Podcasts about companies

What happens when an AI experiment becomes a production service that your employees, customers, and daily operations depend upon? In this episode of Tech Talks Daily, I speak with Brian Klingbeil, Chief Strategy Officer at Ensono, about AI infrastructure resilience, operational dependency, FinOps, legacy modernization, and the growing pressure to prove that enterprise AI investments are producing meaningful returns. Brian has been speaking with major enterprises through Ensono's Executive Advisory Council. Three years ago, many participants were experimenting with proofs of concept. Today, they are being asked to present AI projects that are already in production, approaching production, or demonstrating a clear return through productivity, lower risk, service quality, or financial results. That progression creates a new problem. When an AI model begins supporting product delivery, customer service, logistics, software development, or internal operations, it becomes part of the company's operating infrastructure. Leaders must then ask familiar IT questions about availability, monitoring, security, incident response, disaster recovery, ownership, and cost. Brian believes FinOps often provides the first warning. Token consumption can be difficult for CFOs and business leaders to interpret, particularly when hundreds of agents are operating across different models. Ensono's internal platform has produced around 1,000 agents, prompting questions about which are effective, which are expensive, and who should carry the cost. We discuss why chargeback and showback could change employee behavior. When AI spending is absorbed by a central corporate budget, teams may have little reason to question whether an expensive model is suitable for a routine task. When the cost reaches their departmental budget, the decision can look very different. Architecture also matters. Brian recommends systems that are loosely coupled and tightly integrated. Companies should be able to replace a model, provider, FinOps tool, or service as the market changes, while still connecting each component closely enough to deliver useful business outcomes. That creates a genuine tradeoff. Providers such as Microsoft, Amazon, Google, OpenAI, and Anthropic can offer specialist capabilities that businesses may want to use. Avoiding every provider specific feature can limit what the technology delivers, while becoming too dependent on one provider can make future change expensive and disruptive. The conversation then turns toward legacy technology. Brian argues that many systems described as outdated still process airline reservations, banking transactions, insurance claims, government services, and other high volume workloads. Turning them off without suitable replacements would create far bigger problems than the word "legacy" suggests. AI can change the modernization decision. Ensono worked with Markerstudy Group to analyze six million lines of RPG code running on an IBM i platform. The resulting plan identified applications that should move elsewhere while preserving workloads that still benefited from the platform's reliability and transaction processing capabilities. Brian treats migration as one possible part of modernization. AI tools can document old code, support modern development environments, and allow younger developers to work with established platforms without immediately beginning a lengthy and expensive replacement program. We also discuss Ensono's use of AI operations. Brian says the company reduced mean time to repair by 50% while processing approximately 50,000 tickets each month. The example shows how AI value can be measured through service quality and operational performance rather than relying entirely on direct revenue. The result is a balanced conversation about moving quickly while building enough control to keep AI dependable. Organizations need space for experimentation, but production services also require ownership, budgets, recovery planning, and people who know what to do when something fails. If one AI model or provider disappeared tomorrow, how much of your business would stop working? Listen to the episode and share your thoughts with me.

What happens when an autonomous AI agent makes a financial decision using inaccurate, outdated, or poorly synchronized data? In this episode of Tech Talks Daily, I speak with Marcin Kaźmierczak, cofounder of RedStone Oracles and Credora Ratings, about why verifiable data is becoming so important to financial AI agents. RedStone originally developed its oracle infrastructure to supply smart contracts with reliable information from hundreds of sources. The same principles are now being applied as AI agents begin analyzing markets, recommending allocations, processing payments, and executing trades. Marcin explains what a blockchain oracle does and why smart contracts cannot independently access real world information. RedStone aggregates, cleans, and distributes financial data, including asset prices, liquidity, volatility, and market capitalization. According to Marcin, its network currently secures over $10 billion in total value locked and has operated for six years without a mispricing or downtime event. The discussion then moves into agent driven finance. AI agents can process information and act at considerable speed, but that speed introduces problems when the underlying information is delayed or the model hallucinates. Marcin describes the synchronization challenge created when an oracle updates every five seconds while an agent makes decisions every second. One example captures the risk. An AI trading agent reportedly generated $200,000 over three months before losing $250,000 in two transactions. Marcin explains how Credora Ratings can add financial risk context by rating assets and strategies from D to A. Companies can then instruct an agent to operate only within an approved risk range. We also discuss tokenized assets, the growing interest from major financial institutions, and why blockchain networks offer an attractive operating environment for autonomous finance. Marcin shares practical advice for leaders, including speaking with experienced implementers, testing agents in closed environments, identifying likely failure scenarios, and creating response policies before introducing real money. What evidence would you require before trusting an AI agent with a financial decision? Listen to the episode and share your answer with me.

Why do so many enterprise AI initiatives begin with impressive demonstrations but struggle to produce measurable business value? In this episode of Tech Talks Daily, I speak with Dom Selvon, CTO and value partner at Valiance, about enterprise AI ROI, outcome-based consulting, build versus buy decisions, proprietary data, ontologies, and governance. Valiance is an AI-native consultancy that charges against client outcomes rather than hours worked. Dom explains why his "value partner" title is deliberate. The company begins by identifying the financial or operational result a client wants and connects its own compensation with achieving that result. Dom argues that many AI initiatives begin without a clear definition of success. The pressure to adopt AI is real, but companies frequently select technology before agreeing on the business problem, desired outcome, or measurement. He identifies three recurring mistakes. The first is framing the project around AI rather than the business need. The second is failing to establish a metric and baseline before work begins. The third is using a consulting model that rewards billable time without connecting payment to the client's result. We also discuss how generative AI is changing traditional build versus buy decisions. Companies historically bought software because custom development was slow, expensive, and difficult to maintain. Coding agents can now reduce the time and cost required to create software for specific internal needs. Dom does not believe SaaS will simply disappear. However, vendors selling convenience, workflow wrappers, or integration glue face new competition from customers who can create similar capabilities themselves. He argues that stronger SaaS positions will depend on assets a model cannot easily regenerate, including proprietary data, networks, regulatory standing, and deep workflow adoption. This leads to a wider discussion about competitive advantage. When companies have access to similar models, generated code begins to converge. Dom believes lasting differentiation comes from company data, institutional knowledge, connected systems, employee experience, and the semantic context surrounding that information. Dom explains why ontologies matter to enterprise AI. Raw data tells an agent what is stored in a particular field. An ontology describes the customers, orders, contracts, payments, relationships, and business rules represented by that data. This context allows people and agents to reason about information in a way that reflects how the company actually works. Governance also needs to be designed from the beginning. Dom argues that security, permissions, accountability, and compliance allow successful pilots to expand without forcing the business to rebuild everything later. How can leaders tell when AI is genuinely being adopted? Dom offers a surprisingly simple signal: people stop talking about AI. The technology becomes part of ordinary Monday morning work, and employees focus on completing the task rather than explaining the tool. Has your company defined the business result, measurement, proprietary context, and governance required to turn AI enthusiasm into operational value? Listen to the episode and share your thoughts with me.

Can one accountant really do tax prep five times faster with AI? Blake and David talk with Sam Leon, founder of The Millennial CPA, about how he uses Claude projects to turn client documents into tax workpapers, speed up review, and run a solo firm built around software. They also dig into where AI still falls short, why review remains the bottleneck, and what firms can realistically automate today.SponsorsDigits - http://accountingpodcast.promo/digitsThe Value Builder System - http://accountingpodcast.promo/valueOnPay - http://accountingpodcast.promo/onpayCloud Accountant Staffing - http://accountingpodcast.promo/casChapters(00:00) - Autonomous AI Reality Check (00:11) - Show Welcome and Interview Tease (00:55) - Sponsor Spotlight Digits (02:34) - Trump IRS Deal Dismissed (05:20) - California Billionaire Tax Fight (07:35) - New York Pied a Terre Tax (09:29) - Sponsor Spotlight Value Builder System (11:18) - Xero CEO Pay and Stock Sale (16:39) - Verification Tax and AI Jobs (22:06) - Sponsor Spotlight OnPay (23:21) - 1948 IBM Accounting Machine Lesson (29:56) - Sponsor Spotlight Cloud Accountant Staffing (31:07) - Meet Sam Leon Millennial CPA (32:01) - Solo Firm Vision (33:15) - From Big Firms to Millennial CPA (35:42) - Why AI Agents Weren't Ready (37:19) - Automating Tax Prep Workflow (40:33) - Smart Intake for Better Scoping (43:06) - End to End Return Automation (46:04) - AI Workpapers and Review (49:38) - Claude Setup and Time Savings (58:18) - Tech Spend and Pricing Strategy (01:02:52) - Building TaxWeave Platform (01:06:21) - Wrap Up and CPE Info  Show NotesJudge Smacks Down Trump's IRS Settlement And Orders Sanctionshttps://www.cnn.com/2026/07/13/politics/trump-irs-judge-ruling-settlement-sanctionsInstead of Uniting the Left, California's Billionaire Tax Measure Has Split Democratic Allieshttps://www.cpapracticeadvisor.com/2026/07/08/instead-of-uniting-the-left-californias-billionaire-tax-measure-has-split-democratic-allies/186379/NYC lawyers slam pied-a-terre tax as a half-baked money grabhttps://www.audacy.com/1010wins/news/local/nyc-lawyers-slam-pied-a-terre-tax-as-a-half-baked-money-grabA 1948 IBM computer with no memory at all, fed by punchcards, was still doing the accounting at a Texas filtration company as recently as 2020https://scienceblog.com/t-1948-ibm-402-punchcards-sparkler-filters-accounting-2020/Time saved by AI partially canceled out by time spent checking AIhttps://www.accountingtoday.com/news/time-saved-by-ai-partially-cancelled-out-by-time-spent-checking-aiResearch Suggests Jobs May be Safer at Companies that Embrace AIhttps://www.cpapracticeadvisor.com/2026/07/07/research-suggests-jobs-may-be-safer-at-companies-that-embrace-ai/186281/AI Is No Longer Just a Tech Occupation Story: It's Spreading Across Job Titles in the US and Europehttps://www.hiringlab.org/2026/07/08/ai-is-no-longer-just-a-tech-occupation-story/The 2026 Best Accounting Firms for Technologyhttps://www.accountingtoday.com/list/the-2026-best-accounting-firms-for-technologyNeed CPE?Get CPE for listening to podcasts with Earmark: https://earmarkcpe.comSubscribe to the Earmark Podcast: https://podcast.earmarkcpe.comMeet Our Guest, Sam Leon, CPALinkedIn: https://www.linkedin.com/in/samuelaaronleon/ Website: https://www.millennialcpa.tax/Website: https://www.taxweave.ai/Get in TouchThanks for listening and the great reviews! We appreciate you! Follow and tweet @BlakeTOliver and @DavidLeary. Find us on Facebook and Instagram. If you like what you hear, please do us a favor and write a review on Apple Podcasts or Podchaser. Call us and leave a voicemail; maybe we'll play it on the show. DIAL (202) 695-1040.SponsorshipsAre you interested in sponsoring The Accounting Podcast? For details, read the prospectus.Need Accounting Conference Info? Check out our new website - accountingconferences.comLimited edition shirts, stickers, and other necessitiesTeePublic Store: http://cloudacctpod.link/merchSubscribeApple Podcasts: http://cloudacctpod.link/ApplePodcastsYouTube: https://www.youtube.com/@TheAccountingPodcastSpotify: http://cloudacctpod.link/SpotifyPodchaser: http://cloudacctpod.link/podchaserStitcher: http://cloudacctpod.link/StitcherOvercast: http://cloudacctpod.link/OvercastClassifieds REFRAME 2026 - http://accountingpodcast.promo/reframe2026Flowglad - https://cal.com/team/flowglad/flowgladWant to get the word out about your newsletter, webinar, party, Facebook group, podcast, e-book, job posting, or that fancy Excel macro you just created? Let the listeners of The Accounting Podcast know by running a classified ad. Go here to create your classi...

