Podcasts about bottlenecks

High-voltage electricity cables are in huge demand around the world, so much so that a lack of cabling has become a bottleneck throttling the clean energy transition. So why are cable manufacturers so hesitant to expand? Also, how are these giant cables made? And is China about to eat everyone's lunch? Claes Westerlind, chief executive officer of cable manufacturing company NKT, joins Zero to discuss. This is the third episode in Bottlenecks, a series exploring the lesser known obstacles standing in the way of our electrified future. Explore further: Previous episode in Bloomberg Green’s Bottleneckes series: How a Shortage of Transformers Threatens Electricity Supply There Aren’t Enough Engineers to Meet World’s Growing Hunger for Power Electric Cable Companies Are Making a Killing From Green Energy Zero is a production of Bloomberg Green. Our producer is Oscar Boyd. Special thanks to: Jess Beck, Sommer Saadi, Mohsis Andam and Siobhan Wagner. Thoughts or suggestions? Email us at zeropod@bloomberg.net. For more coverage of climate change and solutions, visit https://www.bloomberg.com/green.See omnystudio.com/listener for privacy information.

A growing team sounds like success, but adding the wrong hire too soon can wreck morale, raise overhead, and increase chaos. In this kickoff to the Hiring Series, Dana and Sandy break down how to assess whether your practice truly needs to hire or if it's time to get serious about systems, training, and communication first. They walk through real-world scenarios (yes, including a team walking out!) and offer tools to help you make strategic hiring decisions instead of emotional ones. You'll learn how to: ✅ Recognize signs of burnout and bottlenecks ✅ Use patient flow (not just production) to assess staffing needs ✅ Perform a job analysis to refine roles before hiring ✅ Outsource strategically while maintaining quality ✅ Avoid hiring when your culture or patient satisfaction is already suffering

The future of coding. We cover multiplying engineering output, vibe coding bottlenecks, agents as reviewer, AI roll-ups, and the future of developing software. Merrill Lutsky is co-founder and CEO of Graphite, bringing AI-acceleration and automation to code review. Founded in 2020 out of New York, Graphite has become a key part of the developer ecosystem — as more code is generated with AI, they enable developers to scale the evaluation, testing, and review process before it is released. A growing bottleneck that has become incredibly important. The startup has raised over $70M from leading VC’s such Accel, A16Z, Menlo as well as a receiving a strategic investment from model provider Anthropic. Last year Graphite grew its revenue 20X and is trusted by over 45,000 developers at top engineering organizations such as Shopify and Figma. His second startup, Merrill has helped develop and manage software products for high output engineering companies such as Square, Oscar Insurance, and SelfMade. He holds a degree in Applies Math and Economics from Harvard. Sign up for new podcasts and our newsletter, and email me on danieldarling@focal.vcSee omnystudio.com/listener for privacy information.

Western economies need to electrify and fast, but where are all the skilled workers going to come from to install the heat pumps, solar panels and batteries needed? This week on Zero, Akshat Rathi talks with Olivia Rudgard about the shortage of labor in electrification industries, and why some experts are calling it an ‘existential’ crisis. This is the second episode in Bottlenecks, a new series exploring the lesser known obstacles standing in the way of our electrified future. Explore further: Read the Big Take: There Aren't Enough Engineers to Meet the World's Growing Hunger for Power Previous episode in Zero’s Bottleneckes series: How a Shortage of Transformers Threatens Electricity Supply Northvolt Hits End of Line After Failing to Reach Rescue Deal Zero is a production of Bloomberg Green. Our producer is Oscar Boyd. Special thanks to: Jess Beck, Sommer Saadi, Mohsis Andam and Siobhan Wagner. Thoughts or suggestions? Email us at zeropod@bloomberg.net. For more coverage of climate change and solutions, visit https://www.bloomberg.com/green.See omnystudio.com/listener for privacy information.

Connect to John Gilroy on LinkedIn   https://www.linkedin.com/in/john-gilroy/ Want to listen to other episodes? www.Federaltechpodcast.com Automation is a two-edged sword. On the one hand, it promises greater efficiency; on the other hand, it can pose inherent risks, such as maliciously modified data, bias, and even data poisoning. During today's interview, Mia Jordan from Salesforce offers a solution.  She is an experienced federal executive with a long-standing involvement in the federal technology community.  She has identified bottlenecks that can be solved with a structured approach that offers flexibility. Rather than grabbing any data set off the shelf, when the data has been curated, it can avoid many of the issues with creating specialized data sets. Secondly, a company like Salesforce may have seen similar processes and have a store of code that can solve an agency's problem.  Re-purposing code that has worked before in a secure environment is a way to accelerate solving vexing federal issues. The conversation also highlights the importance of collaboration and community within the federal government in enhancing efficiency and service delivery. During the interview, Mia Jordan reviewed Agentforce and gave guidance on deploying a process called Role, Knowledge, Action, and Guardrails.    

To slash emissions fast, the formula is simple: electrify everything and clean up the grid. But in practice, progress is slowed by all sorts of bottlenecks — from arcane permitting processes to sky-high electricity costs. This week on Zero, Akshat Rathi sits down with producer Oscar Boyd to spotlight a surprising culprit slowing the transition: a global shortage of transformers, and why it has industry insiders so worried. This episode kicks off Bottlenecks, a new series exploring the lesser known obstacles standing in the way of our electrified future. Explore further: The One Device Throttling the World’s Electrified Future The Device That Brought Down Heathrow Airport Zero is a production of Bloomberg Green. Our producer is Oscar Boyd. Special thanks to: Jess Beck, Sommer Saadi, Mohsis Andam and Siobhan Wagner. Thoughts or suggestions? Email us at zeropod@bloomberg.net. For more coverage of climate change and solutions, visit https://www.bloomberg.com/green.See omnystudio.com/listener for privacy information.

Welcome back to Trading Corner.  This week, James and Manny dive headfirst into the wild ride that is the HSFO market and what it means for cracks, margins, and benchmark distortion.Three trades this week:James' Trade Idea:Hold Long Dec '26 EBOB Crack — Deferred gasoline margins still underpriced with summer upside in sight.Manny's Trade Ideas:Long June/July DFL Roll — Tight barrels and seasonal strength point to continued structure.Long Q3 DFL — Dubai benchmark pricing is misfiring, but physicals suggest upside still to come.From refinery complexity choking HSFO supply, to a benchmark blindspot in Dubai, and a product market that's tightening as the mercury rises, James and Manny unpack the big themes:* Why high-sulfur fuel oil cracks are breaking records* The lead/lag dance between fuel and crude pricing* A deep dive on Dubai's Murban distortion and why it's capping benchmark reaction* When "margin boxes" lie — and how to trade what's really happening* The case for long product / short crude reversals as we enter Q3* Why June vs. July is where the curve gets interestingGlossary terms featured this week:Crack Differential between a barrel of product and crude oil, indicating refinery margin.Volatility Volatility is the degree of variation of a trading price series over time.HSFO Fuel oil with higher sulfur contents - max: 3.5%. Typically used in shipping and power generation.Margins The difference between the prices of refined products and crude oil.Platts Price Reporting Agency which provides benchmark price assessments in the physical energy markets.Lead / Lag The lead-lag relationship in trading describes how one market or asset (the "leader") tends to move ahead of another (the "lagger"), allowing traders to anticipate price movements based on these patterns.Over brought “Over brought” refers to a market condition where a trader has purchased more of a commodity than intended or than the market can absorb, increasing downside risk if demand falls short.Balmo "Balmo" (Balance of Month) refers to contracts covering the remaining days of the current month, used for short-term supply or hedging once the month is underway.Dubai (contract) The Dubai contract is a crude oil benchmark used to price Middle Eastern exports to Asia, reflecting medium sour crude and managed by the Dubai Mercantile Exchange (DME).Naphtha Naphtha is a light, flammable hydrocarbon liquid from petroleum refining, used in gasoline production and widely in industrial and petrochemical processes.

This week on The ifa Show, host Keith Ford is joined by Adele Martin, founder of Financial Adviser Scale Squad, who speaks about the value of collaboration within the financial services sector and how this can help advisers grow and improve their businesses. Ahead of presenting at the AI Summit in June, Martin explains how advisers can use AI in their practices to not only help them be more efficient but also in training the next generation of advisers. Listen as they discuss: Why advisers should be doing more than looking for referral partners. The role of technology in enhancing advisers' service offering. How hosting workshops can help strengthen both client and partner relationships.

Spot the hidden bottlenecks blocking your growth. Learn neuroscience-backed shifts to move from stuck to strategic and unlock real momentum as a purpose-driven founder. The post Ep 47. Invisible Bottlenecks in Your Business (and How to Finally See Them) appeared first on The Do Business Better School.

Lisette Tol moet er niet veel van hebben: high end business coaches. Waarom? Er is niks mis met een stevig tarief. Maar er zijn veel teveel coaches in de markt, die veel geld vragen en weinig waarde toevoegen.Zelf helpt Lisette maximaal 10 ondernemers per jaar. Het doel: meer resultaat, zonder veel harder te gaan werken. Haar filosofie is gebaseerd op ontspannen ondernemen. De perfecte mix vinden van je ideale eigen rol, slimme strategie, hard werken maar ook zeker in het hier en nu genieten van het leven.Scaling Up kan in de prullenbak: Lisette vind die methode te dogmatisch en bureaucratisch. Ze levert liever maatwerk. Wat is er in de specifieke situatie van een ondernemer, nodig om het vliegwiel te vinden? Hoe kom je tot het punt dat je zaak, zonder keihard te moeten werken, als een zonnetje gaat draaien? Elke topsporter heeft een coach, dus waarom zou je als ondernemer niet eens serieus overwegen om je 'rond te laten schoppen' door iemand van buiten? Maar kies dan wel iemand die 'for real' is. Ik heb met veel plezier gesproken met Lisette en ik hoop dat jij ook geniet van haar inzichten! GerhardCALLS TO ACTION

In unprecedented release, AIIA's FOIA request yields the first complete set of EB-5 filing data, exposing the true scale of visa backlogs.View the full article here.Subscribe to the IMI Daily newsletter here. 

