Podcasts about Chief technology officer

Sid Dixit is originally from central India, and came to the states for college. He is a technologist and builder at heart, serving in leadership roles across major companies. He has built and managed a fleet of satellites, built robots at Amazon, worked at Microsoft on surface tablets, and finally, at Google working on Android. Outside of tech in lives in the Bay Area with his wife and kids. He loves water sports, especially sailing. He spent 10 years in San Diego, and stumbled on the sport.Sid's current company started in 1999, and was acquired in 2010. A few years ago, Sid joined the company, at a time when the company was wanting to rebuild its network from the ground up - starting with a powerful index.This is Sid's creation story at iTradeNetwork.SponsorsUnblockedTECH DomainsMezmoBraingrid.aiLinkshttps://www.itradenetwork.com/https://www.linkedin.com/in/siddharthdixit/Our Sponsors:* Check out Cash App and use my code CASHAPP10 for a great deal: https://cash.app* Check out Plaud AI and use my code CODESTORY for a great deal: https://plaud.aiAdvertising Inquiries: https://redcircle.com/brandsPrivacy & Opt-Out: https://redcircle.com/privacy

Financial advisors are being pitched new AI tools almost every day.The promise is simple: more automation, better client service, and fewer hours buried in administrative work.But adding AI to a fragmented technology stack doesn't automatically make your business smarter. If your client data is incomplete, trapped inside disconnected systems, or flowing through tools you haven't properly vetted, AI may amplify the problems you already have.Today, I'm talking with Triad's Chief Technology Officer, Quin Kilgore, to explore why the next era of advisor technology won't be won by the firm with the most software.We discuss why the tools that helped build your firm may not be the tools that carry it forward, where convenience can create hidden compliance risks, and how AI could reshape everything from marketing attribution and advisor coaching to client events and everyday operations.3 Insights From This Week's Episode…#1.) The Hidden Risk Beneath Every AI Tool Advisors tend to focus on what a new AI tool can do. But the bigger risk may be hiding in incomplete client records, fragmented systems, and unclear data policies. We explore why AI adoption can make weaknesses in your firm's foundation much harder to ignore.#2.) Why Today's Tech Stack May Become Tomorrow's BottleneckFor years, advisory firms built their businesses around software that was expensive to customize and painful to replace. Quin explains how quickly that equation is changing, and why advisors may need to reconsider what a “core” technology system even looks like.#3.) The Client Intelligence Advisors Are Leaving BehindYour client conversations contain far more valuable information than a traditional fact finder can capture. We explore what becomes possible when that information can be organized, understood, and used throughout the firm.INTERESTED IN TRIAD'S AI MASTERMIND?Triad's AI Advisor Lab, led personally by Michael Hyatt, is built for financial advisors who want to cut through the hype, apply AI more effectively, and stay ahead as the industry evolves. Apply here to see if the mastermind is the right fit for your firm: https://bradleyjohnson.com/178-ai-advisor-labSHOW NOTEShttps://bradleyjohnson.com/178FOLLOW BRAD JOHNSON ON SOCIALXInstagramLinkedInFOLLOW DBDL ON SOCIAL:YouTubeTwitterInstagramLinkedInFacebookDISCLOSURE DBDL podcast episode conversations are intended to provide financial advisors with ideas, strategies, concepts and tools that could be incorporated into their business and their life. No statements made in the episode are offered as, and shall not constitute financial, investment, tax or legal advice. Financial professionals are responsible for ensuring implementation of anything discussed related to business is done so in accordance with any and all regulatory, compliance responsibilities and obligations. The Triad member statements reflect their own experience which may not be representative of all Triad Member experiences, and their appearances were not paid for. Triad Wealth Partners, LLC is an SEC Registered Investment Adviser. Please visit Triadwealthpartners.com for more information. Triad Wealth Partners, LLC and Triad Partners, LLC are affiliated companies. TP07265629240See Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

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.

La Commissione europea impone a Google di condividere i dati delle ricerche con i motori concorrenti e di aprire Android ai servizi di intelligenza artificiale alternativi a Gemini. Due decisioni importanti per il settore tecnologico destinate a cambiare molte attuali dinamiche. Ne parliamo con Innocenzo Genna, esperto di regolamentazione europea in ambito digitale e Roberto Pezzali, esperto di tecnologia della redazione di Dday.it.Fastweb ha iniziato una sperimentazione con Starlink per usare normali smartphone 4G in aree remote del Paese dove è assente il servizio di telefonia mobile terrestre. È il primo test in Italia della tecnologia “Direct to Cell” come spiega Max Gasparroni, Chief Technology Officer di Fastweb + Vodafone.Con Stefano Sordi, direttore generale di Aruba, ci occupiamo delle nuove estensioni Internet di primo livello che verranno assegnate nei prossimi mesi: nasceranno nuovi domini collegati a specifici brand, regioni o città.E come sempre in Digital News le notizie di innovazione e tecnologia più importanti della settimana.

If you're feeling burnt out, it's not the work you're doing. It's the mission you're on. Today, we're talking to Justin Fanelli, Chief Technology Officer of the Department of the Navy. We discuss why direct communication is fuel rather than friction, how the most driven government workers are often the ones who've already "made it" elsewhere, and why burnout has almost nothing to do with hours worked and everything to do with whether you feel connected to something bigger. All of this right here, right now, on the Modern CTO Podcast! 

Why are companies spending heavily on AI tools while struggling to show meaningful improvements in productivity, revenue, or business performance? In this episode of Tech Talks Daily, I speak with Matt Cloke, Chief Technology Officer at Endava, about what it takes to become an AI-native business, why deploying thousands of AI licenses does not amount to an AI transformation, and how companies can move from experimentation to measurable business outcomes. Matt has played a central role in Endava's own adoption of artificial intelligence and the development of Dava.Flow, the company's methodology for applying AI throughout the technology delivery lifecycle. With more than 11,000 employees and clients operating across multiple industries, Endava has treated itself as "client zero," testing AI internally before advising other companies about how to introduce it across their operations. Matt shares the story of a CEO who proudly told him that his company had completed its AI transformation after purchasing 10,000 licenses for an AI tool. Twelve months later, the business had seen little return on its investment and returned for help understanding what becoming AI-native actually required. The story captures one of the biggest problems with enterprise AI adoption today: buying technology is easy, but changing how people think about problems, redesign workflows, and create business value is much harder. We discuss why Matt believes becoming AI-native is primarily a mindset. Rather than treating AI as another application added to the technology stack, employees should become curious about where AI can improve existing processes, remove unnecessary work, and create new ways of delivering value. Matt also explains his idea that AI works best when it becomes invisible. Instead of requiring employees to constantly interact with chatbots and standalone AI applications, software agents can operate inside existing workflows, monitor information, prepare responses, identify problems, and bring people into the process when human judgment is required. His own use of AI agents provides a practical example. While attending meetings that prevented him from monitoring email for several days, Matt used agents to review incoming messages, redirect requests, identify urgent communications, and prepare draft responses. Rather than handing complete control to automation, he determined which actions required approval and where AI could operate independently. This leads to a wider discussion about human oversight and accountability. Matt argues that managing AI agents may increasingly resemble managing teams. Leaders do not inspect every decision made by every employee, but they establish responsibilities, controls, escalation points, and circumstances where intervention is required. Companies introducing agentic AI need similar approaches to supervision. We also examine two mistakes Matt frequently sees companies make. The first is treating AI adoption as a software rollout, buying tools for employees and expecting productivity gains to appear automatically. The second is creating centralized AI centers of excellence and expecting a small group of specialists to determine how every department should use the technology. Matt argues that employees closest to business processes are often best placed to identify opportunities for improvement. At Endava, the legal team runs monthly AI hackathons to redesign its own workflows, supported by technology specialists but led by people who understand the work itself. For companies operating in payments, financial services, and other regulated industries, the conversation turns to reliability, auditability, traceability, and risk. Matt explains how Dava.Flow allows companies to translate regulatory requirements and operational controls into policies that AI systems must follow and demonstrate throughout the delivery process. Rather than searching for a single killer AI application, Matt recommends examining end-to-end business workflows. Companies can map how information moves between employees, departments, and systems, identify unnecessary handoffs and manual processes, and determine where AI agents can improve speed, cost, and performance without replacing entire technology platforms. Leadership is another major theme throughout the episode. Matt believes the companies that achieve meaningful results from AI will be led by executives who personally use the technology, understand its capabilities, and demonstrate the behaviors they expect from their workforce. He shares how Endava brought senior leaders from legal, technology, people, and other business functions together to build software agents themselves. The experience changed how executives thought about technology investments, including one leader realizing that an existing vendor contract might no longer be necessary because the company could build the required capability internally. For CIOs, CTOs, technology leaders, and business executives under pressure to demonstrate returns from AI investment, this conversation provides practical lessons on becoming AI-native, redesigning workflows, managing software agents, maintaining human accountability, operating AI in regulated industries, and moving beyond technology adoption toward measurable business value. The companies that succeed with AI may not be those buying the most tools or making the biggest announcements. They will be the ones whose leaders understand the technology, whose employees rethink how work gets done, and whose AI systems quietly become part of everyday business operations.

Your cybersecurity tools were built for people: a login, a single sign-on, an email address. But the AI agents now showing up inside your company don't work that way, and most of them slip right past your controls. So how do you find the "Shadow AI" already running in your business, and get a handle on it? Let's find out with our guest Nancy Wang, Chief Technology Officer at 1Password, who works at the front edge of how machines get access to systems. Your hosts are Kip Boyle, CISO with Cyber Risk Opportunities, and Jake Bernstein, Partner with K&L Gates.   LinkedIn profile profile: https://www.linkedin.com/in/wangnancy/   1Password: https://1password.com/

What happens to blockchain networks, digital assets, and the wider internet when quantum computers become powerful enough to break the cryptography protecting them? In this episode of Tech Talks Daily, I speak with Bruno Martins, Chief Technology Officer of the Algorand Foundation, about what quantum computing means for blockchain security, why post-quantum cryptography is becoming a technology priority, and how enterprises should evaluate blockchain infrastructure for payments, digital assets, identity, and other business applications. Bruno brings experience from across several major blockchain ecosystems, including Consensys and IOHK, alongside a background in applied cryptography, key management systems, enterprise blockchain development, and software engineering. His perspective provides a useful view of how the blockchain industry has changed from experimental projects and speculative use cases toward platforms expected to support real financial transactions and business operations. We begin with the quantum threat itself. Bruno explains why the cryptographic systems protecting blockchains, financial infrastructure, communications, messaging platforms, and much of the internet could eventually become vulnerable to sufficiently powerful quantum computers.  While the exact timeline remains uncertain, he argues that waiting for a cryptographically relevant quantum computer to arrive before beginning migration would leave companies with too little time to update infrastructure, applications, wallets, accounts, and user behavior. The conversation examines why post-quantum security is not simply a future technology problem. Large digital ecosystems can take months or years to migrate, and businesses need time to understand their cryptographic dependencies, introduce new standards, educate users, and build systems capable of adopting new security methods without disrupting existing operations. Bruno shares how Algorand has been working on post-quantum security for several years, including the deployment of Falcon signatures for state proofs and plans to introduce quantum-resistant account types and additional protections across consensus and network communications. We discuss why cryptographic agility may be more important than simply replacing existing cryptography with newer algorithms that have not yet experienced decades of testing in real-world systems. This leads to one of the most valuable technical lessons in the episode. Moving directly from classical cryptography to post-quantum cryptography introduces its own risks because newer cryptographic methods may later reveal weaknesses. Bruno explains why hybrid approaches, where digital assets and accounts can be protected by both established and quantum-resistant cryptography, could provide a more responsible path for institutions managing long-lived systems and valuable assets. We also examine how enterprises should evaluate blockchain platforms. With thousands of networks competing for developers, users, and institutional adoption, Bruno argues that businesses need to look beyond market attention and transaction speed. Throughput, decentralization, security, programmability, finality, operational risk, and the ability to trust the state of a ledger all influence whether blockchain infrastructure is suitable for real business operations. Payments provide a practical example. Companies issuing payment products backed by stablecoins need confidence that transactions are final and cannot later be reorganized or reversed by the underlying network. Bruno explains why instant finality can reduce operational uncertainty and risk for companies building financial applications on public blockchain infrastructure. The conversation also turns to AI agents and agentic commerce. If autonomous software agents begin negotiating, purchasing services, exchanging value, and conducting transactions with other agents, they will need payment rails, identity systems, trusted counterparties, and ways to establish ownership and accountability. Bruno explains why stablecoins, digital identity, decentralized finance, and blockchain infrastructure could become increasingly relevant as AI systems begin participating directly in economic activity. Throughout the episode, Bruno offers a balanced assessment of the blockchain industry itself. He discusses the problems created by technical fragmentation, competing standards, thousands of networks, and ecosystem tribalism. Greater cooperation between blockchain communities, particularly around wallets, hardware, cryptographic standards, and post-quantum security, could make it easier for enterprises and developers to build applications that work across ecosystems. For technology leaders, security professionals, blockchain developers, and anyone responsible for long-lived digital infrastructure, this conversation provides a practical introduction to quantum threats, post-quantum cryptography, cryptographic agility, blockchain finality, stablecoins, and the technical questions companies should ask before choosing distributed infrastructure. The quantum threat may not arrive tomorrow, but migrating complex systems takes time. The companies and technology platforms preparing today will be in a much stronger position to protect digital assets, maintain trust, and continue operating when current cryptographic standards eventually need to change.