What happens when AI moves beyond writing emails and summarizing meetings and starts influencing who gets hired, promoted, and paid? In this episode of Tech Talks Daily, I speak with David Lloyd, Chief AI Officer at Dayforce, about why HR is becoming one of the highest-stakes environments for artificial intelligence and how companies can introduce AI while protecting employee data, maintaining human accountability, and preparing for growing regulatory scrutiny. HR systems contain some of the most sensitive information companies hold, from salaries and performance records to benefits and personal data. At the same time, AI is increasingly being introduced across recruitment, workforce management, compensation, performance, and employee experience. David explains why this combination creates enormous opportunities but also places greater responsibility on employers to understand how AI systems operate and how decisions are made. A major theme throughout our conversation is the role of AI governance. David challenges the assumption that governance slows innovation, arguing that the right processes can help companies evaluate AI ideas quickly while reducing the risk of introducing systems that lack appropriate data, transparency, or regulatory safeguards. Dayforce recently achieved ISO/IEC 42001 certification for AI management systems and NIST AI Risk Management Framework attestation. David explains what independent validation means in practice and why companies evaluating AI vendors should ask for evidence of how systems are governed, tested, monitored, and audited. We also discuss the principle of "AI by choice." David argues that CIOs and HR leaders should never discover that a new AI capability has suddenly been activated across hundreds of employees without their knowledge. Companies need visibility into where AI is being used, what data employees can provide to models, and whether customer information is being used to train external AI systems. The conversation examines AI literacy and why HR leaders need to become comfortable with the technology themselves before guiding employees through changes to jobs and working practices. Employees are already experimenting with AI, sometimes through personal tools outside approved company systems. Rather than ignoring this behavior, David explains why companies should provide safe environments where people can learn while establishing clear rules around sensitive data. Human accountability remains central as AI takes on more responsibility. David discusses why people using AI should remain accountable for its outputs and why human oversight matters when technology influences decisions involving recruitment, compensation, performance, and careers. For CEOs, CHROs, CIOs, HR technology leaders, and anyone responsible for enterprise AI, this conversation provides practical guidance on responsible AI adoption, employee data, AI bias, model monitoring, regulatory compliance, vendor selection, and building AI governance that can stand up to scrutiny. The lesson is that governance does not have to be a brake on AI adoption. Done well, it can give companies the structure and confidence to move faster, make better decisions about where AI belongs, and continue using the technology when regulators, employees, customers, and boards start asking harder questions. https://www.dayforce.com/ https://www.linkedin.com/company/dayforce/ https://www.linkedin.com/in/dtlloyd/

With just 15 weeks until the midterm elections, debates over American jobs and foreign labor are taking center stage. West Virginia Congressman Riley Moore joins to discuss why he believes the H-1B visa and OPT programs act as corporate "scams" that undercut local workers, the GOP's legislative record, and his outlook on the battle for control of Congress. As the battle over immigration enforcement rages on, one mother is refusing to stay silent. Cheryl Minter, whose daughter Stephanie Minter was allegedly killed by an illegal immigrant with a long criminal record, is demanding accountability for Fairfax County prosecutor Steve Descano. Minter blames Descano for letting the suspect walk the streets despite more than 30 prior arrests on charges including rape and assault. FOX News Correspondent Bill Melugin speaks with Cheryl Minter about her daughter's case, the national debate over immigration enforcement, and why she started a petition with the Victims Rights Reform Council to recall DA Descano. (edited)  PLUS, commentary from FOX News Contributor and Host of the "Jason in the House" podcast Jason Chaffetz. PHOTO Credit: Adobe Stock Learn more about your ad choices. Visit podcastchoices.com/adchoices

Fifteen years ago, Eric Ries handed a generation of founders a playbook. When Eli was in a Palo Alto-based startup accelerator in 2011, The Lean Startup felt like the only book anyone in that ecosystem was talking about. It was in the middle of a wildly optimistic moment for tech. Marc Andreessen declared that “software is eating the world,” social media was blooming, and there was a widespread belief that technology was about to democratize everything and bring us closer together. Concepts like the MVP (“minimum viable product,”), the pivot, and build-measure-learn became the operating language of Silicon Valley. This is a preview of a premium episode. Listen to the full interview on our Substack: https://designbetterpodcast.com/p/eric-ries But a lot of the companies built on those ideas went on to get corrupted by forces Eric hadn't yet named. His new book, Incorruptible: Why Good Companies Go Bad and How Great Companies Stay Great, is his reckoning with what happens after you build something great — and how to keep it from falling apart. Buy the book In this conversation, we get into why speed itself wasn't the problem, but treating a rising stock price as proof of health is like assuming more exhaust means a faster car. Eric explains why doing the right thing 100% of the time is actually easier than doing it 98% of the time, and how companies behave like superorganisms with their own emergent character — a point he illustrates with a genuinely mind-bending study about ants solving a puzzle that no single ant ever could. We talk about the “harder is easier” principle through stories from Patagonia and the long-term stock exchange he built as a design challenge, and why the value a company makes comes from the design of its products. And because we couldn't resist, we get into AI slop, LLM psychosis, and Eric's clear, simple antidote: never ask these tools to make you an artifact — ask them to teach you how to make one yourself. Bio Over the last two decades, Eric Ries's ideas about continuous innovation, long-term thinking, governance, and market reform have reshaped company building and management practices. He is the creator of the Lean Startup method, and the author of the New York Times bestseller The Lean Startup; The Leader's Guide; and The Startup Way. As a founder, he has put his own ideas into practice with The Long-Term Stock Exchange (LTSE); Answer.AI, an AI R&D lab; the Lean Startup Co, which teaches and supports the implementation of Lean Startup; Virgil, a legal services startup; and IMVU, where the ideas that became the Lean Startup method were forged. On his podcast, The Eric Ries Show, he talks to guests including world-class technologists, thought leaders, and executives working to build profitable companies for the long-term benefit of society. Eric has served as an entrepreneur-in-residence at Harvard Business School and IDEO. He lives in the San Francisco Bay Area with his wife and three children. *** Premium Episodes on Design Better This is a premium episode on Design Better. We release two premium episodes per month, along with two free episodes for everyone. New premium subscriber benefit: we've launched a private Slack workspace…join now to connect with designers, product leaders & creative practitioners in our community. And get a behind-the-scenes pass to every episode with The Roundup, where each week we bring you insights and actionable tactics from recent episodes. Premium subscribers get access to the documentary Design Disruptors and our growing library of books. You'll also get access to our monthly AMAs with former guests, ad-free episodes, discounts and early access to workshops, and our monthly newsletter The Brief that compiles salient insights, quotes, readings, and creative processes uncovered in the show. And subscribers at the annual level now get access to the Design Better Toolkit, which gets you major discounts and free access to tools and courses that will help you unlock new skills, make your workflow more efficient, and take your creativity further. Upgrade to paid Visiting the links below is one of the best ways to support our show: Masterclass: MasterClass is the only streaming platform where you can learn and grow with over 200+ of the world's best. People like Steph Curry, Paul Krugman, Malcolm Gladwell, Dianne Von Furstenberg, Margaret Atwood, Lavar Burton and so many more inspiring thinkers share their wisdom in a format that is easy to follow and can be streamed anywhere on a smartphone, computer, smart TV, or even in audio mode. MasterClass always has great offers during the holidays, sometimes up to as much as 50% off. Head over to http://masterclass.com/designbetter for the current offer. Learn more about your ad choices. Visit megaphone.fm/adchoices

What separates an impressive agentic AI demonstration from a deployment that produces measurable business value across an entire company? In this episode, I speak with Frank Theisen, Vice President of IBM Technology across Europe, the Middle East and Africa, about how businesses can move AI agents beyond isolated pilots and into the processes where work actually happens. Frank believes the conversation has changed considerably. Most large companies are deploying some form of AI, yet many still struggle to demonstrate a significant commercial return. The difference comes from connecting AI with end-to-end business processes rather than creating another assistant that sits outside the systems employees use every day. IBM has attempted to prove this internally through its "client zero" approach, using its own technology across human resources, IT, procurement, sales and software development before taking those practices to customers. The company reports that AI, automation and hybrid cloud have contributed to $4.5 billion in productivity gains over three years. Frank explains how IBM's AskHR service handles common employee inquiries and helps managers complete administrative tasks without learning how to operate several separate enterprise applications. IBM reports that AI now resolves 94 percent of common HR requests automatically, while similar work is taking place across IT support and procurement. The discussion then turns to orchestration. As companies acquire agents from multiple software providers, the problem becomes far larger than creating individual assistants. Businesses need to understand how agents communicate, which systems they can access, what identities they use and who remains accountable for their actions. Frank expects the number of applications, agents and non-human identities to grow rapidly. Without orchestration and governance, companies risk recreating the same application sprawl they have spent years attempting to reduce, this time with software capable of making decisions and generating additional code. Data presents another barrier. Publicly trained models rarely contain the proprietary information that gives a company its commercial advantage. That information remains distributed across databases, applications, mainframes and cloud services. Frank argues that enterprises need a governed, federated way to bring AI to their data without repeatedly copying everything into another repository. We also discuss digital sovereignty across Europe and the Middle East. Frank describes sovereignty as a matter of control across data, operations and technology. Companies need to decide which workloads require isolation, which regulations apply and where dependence on one provider could limit their future choices. Wimbledon provides a timely example of these principles in practice. IBM Bob helped modernize the tournament's digital platform by mapping and migrating approximately 15,000 articles, videos, photographs and related metadata. IBM says work that would traditionally require four or five specialists over several months was completed by one engineer within four weeks, with the assets themselves extracted in 47 minutes. Frank closes with three practical priorities. Understand where AI could affect the business, determine how successful use cases can be automated across complete processes, then address security, governance and provider dependence before expanding them. If your company already has dozens of AI pilots, should the next investment create another agent or coordinate the ones you already have? Listen to the episode and share your thoughts with me.