In this Q&A episode, Alex (@AlexHormozi) gives founders raw, unfiltered advice on scaling, covering everything from seasonal hiring models and family business drama to overbuilt upsells and why “doing more of what works” is still the best growth plan.Welcome to The Game w/Alex Hormozi, hosted by entrepreneur, founder, investor, author, public speaker, and content creator Alex Hormozi. On this podcast, you'll hear how to get more customers, make more profit per customer, how to keep them longer, and the many failures and lessons Alex has learned and will learn on his path from $100M to $1B in net worth.Wanna scale your business? Click here.Follow Alex Hormozi's Socials:LinkedIn | Instagram | Facebook | YouTube | Twitter | AcquisitionMentioned in this episode:Get access to the free $100M Scaling Roadmap at www.acquisition.com/roadmap

Send us a textIn this episode of the Smart Biotech Scientist Podcast, host David Brühlmann dives into continuous bioprocessing - a major shift in biologics manufacturing that's turning traditional batch processes into streamlined, real-time operations.Imagine running your biologics process non-stop for 30 days, with smart monitoring and smaller, more efficient systems replacing massive reactors. It's not just possible - it's already happening across the industry, from Amgen's 80% smaller facility to Sanofi's modular "Factory of the Future."David explores how companies - big and small - are increasing productivity, cutting costs, and reducing waste through continuous strategies. You'll also hear about enabling technologies, phased implementation approaches, and the challenges teams are navigating as they make the shift.Top 3 Takeaways:Efficiency & Cost Savings Are Real: Amgen's results speak volumes: 80% smaller footprint, faster deployment, and cost reductions of over 60% per gram of protein.It's Not Just for Big Pharma: Small and mid-sized biotechs are embracing continuous processes to stay competitive - gaining speed, flexibility, and lowering production costs without massive infrastructure.You Don't Have to Go All In: Challenges like cost, complexity, and workforce readiness exist - but many companies are succeeding with hybrid models, applying continuous techniques step-by-step.What's your take on continuous manufacturing? Tune in, share your thoughts, and join the conversation about the future of biotech production.Next step:Transform your bioprocess development strategy with a complimentary consultation. Schedule your expert session: https://bruehlmann-consulting.com/callReady to scale up? Join our exclusive 1:1 Strategy Call and learn proven methods to reduce development and manufacturing costs while maintaining product quality. Our bioprocess experts will help you navigate complex bioprocessing challenges and regulatory requirements. Limited spots available: https://stan.store/SmartBiotech

Welcome back to the ProfitSchool podcast Business Unfiltered with Mercer and Jeff Sauer. Today's topic is Breaking Bottlenecks In An AI-First Business Today's discussion centers on identifying and eliminating bottlenecks within an AI-first business framework. Bottlenecks can exist even in AI-driven companies, often stemming from limiting beliefs or organizational structure.    The conversation highlights the relevance of capability and capacity in pinpointing bottlenecks. They note AI's potential to significantly enhance both capability and capacity within a business.  Mercer and Jeff discuss practical strategies, such as using loom videos to delegate tasks effectively.  The episode concludes by advocating for a shift toward AI-first thinking to streamline processes and boost efficiency.   

Piotr Tomasik, Co-Founder & President of TensorWave, who’s powering the next wave of AI compute with AMD-optimized super-cloud infrastructure and building Las Vegas into a … Read more The post Powering the AI Revolution: How TensorWave’s AMD Supercloud Is Solving Compute Bottlenecks appeared first on Top Entrepreneurs Podcast | Enterprise Podcast Network.

The voluntary carbon markets have been a source of curiosity for me. There's been a lot of hope that the market would mature and offer a reliable way to offset emissions that otherwise could not be eliminated. Reliability has been the problem, however. Not knowing which carbon reduction projects are additive and truly remove or reduce carbon has held this market back, and I've been excited to learn about how new technologies will enable the reliability that's needed. There are many people working on this problem. Dr. Allister Furey, Founder and CEO of Sylvera is one, and I was excited to learn about his company's approach to removing carbon market bottlenecks and accelerating the investment in carbon projects. As he says it's a mix of software, data, AI, and analysis that have helped Sylvera work with large clients and unlock enormous investments. Hope you learn as much as I did. Enjoy.On today's episode, we cover:[03:37] Allister's background and entrepreneurial journey[05:54] Sylvera's founding and initial business concept[10:42] Exploration of the desert greening concept[11:27] Sylvera's current business offerings[17:10] Sylvera's progress, reach, and client base[20:24] Corporate climate commitment trends[22:44] Corporate demand for carbon projects[26:12] Policy market expectations[29:07] Climate investor sentiment[30:33] Future outlook for carbon marketsResources Mentioned Sylvera Connect on LinkedInAllister FureyJason RissmanKeep up with Invested In ClimateSign up for our NewsletterLinkedInInstagramBlueskyHave feedback or ideas for future episodes, events, or partnerships?Get in touch!

More and more people have been saying that we might have AGI (artificial general intelligence) before 2030. Is that really plausible? This article by Benjamin Todd looks into the cases for and against, and summarises the key things you need to know to understand the debate. You can see all the images and many footnotes in the original article on the 80,000 Hours website.In a nutshell:Four key factors are driving AI progress: larger base models, teaching models to reason, increasing models' thinking time, and building agent scaffolding for multi-step tasks. These are underpinned by increasing computational power to run and train AI systems, as well as increasing human capital going into algorithmic research.All of these drivers are set to continue until 2028 and perhaps until 2032.This means we should expect major further gains in AI performance. We don't know how large they'll be, but extrapolating recent trends on benchmarks suggests we'll reach systems with beyond-human performance in coding and scientific reasoning, and that can autonomously complete multi-week projects.Whether we call these systems 'AGI' or not, they could be sufficient to enable AI research itself, robotics, the technology industry, and scientific research to accelerate — leading to transformative impacts.Alternatively, AI might fail to overcome issues with ill-defined, high-context work over long time horizons and remain a tool (even if much improved compared to today).Increasing AI performance requires exponential growth in investment and the research workforce. At current rates, we will likely start to reach bottlenecks around 2030. Simplifying a bit, that means we'll likely either reach AGI by around 2030 or see progress slow significantly. Hybrid scenarios are also possible, but the next five years seem especially crucial.Chapters:Introduction (00:00:00)The case for AGI by 2030 (00:00:33)The article in a nutshell (00:04:04)Section 1: What's driven recent AI progress? (00:05:46)How we got here: the deep learning era (00:05:52)Where are we now: the four key drivers (00:07:45)Driver 1: Scaling pretraining (00:08:57)Algorithmic efficiency (00:12:14)How much further can pretraining scale? (00:14:22)Driver 2: Training the models to reason (00:16:15)How far can scaling reasoning continue? (00:22:06)Driver 3: Increasing how long models think (00:25:01)Driver 4: Building better agents (00:28:00)How far can agent improvements continue? (00:33:40)Section 2: How good will AI become by 2030? (00:35:59)Trend extrapolation of AI capabilities (00:37:42)What jobs would these systems help with? (00:39:59)Software engineering (00:40:50)Scientific research (00:42:13)AI research (00:43:21)What's the case against this? (00:44:30)Additional resources on the sceptical view (00:49:18)When do the 'experts' expect AGI? (00:49:50)Section 3: Why the next 5 years are crucial (00:51:06)Bottlenecks around 2030 (00:52:10)Two potential futures for AI (00:56:02)Conclusion (00:58:05)Thanks for listening (00:59:27)Audio engineering: Dominic ArmstrongMusic: Ben Cordell

Welcome back to The Vertical Space for our second conversation with Richard Aboulafia, an insightful voice on all things aerospace and defense.  This episode dives deeper than ever into the aerospace and defense supply chain: globalization, vulnerabilities, titanium, rare earth elements, and why Tier 1 integrators may be losing their place in the industry. We explore how shifting geopolitics, material dependencies, and evolving national strategies are redrawing the map of the aerospace and defense industrial base. Richard breaks down why Europe is accelerating its push for industrial sovereignty, how China's role in rare earths and Russia's role in titanium are creating ripple effects, and what the decline of Tier 1 integrators means for the rest of the industry. We also unpack the promise of Collaborative Combat Aircraft, new defense spending priorities, and ATC modernization. This is a wide-ranging and nuanced discussion on the forces disrupting aerospace as we know it, and where the opportunities lie in the new aerospace order.

Building a business is one thing; holding your vision steady through growth, pressure, and uncertainty is something else entirely.   Alex Raymond sits down with John Sampogna, the co-founder and CEO of Wondersauce, to talk about what the entrepreneurial journey really demands once the excitement wears off. John shares how he built a 100-person agency, why he created a “mental balance sheet” to manage the emotional costs of leadership, and what he learned from selling his company while staying true to its original vision. How do you scale without losing yourself in the process? How do you know when a business opportunity is truly right for you, not just financially but personally?   John also digs into the realities of leadership that rarely get talked about: why bottlenecks are your best feedback loop, why approachability matters more than you think, and why a thriving business culture starts with making space for mistakes. He challenges entrepreneurs to rethink what scale really means in the age of AI and shares why lasting success depends on more than just growth metrics.   If you are building a business and want to do it with intention, resilience, and clarity, this conversation will give you a much-needed shift in perspective.   Episode Breakdown: 00:00 Introduction 01:14 Holding a Long-Term Vision Through Growth and Uncertainty 03:49 Selling Wondersauce and Choosing the Right Partner 09:01 How the Founder Role Changes After Acquisition 10:02 Navigating Earn-Outs, COVID, and the Rise of AI 12:10 Building a Mental Balance Sheet for Emotional Resilience 15:00 Scaling a Business Without Burning Out 19:25 Bottlenecks as a Signal for Operational Change 22:05 Creating Psychological Safety and Strong Leadership 25:59 Smart Marketing and True Differentiation for Entrepreneurs 32:44 How AI Is Redefining the Idea of Scale   Links Connect with  John Sampogna: LinkedIn:https://www.linkedin.com/in/johnsampogna/ Website: https://www.wondersauce.com/   Connect with Alex Raymond: LinkedIn: https://www.linkedin.com/in/afraymond/ Website: https://amplifyam.com/ HiveCast.fm is a proud sponsor of The Conscious Entrepreneur Podcast. Podcast production and show notes provided by HiveCast.fm

The U.S. DOT plans to set a policy for oversight of autonomous vehicles – just as one company gears up to test them on Texas roadways. Also, all traffic jams are not created equal, and some stand out nationally. An ATRI study has identified the nation's worst traffic bottlenecks. 0:00 – Newscast 10:11 – A turning point for autonomous trucks? 24:49 – The nation's worst traffic bottlenecks

Apr 25, 2025 – AI and data centers are set to drive a massive surge in U.S. electricity demand, with usage expected to jump 4–5% per year through 2030 and data centers alone consuming up to 12% of total power. Energy expert Robert Bryce...