Sejal Amin is the Chief Technology Officer at Priceline, where she leads product engineering, infrastructure, data, and technology operations. Pedro Gutierrez is Senior Director of Software Engineering, where he has helped drive developer experience initiatives and the adoption of Priceline's product operating model.In this episode of the Engineering Enablement podcast, Justin Reock talks with Sejal and Pedro about Priceline's journey from a project-based organization to a product operating model and the role developer experience played in making that transformation successful. They discuss how DX metrics and developer feedback helped identify organizational bottlenecks, guide structural changes, empower engineering managers, and build trust across teams. They also explore the importance of clear communication, creating a dedicated developer experience team, and how their operating model has helped prepare Priceline for AI-driven software development.Where to find Sejal Amin:  • LinkedIn: https://www.linkedin.com/in/sejal-aminWhere to find Pedro Gutierrez: • LinkedIn: https://www.linkedin.com/in/pedro-gutierrez-b6605422Where to find Justin Reock:• LinkedIn: https://www.linkedin.com/in/justinreock In this episode, we cover:(00:00) Intro(01:07) Meet Sejal Amin and Pedro Gutierrez(01:47) How Priceline's developer experience journey began(04:55) Lessons from Priceline's first developer experience surveys(06:55) How DX improved Priceline's developer experience surveys(09:47) Identifying the causes of organizational slowness(12:33) How the product operating model changed the way Priceline works(14:10) Priceline's phased rollout with DX(18:14) How DX insights drove organizational changes(19:33) Why Priceline improved developer experience before org change was complete(22:18) How clear communication builds trust(24:25) Early results from Priceline's Core Four(25:38) Creating a culture of continuous feedback to build trust(27:40) What has changed in the engineering manager role(30:10) Resources for learning about the product operating model(32:40) What Pedro learned from implementing DX(34:51) The developer experience team(35:59) How AI tools have impacted Priceline's teams (37:20) How the product operating model supports AI-driven development(39:13) Final advice for engineering leadersReferenced:• Measuring developer productivity with the DX Core 4• Transformed: Moving to the Product Operating Model (Silicon Valley Product Group) • Team Topologies• Flow Framework• Project to Product: How to Survive and Thrive in the Age of Digital Disruption with the Flow Framework

Michael speaks with Anthony Vinci, former career intelligence officer and the first Chief Technology Officer of the National Geospatial-Intelligence Agency. They discuss Anthony's new book, "The Fourth Intelligence Revolution: The Future of Espionage and the Battle to Save America", which explores how artificial intelligence and intensive competition with China have transformed modern spycraft. Anthony explains his forecast where "machines are going to spy on machines," rendering legacy counterterrorism and Cold War operations obsolete. He warns that adversarial surveillance strategy now directly targets the digital lives of everyday Americans, demanding an urgent re-assessment of how Washington approaches economic espionage to protect national sovereignty.

In this episode of The Product Podcast by Product School, Carlos González de Villaumbrosia sits down with Jeff Kunins, Chief Product Officer and Chief Technology Officer at Axon, the company that created the Taser and the body cameras federal agencies wear. Axon ingests more video per year than YouTube, and with a market cap of approximately $32.9 billion and $2.78 billion in revenue, growing 33% year over year, it is one of the highest-growth companies in the S&P 500. What you'll learn:How law enforcement agencies are using AI inside body cameras and Tasers to save lives, not just hit metrics.Why Axon declared a public moratorium on facial recognition AI for six years and what finally changed.How Axon embeds external activists and researchers directly into product manager squads as a design input, not a compliance process.Building first-party AI models for real-time license plate detection while using foundation LLMs for everything else.Key takeaways:Axon created the Taser and the body cam, and now ingests more video per year than YouTube. Most people have never heard of them.Build only what you must to be differentiated. Everything else, license from the best available source.Ethics review is not a compliance burden. When embedded in the product lifecycle, external critics help you see around corners and design better products.Credits:Host: Carlos Gonzalez de VillaumbrosiaGuest: Jeff KuninsSocial Links:Find out more about Product School hereFollow our Podcast on TikTok hereFollow Product School on LinkedIn here

Ryan Bishara and Christian Lau team up on an AI and data playbook that delivers an engaging, penalty free experience for LAFC employees and fans on and off the pitch.   Ryan, Christian and Kimberly discuss LAFC's innovative ethos; building an analytics and data program from the pitch up; LAFC's AI plays; making mistakes and continuous learning; keeping AI onside with responsive governance; prioritizing joy and the human experience; if convenience and privacy can co-exist; staying accessible and engaging fans; and how analytics/AI continue to play out in a rapidly evolving ecosystem.  Ryan Bishara and Christian Lau serve as the EVP of Revenue & Strategy and Chief Technology Officer, respectively, at the LA Football Club (LAFC).  A transcript of this episode is here.

Continuing to expand our technology for the betterment of farming is the driving force at Redox. It is passionate quest of our research team, headed by Dr. Gifford Gillette.“It's an incredibly challenging time in agriculture right now,” Gillette said. “We are doing our absolute best to provide answers and solutions for the challenges that growers face.”Each summer, a group of talented interns helps this effort, and this year's additions of  Sheldyn Rogers, Dallas Cummins, Shianne Bair and Cyrus Taylor have made an immediate, positive impact with their work ethic and quick acclimation. The company's firm commitment to research is evidenced by a new state of the art laboratory, three PhD's on staff and the recent addition of Jackeline Garza as Chief Technology Officer. 

Have you ever wondered whether the biggest competitive advantage in wealth management is no longer investment performance alone, but the ability to turn information into action faster than everyone else? In this episode of Tech Talks Daily, I welcome Bob Pisani, Chief Technology Officer at Addepar, a platform that helps investment professionals manage and analyze more than $9 trillion in assets globally. Our conversation explores why modern wealth management has become a technology challenge just as much as a financial one, and why firms that continue relying on fragmented legacy systems risk falling behind in an industry where speed, data quality, and client expectations are changing faster than ever. Bob explains how wealth advisors have historically spent far too much of their day moving between disconnected systems, stitching together spreadsheets, and trying to answer client questions using incomplete information. While that may once have been acceptable, today's investors expect near real-time visibility into their portfolios, along with personalized guidance that reflects rapidly changing market conditions. That changing expectation places an enormous premium on time, making technology one of an advisor's most valuable assets. Our discussion explores why successful AI initiatives begin long before deploying a model. Data quality, governance, and creating a trusted source of truth remain the foundations that determine whether AI produces reliable insights or simply accelerates poor decisions. Bob shares how Addepar approaches this challenge by bringing together fragmented financial data, standardizing it across hundreds of custodians, and creating the conditions where AI can produce meaningful, actionable intelligence rather than more noise. We also look at practical examples of AI already improving advisor productivity today. From summarizing portfolio performance and analyzing complex alternative investment documents to introducing intelligent agents that reduce operational workload, Bob explains how AI is freeing experienced professionals to spend less time gathering information and more time building trusted client relationships. One of my favorite moments in our conversation comes when we discuss predictive intelligence. Instead of waiting for advisors to search for answers, AI is beginning to surface opportunities, risks, and client conversations before anyone even knows which questions to ask. That represents a fundamental change in how financial advice can be delivered, moving from reactive reporting toward proactive guidance that is grounded in trusted data. We also address one of the biggest questions surrounding AI in financial services. Will technology replace human advisors? Bob offers a thoughtful perspective, arguing that while AI can automate repetitive work and accelerate decision-making, qualities such as judgment, precision, trust, and human relationships remain impossible to automate. Those are the characteristics clients ultimately value most when making important financial decisions. As our conversation draws to a close, Bob shares why he believes the gap between firms embracing AI and those delaying modernization will widen rapidly. The organizations investing today in clean data, modern platforms, and AI-ready operations will be better positioned to serve clients, attract talent, and compete in an increasingly fast-moving market. Can wealth management continue to rely on yesterday's technology in an AI-driven world? And if time has become the industry's most valuable asset, how is your business making the most of it? I'd love to hear your thoughts after listening.

Thanks to our Partners, NAPA TRACS, Today's Class, KUKUI, and Pit Crew Loyalty Watch Full Video Episode Artificial intelligence is rapidly changing how consumers search for auto repair services, and shop owners who don't adapt risk becoming invisible online. Carm Capriotto welcomes Heather Myers, Chief Technology Officer at KUKUI, and Connor Tracy, Director of Partner Development at KUKUI, to explain how AI-powered search is transforming local marketing. They separate fact from fiction, share practical strategies for improving AI visibility, and explain why strong marketing fundamentals remain the key to long-term success. What You'll Learn Why optimizing your Google Business Profile remains the most important step for local AI search visibility.How AI platforms like ChatGPT and Google's Gemini use consistent business listings to recommend local repair shops.Why maintaining accurate Name, Address, and Phone (NAP) information across online directories is more critical than ever.How AI now crawls social media platforms for business information and why authentic, human-created content improves discoverability.What "Google jail" is, how AI is filtering reviews, and why violating Google's review policies can seriously damage your online presence.Why review gating and incentivized reviews can put your business at risk.How to use AI effectively by following the principle of "trust but verify."Why better prompting leads to better AI-generated results and how to avoid incomplete or misleading responses. AI is changing the way customers find and evaluate repair shops, but success still depends on the fundamentals. Accurate business listings, a well-maintained Google Business Profile, authentic content, ethical review practices, and thoughtful use of AI tools will position your shop to earn trust, improve visibility, and convert online searches into paying customers. Heather Myers, Chief Technology Officer at KUKUI Connor Tracy, Director of Partner Development at KUKUI, Listen to Connor's other episodes HERE Thanks to our Partner, NAPA TRACS NAPA TRACS will move your shop into the SMS fast lane with onsite training and six days a week of support and local representation. Find NAPA TRACS on the Web at http://napatracs.com/ Thanks to our Partner, Today's Class Optimize training with Today's Class: In just 5 minutes daily, boost knowledge retention and improve team performance. Find Today's Class on the web at https://www.todaysclass.com/ Thanks to our Partner, KUKUI Stop juggling multiple marketing tools. KUKUI's integrated platform delivers 4x better website conversions, automated follow-up, and real-time ROI tracking. Get industry-leading customer support with KUKUI at https://www.kukui.com/ Thanks to our Partner, Pit Crew Loyalty You're probably tired of chasing new customers who never return. We understand. Pit Crew Loyalty ends the one-and-done cycle, turning first visits into lasting, reliable revenue at https://www.pitcrewloyalty.com/ Connect with the Podcast: Visit the Website:https://remarkableresults.biz/Subscribe on YouTube:https://www.youtube.com/carmcapriottoFollow on Facebook:https://www.facebook.com/RemarkableResultsRadioPodcast/Follow on LinkedIn:https://www.linkedin.com/in/carmcapriotto/Follow on Instagram:https://www.instagram.com/remarkableresultsradiopodcast/Join Our Virtual Toastmasters Club:https://remarkableresults.biz/toastmastersJoin Our Private Facebook Community:https://www.facebook.com/groups/1734687266778976Join our Insider List:https://remarkableresults.biz/insiderAll books mentioned on our podcasts:https://remarkableresults.biz/booksOur Classroom page for personal or team learning:https://remarkableresults.biz/classroomBuy Me a Coffee:https://www.buymeacoffee.com/carmSpecial episode collections:https://remarkableresults.biz/collections The Automotive Repair Podcast Network: https://automotiverepairpodcastnetwork.com/ Remarkable Results Radio Podcast with Carm Capriotto: Facilitating Wisdom Through Story Telling and Open Discussion. https://remarkableresults.biz/Diagnosing the Aftermarket A to

È finita l’era dell’elettronica di consumo con prezzi in discesa e migliori prestazioni? La scelta di Apple di aumentare fino al 25% i prezzi dei suoi laptop potrebbe essere l’inizio di un trend generalizzato e diffuso, che potrebbe condizionare le prestazioni dei prodotti e interessare tutto il settore per almeno uno o due anni, spiega Gianfranco Giardina, direttore del magazine digitale Dday,it.I sistemi di AI come i chatbot hanno bisogno delle informazioni presenti sul web per rispondere agli utenti ed è quindi necessario creare motori di ricerca progettati per i modelli linguistici di grandi dimensioni (LLM) e gli agenti autonomi di intelligenza artificiale. Gli strumenti creati per gli esseri umani sono infatti lenti e poco efficienti spiega Antonio Mallia, Ceo di Seltz, startup che ha recentemente raccolto finanziamenti per un valore di 12,5 milioni di dollari.La Commissione Europea ha assegnato ad un consorzio guidato da Domyn una gara per la costruzione di un modello di intelligenza artificiale di frontiera “aperto” basato su oltre 400 miliardi di parametri. Ne parliamo con Luca Antiga, Chief Technology Officer di Domyn, azienda italiana specializzata in intelligenza artificiale.E come sempre in Digital News le notizie di innovazione e tecnologia più importanti della settimana.