Shares of capital market company MSCI and credit rating agency Equifax both posted double digit declines after posting earnings that were…ok? Matt, Lou, and Tyler dive into what went right and wrong in the most recent earnings and what to make of the two stocks today. Plus, what to make of the oil markets using Halliburton's earnings results and what is the best banking ETF today? Have a question? Email us; podcasts@fool.com Want to take the next step in your investing journey? Explore Motley Fool's Epic for our portfolio-centered investing experience, premium research, tools, and guidance: fool.com/epic fool.com/epic Tyler Crowe, Matt Frankel, and Lou Whiteman discuss: - Equifax & MSCI earnings and stock reactions - AI costs eating into profits - Halliburton's comments on the oil market - Mailbag: Best Banking ETF to buy now? Companies discussed: EFX, MSCI, MS, HAL, XLF, VFH, BRK, V, MA, JPM, KBE, KBWB Host: Tyler Crowe Guests: Matt Frankel, Lou Whiteman Engineer: Dan Boyd Disclosure: Advertisements are sponsored content and provided for informational purposes only. The Motley Fool and its affiliates (collectively, “TMF”) do not endorse, recommend, or verify the accuracy or completeness of the statements made within advertisements. TMF is not involved in the offer, sale, or solicitation of any securities advertised herein and makes no representations regarding the suitability, or risks associated with any investment opportunity presented. Investors should conduct their own due diligence and consult with legal, tax, and financial advisors before making any investment decisions. TMF assumes no responsibility for any losses or damages arising from this advertisement. We're committed to transparency: All personal opinions in advertisements from Fools are their own. The product advertised in this episode was loaned to TMF and was returned after a test period or the product advertised in this episode was purchased by TMF. Advertiser has paid for the sponsorship of this episode. Learn more about your ad choices. Visit ⁠⁠megaphone.fm/adchoices Learn more about your ad choices. Visit megaphone.fm/adchoices

First, the agency publicly claimed it found a dangerous parasite in Taylor Farms lettuce. The headlines spread like wildfire. Consumers panicked. Businesses took another hit. Then came the admission. The test was wrong. A false positive. But don't expect an apology. Instead, the FDA insists it's still focused on Taylor Farms while offering little accountability for a mistake that damaged reputations and fueled fear across the country. When federal agencies make accusations before they're certain, the consequences are real. Companies lose business. Consumers lose confidence. And once another government mistake makes the news, Americans are left wondering what they're supposed to believe. We're going to examine exactly what happened, why the FDA got it wrong, why accountability seems to be missing, and whether this is yet another example of a government bureaucracy that refuses to admit when it fails. If trust has to be earned, the FDA has a lot of work to do. Sponsors The Maverick Systemhttps://TheMaverickSystem.com Patriot Mobilehttps://PatriotMobile.com/Grant The Wellness Companyhttps://TWC.Health/GrantPromo Code: GRANT for 10% off Lost Soldier Oil & Gashttps://LostSoldier.com See omnystudio.com/listener for privacy information.

The SaaS world is in the middle of a brutal reckoning. Products that looked innovative 18 months ago are quietly becoming redundant — not because markets disappeared, but because the floor rose. In this episode, Jeff Mains sits down with Brian Herr, a 30-year technology and SaaS veteran, to dissect what it actually takes to build a software business that survives — and wins — in the age of AI.Brian brings sharp investor-grade thinking to the conversation, drawing on his work with startups, venture studios, and PE-backed companies. They cover the death of thin-wrapper SaaS, why blocking AI agents is a catastrophic mistake, how security and compliance have become unexpected competitive moats, and the critical distinction between a product that helps and one that solves. If you build software or provide services, this episode is non-negotiable.Key Takeaways4:08 — The value expectation from SaaS platforms is shifting fast. Thin wrappers around someone else's AI model have no future — customers will ask why they're paying when they can do it themselves.4:53 — Companies that survive will be the ones that solve real problems, curate the right data, and give meaningful feedback — not just deliver a slick interface.6:46 — Investor rubrics have changed. A key new question before committing capital: "Can this be replicated as a Claude skill or agent in six months?" If yes, it's not fundable.7:39 — Where physical world meets digital data is a major investment magnet. These companies have stronger moats, are more AI-resistant, and occupy underserved territory.13:53 — Natural language interfaces are no longer a differentiator — they're an expectation. And Brian's crystal ball: local on-device AI will push this even further into everyday life.14:29 — Natural language is democratizing technology for older users. If you don't have a conversational interface, the market will pass you by.20:23 — Agents are no longer just for technologists. CFOs and revenue officers are using them. Blocking agents is a strategic blunder — competitors are advertising agent compatibility while you're building walls.21:00 — The smart play: figure out what people are doing with agents hitting your platform and monetize it. Blocking just pushes them to your API — or to a competitor.21:20 — Every SaaS company needs a quarterly gut-check: What is my value? What do I do well? How do I evolve? A business plan from one year ago doesn't fit today's market.33:04 — Security, compliance, and certifiability are the new defensible moat. You literally cannot vibe-code your way into SOC 2, HIPAA, or AI trust scores. That's the value story.33:59 — The AIUC-1 framework is making AI applications insurable for the first time. MITRE has joined the consortium. If your SaaS uses AI, this becomes part of your trust story.39:50 — The single most important product question: Does it help, or does it solve? Helpful gets cut from budgets. Essential doesn't.43:09 — Going niche gives you orders-of-magnitude higher odds of success. Trying to do what everyone else is doing? Your chance of success drops to 13% or less.47:37 — Brand trust and human relationships are more important than ever. People do business with people. When you become indifferent to your customers, you become a vendor. Vendors don't survive.Tweetable Quotes"If someone opened a fresh ChatGPT window right now and got roughly the same result your product delivers — would your customers notice the difference, or would they even care?" — Jeff Mains"The thin wrappers aren't going to make it very long. What's going to survive is companies that still solve real problems, curate the right data, and give the right feedback." — Brian Herr"One of our investment rubrics now: Can this be turned into a Claude skill or agent in six months? If so, it doesn't make sense for us to invest." — Brian Herr"Natural language interfaces are now an expectation, not a differentiator. If you think you'll eventually get around to it, the market will pass you." — Brian Herr"Helpful solutions get cut from the budget first. Solutions that solve don't. Stop asking whether you can bolt on AI and start asking whether customers actually need YOUR data and process to make it work at all." — Jeff Mains"Agents are becoming for everyone — especially as the interface evolves. Blocking them is evolve or die." — Brian Herr"Figure out what people are doing with agents and monetize it. People will pay for it. By being a blocker, you're just pushing them to find another way." — Brian Herr"People do business with people. When you become indifferent to your customers, you stop being a partner and become a vendor. Vendors have a hard time surviving." — Brian Herr"Success is a journey, not an endpoint. The founders who make it understand you're going to be a little wrong — as long as you course correct in the right direction." — Brian HerrSaaS Leadership Lessons1. Moat = Data + IP + Experience, Not Interface A beautiful UI sitting on top of a commodity model is not a business — it's a countdown clock. Your defensible moat is proprietary data, domain expertise, and institutional knowledge that competitors cannot prompt their way into.2. Run a Quarterly Value Audit Especially in the $5M–$15M revenue range, ask yourself every quarter: Does my business plan still match the market? What do I do well, and how am I evolving? Founders who don't course-correct veer further off target every quarter until they no longer recognize where the target moved.3. Embrace Agents as a Revenue Channel, Not a Threat Your API traffic spikes are signals, not attacks. When agents are hitting your platform, that's demand you haven't monetized yet. Build for agent access, charge for it, and let your competitors play defense while you build offense.4. Compliance and Trust Are Your Unfair Advantage In a world where anyone can vibe-code a competitor over a weekend, the thing they cannot replicate is your certifications, your compliance posture, your years of regulated-market experience, and your insurance-grade AI trust scores (AIUC-1). Make this part of your sales story.5. Help vs. Solve Is the Only Product Question That Matters Helpful products live in discretionary budgets — they're the first cut when times get hard. Products that solve real, urgent problems command non-negotiable budget lines. Every feature you build, every market you target: ask which one it is.6. Stay a Partner, Never Become a Vendor When customers feel like a transaction to you, you become a commodity to them. In the $5M–$15M range, clients know your team personally — that trust is a competitive advantage. Build systems to maintain it as you scale, or risk waking up one day to find out you've been quietly moved to the vendor pile.Guest ResourcesWebsite: https://www.startingblocks.io/LinkedIn (6k): https://www.linkedin.com/in/brian-herr/https://drive.google.com/drive/folders/1kS1WsPODEaqtMnB_g1_Dut6oTv1FYYvXEpisode SponsorThe Futureproof Series - https://www.youtube.com/playlist?list=PLfkXKUPZ5xuOqMPR7_gzGybncTtavyR1NThe Captain's KeysSmall Fish, Big Pond – https://smallfishbigpond.com/ Use the promo code ‘SaaSFuel'Champion Leadership Group – https://championleadership.com/https://jeffmains.com/books/SaaS Fuel ResourcesWebsite - https://championleadership.com/Jeff Mains on LinkedIn - https://www.linkedin.com/in/jeffkmains/Twitter - https://twitter.com/jeffkmainsFacebook - https://www.facebook.com/thesaasguy/Instagram - https://instagram.com/jeffkmains

The use of AI in the workplace can be a polarizing topic. How inevitable will AI be in our jobs, and what sorts of conversations should corporate leaders be ready to broach? "Marketplace Morning Report" host Kimberly Adams recently dug into that and more with Linda Hill, a Harvard Business School professor, at the Aspen Institute's Business and Society Summit. But first, leading economic indicators aren't as leading as they used to be.Every story has an economic angle. Want some in your inbox? Subscribe to our daily or weekly newsletter.Marketplace Morning Report is more than a radio show. Check out our original reporting and financial literacy content at marketplace.org — and consider making an investment in our future.Stories in this episode:How to approach the AI revolution