Briana Birkholz and Joe Lynch discuss blind spots & bottlenecks: unmasking the hidden enemies of supply chain. Briana is the Vice President of Product Management for the 3PL market segment at SPS Commerce, the world's leading retail network, connecting trading partners around the globe to optimize supply chain operations for all retail partners. About Briana Birkholz Briana Birkholz is the Vice President of Product Management for the 3PL market segment at SPS Commerce. With a passion for overcoming supply chain and logistics challenges, Briana is committed to addressing the distinct needs of customers through comprehensive, full-service solutions. Briana's extensive experience in driving innovation, strategic development and execution consistently delivers outstanding results for third-party logistics companies. About SPS Commerce SPS Commerce is the world's leading retail network, connecting trading partners across the globe to optimize supply chain operations for all stakeholders in the retail ecosystem. The company enables data-driven partnerships through innovative cloud-based technology, customer-centric service, and a team of accessible industry experts—allowing clients to focus on their core business. With over 45,000 recurring revenue customers spanning retail, grocery, distribution, supply, manufacturing, and logistics, SPS Commerce powers a vast and growing global retail network. Key Takeaways: Blind Spots & Bottlenecks: Unmasking the Hidden Enemies of Supply Chain Briana Birkholz and Joe Lynch discuss blind spots & bottlenecks: unmasking the hidden enemies of supply chain. The hidden enemies include the following: Inconsistent Time to Revenue: The Silent Growth Killer - Lengthy onboarding processes erode cash flow and strain customer relationships, highlighting evolving customer expectations. SPS Commerce's "plug-and-play" solutions drastically reduce onboarding time from months to days. The Cost of Chaos: Inconsistent Order Intake - Managing orders through disparate channels (phone, email, portals, PDFs) breeds errors and jeopardizes SLAs due to human error. SPS Commerce standardizes order formats for improved efficiency and control. Decoding Retailer Complexity: Unravel the challenges of adhering to intricate retailer requirements (packing slips, labels, routing guides, ASN timing) and the costly consequences of non-compliance (chargebacks, damaged relationships, lost shelf space). SPS Commerce automates document generation and validation to ensure first-time compliance. SPS Commerce is the world's leading retail network, connecting trading partners around the globe to optimize supply chain operations for all retail partners. SPS Commerce brings the following advantages: Industry Leader in Cloud-Based EDI Solutions: SPS Commerce specializes in cloud-based supply chain management, helping retailers, suppliers, and logistics providers automate and streamline their operations through advanced EDI and data analytics tools. Demonstrated Consistent Growth as a High-Performing Public Company: SPS Commerce has a long and consistent track record of growth, primarily organic, underscoring its position as a strong performer on NASDAQ (ticker: SPSC). Global Presence with Local Support: Headquartered in Minneapolis, SPS has expanded internationally with offices in major cities like Toronto, Melbourne, Amsterdam, and Hong Kong, supporting a worldwide customer base with localized service. Growth via Smart Acquisitions: Strategic buys like Data Masons, InterTrade, and SupplyPike have allowed SPS to broaden its tech stack and deepen its value across the retail supply chain ecosystem. Recognized for Culture and Innovation: Known for its positive workplace environment, SPS was ranked the best large workplace in Minnesota in 2015 and continues to invest in talent and innovation to drive forward-thinking supply chain solutions. Learn More About Blind Spots & Bottlenecks: Unmasking the Hidden Enemies of Supply Chain Briana Birkholz | Linkedin SPS Commerce | Linkedin SPS Commerce Woods Distribution Case Study Arcadia Cold Storage & Logistics Case Study The Logistics of Logistics Podcast If you enjoy the podcast, please leave a positive review, subscribe, and share it with your friends and colleagues. The Logistics of Logistics Podcast: Google, Apple, Castbox, Spotify, Stitcher, PlayerFM, Tunein, Podbean, Owltail, Libsyn, Overcast Check out The Logistics of Logistics on Youtube  

In this insightful episode of the E-commerce Evolution Podcast, host Brett Curry sits down with Jhana Li (https://www.linkedin.com/in/jhana-li), founder of Spyglass Ops, to tackle one of the biggest challenges holding back growing businesses: operational constraints. While many entrepreneurs excel at product development and marketing, they often hit a ceiling when it comes to building operational systems and processes. Jhana shares her expertise as a transformational operations consultant who has helped hundreds of seven and eight-figure businesses scale by creating systems that allow founders to work on their business rather than in it.—Sponsored by OMG Commerce - go to (https://www.omgcommerce.com/contact) and request your FREE strategy session today!—Chapters: (00:00) Introducing Jhana & SpyGlass Ops (04:21) Common Operational Problems Founders Face(07:52) Developing a Strategic Vision to Break Through Bottlenecks(14:39) Setting Yourself Apart From Competitors(17:52) Vision Alignment With Your Team(20:51) Hiring and Onboarding the Right People(32:31) Structuring An Effective Hiring Process(40:28) Coaching a High-Performing Team(46:04) When To Let Underperformers Go(50:43) Final Thoughts—Connect With Brett: LinkedIn: https://www.linkedin.com/in/thebrettcurry/ YouTube: https://www.youtube.com/@omgcommerce Website: https://www.omgcommerce.com/ __Past guests on eCommerce Evolution include Ezra Firestone, Steve Chou, Drew Sanocki, Jacques Spitzer, Jeremy Horowitz, Ryan Moran, Sean Frank, Andrew Youderian, Ryan McKenzie, Joseph Wilkins, Cody Wittick, Miki Agrawal, Justin Brooke, Nish Samantray, Kurt Elster, John Parkes, Chris Mercer, Rabah Rahil, Bear Handlon, Trevor Crump, Frederick Vallaeys, Preston Rutherford, Anthony Mink, Bill D'Allessandro, Bryan Porter and more

Have you ever been stuck in a traffic jam? A big one, like on a major highway that runs through a large city? You know, the good ones where you're parked on the highway next to the speed limit sign that mocks you with a limit of 70 miles per hour. If you make progress at all, it's only inches, or if you're really lucky, feet at a time.Then, all of a sudden, you get past whatever the cause was—the major off-ramp, the accident, or the toll booth/bridge—and the traffic parts like Moses and the Red Sea. You're free, quickly forgetting the stress and frustration of the mess behind you. You have just experienced a bottleneck.Welcome to another episode of the O'Connor Bootstrap Podcast! If you enjoyed the content, drop a comment, and don't forget to give us a 5-star rating on your preferred platform.A massive thank you to Wintergatan for providing our incredible intro/outro music at no cost. Check out their amazing work on YouTube at youtube.com/@Wintergatan.Download the track "Moon And Star" by Wintergatan Build Tracks for free at www.wintergatan.net and get a free license for video use at www.wintergatan.net.Chat with us on DiscordSupport us:BuyMeACoffee.com/BootstrapPayPal.me/IocPodPatreon.com/IocPodExplore our Patreon tiers, including the $5/month Bootstrapper Community Explorer Tier for ad-free content Generous supporters at $25/month and up have a chance to be featured as valued guests.Check out our podcast on YouTube.com/OConnorBootstrap for visual content.This episode is part of the O'Connor Bootstrap Podcast by Atheoz Business Solutions. Visit Atheoz.com/IocPod for more, and find related blogs at Atheoz.com/OConnor-Bootstrap-Blog. Thank you for being part of our community! Until next time, I am your friendly neighborhood Entrepreneur, Isaiah O'Connor, signing off.

In todays episode Will talks about a long day of coaching calls that he had with clients and some key themes and bottlenecks that clients at all levels have had in the businesses, and how you can learn from it.

Cut through workplace red tape—without burning bridges. Ever feel like getting anything done at work means running a marathon through molasses? You're not alone. In this episode, Amy and Jason go full throttle on the soul-sucking systems that slow teams down and wear people out. Sparked by a listener stuck in a tangle of outdated processes, they unpack how well-meaning rules morph into momentum killers—and what to do when speaking up feels like you're just making it worse. With a blend of straight talk, lived experience, and a whole lot of Radical Candor, they offer a new playbook: lead with curiosity, advocate with clarity, and stop waiting for permission to fix what's broken. This one's for anyone who's tired of navigating systems built to say "no" when the work is begging for a "hell yes." Get all of the show notes at RadicalCandor.com/podcast. Episode Links: Transcript Aman Kochar Change Enabler | Radical Candor Podcast 7 | 9 Get Shit Done Step 4 — Push Decisions Into the Facts 4 | 10 How to Practice Radical Candor With Your Boss 3 | 9 How To Give Candid Feedback With the Radical Candor CORE Method Connect: Website Instagram TikTok LinkedIn YouTube Chapters:(00:00:00) IntroductionJason and Amy introduce a listener's question about streamlining approval processes.(00:01:36) When Process Becomes a Trust KillerHow approval bottlenecks erode trust and lead to burnout.(00:02:46) Approvals That Make SenseDifferentiating between meaningful and meaningless approvals.(00:06:10) The Inertia of BureaucracyWhy process isn't evil—but rarely gets reexamined when it should.(00:07:50) Communicating Up Without EscalatingHow to discuss change without putting managers on the defensive.(00:13:22) What Problem Is the Process Solving?A practical script for questioning approval thresholds constructively.(00:15:45) Software Purchase SagaA story about approvals that made no one's life better.(00:20:19) Getting Specific vs. Talking in PatternsWhy it's better to present one example rather than broad frustration.(00:26:01) Role Play: The Rental Car ScenarioHow to challenge a flawed process without triggering a shutdown.(00:34:38) Finding a Third WayCreating solutions that meet both employee and organizational goals.(00:37:45) Radical Candor TipsTips to help you navigate bureaucracy with clarity, care, and results.(00:43:34) Conclusion Learn more about your ad choices. Visit megaphone.fm/adchoices

This week we are joined by Jason Foster, CEO of Ori Biotech to talk about the future of CGT and why scalable strategic manufacturing is in a make or break moment, his experience scaling Indivior from 5 to 1,100 people culminating in a £3B exit and the powerful culture behind that growth, the Bluebird Bio acquisition and what it means for CGT investment today, and why he is deeply optimistic about Ori Biotech's automated, closed platform. A must-listen for anyone building, investing in, or scaling the next era of biotech.

Reuters is reporting that Toyota's hybrid models are in such high demand that parts shortages have led to monthslong delays – or worse.

