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Brendan Foody is the co-founder and CEO of Mercor, a company building the infrastructure for AI-native labor markets. Mercor's platform is already used by top AI labs to label data, evaluate human and AI candidates, and make performance-driven hiring decisions.  They're operating at the intersection of recruiting, evals, and foundation model development—helping companies shift from intuition to measurable prediction. Brendan and his team recently raised $100M and are working with some of the most advanced players in the AI ecosystem today. (0:00) Intro(1:17) State of AI in Talent Evaluation(1:54) Improvements in AI Models(4:07) Mercor Background and Mission(5:09) AI Use Cases in Hiring(13:43) Data Labeling Landscape(16:48) Expanding Beyond Coding(18:39) Company Vision and Market Strategy(21:11) Meeting with xAI(23:47) Does Mercor Use Their Own Product?(25:41) Exploring Multimodal Capabilities(28:03) Skills for the Future: Embracing AI(29:29) The Demand for Software Engineers(34:55) Foundation Model Landscape(38:42) AI Regulations(39:57) Quickfire With your co-hosts: @jacobeffron  - Partner at Redpoint, Former PM Flatiron Health  @patrickachase  - Partner at Redpoint, Former ML Engineer LinkedIn  @ericabrescia  - Former COO Github, Founder Bitnami (acq'd by VMWare)  @jordan_segall  - Partner at Redpoint