Fresh off Macstock, you get the full debrief on this year’s gathering before diving into a stacked round of Quick Tips. You’ll learn how to disable Summarize Notification Previews to stop needless battery churn, clear every unread Apple Watch notification in one shot, and weigh whether it’s finally time to move to macOS Tahoe. There’s a heads-up that Mac minis and Mac Studios are back in Apple’s Refurbished Store, a slick Control-Tilde trick to reveal formulas in Excel, Google Sheets, and LibreOffice, the case for a USB-only cable when you’re heading into DFU recovery mode, and clever moves like stretching a Kindle book loan with an old iPad, building reusable packing-list templates, and scheduling an automatic weekly reboot to keep your Macs running clean. Then you tackle your questions: setting the default audio app on your iPhone, when prepaid mobile data might be the smarter play (and when it’s not!), and a big Don’t Get Caught warning that macOS 28 is dropping support for encrypted HFS+ drives, so decrypt or reformat those external volumes before you upgrade next year. You’ll also hear how Claude Code can become your new macOS troubleshooting partner, including some honest thoughts on leaning on AI to fix your machine. Cool Stuff Found rounds it out with UDM14 for Google results minus the AI summaries, Backdrop for live macOS wallpaper, Clock Rings for tracking time in decimal, and a cheap camera lens cover that works across your MacBook, iPad, and iPhone. As always, come learn at least five new things. 00:00:00 Mac Geek Gab 1151 for Monday, July 20th, 2026 July 20th: National Fortune Cookie Day MGG Monthly Giveaway – Win a license to Mole 00:02:00 Macstock Debrief Some new-for-the-first-time attendees David Pogue Ken Case Ken Ray Paul Conaway Quick Tips 00:00:01 DLH-QT-Disable Summarize Notification Previews to save battery churn 00:06:16 Pilot Pete-QT How to clear all your unread Apple Watch notifications 00:08:34 Is it time to update to Tahoe? 00:09:25 Mac minis and Mac Studios available again in Apple's Refurb Store 00:12:31 Companies safeguarding your data 00:16:46 Marina-QT-Control-Tilde shows the formulas in Excel (and Google Sheets, and LibreOffice, but not Numbers) 00:20:03 Tony-QT-Use a USB-only cable for DFU Recovery Mode 00:21:49 Harvey-QT-Use your old iPad to extend your Kindle Book loan period 00:24:40 Todd-QT-1150-Create Packing List Templates and Sections 00:27:50 Don-QT-Schedule a weekly reboot for your Macs sudo pmset repeat restart U 05:00:00 (“U” means sUnday) 00:33:40 Pilot Pete-QT-Green light Means the Camera is On Sponsors 00:36:56 SPONSOR: Coveron. One scam can cost you everything – use code “macgeekgab” for up to 76% off at https://coveron.com/macgeekgab to safeguard your identity. 00:38:10 SPONSOR: Shopify. If you're ready to stop putting off your business and start selling, sign up for your free trial and start selling today at https://Shopify.com/MGG Your Questions Answered and Tips Shared! 00:39:33 Dave-How can I set the default audio app on my iPhone? 00:45:30 Doug-Why go prepaid for mobile data? US Mobile (allows network flexibility) Get $25 to join America’s Super Carrier, plus get 30 days free when you transfer your number! 00:53:10 Gary-DGC-macOS 28 to drop support for encrypted HFS+ drives 00:58:10 Dave-QT-Use Claude Code for macOS troubleshooting 01:03:57 Some thoughts on Troubleshooting with AI Cool Stuff Found 01:05:35 Mike-CSF-UDM14 to get Google results sans AI summaries 01:09:34 Javier-CSF-1128–Backdrop – Live MacOS Wallpaper 01:11:34 -n-Eric-CSM-Clock Rings to track time in decimal 01:15:39 Pilot Pete-CSF-Camera Lens Cover Macbook, iPad, iPhone 01:18:48 MGG 1151 Outtro MGG Monthly Giveaway Bandwidth Provided by CacheFly Pilot Pete's Aviation Podcast: So There I Was (for Aviation Enthusiasts) The Debut Film Podcast – Adam's new podcast! Dave's Business Brain (for Entrepreneurs) and Gig Gab (for Working Musicians) Podcasts MGG Merch is Available! Mac Geek Gab iOS app Mac Geek Gab YouTube Page Mac Geek Gab Live Calendar This Week's MGG Premium Contributors MGG Apple Podcasts Reviews feedback@macgeekgab.com 224-888-GEEK Active MGG Sponsors and Coupon Codes List BackBeat Media Podcast Network

The use of AI in the workplace can be a polarizing topic. How inevitable will AI be in our jobs, and what sorts of conversations should corporate leaders be ready to broach? "Marketplace Morning Report" host Kimberly Adams recently dug into that and more with Linda Hill, a Harvard Business School professor, at the Aspen Institute's Business and Society Summit. But first, leading economic indicators aren't as leading as they used to be.Every story has an economic angle. Want some in your inbox? Subscribe to our daily or weekly newsletter.Marketplace Morning Report is more than a radio show. Check out our original reporting and financial literacy content at marketplace.org — and consider making an investment in our future.Stories in this episode:How to approach the AI revolution

Companies don't fail because of bad strategy. They fail because leadership ignores the human side of business.In this powerful episode of Mindset Mastery Moments, Dr. Alisa Whyte sits down with executive leadership strategist Natasha Kehimkar, Founder and CEO of Malida Advisors, to uncover why so many organizations become stuck—even when they appear wildly successful from the outside.Together, they explore why trust erodes long before a crisis hits, how burnout is often misunderstood, why true inclusion is much more than a corporate initiative, and why today's leaders must embrace emotional intelligence, self-reflection, and radical curiosity to build resilient teams. Natasha shares nearly three decades of high-level experience helping executive teams transform workplace culture, navigate complex change, and build organizations where core values become daily behaviors—not just empty words on a wall.What We DiscussWhether you lead a global company, a nonprofit, a small business, or simply your own family, this conversation will challenge how you think about leadership forever:The Invisible Stagnation: Why organizations become stuck long before leaders even realize what went wrong.The Erosion of Trust: The hidden, unintentional ways leaders break trust with their teams every single day.Burnout vs. Overwhelm: Why what we label as chronic burnout is often unaddressed, overwhelming operational clutter.Authentic Inclusion: Moving past performative culture and creating environments where diverse perspectives actually thrive.The Power of Reflection: Why taking time to reflect is the single most critical leadership skill almost everyone ignores.Curiosity-Driven Growth: How asking better questions creates stronger, more adaptable organizations.Exclusive Webinar & Educational ResourcesLevel up your organization's human capital strategy and reserve your spot for upcoming executive sessions:Executive Insights & Webinars: Join the latest interactive sessions at the Insights Lab at Malida Advisors.Official Website: Explore consulting and advising frameworks at Malida Advisors Website.Connect with Natasha KehimkarLinkedIn: Connect with Natasha Kehimkar on LinkedInConsulting Firm: Malida AdvisorsMusic Attribution & LicensingMusic Track: Licensed through SoundstripeLicense Codes:  KNPQSMJC0MGSRFRM "Leadership isn't about your position or title. It is about the mindset, empathy, and presence you bring to your people every single day."Send us Fan MailReady to turn your message into a profitable speaking career? Join Dr. Karim Ellis for a FREE live masterclass and discover the proven strategies to get booked, increase your influence, and build a speaking business that creates lasting impact and income. Reserve your seat today: https://thegpsspeakersacademy.com/freeclassSupport the show

Could the disaster recovery plan designed to protect your company make a ransomware incident even worse? In this episode, I speak with Darren Thomson, Vice President and Chief Technology Officer for EMEA at Commvault, about Resilience Operations, commonly known as ResOps, and why cyber recovery now requires security, infrastructure, identity and data teams to work from one coordinated plan. Darren argues that many companies are accepting a difficult reality. Even with considerable investment in prevention and detection, a breach may eventually succeed. That does not make cybersecurity controls any less necessary, but it means recovery can no longer be treated as a secondary activity managed by another department. The problem is that security operations and infrastructure teams have traditionally worked toward different objectives. Security specialists concentrate on identifying and stopping threats. Infrastructure teams protect data, maintain backups and restore systems after outages. During a cyberattack, a successful recovery requires both sets of expertise. A backup administrator may be able to restore data quickly, but a forensic specialist must establish whether that data is clean. Without that confirmation, the company risks restoring malware and restarting the incident. Darren explains why a conventional disaster recovery plan may be particularly dangerous during ransomware. These plans were commonly designed for physical failures such as a lost data center. Data would be copied from one location to another so operations could continue. If the source data is infected, however, fast replication can carry the malware into the recovery environment. This is where ResOps enters the discussion. Darren describes it as an operating model rather than a product. It combines established practices from security and infrastructure management into a continuous program for testing, learning and improving recovery. Individual technology projects may come from the program, but resilience itself never reaches a final completion date. AI adds pressure on both sides. Criminals can use it to create faster and more effective attacks, while defenders can use machine learning to inspect large volumes of information, detect patterns and identify the newest clean recovery point. Companies must also protect AI systems as they would any other business application, including the models, data repositories and identities connected with them. Darren offers one practical starting point for CIOs and CISOs: Mean Time to Clean Recovery, or MTCR. This measures how long it takes to restore an application and its data with evidence that both are free from compromise. Before measuring MTCR, leaders must define their minimum viable company. These are the systems and services the business cannot operate without. Once that list exists, teams can test how long a verified clean recovery would take and replace assumptions with evidence. The initial answer may be uncomfortable. Teams may know how to restore an application without knowing whether the backup is clean. Security may know how to inspect the system but lack an established workflow with the recovery team. Darren sees those gaps as the starting point for a useful ResOps program because they provide everyone with a shared problem and a measurable objective. If your most important systems disappeared today, how long would it take to bring the minimum viable company back using verified clean data? Listen to the episode and share your answer with me.

Here is a FAQ Video on the Courses: https://youtu.be/0F7imrzjXWs Here is a deep dive into which course is best for you: https://youtu.be/JM_jgS8M-iU https://www.b2bRevenue.com - Get Your Free E-Book on How Companies make Decisions. FAQ: 1 YEAR ACCESS, PAY MONTHLY OR ANNUALLY NOT A SUBSCRIPTION OFFICE HOURS EVERY  OTHER WEEK VIA ZOOM. 1 HOUR GROUP Q&A. UNLIMITED 1-ON-1'S  ARE FREE AS LONG AS THEY CAN BE SHARED IN THE COURSE. 1-ON-1 ARE FULL ACCESS ON DAY ONE - NOTHING IS GATED OR TIME RELEASED. ALL CONTENT IS VIDEO BASED AND SELF PACED I RECOMMEND TAKE COURSE ONCE WITHOUT NOTES OR APPLYING IT SO YOU UNDERSTAND THE BIG PICTURE FIRST. THEN TAKE AND APPLY IT STEP BY STEP. YOU START WHEN YOU WANT AND GO AS FAST OR SLOW AS NEEDED.   Email me additional questions: briangburns@me.com     — SAMPLE EMAIL TO EXPENSE THE COURSE MGR,   I have been listening to the brutal truth about sales podcast for X months and it speaks to the issues we face.   They currently offer a course that includes video instruction, group Q&A and One-on-One coaching. I'm committed to my own personal development and would like your help in expensing the course.   It would pay for itself if I closed only one new deal of $X value.   Please let me know by Friday if I can move forward with this 1 year course.   Thanks, ME Here are some student interviews from the courses:      ———————————————————————————————————— Audible 30 day Free Trial: http://www.audibletrial.com/BrutalTruth  