Ever wondered how to unlock a whopping 10 million dollars in your business just by rethinking your time management? In this episode of Thrive Loud with Lou Diamond, we dive into the fascinating world of business operations with Jhana Li, owner of SpyGlass Ops. Known for empowering over a hundred businesses to scale past 7 and 8 figures, Jhana shares her insights on how founders can regain personal freedom while skyrocketing their revenue. Key highlights include: Discover the "magic vending machine" syndrome and how it's sabotaging your leadership effectiveness. Learn about the top four bottlenecks holding 90% of online entrepreneurs back and how to overcome them. Explore the transformative power of AI in operational efficiency and why it's time to transition your team from ‘doers' to ‘thinkers'. Jhana's personal practices for thriving, even when the going gets tough, such as her commitment to spending time outdoors and working with a coach. Jhana also generously offers a free copy of her ebook to listeners who DM her with the code "ThriveLoud" on Instagram. This ebook delves deeper into the six core operational pillars that can transform a business. So, tune in and learn how you can apply these actionable strategies to elevate your business operations and free up your time for visionary thinking.   TIMESTAMPED OVERVIEW 00:00 Accidental CEO to Operations Expert 05:12 Founder Challenges: Vision and Alignment 09:24 Time Mismanagement Costing Millions 11:45 Founder-Dependent Leadership 14:59 "AI: Shifting From Doers to Thinkers" 17:07 "Embracing Efficiency and Leadership" 22:47 Speakeasy Pub Crawl Stroll 23:37 Episode Opening and Closing Music

In this insightful episode of Hoots on the Ground with No Bullshido, Adam Hoots is joined by Hal Macomber, a respected leader, coach, and influential figure in the field of Lean Construction. Hal shares over 35 years of experience pioneering Lean practices, offering profound insights into continuous flow construction, human-centered leadership, and the power of engaging frontline workers. Hal reflects on the industry's progress, emphasizing that while Lean has made significant strides, substantial work remains to integrate its core principles universally. He introduces the concept of "Continuous Flow Construction," explaining the critical importance of designing projects with a clear operational rhythm or "Takt," thereby dramatically improving efficiency and reducing project duration. Key insights from this episode include: How continuous flow construction, designed around Takt time, can revolutionize project delivery by dramatically reducing cycle times, sometimes from weeks to mere hours. The essential role of operational science, including Little's Law, the Law of Bottlenecks, the Law of Variation, and Kingman's Formula, in enhancing production planning and control. The true meaning of "Kaizen," emphasizing personal and collective growth through continuous learning and improvement, extends beyond simply eliminating waste. The critical need to equip trade workers, whom Hal respectfully refers to as "performers," with the skills, mindset, and agency to execute Lean principles in the field effectively. The limitations of traditional scheduling methods (e.g., CPM) necessitate the adoption of collaborative, inclusive scheduling practices that fully integrate Lean methodologies. Hal highlights the transformational power of true worker agency and engagement, urging leaders to foster environments where frontline workers actively contribute to problem-solving and continuous improvement. He challenges conventional wisdom by asserting that push methods are never beneficial, advocating instead for a system based entirely on pull and flow. Through stories and practical advice, Hal and Adam encourage listeners to shift from rigid, hierarchical structures toward empathetic, human-centered approaches that harness the full potential of every team member. This episode is a crucial listen for construction leaders, Lean practitioners, and anyone passionate about driving deep, sustainable improvement through genuine human engagement and systemic thinking. NOTABLE EPISODE QUOTES: “Continuous flow construction isn't just about efficiency; it's about human engagement and empowerment.” – Hal Macomber “Real Kaizen is using every opportunity to grow ourselves, not just the system.” – Hal Macomber “Don't just respect people—respect human nature.” – Hal Macomber   ABOUT HOOTS ON THE GROUND PODCAST:The Lean Builder's absolutely, positively NO Bullshido podcast. Join host Adam Hoots and his guests as they dig deep into topics that matter most to those in the field. With stories from the trenches, lessons learned, and plenty of laughter, this podcast is for the men and women doing the hands-on work of construction. RESOURCE LINKS MENTIONED IN THIS EPISODE: ·        The Lean Builder | Blog, book, resources, news, and events. ·        Toyota Kata | Methodology for systematic continuous improvement. ·        Little's Law, Law of Variation, Law of Bottlenecks, and Kingman's Formula (overview of all laws) | Operational science fundamentals. GUESTS FEATURED IN THIS EPISODE: ·        Adam Hoots | LinkedIn  | Podcast host, Lean Construction Shepherd at ConstructionACHEsolutions. ·        Hal Macomber | LinkedIn  | Lean construction pioneer, influential Lean coach, and mentor.

Watch This NEXT: https://youtu.be/dkixSG4hVRIMost people build a business that caps at $10K/mo.Brook Hiddink built a business that does over $2 million/month.The difference?He didn't just create a coaching offer.He built an ecosystem that drives revenue.This isn't the game most people are playing.Most online business owners are selling overpriced info, begging for likes, and stuck fulfilling 1:1 calls.Meanwhile Brook built a scalable system that brings in cold traffic, sells high-ticket, delivers results at speed, and scales with almost no friction.And here's the truth:You can literally steal his model.We just dropped a full breakdown on the podcast.You'll see exactly:– How he gets 3x better client results than anyone else– How he makes his competitors irrelevant overnight– How to build a real backend that drives revenue constantly– and how to set up a content + offer machine that does the heavy lifting for youIt's all in the episode.Don't just consume it.Copy it.Build it.Use it.Smash that like button for more episodes like this!(00:00) Intro(01:19) The Secret to Brooke's Success(04:02) The Advantage of Entrepreneurship(07:57) Brook's Unique Business Model(09:21) The Psychology of High-Ticket Coaching Clients(12:02) Becoming One of the Top E-Commerce Coaching Programs(14:54) What Makes Brooke's Coaching Program Successful(18:53) Scaling Client Support(20:33) How AI is Helping Brooke's Business Grow(25:00) How AI is Disrupting E-Commerce(28:41) Brook's Decision to Build a Software Company(34:15) Brook's Plans for a Big Software Exit(37:08) Long-Term Vision for Business Growth(45:59) The Role of Fear and Insecurity in Entrepreneurship(48:33) Dubai: The Best Place for Entrepreneur Networking?(52:07) How Family and Relationships Fuel Entrepreneurial Success(56:03) The Power of Focus: One Goal, One Path(59:11) The Bottlenecks of Scaling a VSL Funnel(01:05:43) Brook Hiddink's Sales Process(01:09:01) Using AI to For Sales & Marketing(01:13:04) How AI is Increasing Business Efficiency and Growth(01:17:55) The Role of AI in the Future of Personal Branding(01:22:31) The Rise of Info-Education Programs and VC Interest(01:25:25) The Maturation of the Coaching IndustrySupport the show

If you've built the team, implemented the systems, and done everything you thought would make scaling easier—but you're still overwhelmed and stretched thin—this episode is for you. Because here's the truth: Your business is keeping you stuck.