Artificial intelligence has made translation faster and more accessible than ever, but it isn't the right solution for every learning project. Interpro Translation Solutions' Nicholas Strozza, CEO, and Beshar Bahjat, Chief Technology Officer discuss how AI is changing translation, where human expertise remains essential, and what L&D leaders should consider when creating equitable learning experiences for multilingual audiences.Show Notes:Nicholas Strozza and Beshar Bahjat of Interpro Translation Solutions discuss the evolving role of AI in translation, the difference between translation and localization, and how organizations can balance speed, cost, quality, and learner experience when delivering training across languages. Key points include:Translation and localization are not the same thing. Translation converts content from one language to another, while localization adapts the entire learner experience—including language variations, imagery, audio, cultural references, and regional preferences.AI is a powerful starting point, not always a finished product. For many projects, AI can accelerate translation, but human review remains critical when accuracy, brand reputation, compliance, or learner safety are at stake.The right approach depends on your goals. Organizations should evaluate audience, content type, language, risk level, and long-term translation needs before deciding how much AI or human involvement is appropriate.Learning equity matters. Learners who speak another language deserve the same high-quality experience as English-speaking learners. Poor translations can negatively impact comprehension, engagement, accessibility, and training outcomes.Human expertise remains essential in the age of AI. Professional linguists increasingly serve as reviewers, editors, and quality experts who ensure translated content reflects local language, culture, terminology, and organizational standards.Learn more about Interpro Translation SolutionsPowered by Learning earned Awards of Distinction in the Podcast/Audio and Business Podcast categories from The Communicator Awards and a Gold and Silver Davey Award. The podcast is also named to Feedspot's Top 40 L&D podcasts and Training Industry's Ultimate L&D Podcast Guide. Learn more about d'Vinci at www.dvinci.com. Follow us on LinkedInLike us on Facebook

Predicting the Future: AI, Geopolitics & Better Decision Making w/ Anthony Vinci of VICO - AZ TRT S07 EP10 (292) 6-28-2026       What We Learned This Week Think in Probabilities Great decision-makers don't predict one future. They prepare for multiple possible futures. Look for Leading Indicators Government budgets, regulations, elections, trade policy, and geopolitical developments often signal future trends before markets fully respond. AI Is Becoming a Strategic Advisor AI is increasingly functioning as a research assistant, intelligence analyst, and scenario-planning tool—not just a content generator. Everything Is Connected Politics, economics, technology, energy, and national security influence one another more than ever before. Understanding those relationships creates a competitive advantage. Focus on Second-Order Effects Many investors react to headlines. The bigger opportunities often lie in anticipating the ripple effects that follow.     AZ TRT Podcast Predictive Forecasting: AI, Geopolitics & Better Decision Making Guest: Anthony Vinci Links: https://www.linkedin.com/in/anthony-vinci/ https://www.anthonyvinci.com/ https://www.vico.io/ Anthony Vinci is the Founder and CEO of VICO, an AI-powered forecasting company that helps governments, financial institutions, and corporations assess political, geopolitical, and economic event risk. Rather than predicting a single outcome, VICO converts news, expert analysis, and real-world signals into probability-based forecasts to improve decision-making. Before founding VICO, Anthony served as the first Chief Technology Officer of the National Geospatial-Intelligence Agency (NGA), where he led the integration of artificial intelligence into U.S. intelligence operations. He also held senior leadership roles at Bridgewater Associates and Cerberus Capital Management, focusing on technology, national security, aerospace, and strategic investments. Anthony is the author of The Fourth Intelligence Revolution, recognized by the Financial Times as one of the Best Books of 2025. His work focuses on the intersection of AI, intelligence, geopolitics, and global finance. Theme Today's world moves faster than ever. Political events, wars, technological breakthroughs, trade policy, and artificial intelligence all create ripple effects throughout the economy and financial markets. The question isn't simply: "What will happen?" Instead, it's: "What are the most likely outcomes, and how should we prepare for them?" That is the foundation of predictive forecasting. Segment 1 The World Has Become an Event-Driven Economy One of the biggest themes discussed was how major events rarely stay isolated. Instead, they create ripple effects throughout politics, economics, and financial markets. Examples from 2026 include: The conflict involving Iran Concerns over the Strait of Hormuz disrupting global shipping Oil price volatility Inflation concerns AI adoption across industries Global trade tensions For example, if shipping through the Strait of Hormuz were disrupted, the effects could extend far beyond oil: higher energy prices increased transportation costs higher inflation pressure on consumer spending lower corporate profits political consequences during the 2026 midterm elections One geopolitical event can trigger dozens of second- and third-order consequences. Narrative Economics Markets increasingly react to information almost instantly. News travels within seconds through: X (Twitter) social media financial news AI-generated analysis Sometimes markets move more from the narrative than from the underlying facts. The speed of information has increased volatility. AI as an Intelligence Analyst AI is evolving beyond a simple chatbot. Examples discussed: Claude drafting emails in seconds ChatGPT analyzing massive amounts of information AI summarizing research AI identifying patterns humans might overlook Rather than replacing executives, AI increasingly acts like an executive assistant or intelligence analyst that can evaluate possible outcomes and estimate probabilities. Segment 2 Forecasting Through Leading Indicators One of Anthony's core ideas is that forecasting begins with identifying early signals rather than reacting after events occur. Examples include: Government Spending Watching federal budgets provides clues about future economic priorities. For example: A proposal to increase defense spending from roughly $1 trillion toward $1.5 trillion could benefit industries such as: aerospace defense contractors cybersecurity satellite technology Markets often recognize these trends before the spending actually occurs. Elections Forecasting elections isn't just about polling. Leading indicators include: redistricting economic conditions inflation employment approval ratings legislative trends These become measurable inputs rather than opinions. Tariffs and Trade Tariffs and sanctions affect: supply chains inflation manufacturing exports corporate earnings Rather than relying solely on headlines, investors can monitor government announcements and policy developments as early indicators. VICO Anthony explained that VICO was created to help organizations answer questions like: "What happens if tariffs increase?" "What happens if a regional conflict expands?" "What happens if inflation persists?" Instead of producing opinions, the platform attempts to quantify probabilities so businesses can make better strategic decisions. Current users include: investment firms hedge funds insurance companies corporations government agencies The platform is also available through Bloomberg Terminal. Segment 3 Thinking Like an Intelligence Officer Anthony explained that investing and intelligence analysis are surprisingly similar. Neither profession knows the future with certainty. Instead, both attempt to improve decision-making through probabilities. Questions include: What's the upside? What's the downside? What scenarios exist? What is the probability of each? Instead of asking for certainty, professionals ask for better odds. AI as a Thought Partner Rather than replacing human judgment, AI becomes another analyst at the table. It helps: challenge assumptions compare scenarios estimate probabilities reduce emotional decision-making The objective isn't perfect predictions. It's consistently making better-informed decisions. Indicators and Warnings (I&W) Government intelligence agencies constantly monitor "Indicators and Warnings." Examples include: military activity cyber threats terrorism supply chain disruptions political instability The same thinking can apply to investors and business owners by identifying leading indicators before markets fully react. Rare Earth Minerals A fascinating discussion centered on rare earth materials. These minerals are essential for: semiconductors missiles satellites electric vehicles MRI and CT scanners advanced electronics Although called "rare," many are relatively abundant. The challenge is that mining and processing are concentrated in a handful of countries, particularly China. This explains why governments increasingly view domestic production as a national security issue. Segment 4 Second- and Third-Order Effects One of the strongest concepts discussed was cascading consequences. Instead of focusing only on one event, ask: "What happens next?" Example: Conflict with Iran↓ Shipping disruptions↓ Higher oil prices↓ Higher transportation costs↓ Inflation↓ Reduced consumer spending↓ Lower corporate earnings↓ Market volatility↓ Political consequences↓ Policy changes Understanding these chains of events helps improve forecasting. AI Regulation AI is both part of the opportunity and part of the risk. Potential future regulations may focus on: cybersecurity national security privacy export controls access to advanced AI models computing infrastructure One challenge will be balancing innovation with security while remaining globally competitive. Anthony noted that governments may have access to AI capabilities that are not immediately available to the private sector, highlighting the strategic importance of advanced AI systems.   Closing Thought One of the biggest lessons from this conversation is that forecasting isn't about predicting the future with certainty—it's about improving the quality of your decisions. The best investors, business leaders, and intelligence professionals don't rely on opinions alone. They gather data, monitor leading indicators, evaluate multiple scenarios, and assign probabilities to each possible outcome. In an increasingly interconnected world, those who think like forecasters rather than reactors will be better positioned to navigate uncertainty and identify opportunities before the crowd.         Tech Topic: https://brt-show.libsyn.com/category/Tech-Startup-VC-Cybersecurity-Energy-Science  Best of Tech: https://brt-show.libsyn.com/size/5/?search=best+of+tech   'Best Of' Topic: https://brt-show.libsyn.com/category/Best+of+BRT      Thanks for Listening. Please Subscribe to the AZ TRT Podcast.     AZ Tech Roundtable 2.0 with Matt Battaglia The show where Entrepreneurs, Top Executives, Founders, and Investors come to share insights about the future of business.  AZ TRT 2.0 looks at the new trends in business, & how classic industries are evolving.  Common Topics Discussed: Startups, Founders, Funds & Venture Capital, Business, Entrepreneurship, Biotech, Blockchain / Crypto, Executive Comp, Investing, Stocks, Real Estate + Alternative Investments, and more…    AZ TRT Podcast Home Page: http://aztrtshow.com/ 'Best Of' AZ TRT Podcast: Click Here Podcast on Google: Click Here Podcast on Spotify: Click Here                    More Info: https://www.economicknight.com/azpodcast/ KFNX Info: https://1100kfnx.com/weekend-featured-shows/