Most AI initiatives stall in experimentation mode. Dr. Fern Halper, VP and Senior Research Director for Advanced Analytics at TDWI and founder of the AI Foundations Group, explains why organizations struggle to convert AI pilots into measurable business value. The conversation covers the foundational systems required to operationalize AI beyond experimentation, the organizational readiness gaps that undermine adoption, and how to prioritize a single high-impact focus over the next 12 months to move from testing to results.See Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

Microsoft lawsuit loss, Steam refund controversy, One Piece scalper chaos, PS6 handheld speculation, gaming pickups, and a Popcorn Rocket PS4 review. Chapters: 00:00 Introduction 00:50 Game Pickups and Inflation Deflation Challenge 02:21 Discussion on Popcorn Rocket Game 04:48 Nicktoons Dice of Destiny  08:15 Sky Gunner  10:58 Cold Fear  14:46 Finny the Fish and the Seven Waters 19:56 Dino Stalker and Cruisin Blast  22:49 Ryan's Gaming Week and SGDQ 26:09 Microsoft Lawsuit and Digital Ownership Discussion 30:24 The Future of Digital Ownership 32:12 Scalpers and the Manga Market 36:01 Steam Refunds and Developer Concerns 45:41 Sony's Shift to Digital 54:49 Popcorn Rocket: A New Indie Game Review John and Ryan dive into another week of gaming talk, starting with their recent video game pickups and what's currently on their radar. From new finds to ongoing playthroughs, the duo breaks down what's been keeping their controllers busy. The news segment kicks off with Microsoft's latest legal setback as the company lost a lawsuit in a Brazilian court, raising questions about regional regulation and platform responsibility. They then shift to Steam's refund policies for games under the one‑hour return limit, highlighting a recent developer's experience that sparked debate about fairness, abuse, and consumer protection. Next, the conversation moves to Japan, where scalpers purchased One Piece magazines en masse due to a promotional card — another example of collectible culture colliding with opportunistic reselling. The guys then explore a big speculative question: Is the PS6 going digital‑only because it will be a handheld? They break down rumors, hardware trends, and whether Sony's future might lean toward a hybrid device. To wrap up the episode, the Inflation Deflation Game of the Week features a review of Popcorn Rocket on PS4, as John and Ryan evaluate the quirky title's gameplay, charm, and current market value. Find us on TheGameDeflators.com Twitter - www.twitter.com/GameDeflators Facebook - www.facebook.com/TheGameDeflators Instagram - www.instagram.com/thegamedeflators The views and opinions expressed on this channel are solely those of the author. The content within these recordings are property of their respective Designers, Writers, Creators, Owners, Organizations, Companies and Producers. Copyright Disclaimer Under Section 107 of the Copyright Act 1976, allowance is made for "fair use" for purposes such as criticism, comment, news reporting, teaching, scholarship, and research. Fair use is a use permitted. Permission for intro and outro music provided by Matthew Huffaker http://www.youtube.com/user/teknoaxe 2_25_18

In this episode, I sit down with Zac and Jack from We Have a Meeting to unpack how their done-for-you outbound service has generated over £4M in live pipeline for 9 recruitment companies in the last 12 months, without relying on candidate flips or any of the usual recruiter BD tactics.We dive into their full outbound system: how they build and enrich data before a single call is made, the VAR process that quality-checks every meeting booked, and the "Trojan Horse" strategy they use to break into markets they've never worked in before.Connect with Zac here: https://www.linkedin.com/in/zac-thompson-33a9a39b/Connect with Jack here: https://www.linkedin.com/in/jack-frimston-5010177b/-------------------------Watch the episode on YouTube: https://youtu.be/JySSf2QrVWE-------------------------Podcast Sponsors: Claim your exclusive savings from our partners with the links below:Sourcewhale - Check Out Sourcewhale & Claim Your Exclusive Offer Here.Atlas - Check Out Atlas & Claim Your Exclusive Offer HereRaise - Check Out Raise & Claim Your Exclusive Offer Here.-------------------------Want more content like this?The Wednesday Debrief is our free weekly newsletter for recruiters who take their craft seriously. Join 7,000+ subscribers here: https://newsletter.recruitmentmentors.com/-------------------------Get in touch with me:Linkedin: https://www.linkedin.com/in/hishemazzouz/-------------------------

On this episode of Run the Numbers, CJ sits down with Dave McClure and Aman Verjee of Practical VC to talk about the evolution of startup investing — from the PayPal mafia and Founders Fund era to 500 Startups, YC-style scale, and today's secondary market.—SPONSORS:Rillet is an AI-native ERP built for modern finance teams that want to replace NetSuite and close faster. With revenue recognition, close management, multi-entity support, and native Stripe and Salesforce integrations, Rillet helps scaling companies run their finance stack in one place. Hundreds of teams, including Windsurf and Mercor, use Rillet to make the zero-day close real. Book a demo at https://www.rillet.com/cjMaximor is an autonomous finance platform that runs order-to-cash, procure-to-pay, the close, cash management, and reporting on self-learning agents instead of a dozen disconnected tools. One PE-backed customer cut their close in half, took audit findings from seven to zero, and cut back-office costs by 70% in six months. You pay for outcomes, not seats. See it at https://www.maximor.ai/Brex is an intelligent finance platform with AI-powered agents that capture expenses automatically, enforce policy before the spend happens, and close your books in minutes instead of weeks. 35,000+ companies like OpenAI, Coinbase, Anthropic, and DoorDash already run on Brex. It's time to get Brex AF. Learn more at https://www.brex.com/metricsAnrok is the sales tax platform that watches your exposure everywhere, automates compliance, and flags risk before it turns into a surprise back-tax letter from a state you've never set foot in. Companies like Anthropic, Notion, and Vanta already trust Anrok to stay ahead of rules that move faster than any spreadsheet can. Talk to a sales tax expert for a personalized exposure estimate at https://www.anrok.com/rtnRightRev is an automated revenue recognition platform that lets your product team ship new pricing without asking finance for permission, and your sales team close deals without creating downstream chaos. Check out their free tool at calculator.rightrev.com It scores your rev rec process, shows what's exposing you to risk, and tells you exactly where to focus before it bites you in the rear end. Check it out at https://calculator.rightrev.comPulley is an equity management platform that lets you issue options, model dilution, and complete 409As without your cap table turning into a spreadsheet disaster. Founders raising, hiring, and scaling use Pulley to keep equity clean and stay focused on building. Learn more or request a demo at https://pulley.com/mostlymetrics—LINKS: Mostly Talent: https://mostlymetrics.typeform.com/to/cLTxtAsNGuests:https://www.linkedin.com/in/davemcclure/https://www.linkedin.com/in/aman-verjee/Company:https://practicalvc.com/CJ: https://www.linkedin.com/in/cj-gustafson-13140948/Mostly metrics: https://www.mostlymetrics.com—TIMESTAMPS:0:00 Preview and Intro3:00 Writing as a distribution strategy5:17 How Dave's blog led to Founders Fund7:24 Aman: writing at PayPal and law school9:29 PayPal: the red pen of David Sacks11:44 Sponsors — Rillet | Maximor | Brex14:59 500 Startups: the original thesis16:22 The volume strategy: more shots on goal18:44 Twilio, Lyft, Sendgrid, Credit Karma20:15 60x returns: right place, right time23:07 Sponsors — Anrok | RightRev | Pulley25:58 Accelerator ecosystem evolution28:42 500 vs. YC: scale as a weapon32:52 Globalizing the accelerator model35:04 Seed to secondaries: how it happened37:00 Scratching their own itch for liquidity38:10 The secondary market explained40:50 Types of secondaries43:29 Why would a VC sell a winner?46:07 Managing DPI as a late-stage manager47:02 The five horse framework49:15 Skipping the J curve51:44 Imperfect information as a feature55:22 Landmines: fraud, mismarked valuations57:00 VCs lie about valuations three ways57:58 Forward contracts and counterparty risk1:00:29 Credits

Most people see the trucks, the mascot, the sports partnerships, and the brand, but Spero “The Hero” built Good Greek Moving & Storage from something much deeper than marketing.In this episode, we sit down with Spero, founder of Good Greek Moving & Storage, to talk about the real story behind one of Florida's most recognizable service brands.Spero shares how growing up in an immigrant family, serving in law enforcement, joining SWAT, and later stepping into entrepreneurship shaped the way he built his company. He breaks down why trust matters in a service business, how hiring and training changed the moving industry for him, why the right people are everything, and what it takes to scale a brand that can outlive the founder.The Invest Well Show Is Powered by Wall Private Wealth. Reach Out to Learn How to Protect, Grow, and Reduce Taxes on Your Wealth.

Cryptocurrency companies are advocating for more Americans to use crypto in their everyday lives, particularly Stablecoins which are chained to the value of the dollar. Learn more about your ad choices. Visit podcastchoices.com/adchoices

Companies claim they cannot find enough talent while routinely rejecting professionals with decades of experience. This episode examines the “overqualified” trap, age bias in recruiting, and how outdated hiring systems may be creating the very talent shortages companies are struggling to solve. Brought to you by my newsletters: The Recruiting Life Career Intelligence Weekly https://newsletter.jimstroud.com Learn more about your ad choices. Visit megaphone.fm/adchoices

In this Risky Business sponsor interview Casey Ellis chats with Haroon Meer from Thinkst about building companies customers don't hate. Haroon explains why Thinkst still offers Canary tokens for free and why it has avoided annual price hikes on its paid products. They talk about Eric Ries's “Incorruptible”, Rob Lee's 100-year-company approach at Dragos, and why keeping customers happy is a better business strategy than chasing easy sugar highs. Show notes

Vertical SaaS providers are integrating payments to expand revenue and reduce churn by delivering software and money movement in a single workflow. Companies such as Toast, Lightspeed Commerce, Mindbody, and ServiceTitan use embedded processing to deepen adoption and streamline onboarding. Platforms choose among referral, facilitator, or hybrid models, partnering with processors such as Stripe, Adyen, Worldpay, Fiserv, Global Payments, and PayPal Braintree, and using tools like Stripe Connect and Adyen for Platforms. Greater control can improve margins but requires capabilities in KYC, PCI DSS, fraud, and chargeback management in coordination with sponsor banks. Integrated payments improve merchant onboarding, payouts, and reconciliation, and enable features like instant payouts and installments through partners. Founders should roll out payments in phases, track attach rates and risk costs, and revisit build versus partner decisions as volume grows.Learn more on this news by visiting us at: https://greyjournal.net/news/ Hosted on Acast. See acast.com/privacy for more information.