Genevieve Hayes Consulting Episode 56: How a Data Scientist and a Content Expert Turned Disappointing Results into Viral Research It’s known as the “last mile problem” of data science and you’ve probably already encountered it in your career – the results of your sophisticated analysis mean nothing if you can’t get business adoption.In this episode, data analyst Dr Matt Hoffman and content expert Lauren Lang join Dr Genevieve Hayes to share how they cracked the “last mile problem” by teaming up to pool their expertise.Their surprising findings about Gen AI’s impact on developer productivity went viral across 75 global media outlets – not because of complex statistics, but because of how they told the story.Here’s what you’ll learn:Why the “last mile” is killing your data science impact – and how to fix it through strategic collaboration [01:00]The counterintuitive findings about Gen AI that sparked global attention (including a 40% increase in code defects) [13:02]How to transform “disappointing” technical results into compelling business narratives that drive real change [17:15]The exact process for structuring your insights to keep executives engaged (and off their phones) [08:31] Guest Bio Dr Matt Hoffman is a Senior Data Analyst: Strategic Insights at Uplevel and holds a PhD in Physics from the University of Washington. Lauren Lang is the Director of Content for Uplevel and is also a Content Strategy Coach for B2B marketers. Links Connect with Matt on LinkedInConnect with Lauren on LinkedInCan Generative AI Improve Developer Productivity? (Report) Connect with Genevieve on LinkedInBe among the first to hear about the release of each new podcast episode by signing up HERE Read Full Transcript [00:00:00] Dr Genevieve Hayes: Hello, and welcome to Value Driven Data Science, the podcast that helps data scientists transform their technical expertise into tangible business value, career autonomy, and financial reward. I’m Dr. Genevieve Hayes, and today I’m joined by Lauren Lang and Dr. Matt Hoffman. Lauren is the Director of Content for Uplevel and is also a Content Strategy Coach for B2B marketers.[00:00:26] Matt is a Data Analyst and Product Manager at Uplevel and holds a PhD in Physics from the University of Washington. In this episode, we’ll uncover proven strategies for transforming complex technical findings into compelling business narratives that drive real organizational change. So get ready to boost your impact, earn what you’re worth, and rewrite your career algorithm. Lauren, Matt, welcome to the show.[00:00:55] Lauren Lang: Hi Genevieve, thank you so much.[00:00:57] Dr Matt Hoffman: Thanks for having us. Excited to be here.[00:01:00] Dr Genevieve Hayes: In logistics, there’s a concept known as the last mile problem. Which refers to the fact that the last stage of the delivery process of people or goods is typically the most complex and expensive while also being the most essential. For example, it’s typically easier and cheaper to fly a plane full of packages from Australia to the U.[00:01:22] S. than it is to transport those packages by road to their final destinations within the U. S. Yet if you can’t distribute those packages once they arrive in the U. S., they may as well have never left Australia. It’s for this reason that supply chain managers typically focus a disproportionate amount of effort on planning those final miles.[00:01:43] Data scientists also face their own last mile problem. Despite many data science projects requiring sophisticated modelling and analysis techniques, the most difficult part of data science is often communicating the results of those projects to senior management and gaining adoption of the project from the business.[00:02:04] That is the final stage. Yet, unlike in logistics, This is also the stage where data scientists typically focus the least amount of effort, much to the detriment of their work and their careers. Lauren and Matt, the reason why we’ve got both of you as guests in today’s episode is because you’ve recently backed this trend and pooled your combined experience in communications and data science with outstanding results.[00:02:33] And this is actually the first time I’ve come across a data scientist working directly with the communications expert to address the data science last mile problem. Although, it probably should be far more common. So to begin with, Matt, can you give us an overview of the data science project you were working on and how you came to team up with Lauren when delivering the results?[00:02:57] Dr Matt Hoffman: So we work at Uplevel and Uplevel is a company that pulls in data about software engineers and we help tell those data stories to our customers. Senior leaders of engineering, like software engineering firms so that they can make data driven decisions and drive change within their organizations.[00:03:17] One of the things that’s really come up in the past year is this full topic of gen. AI software engineers being able to talk to an AI assistant to help them write code and the thinking was, oh, this is a silver bullet. We’re just going to be able to. Turn on this system. Our developers are going to be more productive.[00:03:36] Instantly. The code is going to get better. There’s going to be nothing but greenfield. If we just turn this on, it’s a no brainer, we heard those questions and we don’t develop our own gen AI tool. But what we do have is data about software engineers and how they spend their time, the effectiveness of their work.[00:03:54] Are they able to deliver more? Are they getting more things done? How’s the bug rate of their code? So it was natural for us to go explore that problem and really try to understand what is the impact of Gen AI on software engineers. That’s the problem that we were facing. So I work with our data science team.[00:04:13] I’m not actually on our data science team, but worked with them to go do this analysis to really try to understand how do people compare to themselves and what changes do we see within this. And then we pulled in Lauren to go start showing off what we found. And that’s where that story kicked off.[00:04:32] Dr Genevieve Hayes: Prior to working with Lauren, what are some of the challenges you encountered in communicating the results of your analysis?[00:04:38] Dr Matt Hoffman: Well, it’s always a tricky one when the answer is complicated. The real fundamental place that we at Uplevel are at is that this is human data. While we may be able to measure timestamps to a millisecond, This is all still predicated that this is people data and people do weird things. And the data is messy and the data is muddy.[00:05:03] So there’s the constant battle of, well, what can we trust? We’re looking for correlations and, you know, you squint to see if like, there’s something there you peel back a layer and then there’s something more, but people data is hard to work with. So that’s really a skill of our data science team to help pull that back.[00:05:20] But we were. Kind of struggling to make heads and tails of what were the real conclusions. And Lauren really helped clarify that story for us and get that communication there.[00:05:30] Dr Genevieve Hayes: People are irrational. I mean that’s the big problem with us. Before you did this, had you ever made some massive mistake because you just assumed people were rational when they worked?[00:05:44] Dr Matt Hoffman: It’s funny stuff so sometime when some work’s becoming delayed and you go ask for the root cause and it’s like, oh, someone’s saying, I thought I did that and I forgot. Like, I never hit the button. That’s the kind of, people data that we see is that, like, yeah, that happened.[00:05:59] It was late, but that was just because you forgot to hit the button. People’s behavior is really funny. So yeah, we just have to kind of take that into account that everybody’s different. That’s okay. And we need to bake that into our analysis, that people work differently and not try to over fit one model that applies to everybody .[00:06:18] Dr Genevieve Hayes: Yeah, I actually wrote a LinkedIn post a while ago saying, people are a problem with data and wouldn’t it be nice to just be dealing with mechanical processes? And I had someone reply to that post who works at a water agency where they don’t deal with people, it’s, water going through pipes, and they said, well actually mechanical processes are just as annoying, they just are annoying in different ways because you have the sensors malfunctioning and all this.[00:06:44] You can dream about not dealing with people but Machines cause problems too .[00:06:48] Dr Matt Hoffman: Yeah, that’s exactly right. So you just have to know that going in and know that it’s going to be messy. And plan for that.[00:06:56] Dr Genevieve Hayes: So Lauren, in your content strategy coaching work you’ve done a lot of work with software as a service companies. And as Matt said, Up Level itself is a company that Works with engineers and probably has a lot of engineers as its employees. So, I’d imagine you’ve worked with a lot of very technical people throughout your career.[00:07:20] Lauren Lang: I have. Yes.[00:07:21] Dr Genevieve Hayes: What are some of the biggest issues you’ve noticed in how technically minded people, especially data scientists and data analysts, present their findings to business stakeholders?[00:07:33] Lauren Lang: It’s very funny because I think that there is a lot of similarities actually between how data scientists might present their findings and how a lot of marketers present their findings. And you would think like, Oh, marketing is so much more. We have our thumb on the pulse of the business.[00:07:48] And, marketers are so much more business driven, but I think, anyone who is looking at data as marketers, we look at data too. We are. Not data scientists, but there’s a fair amount of data science, sometimes in marketing. And there’s a lot of data analysis that happens. And I think there is just this tendency sometimes to.[00:08:07] Get very myopic and get very focused on your own specific context in looking at the data and forgetting that there is probably a larger story that the data existed to tell. I see this a lot. 1 of the. Challenges that I see a lot is, marketers will go into a meeting with a CEO and they will have dashboard after dashboard and chart after chart.[00:08:31] And there is a very sort of distinct look on an executive space when. You’ve shown them three charts in a row or three dashboards and it’s like a completely blank look and you know that they are literally anywhere else. but in the conversation and it’s a little bit of like a death now.[00:08:51] And so I think for anyone who likes to geek out on data, whatever part of the business you’re in, you have to remember that there is this larger value story that you need to be telling, and you need to be showing that data and be mindful of the context in which you’re showing that data.[00:09:08] To what end? Rather than just taking people down the rabbit hole with you. I think sometimes there’s an assumption that everyone should be as interested about all of the nuances and slight, variances in the data as you are, and that’s not always the case.[00:09:24] Dr Genevieve Hayes: Yeah the way you’re describing that death knell face, yeah, I’ve seen that before. And worse than that is when the people you’re presenting to start playing with their phones. Then you definitely know that you’ve failed.[00:09:35] Lauren Lang: Might as well call it right there.[00:09:37] Dr Genevieve Hayes: Yeah, , just pack up and walk out of the room at that point.[00:09:39] Lauren Lang: That’s right. That’s right.[00:09:42] Dr Genevieve Hayes: So, I assume you’ve pointed out these issues to technical people who you’ve worked with. How do they typically respond when you say, hey, not everyone’s as geeky as you?[00:09:53] Lauren Lang: I think there’s a way to couch that in a way, because I have a lot of empathy for it. Geeky people are excited about what we do. I mean, there’s a passion there. And so you don’t want to not communicate that passion.[00:10:05] I think that’s really important. And, there’s some exciting results or, even. Not exciting results that you didn’t think were going to pan out, but there’s always a story to tell, but it’s just, can you tell it maybe at a slightly more abstract level of specificity, maybe? Or can you tell it with an understanding of the context in which your audience exists[00:10:28] I think there’s just a lot of tendency to Just forget that not everyone brings the same experiences and the same understanding and the same depth of knowledge to the table. And so the best way that the stories we tell with data can be impactful is to tell them in context and to be able to pull out the important parts that really can bring the message home.[00:10:50] Dr Genevieve Hayes: So, put yourself in the shoes of your audience,[00:10:53] Lauren Lang: absolutely. You should always have empathy with the person you’re trying to communicate to. I think it was Kim Scott said that communication happens at the listener’s ear and not the speaker’s mouth. That’s where meaning is made. It’s really important to keep that in mind as you are stepping into the shoes.[00:11:09] Of the communicator,[00:11:11] Dr Genevieve Hayes: so, I’d like to now take a deep dive into the project that the two of you collaborated on so Matt, how did you determine which insights from your analysis were most relevant for communicating with management? Are[00:11:24] Dr Matt Hoffman: So we have a set of measures at up level that are kind of part of our standard suite of analysis. So 1st, because if you can’t go explore the data for yourself and understand where your team’s at, then that’s a really unsatisfying experiment. So we knew that we wanted to look at some of these measures.[00:11:43] We’ve also been doing this for a few years now, so we do have a pretty good grasp on. You know, what are appropriate measures to look at for software engineers? And then what is completely inappropriate? That’s like, this is just not a good measure. You shouldn’t use it. It’s problematic for 1 reason or another.[00:12:01] So choosing those measures that we think. Are kind of universally applicable, are good proxies of how this experience may look, and then really trying to see what’s going to move and shift when we look at these. Those were kind of the criteria. We had a few hypotheses that we went in for how we thought things were going to move once you introduced Gen AI to the mix.[00:12:22] And we were surprised by our hypotheses, and we had to reject some of them, which was really fun. And it makes you really challenged that you’re doing it right. And then finding that this actually does go against what we thought would happen.[00:12:36] Dr Genevieve Hayes: you able to share any examples of these?[00:12:39] Dr Matt Hoffman: One of the things that we wrote about and we can share the link to our study was the general thinking was, hey, if you’re going to use Gen AI, you’re going to be able to ask questions and Jenny is going to help you write better code. So one of the things we looked at was. What’s the defect rate of code that gets merged and then it needs to get fixed later?[00:13:02] So how often does that happen? You would think that that would go down if the code is going to be of higher quality because Gen AI is helping you. Now what we found was that actually the defect rate went up. Another organization seemed to find the same thing, saying that the result of Gen AI was that there’s larger changes to code.[00:13:23] And then more things are going to get missed because the batch size is getting larger. So you might find things. four bugs, but there’s five because you’re writing bigger and bigger code changes. So we saw that the defect rate for the cohort that was using Gen AI went up by 40 percent compared to themselves, which is a pretty market change.[00:13:43] So that was one that , we were very surprised to see and are really interested to see what happens next with that as all these tools get better and better and better.[00:13:53] Dr Genevieve Hayes: insight you just described, that doesn’t surprise me because my own personal experience I’ve found with writing code using Gen AI, you can produce the code really, really fast. You’re spending. twice as long or three or four times as long debugging it, because there are all these bugs in it that would not be in there if you’d written it yourself.[00:14:14] And you’re just not used to having that many bugs to fix.[00:14:19] Dr Matt Hoffman: Yeah, and it might be not stylistic, like, the way that you think that you should write your code it might pull some solution that looks reasonable at first pass, but it’s pretty hard to debug if it’s the right thing when it, looks right, smells right, but then under the hood, there’s something wrong with it.[00:14:36] Also, Jenna, I doesn’t understand the context of the problem that you’re trying to go write code for. You have that in your head, you know where you’re at and where the destination is, and it’s going to help you write some code. But you have that.[00:14:49] Dr Genevieve Hayes: Yeah. And I’ve found it creates. Non existent Python packages and non existent Python functions, which is fun, because then you spend half an hour trying to find this package that doesn’t even exist.[00:15:02] Dr Matt Hoffman: It’s tricky. It really is. The other one that I would just briefly say that we looked at is we thought people would write code faster. That’s the statement that you just said. How quickly does it take to get from commit to merge? Does that really pick up? Because you’re using Gen AI.[00:15:16] And we found that it didn’t make much of a tangible impact. That there’s still a lot of time that’s spent when you’re trying to understand the problem of what you’re trying to solve, how you might approach it, the architecture of it. None of those things are going to go away.[00:15:31] Bottlenecks of having another human review your code, that doesn’t change whether they both have Gen AI or not. You’re still working with other people. So those structural factors do tend to be very important in this problem. And those are ones that you need to pursue and kind of conventional means of understanding how your teams work and doing better.[00:15:51] So that one didn’t move at all. And we thought that that would speed up. That was our hypothesis.[00:15:56] Dr Genevieve Hayes: Yeah, doesn’t surprise me. So, Lauren, how did you take these insights and structure them into a narrative that maximized their impact?[00:16:04] Lauren Lang: well, it was funny because even before we had done the research, we knew we wanted to do this research and we wanted to publish it. And looking from a content marketing perspective, I think original research right now is one of the most, potentially impactful formats for creating content.[00:16:23] And some of that is that, there is so much out there. That is just really bland. And I is not helping. Jenna is not helping with that. There’s a lot of content. That is just not special. It’s not differentiated. It’s not helping to educate or inform anybody or share anything new. And so when you have the opportunity to sort of lend something new to the conversation, that’s an important opportunity.[00:16:46] So we knew going in that we were going to do it. What we were not expecting were the results that we got. And I laughed a little bit when we got these results. I had a meeting with our data science team and with Matt, and., we all are sitting down and I’m like, lay it on me tell me what the results were and they were a little bit disappointed and they said, it’s kind of we’re not seeing, a big thing from Impact perspective or a data perspective, like, it’s just not that exciting.[00:17:15] And I said, oh, no, actually, this is very exciting because there were a number of factors. I think that really made this a really impactful report. 1st was just having some new original research on this topic. That is maybe the hot topic of the decade.[00:17:31] I think was really exciting. So it was like, listen, we know that people are very interested in this. We know that this is the question that they are asking, especially engineers and engineering leaders, the people who we serve from a business standpoint. They want to know is gen AI actually helping my developers be more productive.[00:17:48] And we have like some. Things that we can show around that. And then also the fact that we were able to then bring a little bit of a spiky and contrarian point of view about this because a lot of the research that’s been published already is either survey based. So, a lot of developers reporting whether or not they feel more productive.[00:18:11] Which is data as well, but, this is we’re bringing some quantitative data to bear or some of the other data was published by the. AI tools themselves, so you have to take that with a grain of salt. So, we came in[00:18:27] with this sort of interesting and different point of view. And that really, really took off for folks. And we found that some people were surprised. We found a lot of developers and engineers like you, Genevieve, who are not who said, I have been saying this all along. And this feels very validating because I think there is some anxiety among engineers that, Hey, like leadership just thinks that can be replaced.[00:18:50] But it really kicked off a really big conversation in the industry where we just said, Hey, you know, there’s a little bit of a hype cycle right now. We don’t know for sure. , we have results from one sample. There’s no big claims that we can make about the efficacy in the long run.[00:19:06] And things change very quickly. Gen AI is improving all the time, but. We do have some data points that we think are interesting to share and it really took off and it was great for us from a business perspective. It really helped take the work that we do into that last mile. And it helped make the work that we do feel very tangible and accessible for folks.[00:19:29] Dr Genevieve Hayes: So it sounds like, rather than taking a whole bunch of statistics and graphs, which would have been the output of Matt’s work. You translated those statistics and graphs into a narrative that could be understood by a person who wasn’t a data scientist or wasn’t a data analyst. Is that right?[00:19:49] Lauren Lang: Yes, we did. And our audience is primarily engineering leaders, engineering leaders are not data scientists, but they’re technical. So we identified three main takeaways. And we presented that we shared a little bit about our methodology.[00:20:03] And we shared essentially Some thoughts about what does this mean, what is the larger significance of what we found? What does this mean for you as an engineering leader does this mean that we think that you should stop adopting AI?[00:20:17] Does it mean that, right?, you should be more controlling of how your engineers are experimenting with AI. And, we don’t believe that’s the case at all. But it allowed us to sort of share some of our perspective about, how you build effective engineering organizations and what role we think I may have to play in that.[00:20:35] And, that is the larger story where data becomes very interesting because there’s sharing the data and then they’re sharing the so what around the data. So, what does this mean for me as an engineering leader? And so we really tried to bring those 2 elements together in the report.[00:20:51] Dr Genevieve Hayes: How was this report ultimately received by the audience?[00:20:55] Lauren Lang: Very well. We issued a press release around it. And I think we were picked up globally by somewhere between 50 and 75 media outlets, which. For a small engineering analytics platform, I’m pretty happy about that. It was in some engineering forums, it really became a big topic of discussion. We went sort of medium level viral. And it felt really good. It’s like, this is a really interesting topic. We accept that it’s an interesting topic.[00:21:22] We think that we have something that is very interesting to add to the conversation. So, yeah, it was good and some folks to it was great, you know, because engineering leaders are naturally skeptical. This is 1 of the most fun parts about marketing to engineering leaders that engineering leaders hate marketing.[00:21:38] So we got a few emails of folks who are like, tell us more about your methodology. And they really sort of wanted to, see behind the scenes and really, really dig in. And, that is par for the course. And we would expect nothing less[00:21:51] It was a really positive impact. I’m really glad we did it.[00:21:53] Dr Genevieve Hayes: So with all that in mind, I’d like to ask this of each of you. What is the single most important change our listeners could make tomorrow to accelerate their data science impact and results?[00:22:05] Dr Matt Hoffman: I. am very fortunate to have Lauren as an editor even when we collaborate on writing, an article I think having someone who can help you clarify and simplify your story is so important. You really do want to edit and bounce back and forth and try to distill down the most important bits of what you’re doing.[00:22:28] I tend to want to share, like, Everything, all of the details, all the gritty stuff, the exact perfect chart and it’s like, let’s simplify, simplify, simplify. And part of that conversation is also, who’s going to be receiving this? And what’s their persona? At what level are we going to explain this work?[00:22:47] Are they going to be familiar with, the methodology that we’re using? Or do we need to explain that too? So, how do we write everything at the most appropriate level and understand the life cycle of? This report that we’re doing. So having an editor would be my big one and understanding your audience would be the other.[00:23:06] Lauren Lang: I absolutely agree with everything Matt said. I think that the more that you make Sharing the results of your research, a team effort and a team sport, the more you’re likely going to succeed at it. But I think probably, and I’ll just come at it from, more of a technical perspective.[00:23:23] When you are presenting information, 1 of the things that could be very helpful is to present it at various levels of detail. So, making sure that you are presenting key takeaways or abstracts at 1 level and then. People can always double click into things and dive deeper and, you can include appendices or include links to , more of the detailed research.[00:23:47] But I think sort of having these executive summaries and really sort of being able to come at things from a very high level Can help sort of get that initial interest so that people understand quickly. what did the research find? What is the impact? And what is the context that this research was performed in?[00:24:06] Where is the business value, so, being able to connect the dots for your audience in terms of not only did we find this, but here’s what it means. And that thing that it means is actually very impactful to you and the job that you are trying to accomplish .[00:24:19] Dr Genevieve Hayes: So for listeners who want to get in contact with each of you, what can they do?[00:24:23] Lauren Lang: I live on LinkedIn. So they can look me up on LinkedIn. I think my little handle there is ask Lauren Lang.[00:24:31] Dr Matt Hoffman: Likewise, I don’t know what my LinkedIn handle is, but I’m on there. That would be the easiest way to get a hold of me on that.[00:24:39] Lauren Lang: You obviously need to spend more time on LinkedIn than Matt.[00:24:42] Dr Genevieve Hayes: Yes. And there you have it. Another value packed episode to help turn your data skills into serious clout, cash, and career freedom. And if you enjoyed this episode, why not make it a double? Next week, catch Lauren and Matt’s Value Boost, a five minute episode where they share one powerful tip for getting real results real fast.[00:25:08] Make sure you’re subscribed so you don’t miss it. Thanks for joining me today, Lauren and Matt.[00:25:12] Lauren Lang: Thank you so much for having us.[00:25:14] Dr Matt Hoffman: Thank you. It was really lovely.[00:25:16] Dr Genevieve Hayes: And for those in the audience, thanks for listening. I’m Dr. Genevieve Hayes, and this has been value driven data science. The post Episode 56: How a Data Scientist and a Content Expert Turned Disappointing Results into Viral Research first appeared on Genevieve Hayes Consulting and is written by Dr Genevieve Hayes.