On this episode of Coaching Call, Sifu Rafael welcomes Yosi Kossowsky, MCEC, PCC, for a thought provoking conversation on leadership, communication, team performance, and creating lasting impact.With more than 30 years of multinational corporate experience and 17 years as a professional coach, Yosi has helped leaders and organizations transform the way they think, communicate, and lead. His unique journey from Chief Technology Officer and Senior Director of Talent Management to executive coach gives him a rare ability to combine analytical thinking with a deep understanding of people.Yosi specializes in helping leaders gain strategic clarity, improve communication, strengthen team dynamics, and build cultures where people and performance thrive together. His practical coaching approach empowers individuals to navigate change, prevent burnout, lead through uncertainty, and align professional success with personal fulfillment.Whether you're leading a business, managing a growing team, or striving to become a more intentional leader, this conversation will provide valuable insights you can apply immediately.Join us as we explore what it really takes to lead with purpose, communicate with confidence, and inspire others to perform at their highest level.Watch on YouTube and subscribe:https://www.youtube.com/@sifurafaeltv?sub_confirmation=1Sifu Rafael is a master instructor and the founder of Speaking Prowess, where he combines expertise in communication and leadership to help individuals unlock their full potential. As a professional speaker, solutions expert, and executive coach, Sifu Rafael leverages years of experience to guide clients toward their goals with clarity, purpose, and strategic insight. His mission is to make the art of effective communication accessible to all, empowering personal and professional growth. Sifu Rafael's unwavering dedication to improving communication skills has earned him a reputation as a trusted mentor and coach. His vision is clear: to enhance communication worldwide, one individual at a time.This episode is brought to you by Sifu's Mind Body Method, a lifestyle transformation that blends movement, mindset, nutrition, hydration, fasting, journaling, and faith. Learn more at sifumethod.comThat's where connecting with Sifu Rafael matters.Through Speaking Prowess and Sifu's Mind Body Method, Sifu Rafael helps leaders, entrepreneurs, and experts refine their message, command a room, and step onto more stages with clarity and confidence. From podcasts and live shows to keynote stages and curated experiences, Sifu Rafael helps people get seen, heard, and positioned as trusted voices in their industry while sharpening their speaking skills along the way.If you know you're meant to speak, lead, and impact at a higher level, this conversation is your invitation.Visit sifurafael.com to connect, explore speaking opportunities, and start positioning yourself for more stages, stronger presence, and real influence.#coachingcall #sifurafael #leadership #executivecoaching #teamperformance #communication #leadershipdevelopment #personalgrowth #speakingprowess #coaching

What happens when a software company building AI tools for HR teams uses those same tools to transform itself? Josh McKenzie, Chief Technology Officer at ELMO Software Group, shares how his team rebuilt their entire software development lifecycle around AI agents and redrew the boundaries of every engineering role. He breaks down how to lead that shift without losing people's trust, why domain expertise is the real SaaS moat, and how the right analytics partner unlocks decisions HR teams have never been able to make before. Key Moments: The SaaS Moat: What AI Can't Erode (06:37): Josh argues SaaS value runs deeper than software. Accountability, compliance, and domain expertise keep purpose-built platforms irreplaceable. How ELMO's AI Journey Started (10:23): ELMO started by mapping every role against AI impact. Turning that lens on their own engineering team set the full transformation in motion. Why ELMO Chose ThoughtSpot Over Building Its Own Analytics (18:42): A homegrown tool requiring too much user expertise led ELMO to look elsewhere. ThoughtSpot Spotter and natural language capabilities closed the gap. Why HR Teams Are the Most Underserved (20:21): Payroll here, benchmarking data there, performance data somewhere else. HR teams have been drowning in spreadsheet hell for years. Josh explains how AI finally closes that gap. From Engineer to CTO: Build a Team of Complements (24:17): Josh reflects on the mindset shift that defined his path to the C-suite. Great leadership means building a team whose strengths cover your blind spots. Key Quotes: “ ThoughtSpot was particularly interesting for us… The big thing for us was the Spotter product. Allowing users to bridge that data analyst gap was really important. So, that product has yielded really, really great results for us.” - Josh McKenzie “I think it's really important that we instill a culture where it's okay to fail, and it's okay to make a mistake. You want to be vocal about your mistakes so others don't repeat the same mistake.” - Josh McKenzie “My belief is you want to focus on your secret sauce. So, what is the thing that makes your business super successful? And for us, that's where we came to look at ThoughtSpot. It has a really nice visual user interface and allows you to create some great dashboards.” - Josh McKenzie Mentions Hiring and Onboarding Taking Longer Despite Widespread AI Adoption, New Australian Research Finds The 5 Levels of AI Coding (Why Most of You Won't Make It Past Level 2) WireGuard: Next Generation Kernel Network Tunnel | Jason A. Donenfeld Guest Bio As the Chief Technology Officer, Josh McKenzie is responsible for both technical strategy and delivery (build, release and operation) of the ELMO product suite. Josh has a proven track record of successfully leading technology teams and implementing transformative strategies that enhance efficiency, drive growth, and elevate overall technological capabilities. Josh has 20 years of experience in technology, primarily in FinTech. Before joining ELMO in 2024, Josh held executive and senior positions at Lendi Group, OFX, ASX and Westpac. Josh holds a Bachelor of Computer Science from the University of Newcastle and an MBA from the University of Sydney. Hear more from Cindi Howson here. Sponsored by ThoughtSpot.

Send us Fan MailIn this episode of the WTR Small Cap Spotlight podcast, Eric Robinson, Senior Vice President of Operations, and Joe Wong, Chief Technology Officer of Arq, Inc. (Nasdaq: ARQ), join Tim Gerdeman (Vice Chair, Co-Founder & CMO, Water Tower Research) and Peter Gastreich (Managing Director, Water Tower Research).In a technical deep-dive into operations, Eric and Joe shared views on the science and commercial applications of activated carbon, the engineering challenges Arq encountered in scaling granular activated carbon (GAC) production at its Red River facility, the surging demand for GAC in PFAS drinking water treatment, the competitive dynamics and supply-side barriers in the activated carbon market, Arq's path forward on GAC capacity decisions, and the strategic optionality remaining at the idled Corbin facility.Subscribe and visit watertowerresearch.com for open-access small cap research, podcasts, and conference schedules.

Today on Leader Generation, Tessa Burg welcomes back Linda Owens, Global Vice President of Digital Customer Experience at Sherwin-Williams. Six years after becoming the podcast's very first guest, Linda returns to discuss how B2B leaders can navigate rapid changes in technology, AI and buyer behavior while staying focused on what matters most: the customer. Linda shares practical advice for separating meaningful trends from hype, creating trust earlier in the buying journey and designing customer experiences that reduce friction across every touchpoint. She also explains why customer obsession should drive every decision, how to use experimentation without losing sight of scale and what leaders need to do to successfully manage change across their organizations. Whether you're leading digital transformation, evaluating AI initiatives or looking for ways to create more value for customers, this conversation offers actionable insights you can apply immediately. Tune in to learn how today's most effective B2B leaders are building customer experiences that drive both business growth and long-term loyalty. Leader Generation is hosted by Tessa Burg and brought to you by Mod Op. About Linda Owens: Linda Owens is the Global Vice President of Digital Customer Experience at Sherwin-Williams, where she leads initiatives that advance digital customer experiences, scale eBusiness capabilities and drive enterprise transformation. With more than 20 years of experience spanning marketing, sales, ecommerce and digital customer experience, she has helped organizations modernize customer engagement and accelerate growth across B2B and B2C markets. Throughout her career, Linda has led cross-functional teams and developed digital strategies that improve customer experiences across channels and global regions. Her expertise includes ecommerce strategy, digital marketing, customer journey optimization, CRM lifecycle programs, Martech and digital innovation. She is passionate about simplifying complexity, empowering high-performing teams and creating customer-centric solutions that deliver measurable business impact. Linda can be reached on LinkedIn. About Tessa Burg: Tessa is the Chief Technology Officer at Mod Op and Host of the Leader Generation podcast. She has led both technology and marketing teams for 15+ years. Tessa initiated and now leads Mod Op's AI/ML Pilot Team, AI Council and Innovation Pipeline. She started her career in IT and development before following her love for data and strategy into digital marketing. Tessa has held roles on both the consulting and client sides of the business for domestic and international brands, including American Greetings, Amazon, Nestlé, Anlene, Moen and many more. Tessa can be reached on LinkedIn or at Tessa.Burg@ModOp.com.

The Big Unlock · Marshall Glanzer, Chief Technology Officer, Town Square Health In this episode, Marshall Glanzer, Chief Technology Officer of Town Square Health, outlines a bold model for scaling fully capitated risk programs for Medicare recipients. Transitioning from food-delivery logistics at GrubHub, Marshall brings critical structural insights for digital health innovators seeking to scale clinical models without eroding patient trust. The core theme of the discussion centers on a counter-intuitive tech strategy: utilizing advanced digital infrastructure to intentionally deepen human relationships rather than automate them away. Town Square orchestrates unified “coordinated care visits,” bringing the patient, primary clinician, and a remote specialist into a single conversation to act as a multi-disciplinary “healthcare oracle” at the point of care. For technology vendors, Marshall defines a safe clinical AI deployment roadmap using an “augmented clinician” framework. Advanced workflows, like chat-first patient portals managed by an automated “AI judge,” rely on the licensed physician as the ultimate orchestrator. This approach elegantly bypasses commercial barriers like malpractice liability, credentialing, and fractured billing, leveraging the financial alignment of value-based care to fully absorb modern R&D costs. Take a listen.

Most of us think about water in terms of filtration, purity, and quantity. But what about movement? What if water was never meant to be still?  Zeev Zohar, co-founder and Chief Technology Officer of Mayu Water joins us this week on the podcast. Zeev is a multidisciplinary entrepreneur, inventor, award-winning industrial designer, and advanced physics thinker who is helping people look at water in a completely new way.  Through Mayu, Zeev has helped create the Mayu Swirl, a glass water system inspired by the natural movement of spring water. By using vortex motion, Mayu encourages water to move the way it does in nature, supporting aeration, taste, and a more intentional relationship with the water we drink every day. In this conversation, Autumn and Zeev explore: • What structured water actually means • Why movement matters in nature • The difference between tap water and spring water • How vortex motion may change the way water behaves • Why oxygenation and aeration can impact taste • The role minerals may play in hydration • Why water interacts with everything it touches • How intention, gratitude, and ritual can change the way we relate to water • Why hydration is about more than simply drinking more This conversation will make you rethink something you use every single day. Water is not just a background part of health. It may be one of the most foundational. ✴️ Find Mayu Water on Facebook, Instagram, YouTube, or X

Send us Fan MailIn this special compilation episode of AI and the Future of Work, we are bringing you four conversations recorded live on the show floor at HumanX 2026. This is the second and final compilation of our three-part HumanX Live series.Our first compilation explored how AI amplifies the human potential it can never replace. This one turns to the technical side, and to a question that gets harder the more these systems touch our lives: how do you build AI you can actually trust not to fail when it matters most? As technology reaches further into the moments that count (the systems that monitor our health, drive our cars, and work alongside us on the job), these four builders share how they design for accountability, safety, and harmony between people and machines.What You'll LearnWhy reading code is no longer enough, and how observing real outcomes (not system metrics alone) is the only way to know whether AI is actually serving the people who depend on itWhat "AI values" are, and why companies will soon need shared norms for how people disclose, review, and engage with work produced by agentic systemsHow robots earn trust on a job site by measuring their own uncertainty, asking questions, and communicating their intentions before they actWhy the most valuable place for automation is the dirty, dull, and dangerous work humans were never meant to do, and what that means for keeping people safeWhy physical AI should be built first as a reasoning and communication model that can explain its thinking to people, rather than one that jumps straight to actionHow "harness engineering" moves teams beyond prompt and context engineering, and why orchestrating several frontier models together can outperform any single oneFeatured GuestsChristine Yen, CEO and Co-Founder of Honeycomb. Listen to the full conversation here: https://www.buzzsprout.com/520474/episodes/19362645 Dr. Ali Agha, CEO and Co-Founder of FieldAI. Listen to the full conversation here: https://www.buzzsprout.com/520474/episodes/19362711 Dr. Jaime Lien, Co-Founder & Chief Scientist of Archetype AI. Listen to the full conversation here: https://www.buzzsprout.com/520474/episodes/19363341 XD Huang, Chief Technology Officer of Zoom. Listen to the full conversation here: https://www.buzzsprout.com/520474/episodes/19363454 Inspired by something you heard in this episode? Share your favorite insight about the future of work and tag us on social:LinkedIn: https://www.linkedin.com/showcase/ai-and-the-future-of-work Instagram: https://www.instagram.com/aifutureofwork/ And don't forget to subscribe to AI and the Future of Work for more conversations with the leaders shaping what comes next.Explore the Full HumanX 2026 SeriesThis episode is part of a special three-part series recorded live at HumanX 2026:Episode 1: Special conversation with Stefan Weitz, CEO of HumanX: https://www.buzzsprout.com/520474/episodes/19210355Episode 2: Compilation featuring the CEOs of Scribe, Operative Games, and Dataiku, and the Chief Business Officer of Zensai: https://www.buzzsprout.com/520474/episodes/19257142LIVE EVENT: See how leading enterprises are using agentic AI to give employees back 4–6 productive hours every week. Join PeopleReign CEO Dan Turchin for a live demo on June 25, 2026.Register here: https://go.peoplereign.io/live-demo-how-agentic-ai-is-being-used-by-global-enterprises