Most companies say they're doing AI. A surprising number are doing very little — and a Chief AI Officer at one of the world's largest automation platforms has the receipts to prove it. Motley Fool analyst Rachel Warren talks with Adam Field, Chief AI Officer at Tungsten Automation — a company serving 25,000 organizations including 40% of the Fortune 100 — about what separates real AI transformation from expensive spin. They get into why most enterprise AI pilots quietly die before they scale, what "boring AI" actually means and why it's the most important signal investors aren't paying attention to, and why the competitive moat that once made legacy software giants unassailable has effectively disappeared overnight. Host: Rachel Warren Guest: Adam Field Producers: Adam Landfair, Lauren Budabin Disclosure: Advertisements are sponsored content and provided for informational purposes only. The Motley Fool and its affiliates (collectively, “TMF”) do not endorse, recommend, or verify the accuracy or completeness of the statements made within advertisements. TMF is not involved in the offer, sale, or solicitation of any securities advertised herein and makes no representations regarding the suitability, or risks associated with any investment opportunity presented. Investors should conduct their own due diligence and consult with legal, tax, and financial advisors before making any investment decisions. TMF assumes no responsibility for any losses or damages arising from this advertisement. We're committed to transparency: All personal opinions in advertisements from Fools are their own. The product advertised in this episode was loaned to TMF and was returned after a test period or the product advertised in this episode was purchased by TMF. Advertiser has paid for the sponsorship of this episode. Learn more about your ad choices. Visit megaphone.fm/adchoices Learn more about your ad choices. Visit megaphone.fm/adchoices

Episode Overview What if you could invest in some of the world's most valuable private technology companies—before they ever go public? In this episode of The Silicon Valley Podcast, host Shawn Flynn sits down with Mark Klein, CEO of Neostellar  Capital, one of the few publicly traded venture capital firms providing investors with exposure to late-stage private companies. Neostellar 's portfolio includes investments in some of the most influential technology companies of the AI era, including OpenAI, Canva, Whoop, Vast Data, and it was also an early investor in CoreWeave. Mark shares how Neostellar 's "Public VC" model opens the door for public market investors to participate in venture-backed innovation—an opportunity that has traditionally been reserved for institutional investors and elite venture capital firms. The discussion dives into one of Neostellar 's most notable investments: its $17.5 million investment in OpenAI during the company's September 2024 funding round. As OpenAI's valuation has risen dramatically, Mark explains what that means for Neostellar  shareholders and how the firm evaluates opportunities in today's rapidly evolving AI investment landscape.. Beyond AI, Mark provides a behind-the-scenes look at the venture capital ecosystem, discussing secondary markets, companies remaining private longer, valuation discipline, and the unique challenges of operating a publicly traded venture capital firm while investing in private businesses. Whether you're a founder, investor, venture capitalist, or simply fascinated by the intersection of AI and capital markets, this episode provides valuable insight into how some of today's most sought-after private companies become investment opportunities. In This Episode Mark Klein's path to leading Neostellar  Capital Understanding the Public Venture Capital model Why private companies are staying private longer Investing in OpenAI before its valuation surge Lessons from being an early CoreWeave investor The future of AI infrastructure investing The growing role of secondary markets in venture investing Balancing public company transparency with private company confidentiality Where Mark sees the next wave of technology investment opportunities About Mark Klein Mark Klein is the Chief Executive Officer of Neostellar  Capital Corp. (NASDAQ: SSSS), a publicly traded venture capital firm focused on investing in high-growth, venture-backed private technology companies. Since its inception, Neostellar  has provided public market investors with access to companies that traditionally remain unavailable until IPO, building a portfolio that includes OpenAI, Canva, Whoop, Vast Data, CoreWeave, and numerous other category-defining businesses. Key Takeaways Public markets can provide exposure to private innovation through specialized investment vehicles. Secondary markets have become an increasingly important source of liquidity and deal flow. Companies staying private longer have fundamentally changed venture investing. Successful venture investing requires balancing long-term conviction with disciplined valuation analysis. Connect with Mark Klein LinkedIn: https://www.linkedin.com/in/mark-klein-6a5b72198/   Disclaimer: The views expressed in this podcast are for informational purposes only. They do not constitute financial or legal, tax, or investment advice, nor do they necessarily reflect the views of Finalis Inc. or Finalis Securities LLC, Member FINRA/SIPC. Any discussion of investments, valuations, or portfolio companies is for educational purposes only and should not be considered a recommendation or solicitation to buy or sell any security. Investors should conduct their own due diligence and consult their professional advisors before making any investment decisions.   #SiliconValleySuccesses #VentureCapital #PrivateMarkets #OpenAI #ArtificialIntelligence #AIInfrastructure #CoreWeave #TensorWave #AMD #NVIDIA #PublicMarkets #NASDAQ #StartupInvesting #Innovation

Hey everyone... welcome back to The Malayali Podcast.Njan innu ningalodu oru simple question chodikan aanu vannirikkunnath."Exactly one year kazhinjal... ningalude life engane irikkum?"Seriously... close your eyes for a second.Oru varsham.365 days.Athrayum time-il enthellam sambhavikkam?New job.New city.New business.Marriage.Breakup.Promotion.Million subscribers.Or maybe... just finally becoming the person you've always wanted to be.You know...Oru year-il life full change aavan pattum.Pakshe...Most of us underestimate what one year can do.Nammal ellarum January first varumbo goals ezhuthum.Gym.Reading.Business.Learning AI.Saving money.January 10 aavumbo...Notebook drawer-il.Dreams postpone cheyyum.Because...Nammal oru mistake cheyyunnu.We overestimate what we can do in one week...But underestimate what we can do in one year.Imagine...Daily just 1 hour padichal...One year kazhinjal...365 hours.That's almost enough to become really good at a completely new skill.One small habit.One hour.Every day.That's how lives change.Not overnight.But over time.Enikku oru story parayam.Imagine two friends.Rahulum Arjunum.Both are 25.Both have the same salary.Same laptop.Same internet.Same opportunities.Rahul every day parayum..."Nale thudangam.""Ippo time illa.""I'll start after Onam.""After New Year."One year passes.Nothing changes.Arjun?Daily 30 minutes coding padichu.Weekend-il freelancing start cheythu.LinkedIn-il content post cheythu.AI tools padichu.One year later...Same person.Different life.Difference?Not talent.Not luck.Just...He started.Last one week news nokkiyal...Almost every day AI-il puthiya updates varunnu.Companies are hiring people who know how to work with AI—not because AI replaces everyone, but because people who use AI effectively often work faster and smarter.Every week...Someone launches a startup.Someone gets funding.Someone builds an app over a weekend.Someone uploads their first YouTube video.Someone quits their job.Someone gets their dream job.Someone starts learning at age 40.Someone changes their life at age 60.News nammale oru karyam padhippikkunnu.The world doesn't wait.Technology doesn't wait.Time doesn't wait.Question is...Will you?Njan oru karyam notice cheythittund.People think confidence comes first.Actually...Confidence comes after action.Nobody starts confident.The first podcast...Awkward.First video...Cringe.First business...Probably fails.First speech...Hands shake.First gym day...Embarrassing.Pakshe...Second time becomes easier.Tenth time becomes normal.Hundredth time...That's your identity.Self-belief isn't born.It's built.Imagine...Exactly one year from today.You wake up.You open your phone.Bank account is healthier.Mind is calmer.Body feels stronger.Family is proud.You're living in a different city.Maybe even a different country.Or maybe...You're still in the same place.But you're a completely different person.Because...You decided to start.One decision.One year.A completely different life.So today...I don't want you to promise yourself ten things.Just one.Start.Not tomorrow.Not Monday.Not next month.Today.Because...Oru year passes really fast.And one year from now...You'll either say..."I'm so glad I started."Or..."I wish I had started."The choice is yours.Live your life.Ellam nannayi aavum.Trust the process.This is Krishnalal, and you're listening to The Malayali Podcast.See you in the next episode.Take care. ❤️INTRO (0:00 – 1:00)PART 1 – The One-Year Illusion (1:00 – 3:00)PART 2 – A Story About Two Friends (3:00 – 5:00)PART 3 – What Happened This Week? (5:00 – 7:00)PART 4 – My Own Observation (7:00 – 8:30)PART 5 – Imagine Future You (8:30 – 9:30)OUTRO (9:30 – 10:00)

Alan Mikhail details the background of Anthony's wife, Grietje, a German migrant who worked as a barmaid or sex worker in Amsterdam. He explains the "soul seller" system used by maritime companies to recruit laborers. The couple married in 1629 and eventually sailed for New Amsterdam. (10)1650 AMSTERDAM

Rick Miranda, President of Aquidneck Landworks, joins the show to share the story behind building one of New England's most respected landscape companies. We dive into leadership, creating a premium customer experience, building a winning team, and the lessons learned from growing a business that stands out in a competitive market. If you're looking to elevate your company, improve your systems, and build a business you're proud of, this episode is packed with practical insights you won't want to miss.

On this week's show we take a hypothetical look at Cable and Satellite TV's future. We also read your emails and take a look at the week's news! News: Netflix Is Exploring Live TV and Bundles as It Struggles to Keep Viewers Hooked Scripps, DirecTV End Blackout, Ink New Retrans Deal RGB LED TVs Set For Market Growth In Coming Years What If Cable & Satellite Providers Exit Traditional Linear TV Business On this week's show we take a hypothetical look at Cable and Satellite TV's future.   We have said that we see TV being delivered via the Internet vs the traditional means of OTA, Cable, or Satellite. What would this world look like and who are the winners and losers? Scenario Setup Major providers — Comcast/Xfinity, Charter/Spectrum, DirecTV, Dish Network, Altice, and smaller cable operators — face accelerating cord-cutting. Traditional pay-TV subscribers have already dropped to ~34% of U.S. households. Revenue from linear TV (cable channels + satellite) is shrinking fast due to high programming costs, declining ad revenue, and competition from streamers. In this scenario, the industry collectively decides to abandon legacy linear TV (bundled channel packages) and pivots hard to two main businesses: High-speed broadband/data which is their most profitable product. IPTV / Streaming aggregation with their own apps or virtual third party MVPD services like YouTube TV-style offerings. They sunset traditional cable TV boxes, satellite dishes, and legacy contracts over 2–3 years. What Happens Next For the Providers it's mostly upside. Broadband becomes ~70–80% of revenue. Margins on data are much higher than on video because there are no expensive content carriage fees. Companies like Comcast and Charter already make most of their profit from data. Huge reduction in programming fees paid to Disney, NBCU, Warner, etc. No more maintaining old coaxial/satellite infrastructure for TV. All of which greatly cuts costs. New Growth Areas: Sell/partner on IPTV services (e.g., Xfinity Stream becomes the main offering, or they white-label streaming bundles). Mobile + home internet bundles (5G fixed wireless + fiber expansion). Advertising on their own streaming platforms. The biggest hurdles are massive customer service transition, potential loss of some rural satellite customers, and potential regulatory scrutiny over broadband monopolies. For Consumers the benefits include: Lower base bills, faster innovation in home internet which results in more fiber, better speeds, and  lower latency, and IPTV options could be cheaper/better than old cable (cloud DVR, multi-device streaming). Of course there is a downside. Sports fans and older viewers lose easy "flip channels" experience. Live sports become fragmented across streamers which could end up costing more if you want everything.  There will be Market & Industry Ripple Effects Streaming Wars Accelerate: YouTube TV, Hulu + Live TV, Sling, Fubo, and new entrants gain millions of former cable customers. Netflix, Amazon, etc., may expand live offerings. Content Owners Adapt: Networks like ESPN, CNN, TBS shift to direct-to-consumer or wholesale deals with IPTV platforms. Some channels may disappear or go streaming-only. Competition & Consolidation: Telecoms (AT&T, Verizon) and tech giants (Google Fiber, Amazon, Starlink) push harder into broadband. We could see more mergers. Advertising: Shift from traditional cable ads to targeted streaming ads and broadband data insights. The reality is that it's already happening gradually. Cable companies have been de-emphasizing video for years, pushing broadband bundles, and launching their own streaming apps. Satellite providers are in steeper decline. The full pivot described here would simply formalize and accelerate a trend that's well underway.   