Join host Nick Schutt on Robots & Red Tape as he sits down with Aaron St Clair and Jonathan Rendon from Omni Consulting Solutions to discuss how cutting-edge AI technology is revolutionizing procurement processes. Dive into VisionX, their innovative platform designed to automate and dramatically streamline government and private-sector procurement tasks—reducing time spent from days to minutes. In this insightful conversation, discover: How VisionX uses explainable AI and advanced automation to manage high-volume proposal evaluations rapidly and accurately. Real-world case studies demonstrating significant efficiency gains in compliance checks, evaluation assignments, and procurement workflows. Discussions on how explainable AI can reduce procurement delays, including handling protests effectively. The evolution of VisionX and its adaptability for both high-volume proposals and traditional federal procurement. Ideal for procurement professionals, government contractors, and tech enthusiasts looking to understand the future of AI in procurement. #govcon #ai #visionx #ProcurementAutomation #federalcontracting #innovation #govtech #explainableai #govtech #efficiency #RobotsAndRedTape #technologypodcast #innovation #AIProcurement #contractmanagement #OmniConsulting #governmentinnovation #governmentefficiency #aiinnovation #artificialintelligence #podcast #nextgenai #agenticai

Port congestion—it's a phrase thrown around in logistics, but what does it actually mean? In this episode of Supply Chain Secrets, hosts Caroline Weaver and Lars Jensen break down the layers of port congestion, from bottlenecks at the quay to inefficiencies in inland infrastructure. They discuss how factors like crane productivity, labor dynamics, chassis availability, and even customs staffing shortages all play a role.Plus, they unpack the latest industry shakeups, including the Hutchison terminal sale in China and the ongoing Red Sea crisis. Tune in to understand where the real choke points are and what businesses can do to mitigate disruption.