Send us Fan MailHow do you scale a Home Services Business past the $10M mark without losing your Company Culture or selling out to Private Equity? In this episode of Let's Vent, we sit down with the Owners of Go Green Plumbing, Heating & Air, Alicia Green and Pete Green to break down the exact operational tips, strategies and ideas they implemented to build an independent trade powerhouse. Connect with out Guests: Go Green Plumbing: https://gogreenplumb.com/Alicia Green: https://www.linkedin.com/in/alicia-green-14bb3495/Pete Green: https://www.linkedin.com/in/pete-green-25496072/ Connect with our sponsor: https://freeagency.aiTime Stamps: 01:10 - Introducing Pete & Alicia Green from Go Green Plumbing02:18 - Pete Green's Transition from Programming to "Chief Technology Officer"03:45 - The Truth About Company Culture: There are Always Ups & Downs05:15 - What Happens When People Don't Fit the Mold?06:13 - Shifting from Professional to Lightheartedness in Tough Times07:45 - The Go Green Hiring Process: Do You Let Your Team Make the Decisions?09:20 - The "Princess Castle" Lego Challenge & Out Of Comfort Zone Testing13:16 - Quick to Hire, Slow to Fire: Should Be The Opposite Way Around? 14:15 - The ROI of Training16:55 - Joining Nextstar Network & Implementing Soft Skills Training17:58 - The Academy Structure: Weekly Breakdown of Trades & Certifications22:38 - 60% of Our Business Wouldn't Exist Without the Training Academy23:45 - The Myth of the Unicorn Employee25:03 - Balancing IQ and EQ: Why Technical Skills and Soft Skills Are 50/5027:50 - The Chaos of Early Training Programs vs. Today's Managed Structure29:15 - Building a Clear Pay Plan and Incentivized Levels32:14 - Advanced Lab Training: Partnering with Ultimate Tech Academy in Arkansas33:20 - The Tax Perspective: Are you Paying More? 34:00 - Facing Private Equity (PE) in the Trades38:12 - The Positive Side of PE: Injecting Business Logic and Real Value into the Trades42:50 - Growing Big with Zero Outside Capital45:15 - Why Cheap Prices Come at the Expense of Employees?47:50 - Built on Community assistance: The Go Green Community Promise Program49:35 - "Owned by Google": Venting About the Real Monopolies Dictated by the Industry53:48 - Where Does the Cash Flow? Canadian Agencies vs. Local Greensboro Wages57:25 - Understanding KPI Pressures and Employee Mass Exits58:35 - Why Technicians Stay for Culture and Run from Structure Changes01:01:40 - The Flaw in Flipping: Why Passing Hands Leads to Volume Loss01:05:43 - Processing the Reality of Multi-Billion Dollar Acquisitions in the Trades01:07:55 - The Challenge to Maintain Massive Service Value Over Time01:10:17 - Will AI Supplement or Completely Replace Modern Jobs?01:12:00 - How To Choose a Software That Actually Helps Reduce Workload?01:12:42 - Why the CTO's Workload Increases When Implementing AI?01:13:55 - The Sandbox Mindset: Starting From a Place of Natural Curiosity01:18:15 - Managing Scope Creep When Coding with Accelerated AI Speed01:21:38 - How Non-Technical Leaders Can Leverage Claude?01:23:59 - The "Twice a Day" Automation Rule: Building Your Operational Task List01:28:46 - The Importance of Context and Direct Communication to Create a Prompt correctly01:31:12 - Ostrich Mentality: Why Ignoring the Automation Wave Will Cost People Their Careers01:31:47 - Focus on Eliminating Time Rather Than Solving the World's Problems01:34:00 - How To Hold People Accountable Without Destroying The Company Culture ?01:34:48 - Facts Over Feelings: Gathering Documentation and Data Before Tough Conversations01:38:25 - Final Thoughts on How to Build a Scalable Organization

Coming up with AI ideas isn't the struggle for most teams. The real challenge is to make those ideas stick. In this episode, Shashank Kadetotad, Global Senior Director of Enterprise Data Science and AI at Mars, breaks down what helps companies move from interesting pilots to real business impact. He explains why adoption matters just as much as the technology itself, how culture and leadership shape success and why the best AI solution is not always the most complex one.  You'll get practical advice on involving the right users early, setting clear success and failure criteria for pilots and deciding when to build versus buy. Shashank shares lessons from leading AI work inside major organizations and offers a grounded view of what it takes to scale responsibly. If your team is trying to get more value from AI, this conversation will give you a clearer and more useful way to think about the work.  Leader Generation is hosted by Tessa Burg and brought to you by Mod Op. About Shashank Kadetotad: Shashank Kadetotad is the Global Senior Director of Enterprise Data Science and AI at Mars, where he leads the deployment of AI and advanced analytics across global consumer goods operations. With a background that spans Amazon operations, retail and CPG forecasting, and AI leadership across multiple Fortune 500 companies, he has built and scaled enterprise AI platforms that power decisions in supply chain, marketing, and finance. Shashank is recognized for his work on generative AI and multi-agent architectures, with multiple provisional patents focused on applying AI to product innovation, analytics, and consumer engagement. A frequent industry speaker, he is known for making complex AI topics accessible to business leaders while keeping the focus on responsible, high-impact AI in retail and CPG. He can be reached on LinkedIn. About Tessa Burg: Tessa is the Chief Technology Officer at Mod Op and Host of the Leader Generation podcast. She has led both technology and marketing teams for 15+ years. Tessa initiated and now leads Mod Op's AI/ML Pilot Team, AI Council and Innovation Pipeline. She started her career in IT and development before following her love for data and strategy into digital marketing. Tessa has held roles on both the consulting and client sides of the business for domestic and international brands, including American Greetings, Amazon, Nestlé, Anlene, Moen and many more. Tessa can be reached on LinkedIn or at Tessa.Burg@ModOp.com.

In PR Masters Podcast Series Episode #106, Rich Jachetti and Joseph Franklyn McElroy interview Tejas Totade, Chief Technology Officer and Head of AI at Ruder Finn, about how artificial intelligence is transforming communications, marketing, and agency operations. Totade shares how Ruder Finn is integrating AI across workflows, content creation, analytics, governance, and client service while maintaining the human creativity and strategic thinking that drive successful communications. The conversation explores GEO, AI-powered workflows, leadership, data governance, and what communications professionals need to know to stay competitive in an AI-driven future.

In this episode of The Geek in Review, we welcome Greg Dickason, Chief Technology Officer at LexisNexis, for a wide-ranging conversation on agentic legal AI, Lexis+ AI Protégé, and the movement from AI chat toward AI work. Dickason frames the shift through a simple contrast: earlier legal AI answered questions, while agentic workflows take on multi-step assignments, conduct research, create drafts, verify citations, and move legal professionals closer to finished work product. For law firms and legal departments trying to understand where AI goes next, this episode places agentic AI squarely inside legal workflow, legal research, drafting, and risk management.A major theme of the conversation is trust. Dickason explains how Shepard's Verify extends the familiar Shepard's signal beyond traditional research screens and into uploaded work product. Rather than asking lawyers to rely on AI-generated text without a verification layer, LexisNexis is building citation checking into the workflow, giving lawyers a path to confirm whether cited authority exists, whether authority is still good law, and how later courts treated the cited case. For lawyers worried about hallucinated citations, AI-generated briefs, and unreliable authority, this verification layer becomes part of the product architecture, rather than an afterthought.The discussion also explores the relationship between LexisNexis and Anthropic, along with the rise of legal AI skills. Dickason describes a market where model choice, orchestration, and legal skills increasingly matter as separate layers. Anthropic, OpenAI, Google, and other model providers offer impressive foundations, yet legal work needs more than general-purpose intelligence. Large law workflows require legal content, expert reasoning, matter-specific playbooks, and firm-defined processes. Dickason notes the ability to upload firm playbooks as skills, giving firms a path to bring their own way of working into Protégé.Security receives equal billing with accuracy. As firms place client documents into AI vaults and connect work product to legal AI platforms, Dickason explains bring your own key, or BYOK, through a practical office-and-locked-cabinet analogy. The point is control: client content sits encrypted, access depends on the user's key, and access stops when the key is withdrawn. He also discusses legal chunking, indexing, vector stores, retrieval-augmented generation, and knowledge graphs as part of building AI systems suited for legal documents, rather than generic file handling.The episode closes with a broader view of legal AI's impact on junior associates, legal training, and access to law. Dickason does not predict the end of junior lawyers. Instead, he sees AI helping junior lawyers become senior faster through mock trials, mock depositions, and richer training environments. He also warns of risks from agent volume, security vulnerabilities, and legal systems struggling to keep pace with AI-enabled industries. The message is pragmatic and optimistic: agentic legal AI will change legal work, yet the winners will be those who combine trusted content, secure systems, verification, workflow design, and human judgment.Listen on mobile platforms:  ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Apple Podcasts⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ |  ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Spotify⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ | ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠YouTube⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ | ⁠Substack⁠[Special Thanks to ⁠⁠Legal Technology Hub⁠⁠ for their sponsoring this episode.]⁠⁠⁠⁠⁠Email: geekinreviewpodcast@gmail.comMusic: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Jerry David DeCicca⁠⁠⁠⁠⁠⁠⁠⁠⁠Transcript:

“AI is often framed as a software revolution. But the real constraint isn't software. It is whether we can power and cool it at scale".  In this episode of the AI at Scale Podcast, Chris Sharp, Chief Technology Officer at Digital Realty, and Steven Carlini, Thought Leadership Leader at Schneider Electric, explain a fascinating shift in the data center industry. AI is not only about AI models or chips. As data centers are becoming AI factories success depends on physical systems that must keep up. There is a clear message on planning: decision makers need to design for what is coming, not what exists today. Building only for current demand will not hold up.   For C-level executives, this is a practical view of where AI can slow down and what needs attention now.  In this episode, you will learn:  ✔ why power and cooling must be designed as one system to support AI innovation  ✔ how rising power density is changing data center design  ✔ what token economics means for cost, value, and ROI  ✔ why planning ahead is critical to avoid future limits  ✔ how infrastructure decisions affect AI performance and growth 