Why do AI agents and applications look impressive in demos but struggle when companies try to deploy them in production? In this episode of Tech Talks Daily, I speak with Nikunj Bajaj, co-founder and CEO of TrueFoundry, about why enterprise AI has become a systems problem, what companies need to move AI from proof of concept to production, and how better infrastructure can improve reliability, governance, security, observability, and cost control. Before founding TrueFoundry, Nikunj worked at Meta on conversational AI systems serving more than a billion users and contributed to the company's internal machine learning platforms. He explains how developers at Meta could concentrate on solving business problems while infrastructure handled logging, monitoring, deployment, and governance by default. In many enterprises, the same journey from an AI idea to a production application can still take weeks or months. Nikunj argues that increasingly capable AI models are not necessarily the biggest barrier to enterprise adoption. The harder challenge is building reliable systems around them. Companies need to know what happens when a model becomes unavailable, how an agent is behaving, which data it can access, how much it is costing, when a human should intervene, and whether there is a kill switch when something goes wrong. We discuss why AI proofs of concept often fail when exposed to real users. Controlled demonstrations rarely reproduce production conditions such as unexpected prompts, malicious actors, heavy workloads, model outages, latency, and dependencies between multiple components. Even when individual parts of a system perform reliably, combining them can create failure rates that businesses cannot accept for mission-critical workflows. The conversation also examines the infrastructure required as companies introduce multiple AI models and agents. Nikunj explains the roles of model gateways, MCP gateways, and agent gateways, and how bringing these components together through an AI gateway can give enterprises a control plane for observing and governing AI traffic. Cost is another major challenge. Nikunj explains why sending every request to the most powerful model can waste significant amounts of money when smaller or cheaper models could produce comparable results for simpler tasks. Intelligent model routing can help companies balance quality, latency, availability, and price. He shares how organizations using this approach have reduced model costs by as much as 75 to 80 percent in some production environments. We also discuss what reliable multi-agent systems require in practice. Companies need clearly defined boundaries for what agents can do, escalation routes to other agents or people, safeguards against infinite agent loops, and complete audit trails of interactions and decisions. For CIOs, CTOs, AI engineering teams, platform leaders, and companies trying to move generative AI and agentic AI into production, this conversation provides a practical guide to the infrastructure decisions that determine whether AI applications remain impressive prototypes or become reliable business systems. The next stage of enterprise AI will not be defined by models alone. Companies that can connect, observe, govern, secure, and control their AI applications while managing costs will be better positioned to turn experimentation into dependable production systems.

Most of us have no idea what our retirement money is actually funding. A few years ago I started wondering if some of mine was supporting things I would never support on purpose. So in this episode, I answer a question I get all the time. Should Christians invest in companies that conflict with their faith? I walk through the two main approaches: biblically responsible investing and buying in to influence a company from the inside. I share the question I ask before buying any individual stock. And I reveal the spending blind spot that might matter even more than your portfolio. Strong believers land on both sides of this one, so we're not going to pretend it's simple. If you enjoyed this, we'd love to send you a free copy of our book. You just cover shipping. It has over 1,000 5-star reviews on Amazon. Grab it at: seedtime.com/free.   What We Cover Here's a little of what we cover in this episode: The uncomfortable question I finally had to ask about my own investments Two completely opposite approaches Christians take (both from strong believers) The one question I ask before buying any individual stock Why boycotting a stock might matter less than you think The everyday habit that funds companies far more than any shareholder does The story behind the shirt I'm wearing and the 50 cent wage that inspired it   Bible Verses Mentioned Romans 3:23   Resources Mentioned 10x Investing course Real Money Method course   Disclaimer Obligatory legal disclaimer: I'm a financial educator, not your financial advisor, investment advisor, tax pro, or lawyer. This channel is for general education, not personalized advice, and nothing here should be taken as a recommendation to buy, sell, or use any specific investment, account, or financial product. I'm just sharing what I'm doing, what I'm learning, and what I find interesting. Markets can be humbling. Investing involves risk, including the risk of losing money, and my results are personal, may not be typical, and are not guaranteed. Do your own research, use wisdom, and talk with a qualified professional before making financial decisions. Some links are to our resources and some are affiliate links, which means we may earn a commission at no extra cost to you. That helps keep the lights on around here, so thanks for the support.

The operating model implication is clear: AI deployment is now fundamentally an organizational redesign challenge, not a software procurement exercise. Companies winning with AI are restructuring workflows, flattening management, embedding engineering into operations, and accelerating decision cycles. The largest leadership execution risk is cognitive overload at the executive layer. Teams are shrinking while ambiguity, pace, and strategic complexity are increasing simultaneously. Highest leverage focus area today: Redesign decision systems before scaling AI systems. https://www.breakfastleadership.com/  

For more thoughts, clips, and updates, follow Avetis Antaplyan on Instagram: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠https://www.instagram.com/avetisantaplyan⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠In this solo episode of The Tech Leader's Playbook, Avetis Antaplyan challenges one of the most common questions surrounding artificial intelligence: How quickly can companies replace people with AI? Instead, he argues that leaders should ask whether they are making expensive organizational decisions by overestimating what AI can accomplish without experienced people.Drawing on emerging workforce trends and examples from major technology companies, Avetis examines why some organizations now regret making deep, AI-driven staffing cuts. He explains that while AI can generate code, summarize meetings, analyze data, and accelerate administrative work, it cannot replace judgment, accountability, leadership, customer understanding, or institutional knowledge.Avetis also explores the hidden costs of AI adoption, including infrastructure expenses, governance, human oversight, rehiring, retraining, cultural damage, and the risk of repeating errors at scale. He encourages technology leaders to use AI to increase employee output rather than treating it as a blanket headcount-reduction strategy.Ultimately, the episode offers a balanced warning against both overreacting and underreacting to AI. The companies that win will not necessarily be those that eliminate the most jobs, but those that combine powerful AI tools with experienced people, disciplined decision-making, and strong leadership.TakeawaysLeaders should ask how AI can improve employee output—not simply how many employees it can replace.Many companies are discovering that they cut staff too deeply or too quickly.AI can generate options, but leaders must remain responsible for decisions.Long-tenured employees carry institutional knowledge that may disappear when they leave.Rebuilding an eliminated team can cost significantly more than the original payroll savings.AI can scale excellence, but it can also repeat one mistake thousands of times.Aggressive automation can damage trust, retention, innovation, and company culture.Underreacting to AI is also dangerous; leaders need adoption without reckless organizational disruption.Chapters00:00 The Wrong Question About AI02:05 Companies Are Regretting AI-Driven Cuts03:55 What AI Still Cannot Replace05:45 The Hidden Cost of Lost Knowledge07:45 Rehiring and Rebuilding Teams09:55 Infrastructure, Oversight, and Errors at Scale11:55 AI's Impact on Trust and Culture13:35 How the Best Companies Use AI16:10 Productivity Is Not Replacement17:25 What Technology Leaders Should Do18:55 AI Exposes Average Work20:15 The Risk of UnderreactingResources and Links:⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠https://www.hireclout.com⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠https://www.podcast.hireclout.com⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠https://www.linkedin.com/in/hirefasthireright⁠

Over 100 scientists have left ISRO in one year & following the spate of resignations, the Centre has tightened rules around exits and voluntary retirement. #CutTheClutter Episode 1865 looks at reasons behind this exodus, brewing crises in ISRO and why these point to challenges for India's space programme. ThePrint Editor-In-Chief Shekhar Gupta also details the private sector boom in our nation's space sector, and some of the companies doing noteworthy work in the area.----more----Watch #OffTheCuff with Pawan Kumar Chandana, Co-Founder & CEO of Skyroot Aerospace here: https://www.youtube.com/watch?v=qcUpyye3OwM----more----Read Soumya Pillai's story on scientists leaving ISRO here: https://theprint.in/india/india-opened-space-to-private-players-isro-brain-drain-is-one-result/2987999/----more----Watch #CutTheClutter on importance of satellites in modern warfare here: https://www.youtube.com/watch?v=U839-QEUZ7s----more----Watch #CutTheClutter on Pakistan's space programme here: https://www.youtube.com/watch?v=aqaxD1rgQFw----more----Watch Walk The Talk with Prof CNR Rao here: https://www.ndtv.com/video/walk-the-talk-with-bharat-ratna-cnr-rao-308738 