Karl and Erum sit down with Veronica Breckenridge, founder of First Bight Ventures, to discuss how the convergence of biology and technology is driving the biggest innovations of the 21st century. Drawing from her deep tech background, including her time at Apple, Veronica explores rapid advancements in genome sequencing, AI-driven biotech, and the vast untapped potential of microbes, emphasizing why now is the time to harness biology to tackle global challenges in health, nutrition, sustainability, and manufacturing. From synthetic biology startups to biomanufacturing at scale, this episode delves into the future of biomaterials and how venture capital can accelerate the next wave of biotech breakthroughs—making it a must-listen for anyone interested in scaling biotech innovations, investing in the bioeconomy, or exploring the intersection of computation and biology.Grow Everything brings the bioeconomy to life. Hosts Karl Schmieder and Erum Azeez Khan share stories and interview the leaders and influencers changing the world by growing everything. Biology is the oldest technology. And it can be engineered. What are we growing?Learn more at ⁠⁠⁠⁠⁠www.messaginglab.com/groweverything⁠⁠⁠⁠⁠ Chapters:00:00:00 - How Biology is Moving Faster Than Moore's Law00:00:17 - Checking In from Panama00:00:42 - Exploring Panama City's Biotech Potential00:01:26 - A Futuristic Robot Massage Experience00:02:11 - Reflecting on International Women's Day00:02:40 - Networking with Women in Biotech in Brooklyn00:05:27 - Inside the Merck Digital Sciences Studio Event00:06:19 - Breakthroughs Shaping the Future of Drug Development00:07:15 - The Biggest Hurdles for Startups in Pharma00:16:20 - A Deep Dive with Veronica Breckenridge00:30:41 - Why Manufacturability Matters in Biotech00:31:28 - The Role of Research and Pilot Facilities00:33:48 - How Scientific Founders Can Accelerate Their Business00:35:25 - Houston's Rising Status in Biomanufacturing00:39:12 - The Power of Collaboration and Mentorship00:43:04 - What It Takes to Scale and Commercialize Biotech Innovations00:48:12 - First Bight Ventures' Approach to Investing in the Bioeconomy00:51:26 - Building the Biotech Ecosystem & What's Coming Next00:54:28 - Final Advice for Startups Looking to ScaleLinks and Resources:First Bight Ventures  Biowell - nonprofit acceleratorThe Machine That Changed the World (book)Cemvita (company)  / Grow Everything Episode with CEO Moji KarimiIndustrial Microbes (company) / Grow Everything Episode with CEO Noah HelmanTopics Covered: biomanufacturing, biotech startups, biotech investing, biomanufacturing pilot plants, Houston economic development, synbioHave a question or comment? Message us here:Text or Call (804) 505-5553 ⁠⁠⁠⁠⁠Instagram⁠⁠⁠⁠⁠  / ⁠⁠⁠⁠⁠Twitter⁠⁠⁠⁠⁠ / ⁠⁠⁠⁠⁠LinkedIn⁠⁠⁠⁠⁠ / ⁠⁠⁠⁠⁠Youtube⁠⁠⁠⁠⁠ / ⁠⁠⁠⁠⁠Grow Everything⁠⁠⁠Email: groweverything@messaginglab.comMusic by: Nihilore

AI Automation Agents are transforming revenue cycle management by eliminating manual tasks like prior authorizations, eligibility checks, and claims follow-ups. Unlike traditional bots, AI-driven agents can adapt to system changes in real time, ensuring seamless automation without constant reprogramming.

In Episode 148 of the Best Coach Ever podcast, we're getting real about the mistakes that keep coaches stuck when they're trying to scale to $10K, $20K, or even $50K+ months. Scaling isn't just about working harder or slapping together new offers—it's about making the right strategic moves at the right time. And let's be honest, a lot of coaches are making moves that are actually holding them back.We break down four major mistakes that keep businesses stuck: expanding a product suite too soon, constantly launching new offers without strategy, chasing shiny new marketing tactics instead of sticking to what works, and ignoring the real bottlenecks in their business. If you've been throwing spaghetti at the wall, feeling overwhelmed by slow growth, or struggling to convert at higher price points, this episode is packed with insights to help you course-correct and finally scale with confidence.If you're serious about breaking out of your current revenue plateau and scaling in a way that doesn't burn you out, this episode is a must-listen. Get ready for some tough love and strategic shifts that will set your business up for real, sustainable growth.In this episode, we cover:1) The Perfectionism Trap & Blanket Dome Setup [0:00 - 6:30]-Why perfectionism will kill your progress (and why this episode almost didn't happen).-A behind-the-scenes look at recording under a “blanket dome” for better podcast acoustics.2) Mistake #1: Expanding Your Product Suite Too Soon [6:31 - 16:50]-Why adding more offers before you've mastered your core offer leads to more problems, not more money.-The difference between scaling out of overflow vs. desperation.3) Mistake #2: Offering Too Many Things, Too Soon [16:51 - 26:40]-How constantly launching new offers creates confusion for your audience and dilutes your brand.-Why being known for one primary solution first is the fastest path to growth.4) Mistake #3: Shiny Object Syndrome – Jumping from Strategy to Strategy [26:41 - 39:30]-How constantly switching tactics and not giving them time to work is keeping you stuck.-Why most business strategies need at least 30-90 days of consistent effort to see real results.5) Mistake #4: Ignoring the Bottlenecks in Your Business [39:31 - End]-How to identify the “dams” and leaks in your business that are preventing growth.-Why fixing bottlenecks (instead of chasing new strategies) is the key to breaking through income ceilings.Connect with Lynette:Instagram: https://www.instagram.com/lynettemarieh Fitness Coaching Business Accelerator: https://fcbaprogram.comThe Wellness CEO Mastermind: https://wcmprogram.com

Last year, South Australia convened a Royal Commission into Family Violence amid concern about a spike in domestic violence related assaults and deaths across the country. It's estimated that in Australia, one woman is killed by an intimate partner every 11 days. And across Australia, just over 1 in 4 women experience partner violence or abuse, while for men it's 1 in 7. In this episode of the Too Hard Basket, we explore just what evidence the Royal Commission is uncovering about how public officials respond to this violence, and the effectiveness of the institutions meant to protect victims.

Your business can only grow as fast as your systems allow. James and guest Lloyd Thompson discuss bottlenecks and business process optimization.

This week on No Priors, Sarah sits down with Noubar Afeyan, Co-founder and CEO of Flagship Pioneering, the biotech firm behind groundbreaking companies like Moderna. They explore how Flagship creates the conditions for scientific breakthroughs, tackles regulatory uncertainty, and pushes the boundaries of discovery. Noubar shares insights on AI's role in healthcare, the challenges of bringing new therapies to market, and lessons learned from past pandemics. He also discusses Flagship's platform approach to biotech innovation and introduces the idea of polyintelligence. Sign up for new podcasts every week. Email feedback to show@no-priors.com Follow us on Twitter: @NoPriorsPod | @Saranormous | @EladGil | @NoubarAfeyan Show Notes:  0:00 Introduction 0:48 Founding Flagship  5:51 Fostering environments for emergence 11:17 Expanding into new frontiers 14:26 Developing technology amid regulatory uncertainty and risk 19:12 How Flagship has evolved 22:47 AI applications in healthcare 27:30 Bottlenecks in bringing new therapies to market 32:20 Lessons for the next pandemic 34:11 Building a platform 38:10 Polyintelligence 

In this solo episode, I dive deep into the recurring marketing and sales challenges that plague seven-figure businesses trying to scale higher. Drawing from my personal experience and conversations with numerous founders, I explore how scattered marketing data, unclear ROI, and founder bottlenecks can stall growth.Key areas covered:✅ The challenge of fragmented marketing data across multiple platforms✅ High customer acquisition costs in premium markets✅ The importance of proper lead management and follow-up✅ Breaking free from the founder bottleneck✅ Implementing practical solutions for sustainable growthActionable Insights:Unify your marketing data tracking systemsImplement a 10-minute response rule for leadsFocus on existing customer retention before aggressive acquisitionCreate clear systems to delegate critical decisionsStart with one key improvement rather than trying to fix everything at onceKey Quote:"Pick your biggest pain point...and focus on that first. Remember, it's all about directionally correct incremental progress."

Waymo is an autonomous driving technology company with the mission to be the world's most trusted driver. The company operates a 24/7 public ride-hail service and provides over 150,000 trips each week across San Francisco, Los Angeles, Phoenix, and Austin, making mobility more accessible, sustainable, and safer for everyone.In this week's episode of Unsupervised Learning, we dive deep into the frontier where AI meets hardware — and there's no better guide than Vincent Vanhoucke, Distinguished Engineer at Waymo and former Head of Robotics at DeepMind. [0:00] Intro[0:50] Waymo's Technological Evolution[2:40] The Role of LLMs in Autonomous Driving[6:02] Vincent's Journey to Waymo[9:17] Challenges in Autonomous Driving[11:58] Simulation and World Models[27:44] Future Milestones and Expansion[30:10] Broader Robotics and AI[36:12] Future of General Robotics Models[38:14] Hardware vs. Software Approaches in Robotics[40:19] Challenges in Robotic Data Acquisition[40:38] Simulation vs. Real-World Data in Robotics[43:02] Human-Robot Interaction for Data Collection[45:03] Advancements in Multimodal Models[47:08] Unanswered Questions in Robotics[52:02] Reasoning Capabilities in AI[54:57] Future of Robotics and AI[1:00:51] 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

SummaryIn this conversation, Christine Jewell, an executive coach and founder of the Momentum Company, shares her journey from building multiple successful businesses to realizing the importance of slowing down and being present. She discusses the common bottlenecks faced by high-performing individuals, particularly in their personal and professional relationships, and emphasizes the need for introspection and alignment with one's values. Christine also highlights the significance of faith in her coaching practice, advocating for a partnership with God in business decisions. The discussion culminates in practical advice on how to identify areas to slow down and the importance of energy management over time management.Listeners can connect with Christine Jewell through the following platforms:Podcast: Breaking Chains Podcast – Tune in for powerful conversations on leadership, personal growth, and faith-based principles.Website: The Momentum Company – Learn more about her executive coaching, leadership programs, and upcoming events.Instagram: @thechristinejewell – Follow her for daily insights, leadership wisdom, and personal updates.Book: Drop the Armor – Available on Amazon, Barnes & Noble, and Audible with actionable exercises after each chapter.Free Resource: Download the first chapters of Drop the Armor for free here to get a taste of her transformative approach.Email: Contact Christine directly through her website's contact form for coaching inquiries or collaborations.#1 a FREE GIFT for your peeps! Free Guided Presence Practice: PRESENCE is POWER https://www.thechristinejewell.com/Guided-RecalibrationBook Order Link! "Drop the Armor" Written for the ultra-high achiever longing to find a way to bridge the gap between earthly pursuits and true fulfillment only comes by living according to faith. Order direct + get over $200 in Bonus Resources https://www.dropthearmorbook.comChapters00:00 The Journey of Christine Jewell02:05 Presence is Power04:40 Bottlenecks in Business and Relationships07:46 Slowing Down to Speed Up12:52 Identifying Areas to Slow Down20:04 Faith and Business24:42 Christine's Daily Flow32:27 Distinguishing Between Slowing Down and Laziness

The future of data infrastructure. We cover the explosion in compute demand, the petabytes of untapped enterprise data, energy-efficient GPUs, DeepSeek, the $500B Stargate project, and how AI is transforming data processing. Craig Dunham is CEO of Voltron Data, a company at the forefront of accelerating data processing for AI, analytics, and enterprise-scale workloads. Voltron provides the infrastructure necessary to handle enormous amounts of data — transforming bottlenecks into breakthroughs. By championing open-source frameworks like Apache Arrow, Voltron is building the connective tissue that allows businesses to process data at orders-of-magnitude speed and efficiency, reshaping industries from finance to healthcare to national security — partnering with the likes of Snowflake and Meta. Voltron have established themselves as a key part of the AI infrastructure stack and have raised a total of $110M from the likes of Coatue, LightSpeed, Google Ventures and BlackRock. With a deep background in scaling data infrastructure businesses, Craig is Voltron’s CEO. Before Voltron Data, Craig was the CEO of Lumar, a leading SaaS technical SEO platform. Prior to that, he held significant roles including General Manager at Guild Education and Seismic, where he led the integration of Seismic’s acquisition of The Savo Group and drove go-to-market strategies in the financial services sector. Craig began his career in investment banking with Citi and Lehman Brothers before transitioning into technology. He holds an MBA from Northwestern University’s Kellogg School of Management Sign up for new podcasts and our newsletter, and email me on danieldarling@focal.vcSee omnystudio.com/listener for privacy information.