BONUS S6E8 A Zebra ZONE 2026 recap on pragmatic AI, on-device AI, super apps, and giving store associates their day backRicardo Belmar just got back from Zebra Technologies' ZONE 2026 conference in Nashville, where pragmatic AI was the main theme. In this special bonus episode of The Retail Razor Show, he and Casey Golden unpack what it all means for retail's frontline workers. This is a story about pragmatic AI, the kind that gives store associates and warehouse teams their day back instead of promising the moon.The headline from ZONE 2026? Zebra is no longer telling a devices story. It's telling a frontline platform story, anchored by on-device AI that runs with no cloud, no tokens, and no waiting. Ricardo brought back two exclusive interviews, with Zebra CTO Tom Bianculli and Mobile Computing chief James Poulton, plus a notebook full of stats, demos, and hallway conversations that deliver the full pragmatic AI story.We get into why frontline workers are drowning in 70 to 80 apps when they only use about a dozen, the super app built to fix it, real-time translation running live on a device, and why “tokenless” pragmatic AI became the word of the week. If you want to understand on-device AI and what it delivers for frontline workers, this episode is your shortcut.In This Episode, You'll Learn•     Zebra's three big software announcements: Nucleus, Workcloud IO, and Workcloud BI•     The 80-apps problem and the super app designed to collapse it down to one experience•     Why on-device AI, tokenless and at the edge, beats cloud round trips for frontline use cases•     Real-time translation in any language, live on the device•     Micro-learning, the “TikTok of learning,” and tackling 70 to 80% frontline turnover•     Picture proof of delivery: how a second and a half scales into tens of millions of dollars•     The octopus organization, and why intelligence belongs at the edge of the org•     James Poulton on why large language models are overhyped for the enterpriseWhy it mattersWe've spent years on this show arguing that your associate experience is your customer experience. ZONE 2026 felt like the technology industry finally catching up to that idea, treating frontline workers as the most under-invested asset in retail and giving them on-device AI that augments rather than replaces. Pragmatic AI wins on the accumulation of small moments, and that is the thread we pull all episode long.Subscribe & FollowIf you enjoyed this episode, please leave us a 5‑star rating and review on Apple Podcasts, Spotify, or Goodpods. Subscribe on YouTube so you never miss an episode and check out the other shows in the Retail Razor Podcast Network: Retail Transformers, Blade to Greatness, and Data Blades.Subscribe to the Retail Razor Podcast Network: https://retailrazor.com/Subscribe to our Newsletter: https://retailrazor.substack.comSubscribe to our YouTube channel: https://go.retailrazor.com/utubeFeatured guestsTom Bianculli, Chief Technology Officer, Zebra Technologieshttps://www.linkedin.com/in/tom-bianculli-9053892/James Poulton, SVP & GM, Mobile Computing, Zebra Technologieshttps://www.linkedin.com/in/jamespoulton/Chapters00:00 Teaser01:01 Show intro02:12 What Zebra announced at ZONE 202604:00 The 80-apps problem and the super app06:53 Real-time translation on the device08:55 Tokenless, on-device AI explained11:46 Best moment: the octopus organization15:43 Interview: Tom Bianculli, CTO Zebra Technologies35:50 Recap: pragmatic AI and returning time to workers40:27 Interview: James Poulton, SVP & GM Mobile Computing53:21 Big takeaways from ZONE 202659:32 Show CloseMeet your hostsHelping you cut through the clutter in retail & retail tech:Ricardo Belmar is an NRF Top Retail Voice for 2025 and a RETHINK Retail Top Retail Expert from 2021 – 2026. Thinkers 360 has named him a Top 10 Thought Leader in Retail, a Top 25 Thought Leader in AGI and Careers, a Top 50 Thought Leader in Agentic AIand Management, and a Top 100 Thought Leader in Digital Transformation and Transformation. Thinkers 360 also named him a Top Digital Voice for 2024 and 2025. He is an advisory council member at George Mason University's Center for Retail Transformationand the Retail Cloud Alliance. He was most recently the partner marketing leader for retail & consumer goods in the Americas at Microsoft.Casey Golden, is the North America Leader for Retail & Consumer Goods at CI&T, and CEO of Luxlock. She is a RETHINK Retail Top Retail Expert from 2023 - 2026, and Retail Cloud Alliance advisory council member. After a career on the fashion and supply chain technology side of the business, Casey is obsessed with the customer relationship between the brand and the consumer and is slaying franken-stacks and building retail tech! MusicIncludes music provided by imunobeats.com, featuring Overclocked, and E-Motive from the album Beat Hype, written by Heston Mimms, published by Imuno.

Fabrice Bernhard is the co‑founder and Chief Technology Officer of Theodo Group, a global technology consulting firm he co‑founded in Paris in 2009. Under his technical leadership, Theodo has grown rapidly by combining Lean principles with modern software engineering to help organizations build scalable, resilient digital capabilities. Fabrice is a recognized thought leader in Lean Tech, advocating for the application of Toyota Production System principles to software development and technology organizations. He is a frequent speaker and writer on continuous improvement, learning cultures, and human‑centered technology, and is a co‑author of The Lean Tech Manifesto. His work focuses on enabling teams to deliver value faster while empowering people through better systems and smarter use of technology.Link to claim CME credit: https://www.surveymonkey.com/r/3DXCFW3CME credit is available for up to 3 years after the stated release dateContact CEOD@bmhcc.org if you have any questions about claiming credit.

In Episode 106 of the Cybersecurity Readiness Podcast Series, Dr. Dave Chatterjee is joined by Holger Hügel, Chief Technology Officer of SecurityBridge and a global authority on SAP cybersecurity with over 26 years of experience — to address a governance blind spot that exists inside the security perimeters of even the most mature enterprise organizations: the SAP environment.Opening with the August 2024 ransomware attack on Stoli Group USA — where attackers went straight for the company's SAP enterprise resource planning (ERP) system, disrupting financial operations and contributing directly to a bankruptcy filing within three months — Dr. Chatterjee frames the episode's central challenge: organizations can have zero trust architecture, network segmentation, and identity governance fully deployed across their IT landscape, and still be critically exposed, because most CISOs have never formally claimed accountability for SAP security, and most SAP teams do not think of themselves as part of the security function.Hügel explains the structural gap at the heart of this problem. SAP systems are simultaneously the most business-critical and the least security-governed assets in most large organizations. The C-suite depends on them for financial operations, payroll, procurement, and supply chain continuity, yet SAP teams and security teams speak different languages, operate under different budgets, and rarely collaborate. SAP departments typically define "security" as managing user authorizations and privileges — a narrow interpretation that leaves configuration drift, patch backlogs, and monitoring gaps entirely unaddressed.Analyzed through Dr. Chatterjee's Commitment–Preparedness–Discipline (CPD) framework, the conversation translates SAP cybersecurity from a technical niche into a governance imperative. The Medtronic case study demonstrates what good looks like: a CISO who crossed the organizational divide, sponsored SAP hardening from the cybersecurity budget, built a continuous patch management process, and created the governance structure that allowed the team to respond to an out-of-band vulnerability within hours rather than weeks.The episode's central message is neither technical nor abstract: the organizations that will survive the next ERP-targeted ransomware attack are not those with the most sophisticated tools — they are the ones that have claimed ownership of the problem, built the processes to address it continuously, and created the cross-functional governance structures that SAP and cybersecurity teams cannot build on their own.To access and download the entire podcast summary with discussion highlights - https://www.dchatte.com/episode-106-the-invisible-attack-surface-zero-trust-for-sap-and-erp-environments/Connect with Host Dr. Dave ChatterjeeLinkedIn: https://www.linkedin.com/in/dchatte/ Website: https://dchatte.com/Books PublishedThe DeepFake ConspiracyCybersecurity Readiness: A Holistic and High-Performance ApproachArticles & Cases PublishedChatterjee, D. (2026). Root: Automating the Remediation Gap, Ivey Publishing, Jan 7, 2026.Ramasastry, C. and Chatterjee, D. (2025). Trusona: Recruiting For The Hacker Mindset, Ivey Publishing, Oct 3, 2025.Chatterjee, D. and Leslie, A. (2024). “Ignorance is not bliss: A human-centered whole-of-enterprise approach to cybersecurity preparedness,” Business Horizons, Accepted on Oct 29, 2024.Isik, O., Chatterjee, D., and Lourenco, D.A. (2024). “Getting Cybersecurity Right,” California Management Review — Insights, Accepted for Publication, July 8, 2024. Chatterjee, D. (2023). “Mission critical – How American Cancer Society successfully and securely migrated to the cloud amid the pandemic,” I by IMD, March 13, 2023.Chatterjee, D. (2022). “Preventing security breaches must start at the top,” I by IMD, September 28, 2022, Institute for Management Development, Lausanne, SwitzerlandChatterjee, D. (2022). “Making Cybersecurity Readiness Mainstream,” Executive Blog Post, NETSPI, March 1, 2022Benz, M. and Chatterjee, D. (2020). “Calculated Risk? A Cybersecurity Evaluation Tool for SMEs,” Business Horizons, available online from May 4, 2020Chatterjee, D. (2019). “Should Executives Go To Jail Over Cyber Attacks,” Journal of Organizational Computing and Electronic Commerce, Vol 29, Issue 1, pp. 1-3.Abraham, C., Chatterjee, D., and Sims, R. (2019). “Muddling through cybersecurity: Insights from the U.S. healthcare industry,” Business Horizons, July 2019.

Most enterprises are renters, not owners, of their technology and AI. Raffi Krikorian, Chief Technology Officer of Mozilla, explains why dependence on a handful of closed model providers means losing control over model behavior, pricing, and your own data.In CXOTalk episode 920, Krikorian lays out where open-source AI actually wins in the enterprise, how lock-in happens quietly, and what CIOs and CTOs should do about it now. Krikorian draws on his experience building infrastructure at Twitter and running the self-driving division at Uber to ground the discussion in real engineering and economic tradeoffs, not hype.YOU'LL DISCOVER✅ Why 85% of enterprises believed they could switch AI vendors, but only about 30% actually could when they tried✅ The "renters vs. owners" framing and what it means to control your AI destiny✅ Why Krikorian wants data "protected by architecture, not legal handshakes"✅ How Pinterest reportedly saved on the order of $10 million in a single quarter by switching from closed to open models✅ Why IT is becoming "the HR team for agents," and the read/write "dangerous triangle" of agentic permissions✅ The case for recording your prompts and running your own evaluations instead of trusting public benchmarks✅ Why roughly 70% of enterprise GPUs sit idle, and the missing "LAMP stack for AI" that could put them to work✅ How closed "validation machines" can quietly steer answers toward sponsored outcomes⏱️ TIMESTAMPS (estimated, verify before publishing)0:00 Renters vs. owners: who controls enterprise AI2:26 The risks of depending on closed model makers6:23 How lock-in happens and where open source fits9:53 Regression testing and building your own evals13:24 Pricing instability and the post-IPO cost question23:31 Governance: IT as HR for AI agents32:38 Can a small organization own its AI stack end-to-end?38:47 Validation machines, trust, and sponsored answers43:39 Keeping humans at the center, not in the loop47:23 Can open source beat big tech in AI?51:39 Inside Mozilla.ai: Otari, CQ, Octanus, Thunderbolt55:21 The "rebel alliance" strategy

Passwords were built for a different era of the internet. It's time to move past shared secrets to close your organization's largest threat vector for good.Traditional passwords and legacy Multi-Factor Authentication (MFA) are no longer enough to protect your business. Automated, scaling phishing toolkits easily intercept shared secrets, leaving small and medium businesses highly vulnerable to credential breaches.In this episode, Jen sits down with Nishant Kaushik, Chief Technology Officer at the FIDO Alliance, to translate complex cryptographic standards into an actionable, resource-light deployment plan. Learn how to transition away from legacy authentication and close the hidden operational loopholes that hackers actively exploit.What You Will Learn:The Flaw in Basic MFA: Why SMS codes and standard one-time passwords (OTPs) are failing, and what true "phishing-resistant" security means.The Account Recovery Trap: Why a weak "Forgot Password" workflow accidentally gives hackers their primary attack vector back—and how to fix it.The Bottom-Line Benefit: How moving to passkeys drastically reduces internal IT helpdesk tickets, manual password resets, and overhead costs.Right-Sizing Your Passkey Deployment: How to easily segment your workforce strategy:Standard Users: Synced passkeys via platform credential managers (Apple, Google, 1Password, Bitwarden).Privileged Users: Dedicated hardware keys (YubiKeys) for root admins and high-sensitivity infrastructure.The 1-Week Action Plan: How to leverage the identity infrastructure you already own (like Google Workspace or Microsoft Entra ID) to deploy passkeys today.Resources Mentioned:Learn more about modern identity standards: FIDO Alliance WebsiteReview baseline federal security recommendations: CISA Guidance on Phishing-Resistant MFADiscover SecurityMetrics compliance resources: SecurityMetrics Official SiteThreat Intelligence Data: Read the data behind credential exploitation in the latest Verizon Data Breach Investigations Report (DBIR). Federal Passkey Standards: Review the updated identity and passkey frameworks via the NIST SP 800-63 Digital Identity Guidelines. Enterprise Identity Platforms: Learn how modern stacks integrate passwordless via Okta Verify and Microsoft Entra ID. About the Guest: Nishant Kaushik is the Chief Technology Officer at the FIDO Alliance, bringing over 25 years of leadership in digital identity and access management (IAM). He holds nine patents, frequently serves on the advisory committees for the RSA Conference and Identiverse, and is a founding member of IDPro.A note from Jen: We built Practical Cybersecurity because we were tired of the fear-mongering in this industry. Security shouldn't be a secret club.If you're trying to figure out PCI compliance or need a pen test, my team at SecurityMetrics can help you out: https://www.securitymetrics.com/contact/lets-get-you-to-the-right-place But if you just want to learn how to protect yourself for free, start here:  https://academy.securitymetrics.com/ 

Why do so many promising pilots fail to scale? In this episode of Leader Generation, Tessa Burg talks with digital transformation leader Kenneth Phua to explore what separates successful pilots from initiatives that never move beyond the testing phase. Drawing on his experience leading digital strategy and transformation programs for global brands, Kenneth shares the common mistakes organizations make when measuring pilot success, why repeatability matters more than one-time wins and how businesses can build the capabilities needed to scale digital and AI initiatives across teams, markets and functions. The conversation also explores the role of leadership in successful transformation. Kenneth explains why empathy, curiosity, trust and a willingness to challenge assumptions are essential for leaders navigating rapid technological change.  Whether you're launching a new digital platform, testing an AI-powered solution or leading enterprise transformation, this episode offers practical insights for turning experimentation into sustainable growth. Leader Generation is hosted by Tessa Burg and brought to you by Mod Op. About Kenneth Phua: Kenneth Phua is a global digital transformation, ecommerce, and AI leader with more than 15 years of experience helping organizations turn digital investments into measurable business growth. Most recently, he served as Global Head of Digital Strategy & Innovation at The Coca-Cola Company, where he led enterprise-scale transformation initiatives across 115 markets and delivered approximately USD $900 million in system value. His work has spanned digital strategy, ecommerce, consumer platforms, first-party data, AI and operating model design. About Tessa Burg: Tessa is the Chief Technology Officer at Mod Op and Host of the Leader Generation podcast. She has led both technology and marketing teams for 15+ years. Tessa initiated and now leads Mod Op's AI/ML Pilot Team, AI Council and Innovation Pipeline. She started her career in IT and development before following her love for data and strategy into digital marketing. Tessa has held roles on both the consulting and client sides of the business for domestic and international brands, including American Greetings, Amazon, Nestlé, Anlene, Moen and many more. Tessa can be reached on LinkedIn or at Tessa.Burg@ModOp.com.