What happens when your next customer is represented by an AI agent that can research products, compare prices, evaluate suppliers, negotiate terms, and make purchasing decisions? In this episode of Tech Talks Daily, I speak with Ian Kahn, Partner and Customer and Commercial Excellence Platform Leader at PwC, about the rise of the Intelligent Customer Edge and why companies need to rethink how they sell, market, price, serve customers, and compete as artificial intelligence changes the buying process. Much of the enterprise AI conversation has focused on helping employees become more productive. Ian argues that this overlooks a much bigger change already taking place. Customers are using AI to research products, compare alternatives, evaluate pricing, and make decisions. In some consumer and business markets, AI agents are already being given permission to make routine purchases. Companies are no longer selling only to people. They increasingly need to serve customers whose AI agents expect accurate product information, transparent pricing, availability, service history, and performance data that can be discovered, verified, and understood by machines. This creates a serious problem for companies operating with fragmented front offices. Marketing, sales, pricing, commerce, and customer service have traditionally operated as separate functions, each with its own technology, data, processes, incentives, and performance measures. Customers do not experience companies through those internal structures. They expect consistent information and relevant experiences across the entire relationship. Ian explains why adding AI to each department independently will not solve this problem. Companies risk making existing processes faster without improving the customer experience or business performance. Instead, he argues that leaders need to reconsider the operating model behind the entire customer journey. The Intelligent Customer Edge is PwC's approach to bringing these commercial functions together into a connected system centered on the customer. Powered by proprietary company data and AI, the system can continuously learn from customer interactions, support real-time decisions, and help companies respond to changing customer needs. We also discuss the idea of the commercial brain and why proprietary data could become one of the most valuable competitive advantages available to companies adopting AI. Most businesses already possess customer records, transaction histories, operational information, market signals, service interactions, and other data their competitors cannot access. Yet much of that information remains fragmented across systems and departments. Ian explains how connecting these sources can create an intelligence layer that informs pricing decisions, marketing activity, sales opportunities, service interactions, and the moments that matter throughout the customer relationship. For CEOs, chief customer officers, marketing leaders, sales executives, CIOs, and technology teams, the conversation offers an important lesson about AI transformation. The companies achieving meaningful results are not starting with the technology. They begin with customer outcomes and redesign the work, decisions, workflows, and operating models required to achieve them. Human judgment remains an important part of that model. AI can process large amounts of information, identify patterns, provide recommendations, and handle routine tasks consistently. People continue to bring judgment, creativity, empathy, relationship-building, and strategic decision-making to customer interactions where trust and context matter. Ian argues that the goal is not to choose between people and AI. Companies need to design customer systems that use the strengths of both, determining where automation can improve speed and consistency and where people can create greater customer and commercial value. Trust, governance, explainability, and accountability also become more important as AI agents are given greater authority. Rather than treating guardrails as barriers to adoption, Ian explains why companies should design controls into AI-enabled customer processes from the beginning. The conversation also examines the cost of waiting. Customers are already adopting AI, and businesses that continue relying on fragmented front-office operations risk falling behind competitors capable of responding faster, providing better information, and creating more relevant customer experiences. Ian offers practical advice for companies deciding where to begin. Start with the customer journey. Understand how customer behavior is changing, identify where friction exists, determine how AI could improve the experience, and establish clear measures for customer outcomes and business value before investing heavily in new technology. For business and technology leaders under pressure to deliver growth, improve margins, control costs, and demonstrate returns from AI investment, this conversation provides a practical framework for redesigning the front office, using proprietary data more effectively, preparing for AI agents as buyers, and creating better customer experiences. Your customers are already using AI. Some AI agents are already making purchasing decisions. The question for companies is whether their customer systems, data, commercial models, and operating structures are ready to compete for business when the buyer on the other side of the transaction is no longer always human.

What if the biggest barrier to better customer service isn't how quickly employees work, but how much time they lose coordinating with everyone else? In this episode of Tech Talks Daily, I speak with Kevin Yang, Head of AI at Front, about why customer conversations are becoming a valuable source of business intelligence, how AI can improve work across entire teams rather than simply making individuals faster, and the hidden coordination costs affecting customer operations. Kevin brings a unique perspective to the conversation. Before joining Front following its acquisition of his AI voice-of-customer company, Syllable, he spent 15 years as an entrepreneur. While building an office food delivery business, he experienced firsthand how customer conversations could reveal problems that traditional surveys and dashboards failed to identify. By analyzing customer feedback at scale, his team could connect specific issues directly to retention, account growth, and referrals. Today, AI makes it possible for companies to analyze enormous volumes of customer conversations and turn unstructured feedback into intelligence that can inform decisions across product development, sales, marketing, and customer success. Kevin shares how Front analyzes conversations to understand why deals are lost, why customers leave, and which topics are associated with higher sales conversion rates. The result is a feedback loop that helps companies direct product investment toward problems customers genuinely care about while giving sales and marketing teams a clearer understanding of the conversations that influence buying decisions. But the episode also challenges the assumption that giving every employee an AI assistant will transform productivity. Front's Coordination Tax research found that teams can spend almost three hours coordinating work for every hour spent solving customer problems. When a single customer request requires input from sales, finance, support, operations, or external systems, employees can lose time to emails, Slack messages, meetings, handoffs, and information searches. Kevin explains why making one person faster does little to solve this problem if the rest of the workflow remains fragmented. The bigger opportunity is to use AI across end-to-end processes, automatically handling research and analysis while allowing people to concentrate on work requiring judgment, empathy, relationships, and human decision-making. We also discuss the growing use of AI agents in customer operations and why governance becomes harder as companies move from experimenting with one agent to managing many. Kevin outlines the need to measure whether agents follow processes correctly, understand customer satisfaction, identify where failures occur, and continuously improve the knowledge and guidance available to AI systems. For business and technology leaders considering where to apply AI, Kevin offers a practical starting point. Map the work your teams perform into three categories: tasks AI can automate, tasks AI can support with human review, and tasks that should remain human. This helps companies focus investment where AI performs well rather than forcing automation into customer interactions that depend on empathy, context, and relationships. For anyone responsible for customer experience, AI strategy, operations, or digital transformation, this conversation provides practical ideas for turning customer conversations into business intelligence, reducing coordination friction, designing better workflows, and introducing AI agents with greater visibility and oversight. The opportunity is not simply to make individuals work faster. It is to redesign how work moves across the organization so employees spend less time coordinating and more time solving the problems that matter to customers.

Today's listener is at risk of falling prey to a shady network marketing (MLM) company. How do we know it's shady? Because it's a network marketing company! Listen and learn.Side Hustle School features a new episode EVERY DAY, featuring detailed case studies of people who earn extra money without quitting their job. This year, the show includes free guided lessons and listener Q&A several days each week.Show notes: SideHustleSchool.comEmail: team@sidehustleschool.comBe on the show: SideHustleSchool.com/questionsConnect on Instagram: @193countriesVisit Chris's main site: ChrisGuillebeau.comRead A Year of Mental Health: yearofmentalhealth.comIf you're enjoying the show, please pass it along! It's free and has been published every single day since January 1, 2017. We're also very grateful for your five-star ratings—it shows that people are listening and looking forward to new episodes.

Patrick Samuels is the founder of Sunnyside Egg Co. and is taking on the entire industrial egg industry. We dive deep on the corrupt system of big egg corporations and how, as consumers, we're being lied to and are victims of clever marketing, and nice-sounding word choices.  Sunnyside Egg Co. provides an alternative to a system that is taking advantage of people who want the healthiest eggs possible, and is the only company in the United States truly scaling REGENERATIVE eggs.  Where you can find Sunnyside Egg Co. Website - https://sunnysideeggco.com Instagram - https://www.instagram.com/sunnysideeggco/ Request Sunnyside Egg Co. at Sprouts:  https://www.sprouts.com/contact/ Sunnyside Egg nutrient density test results: https://www.instagram.com/p/DalsAL0Bj7i/ Learn more about your ad choices. Visit megaphone.fm/adchoices

In this episode of The Brainstorm, Brett, Sam, and Nick are joined by Frank Downing to break down how OpenAI, Anthropic, Meta, and X are competing on performance, pricing, and deployment strategy as the AI market gets more efficient. Frank Downing explains why the economics of AI matter as much as the benchmarks, while Brett Winton argues the true “iPhone moment” for agentic AI may still be ahead.Key Points From This Episode:AI competition is increasingly about economics, not just intelligence. Companies are choosing between expensive frontier models and cheaper open-source alternatives based on cost, performance, and strategic fit.The real "iPhone moment" for AI may still be ahead. Model benchmarks are improving, but reliable autonomous task execution is what could ultimately matter.Open-source and lower-cost models are gaining traction on simpler knowledge work. That could commoditize parts of the market and pressure the business models of frontier labs.If you know ARK, you know we focus on long-term innovation. But that doesn't mean we ignore breaking news. Every day, we debate the latest developments in tech and markets. Now, we're bringing those conversations to you in “The Brainstorm,” a co-production from ARK, WOLF, and Public. Tune in weekly for our quick takes on what's shaping innovation right now.Learn more about WOLF: https://wolf.financialLearn more about Public: https://public.com/Disclosure: http://arkinv.st/39rzF94

Last month, comedians Harris Alterman and Dave Ross posted a series of advertisements for made-up tech companies around the New York City subway system. The ads are fake, but they bear an eerie resemblance to the real AI marketing campaigns proliferating throughout U.S. cities. Marketplace's Meghan McCarty Carino spoke with the two comedians about why the joke resonated with so many people and what's next in terms of AI mockery.

Last month, comedians Harris Alterman and Dave Ross posted a series of advertisements for made-up tech companies around the New York City subway system. The ads are fake, but they bear an eerie resemblance to the real AI marketing campaigns proliferating throughout U.S. cities. Marketplace's Meghan McCarty Carino spoke with the two comedians about why the joke resonated with so many people and what's next in terms of AI mockery.

Companies like 'Anthropic' and 'OpenAI' are warning Congress that China is stealing their cutting-edge AI to produce cheaper, open-source chatbots. The U.S. firm alleges 'DeepSeek', 'Moonshot AI' and 'MiniMax' are using 'distillation' attacks to generate more than 16 million exchanges with 'Anthropic's Claude' chatbot in a coordinated campaign designed to extract high-value model outputs which is cutting into the U.S.'s thin lead in AI development. Meanwhile, New York State Governor Kathy Hochul has put a one year moratorium on building 'hyperscale' data centers in her state. FOX's Gurnal Scott speaks with Kyler Schmitz, Vice President of 'Patmos Hosting', an AI infrastructure company, who says coordination from both the private sector and the Federal Government is needed to secure AI innovations , as does the building and powering of data centers. Click Here⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ To Follow 'The FOX News Rundown: Evening Edition' Learn more about your ad choices. Visit podcastchoices.com/adchoices

Many investors feel like the AI trend peaked and some AI stocks are taking it on the chin in response. However, Taiwan Semiconductor is showing an accelerated growth rate and Meta Platforms is nearly doubling the scope of one of its important data centers, suggesting the AI buildout is still on. In light of this, Matt and Rachel each highlight a hidden company that can benefit from the trends. Finally, Jon throws a question to them from a listener regarding selling stocks to pay for school, avoiding student loan debt. Jon Quast, Matt Frankel, and Rachel Warren discuss:-Taiwan Semiconductor's accelerated growth in June-Meta Platforms' greatly expanded data center in Louisiana-How Comfort Systems USA benefits from the trends-How Celestica benefits from the trends-Listener question: Should I sell stocks to pay for school? Companies discussed: Taiwan Semiconductor Manufacturing (TSM), Meta Platforms (META), Comfort Systems (FIX), Celestica (CLS) Host: Jon QuastGuests: Matt Frankel, Rachel WarrenEngineer: Kristi Waterworth Disclosure: Advertisements are sponsored content and provided for informational purposes only. The Motley Fool and its affiliates (collectively, “TMF”) do not endorse, recommend, or verify the accuracy or completeness of the statements made within advertisements. TMF is not involved in the offer, sale, or solicitation of any securities advertised herein and makes no representations regarding the suitability, or risks associated with any investment opportunity presented. Investors should conduct their own due diligence and consult with legal, tax, and financial advisors before making any investment decisions. TMF assumes no responsibility for any losses or damages arising from this advertisement. We're committed to transparency: All personal opinions in advertisements from Fools are their own. The product advertised in this episode was loaned to TMF and was returned after a test period or the product advertised in this episode was purchased by TMF. Advertiser has paid for the sponsorship of this episode. Learn more about your ad choices. Visit ⁠megaphone.fm/adchoices⁠ Learn more about your ad choices. Visit megaphone.fm/adchoices