Jonathan Ross is the Founder & CEO of Groq, the creator of the world's  first Language Processing Unit (LPUTM). Prior to Groq, Jonathan began  what became Google's Tensor Processing Unit (TPU) as a 20% project where he  designed and implemented the core elements of the first-generation TPU chip.  Jonathan next joined Google X's Rapid Eval Team, the initial stage of the famed  “Moonshots Factory”, where he devised and incubated new Bets (Units) for Google's  parent company, Alphabet. In Today's Episode We Discuss: 04:20 Interview with Jonathan Ross Begins 04:59 Scaling Laws and AI Model Training 06:22 Synthetic Data and Model Efficiency 12:01 Inference vs. Training Costs: Why NVIDIA Loses Inference 17:06 The Future of AI Inference: Efficiency and Cost 18:15 Chip Supply and Scaling Concerns 20:57 Energy Efficiency in AI Computation 25:40 Why Most Dollars Into Datacenters Will Be Lost 31:05 Meta, Google, and Microsoft's Data Center Investments 41:11 Distribution of Value in the AI Economy 42:10 Stages of Startup Success 43:17 The AI Investment Bubble 45:00 The Keynesian Beauty Contest in VC 48:40 NVIDIA's Role in the AI Ecosystem 53:39 China's AI Strategy and Global Implications 57:51 Europe's Potential in the AI Revolution 01:10:14 Future Predictions and AI's Impact on Society  

Our guest on this week's episode is John (Jay) Rogers, CEO and co-founder of Haddy. There has been a push in the past few years to do more manufacturing here at home. One of the key technologies that is enabling more domestic production is digital manufacturing. That's where Haddy comes in. Haddy is the world's first 3D printing furniture manufacturer powered by AI and advanced robotic technology. Jay Rogers talks with us about this unique approach to manufacturing. A new report from Colliers, the industrial real estate firm, reveals data on fourth quarter warehouse construction. The report shows that renters of warehouse space should begin to see some relief after the seriously steep rent hikes they're seen in recent years. The American Transportation Research Institute (ATRI) released its annual list of the nation's top truck bottlenecks. This is the group's 14th annual report on this issue. Its goal is not only to identify the top congested freight markets, but also to help local, state, and federal governments target funding to areas most in need of relief. The full report shares ways to reduce chokepoints, lower emissions, and drive economic growth. Supply Chain Xchange  also offers a podcast series called Supply Chain in the Fast Lane.  It is co-produced with the Council of Supply Chain Management Professionals. A series of ten episodes is now available on the "State of Logistics." The episodes provide in-depth looks into the current states of key transportation modes, such as trucking, rail, air, and ocean. It also looks at inventory management, 3PLs and more.  All ten episodes are available to stream now. Go to your favorite podcast platform to subscribe and to listen to past and future episodes. The podcast is also available at www.thescxchange.com.Articles and resources mentioned in this episode:HaddyColliers reports that warehouse construction rates return to pre-pandemic levelsATRI releases the annual list of the nation's top truck bottlenecksVisit Supply Chain XchangeListen to CSCMP and Supply Chain Xchange's Supply Chain in the Fast Lane podcastSend feedback about this podcast to podcast@agilebme.comPodcast is sponsored by: Zebra Robotics AutomationOther linksAbout DC VELOCITYSubscribe to DC VELOCITYSign up for our FREE newslettersAdvertise with DC VELOCITYTop 10 Supply

Irene Chen and Matthew Grenby are the co-founders of Parker Thatch, a luxury handbag and accessories brand they bootstrapped to 8-figures over the course of 20 years. Matt's expertise spans tech, design, and marketing, while Irene brings deep fashion industry knowledge from working with powerhouse brands like Donna Karan and Calvin Klein.In this episode of DTC Pod, Matt and Irene share how they navigated the shift from an e-stationery startup to eventually finding product-market fit with their signature luxury bags. They discuss key lessons learned in bootstrapping—the importance of market timing, how to manage inventory risks, and why flexibility and systems are critical when growing a brand.Interact with other DTC experts and access our monthly fireside chats with industry leaders on DTC Pod Slack.On this episode of DTC Pod, we cover:1. Founding and Evolution of Parker Thatch2. Initial Business Concepts and Pivots3. Strategies for Managing and Allocating Inventory4. Importance of Flexibility in Business Operations5. Bootstrapping and Capital Allocation6. Building Systems for Scalability7. Marketing and Demand Generation Strategies8. Community and Customer EngagementTimestamps00:00 Matt and Irene's backgrounds before Parker Thatch 06:55 Starting an e-stationery business in 200007:43 Pivoting to selling physical stationery and home goods 9:00 Lessons on market timing and pivoting when starting a business11:51 Changing company name from iomoi to Parker Thatch13:52 Creating Parker Thatch's debut handbag18:19 Bootstrapping, capital allocation, inventory decisions22:08 Why early business success depends on flexibility and testing25:53 Introducing leather bags and streamlining production29:10 Why small businesses fail without systems32:29 Shifting to systems thinking to enable business growth35:07 Marketing strategies to drive customer demand37:01 Building community and brand identity around "functional luxury"42:34 Relationship dynamics as husband and wife co-founders45:55 Key focuses for 2025 and beyond with PTTV 47:48 Where to find and connect with Parker ThatchShow notes powered by CastmagicPast guests & brands on DTC Pod include Gilt, PopSugar, Glossier, MadeIN, Prose, Bala, P.volve, Ritual, Bite, Oura, Levels, General Mills, Mid Day Squares, Prose, Arrae, Olipop, Ghia, Rosaluna, Form, Uncle Studios & many more.  Additional episodes you might like:• #175 Ariel Vaisbort - How OLIPOP Runs Influencer, Community, & Affiliate Growth• #184 Jake Karls, Midday Squares - Turning Your Brand Into The Influencer With Content• #205 Kasey Stewart: Suckerz- - Powering Your Launch With 300 Million Organic Views• #219 JT Barnett: The TikTok Masterclass For Brands• #223 Lauren Kleinman: The PR & Affiliate Marketing Playbook• ​​​​#243 Kian Golzari - Source & Develop Products Like The World's Best Brands-----Have any questions about the show or topics you'd like us to explore further?Shoot us a DM; we'd love to hear from you.Want the weekly TL;DR of tips delivered to your mailbox?Check out our newsletter here.Projects the DTC Pod team is working on:DTCetc - all our favorite brands on the internetOlivea - the extra virgin olive oil & hydroxytyrosol supplementCastmagic - AI Workspace for ContentFollow us for content, clips, giveaways, & updates!DTCPod InstagramDTCPod TwitterDTCPod TikTok  Irene Chen and Matthew Grenby -  Co-Founders of Parker ThatchBlaine Bolus - Co-Founder of CastmagicRamon Berrios - Co-Founder of Castmagic

Dylan Patel, founder of SemiAnalysis and one of my go-to experts on semiconductors and data center infrastructure joins me to discuss AI in 2025. Several key themes emerged about where AI might be headed in 2025:1/ Big Tech's accelerating CapEx and market adjustmentsThe hyperscalers are racing ahead in capital expenditure, with Microsoft's annual outlay likely to surpass $80 billion (up from around $15 billion just five years ago). By mid-decade, total annual investments in AI-driven data centers could climb from around $150–200 billion today to $400–500 billion. While these expansions power more advanced models and services, such rapid spending raises questions for investors. Are shareholders ready for ongoing, multi-fold increases in data center build-outs?2/ The competitive landscape and new infrastructure playersThe expected explosion in AI workloads is drawing in a wave of new specialized GPU cloud providers—names like CoreWeave, Niveus, Crusoe—each gunning to become the next vital utility layer of AI compute. Unlike the hyperscalers, these players tap different pools of capital, including real-estate-like finance and private credit, enabling them to ramp up aggressively. This dynamic threatens the established order and could squeeze margins as competition heats up. The market is starting to understand that.3/ The semiconductor supply chain isn't the only bottleneckWe often talk about GPU shortages, but the real sticking point is broader infrastructural complexity. Yes, Nvidia and TSMC can ramp up chip supply. But even if you have enough high-end silicon, you still need power infrastructure and grid connectivity. Building multi-gigawatt data centers in the US—each the size of a utility-scale power plant—is now firmly on the agenda. In some states, data centers already consume 30% of the grid's electricity. By 2027, AI data centers alone could account for 10% or more of total US electricity consumption, straining America's aging infrastructure.4/ Commoditization of models and margin pressureA year ago, advanced language models were scarce and expensive. Today, open-source variants like Llama 3.1 are driving commoditization at speed, slicing away the profit margins of plain-vanilla model-serving. If your model doesn't outperform the best open source, you're forced to compete on price—and that's a race to the bottom. Currently, only a handful of players (OpenAI and Anthropic among them) enjoy meaningful margins. As models proliferate, value will increasingly flow to those offering distinctive tools, integrating closely into enterprise workflows and locking in switching costs.5/ Into 2025: exponential curves and new market normsDespite these challenges—soaring costs, stalled infrastructure build-outs, margin erosion—Dylan is confident that exponential scaling will continue. The sector's appetite for GPUs, specialized chips and next-gen data centers appears insatiable. We could easily see record-breaking fundraising rounds north of $10 billion for private AI ventures—funded by sovereign wealth funds and other capital pools that have barely scratched the surface of their capacity to invest in AI infrastructure. There's also a very tangible productivity angle. AI coding assistants continue to reduce the cost of software development. Some software companies could be looking at 20–30% staff reductions in these technical teams as high-level coding becomes automated. This shift, still in its early days, will have profound downstream effects on the entire software ecosystem.Find us:Exponential ViewSemiAnalysis