Industry experts estimate synthetic identity fraud costs the financial industry as high as $95 billion a year, and the most damaging attacks pass every verification check without triggering a single alert.Tedd Huff, CEO of fintech advisory firm Voalyre and founder of Fintech Confidential, brings 25 years of payments and fraud infrastructure experience to a direct conversation with Hal Lonas, Chief Technology Officer of Trulioo, the identity verification platform trusted by Google, JP Morgan Payments, Stripe, Airbnb, and Meta.Lonas explains why detection rates hide more than they reveal, how fraudsters now add intentional imperfections to AI-generated deepfakes to beat detection systems, and why agentic commerce requires an entirely new verification layer beyond KYC and KYB. The conversation covers Trulioo's Know Your Agent (KYA) framework, the Digital Agent Passport, Google's Agent Payments Protocol (AP2), and the privacy regulation debate most compliance teams have not fully worked through.Find out more1️⃣ Ask your identity vendor for their false negative rate, not just their detection rate, and demand specific numbers.2️⃣ Build continuous monitoring into your post-onboarding workflow so your system is still watching on day 30, 60, and 90.3️⃣ Audit every automated decision model in your stack and document the logic before your next regulatory exam.4️⃣ Map your verification flow and tier friction based on real-time risk signals instead of running flat checks on every customer.5️⃣ Get your compliance and growth teams in the same room with a shared dashboard showing fraud loss rates and abandonment rates side by side.Guest:Hal Lonas LinkedIn: https://www.linkedin.com/in/hal-lonas-4555b1Hal Lonas X: https://x.com/hal_lonasCompany:Trulioo: https://www.trulioo.comFintech Confidential:Podcast: https://fintechconfidential.com/listenNotifications: https://fintechconfidential.com/accessLinkedIn: https://www.linkedin.com/company/fintechconfidentialX: https://x.com/FTconfidentialInstagram: https://www.instagram.com/fintechconfidentialFacebook: https://www.facebook.com/fintechconfidentialSupporters:Under.io streamlines application and underwriting by digitizing PDFs for digital signature: under.io/FTCSkyflow is a zero trust data privacy vault delivered as an API, covering PCI, CCPA, GDPR, SOC 2, and beyond: skyflowsecure.comDFNS provides wallets as a service, API first, multi-chain, secured with MPC, used by Stripe, Fidelity, and others: fintechconfidential.com/dfnsHawk AI offers real-time payment screening, AML monitoring, and dynamic customer risk rating to reduce false positives: gethawk.comAbout:Hal Lonas is the Chief Technology Officer of Trulioo, where he leads technology strategy, product development, and engineering. He co-founded BrightCloud, a cloud-native threat intelligence company, and previously served as CTO at Webroot, Carbonite, and OpenText before joining Trulioo in 2021.Trulioo is a global identity verification platform operating across 195 countries, covering 14,000+ ID document types, 6,000+ watchlists, and 700 million business entities.Tedd Huff is CEO of Voalyre and founder of Fintech Confidential. The show is produced by DD3 Media and brings you the people, tech, and companies that change how you pay and get paid.Chapters: 00:00 Introduction01:28 Meet Trulioo CTO02:48 From Space to Security04:11 Dfns: Wallets as a Service (sponsor)05:32 Sleeper Accounts Explained08:33 False Negatives Metric11:43 Explainable Adaptive ML13:23 Deepfakes Raise Stakes15:03 Asymmetric Defense Signals17:51 Privacy Versus Safety21:25 Sky Flow: Building Fast and Secure (sponsor)22:27 Friction Based Risk24:16 Case Study ConsenSys26:04 Know Your Agent Future27:52 Agent Passport Checks32:43 Open Standards AP234:35 Are Defenders Losing36:05 Leader Advice Wrap40:37 Final Thoughts and Outro41:36 Hawk AI - Realtime Fraud Monitoring (sponsor)42:23 DisclaimerDisclaimer: The information provided in this episode is for informational purposes only and should not be considered financial, legal, or investment advice.#syntheticidentityfraud #identityverification #KYC #KYB #agenticcommerce #KnowYourAgent #deepfakedetection #fintechfraud #fraudprevention #AML #trulioo #AP2 #GoogleAP2 #AIfraud #fintechcompliance #fintechconfidential

In this episode of The Geek in Review, Greg Lambert and Marlene Gebauer welcome back Joel Hron, Chief Technology Officer at Thomson Reuters, for a timely conversation about the shifting relationship among foundation models, legal content providers, legal tech platforms, and the lawyers trying to make sense of the mess. Recent moves by Anthropic, including Claude's legal practice area tools and MCP connections into legal platforms, raise a larger question for the market. Is a model provider still sitting behind the scenes, or is it starting to become a legal work environment of its own?Hron explains Thomson Reuters' commitment to what it calls fiduciary-grade AI, a standard built around trust, verification, transparency, and accountability. For TR, legal AI needs more than a fast answer. It needs systems lawyers trust enough to stand behind. Hron points to Westlaw, Practical Law, KeyCite validity signals, citation ledgers, and verification tools as core ingredients in building AI systems suited for high-stakes professional work. In his view, almost right is not good enough when clients, courts, regulators, and professional obligations sit on the other side of the output.The conversation turns to how CoCounsel and Westlaw Deep Research use legal content across far more than traditional research tasks. Hron explains that when AI systems gain access to trusted legal content and verification tools, they begin researching throughout the workflow, even while revising contract language or analyzing provisions. He also describes Litigation Document Analyzer, internally nicknamed the BS Detector, a tool designed to review claims in a document and map them to supporting authority, weak support, or no support at all. For lawyers who spend as much time verifying AI output as generating it, tools like these aim to move verification from a manual scavenger hunt into a structured process.Greg and Marlene also press Hron on Anthropic's legal plugins, MCP, and the idea of headless legal technology. Hron argues that MCP changes access, not advantage. In his view, the application layer is shifting, but the real competitive value sits in trusted content, expert systems, governance, and domain-specific intelligence. CoCounsel's user interface represents one expression of TR's legal agent capabilities, while MCP opens other ways for those capabilities to appear inside broader work environments. Some work will still need a purpose-built legal interface; other work might happen through email, Word, Claude, or another agentic workflow with little visible interface at all.The episode closes with a larger discussion about what happens when AI starts performing more of the work itself. Hron shares TR's internal engineering OKR, where more than 50 percent of pull requests should be written by AI, and explains why 51 percent serves as a useful mental model. Once AI performs a controlling share of the work, the human role shifts from doing the task to governing the system. For legal professionals, the same transition is coming. The key question is no longer only whether AI produces useful work. It is whether lawyers have built the systems, context, safeguards, and verification layers needed to trust the work, defend the work, and remain accountable for the work.Listen on mobile platforms:  ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Apple Podcasts⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ |  ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Spotify⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ | ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠YouTube⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ | Substack[Special Thanks to ⁠Legal Technology Hub⁠ for their sponsoring this episode.] ⁠⁠⁠⁠⁠Email: geekinreviewpodcast@gmail.comMusic: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Jerry David DeCicca⁠⁠⁠⁠⁠⁠⁠⁠⁠

Cybersecurity is no longer just an IT issue. It is a business survival issue, and every leader needs to understand where the real risks are hiding. In this episode, I had the pleasure of speaking with Dave “merk” Merkel, CEO and co-founder of Expel, about the evolving world of cybersecurity, AI, and business resilience. Dave shared the founder's journey behind Expel, how the company grew by solving cybersecurity as a technology-driven scale problem, and why businesses of every size need to think seriously about 24/7 protection.  We also explored the growing risks created by supply chains, fragmented systems, AI adoption, and increasingly sophisticated threat actors, while still keeping the conversation grounded, practical, and encouraging for business leaders. Here are the highlights: Cybersecurity matters for every business, not just large enterprises. Dave explained that even smaller companies can become targets when they are part of the supply chain for larger organizations. Expel was built to solve the scale-and-quality problem in cybersecurity. Rather than operating like a traditional services business, Expel uses software and human expertise together to deliver consistent 24/7 protection. AI is changing the speed and complexity of cyber risk. Dave emphasized that both attackers and defenders are using AI, which means businesses need security partners who understand how AI is reshaping the threat landscape. Business owners should look for outcome-focused security partners. Dave cautioned leaders to avoid fear-based selling and instead seek providers who understand their business, ask smart questions, and can clearly explain their approach. Cybersecurity professionals are doing mission-driven work. One of the most powerful moments in the conversation was Dave's reminder that cybersecurity teams are protecting companies, employees, families, and livelihoods every day. About the guest: Dave “merk” Merkel is the co-founder and CEO of Expel, a leading provider of Managed Detection and Response cybersecurity. He has been involved in the information security field for nearly 30 years, first as a federal agent pursuing cyber criminals in the era of floppy disks and 2400 baud modems, then as Chief Technology Officer and vice president of Mandiant. Following FireEye's acquisition of Mandiant, Dave served as the global CTO of FireEye. Connect with merk: LinkedIn: https://www.linkedin.com/in/davemerkel  Website: https://expel.com/  Connect with Allison: Feedspot has named Disruptive CEO Nation as one of the Top 25 CEO Podcasts on the web. LinkedIn: https://www.linkedin.com/in/allisonsummerschicago/  Website: https://www.disruptiveceonation.com/   #CEO #leadership #startup #founder #business #businesspodcast Learn more about your ad choices. Visit megaphone.fm/adchoices

In this celebratory episode, The Suite Spot hosts two TMG veterans, Director of Product – Respond and Resolve™, Jackie Avery, and Chief Technology Officer, Jason Lee, on the podcast to commemorate the 10 year anniversary of the Respond and Resolve™ digital solution.  Jackie Avery discusses what the milestone means to her and her team, and how responding to reviews is the foundation for connecting to guests and why it’s critical for hoteliers to give authentic responses to their guests. Jason joins the podcast to share the history and evolution of the Respond and Resolve™ digital solution and how it has become the industry solution service it is today.  Ryan Embree: Welcome to Suite Spot, where hoteliers check in, and we check out what’s trending in hotel marketing. I’m your host, Ryan Embree. Hello everyone, and welcome to another episode of The Suite Spot, a celebration, my favorite type of episodes we have on the Suite Spot. Very excited to share a milestone and achievement, a celebration, like I said, a 10 year anniversary of our award-winning, industry leading Respond and Resolve™, review response solution. Here with the Product Director of Respond and Resolve™, Jackie Avery. Jackie, welcome back to the Suite Spot. Jackie Avery: Thank you. I’m so happy to be here. I’m so excited to talk about this too. Ryan Embree: Congratulations, what a feat. 10 years of responding to reviews. We are gonna have the opportunity to speak with Jason Lee, our Chief Technology Officer, and we’re gonna talk to him about really the history and evolution of this solution, and really guest feedback management in general, how that’s evolved over time. But with you, I thought we’d start with talking about present today and this solution respond and resolve, again, responding to guest, hotel, guest reviews. What makes this so special? What is the secret sauce? Why has it seen such an explosion of growth from our hotel partners, and what do people love about it? Jackie Avery: Yeah, so I’d say everyone on my team probably has a different answer to this, but for me, it really comes down to passion, time, and flexibility. So we’re really passionate about that connection making, you know, that moment with the guest truly matter. Taking the time to really connect in that way with them. And I’d say, I guess right, others might say, well, you know, these other people within the industry or at the hotel also have that passion and, and care about that connection. So, I think we all agree that that’s really important. But then you come to also adding in time. So someone might be able to dedicate an hour to responding to their guest reviews, or maybe even a few hours a week, and they feel really good about that. But like for us, right? This is day in, day out. This is what we do all day long. We really have the time to not only have the passion for that connection with the guest, but take the time to think about what they wrote and how they wrote it. And so, and there are gonna be people who have the passion and have the time, and I absolutely do not wanna diminish that. I’m so happy that they do. I’d say the third, and just as equally important aspect though, is flexibility. So this is an ever changing landscape, right? One moment. The M dash in writing makes you sound human. It’s casual. This is how you connect. The very next day, that’s an indicator of AI. If you’re using that, no one thinks you’re you. So in the past, right, you would start writing a response and you just wanna make sure you’re not sounding defensive, you’re not being dismissive of, whatever their concern is. And that’s still important, but that’s not where you start anymore. You start by convincing someone that you’re a person, you’re sitting at a computer taking away from all of these other aspects of your job, and you’re like, my first step is showing everyone that I’m me and I’m real. So, on top of all of that, right now, you’ve got that going on. Maybe, you know, you feel like you’ve got a handle on it. There is a very intense, again, ever changing landscape when you’re thinking about the political climate, the economic climate, and those impacts the guests and travel. We all know that. And so it’s really hard to meet a guest where they’re at. If you’re not keeping up to date with everything going on. You have to be aware of those shifts that are happening all the time to everyone. Ryan Embree: Yeah. It’s ever changing, especially over the course of a decade, which has obviously been the timeline of this solution here. And you’re absolutely right. I mean, that authenticity is so key to show the guest that you actually care about what you wrote. And you’re right, there’s a challenge now to almost convince that guest that I am real. I am listening to you and I’m connecting. And there’s a reason why in this age of technological advancement and AI, we were talking about it every single day. We’re at the peak of technological advancement. Every single day we move forward, there are still hotels that come to us and say, we want to maintain a human to human connection. We don’t want AI to be responding or generating responses that are going straight to our guests. Why do you feel like that is, and and what are the feedback you’re hearing for these hotel partners? Jackie Avery: Yeah, so when you zoom out, right? Guests are the entire reason that hotels exist. So when you’re considering reviews and checking reviews before you stay somewhere or leaving a review, after you’ve departed, these are really important aspects of the guest journey. They’re a part of your guest experience. So when you are a property who is fully invested in your guests having a great experience at your hotel, you want them to be surprised when they come in the best ways. You want them to leave with the best memories and spread that by word of mouth and online, you understand that you have to continue that real connection the same way you want to at the front desk in those points online. You have to connect with them human to human in that review response. Ryan Embree: You know, Jackie, one of the things that I think makes the solution so special, and something you’ve done a great job of is curating this team of professional writers where a lot of these writers here went to school for writing and communication. You know, these are degrees that are their specialty. They have a passion for this, right? And you talk to a general manager nowadays maybe they didn’t, maybe they don’t have a passion in writing, right? Like, that wasn’t why they got into hospitality to say, I wanna be a writer. But, you know, you created this team that also understands the nuances of the hotel world. It’s the only vertical that we work with in hospitality. And there’s so many of those little nuances that you have to teach and you have to incorporate in your messaging and in your review response writing to make sure that is articulated so clearly to your guests, or really it undermines your reputation as a whole. Talk to us a little bit about some of those nuances, maybe some examples and how you’ve been able to generate just this team of, again, just incredible writers. Jackie Avery: So, I’m fortunate because we’re doing this episode to celebrate 10 years. So we know what we’re looking for and we have experience in how to train specifically writing for hospitality and guest reviews. So fortunately, you have these degrees where people come in, they’re educated, they know how to write well, and then you have this training based on real world experience. And having seen the evolution of guest reviews. You used to get it where guests only left reviews when they’re angry. That’s not the case anymore. Guests go, they love the praise of feeling rewarded for leaving a good review. They wanna leave a good review. And having written so many, right? Each individual learns something and takes it back to the team. So it’s consistent workshops, it’s creative workshops, it’s adjusting to the new landscape, right? Being aware of what is seen as AI and what is AI. Being able to identify a review where a guest used AI to leave it, maybe. Or also being able to take a moment and pause and know the best way to reach another human when they’re being skeptical. So where as someone on property, right? They’re so focused maybe on, well, I wanna let this guest know that’s not how we do things, or that’s not really what happened here. And this professional writer on the team realizes the first line of this review was, and I bet a bot is gonna answer this. You have to cross that bridge first. You have to tackle that first. And if you don’t know how, it’s gonna be really hard to get your actual message across to this person that you really want to. So, we’re always building on what we know, because we realize what we know today can’t be what we rely on forever. Everything is gonna be different in three months. Everything will be different in one year. And when you’re set up to be able to make those adjustments, and you’re excited about that, when you love writing, when you love being able to write in a different way and connect with someone, and this is your passion, you know, you thrive in that landscape, it’s not a challenge that you don’t wanna take on. You look forward to it. Ryan Embree: Yeah, absolutely. And you’re absolutely right about the landscape. Completely changing. Sometimes, even though over the course of 10 years, I mean, booking has their pros and cons. They actually essentially solicit some of the negative feedback so that you can address that character count, right? With a TripAdvisor and maybe now going into reviews with no content at all, and responding to those PPI and personal information using people’s names in those responses. Is that something that a site allows or not? All of these are things that you wouldn’t really think through in responding to reviews, but it’s so critical and so important because, again, it’s an underlying foundation of your reputation management. And why do we respond to reviews to show we care? So if that care isn’t being shown, it really undermines your reputation. So, anything that lasts for 10 years obviously, means that it’s a success. I’m sure you’ve heard over the years some really, really rewarding pieces of feedback from our hotel partners. Can you share, we love a good story here on the Suite Spot in the podcast. Can you share any examples, maybe just one or two of some special moments or conversations with some of our Respond and Resolve™ clients? Jackie Avery: Yeah. Thinking back, because it feels really relevant this year, because it does seem to be happening more frequently, I think back to an email I got from a client, and they were going through it, their property started receiving hundreds of reviews within an hour to, because of something happening within the city, it was something going on. That was happening citywide and really had nothing to do with their hotel. And you can imagine in that moment, they’re fielding calls at the front desk from guests who haven’t arrived yet. They’re trying to ease concerns from guests in house, and their online listings are just being flooded from people who aren’t there and are just saying stuff. And really, it’s just because of the city they’re in and something that the property has nothing to do with. So in those moments, I’m so grateful that we can help. I got this email from this hotel, and they were just like, thank you. I had so much on my shoulders, and I know I have this support and this, and I put out these things, you know, to these other people at the property who help us. But in that moment, I knew, I knew you guys were there. Yeah. And I knew that you could give advice on what to do. You’ve seen it before. You helped guide my steps. And I’m so grateful for that, that our years of experience mean that in the moment a guest can be served face to face, and we can be assisting, you know, with things happening outside of this property’s control. Ryan Embree: And what a line to tiptoe too, if AI is involved, right? And that, and the messaging is not communicated the right way there, it could mean so much more than just a one star review. It could mean detrimental damage to your reputation, especially in those moments of crisis. Jackie Avery: Absolutely. And some sites let you edit what you post back and some don’t. So the stakes are high. And it’s happening fast. Ryan Embree: Absolutely. Very fast. And so, as we wrap up our conversation here, and again, congratulations. As Product Director, you look at this, what do you look at this 10 year milestone? What does it mean to you and what’s your vision for the future of this solution? Jackie Avery: Yeah, this milestone, I feel it, I feel it personally. Not just for me but my entire team. When you genuinely care about connecting with other people and helping and being support in this way, it’s really easy to feel the joy in what you’re doing. So this milestone, to me, is just something that I am reflecting on that I’m so grateful, I’m so grateful to be able to work with clients across the country and help people out there connect in a space where they’re expecting not to have that opportunity. More often than not, people are expecting not to hear back, or they don’t wanna get their hopes up that they will hear back, but they do. Yeah. And it feels great. And I love that. Ryan Embree: Yeah. The stakes can’t be any higher right now when it comes to that. And hotels are getting creative with trying to figure out ways to connect with guests in a world where, you know, you don’t have to visit the front desk anymore. You can, you don’t have to interact with hotel staff anymore. So hotels are trying to figure out ways that they can keep a constant line of communication. And this is always gonna be a place where guests are, are gonna be, do not make it a one-way conversation. They’re gonna continue to leave feedback. Are you genuinely listening? Are you authentically responding? And we’re so grateful to have you on this podcast to celebrate this milestone. Thank you, Jackie. And congratulations again to you and your team. Jackie Avery: Ah, thanks so much. It was great to be here. Ryan Embree: Next wee’re gonna be talking with Jason Lee, Chief Technology Officer at Travel Media Group, where we’ll talk a little bit about the history and evolution of this Respond and R™esolve solution, which just turned 10 years old. Ryan Embree: Hello everyone. Welcome to part two of our 10 year celebration of TMGs Respond and Resolve™ review response solution. I am here with one of the architects, CTO, Jason Lee, congratulations to you and your team 10 years. Jason, you know, we love a good origin story. Talk to us, bring us back 10 years ago when you started, maybe it was even before 10 years. But tell us a little bit about how Respond and Resolve™ came to be and kind of the evolution of the solution that now turns 10 years old. Jason Lee: I mean, I think we at that time, we had been kind of doing reputation for hotels for a little bit, mostly in post-day engagement. And then also monitoring reputation scores and reputation flow. And we were getting questions like, hey, can you handle review response? And so we sat down and we were like, we’re getting this more and more. And we had salespeople that were saying the same thing, like, hey, I just got the phone with this guy, and he said he would buy except if we had this product. And so we sat down and we started thinking about like, what is it gonna take to, to get this done? And we had, we happened to have a tech summit during that same time, and we all sat down. So at that time, it was all the tech leaders we had and our tech team as well. And we really just kind of mapped out, like, what would it take to, to do this? Yeah. And at the time I was like, listen, the only way this is gonna work, anybody will even buy this, is if they can ensure that whoever is providing them the response is gonna do it in their voice is gonna be able to do it in a way that they would do it. Speak to their guests in the way that they would wanna be spoken to. And so we sat down and we put together what was kind of the building blocks of what is today’s, Respond and Resolve™, Travel Media Group. But at the time was even more complicated. It had multiple touch points. So it had a single, it had a touchpoint of the review coming in. It had a touchpoint, after the response where we would audit the response before the response went to the hotel, the hotel would then approve the response. And then once the hotel approved this approved the response or edited the response, it would come back to us and we would touch it one more time before we would then publish that response. So we had this, like, we had a three touch internal, like four touch, if you include the hotelier system. And, you know, and of course, you know, anybody who’s done any kind of product work or anything would think like, that’s an insane amount of touches, that’s a crazy amount of scaling. And so then our secondary thing was like, how do we do this based on the number of reviews or whatever? And we weren’t even thinking that way. We’re like, because there’s an unknown number of reviews, how do we even do this? So we started the product out with, with that kind of cadence, with 20 reviews being kind of the core. So you get 20 reviews a month, and it was TripAdvisor only. Yeah. And you had this one critical response. So we would like, you know, if there was a, something that really, that happened that was really bad, we would write this like very specific kind of PR version of a response. And that was the original product. So we put it all together, we put our price point out, and, and I believe you were the first person to sell one to a hotel. So, so as we got that going, then it was, you know, then, then we went through the rest of kind of like the evolution of the product. But at that time, it was something I think one other company was doing, but we, you know, we didn’t really know what they were doing or how they were doing it. So we kind of took our own path in how we created it. Ryan Embree: And we were talking off camera about, you know, some of the challenges. And maybe I think it’s through some of the unexpected. ’cause you think about, all right, you know, if tomorrow, you know, someone was like, let’s, let’s create a company that responds to reviews, and then all of a sudden you start building that and you come across these challenges, these, these issues, these problems that you’re like, well, I didn’t think about that. I just kind of thought about the output and input. What were some of those kind of learning lessons along the way, and how did you kind of adapt to that, whether using efficiencies technology, because it’s a lot more difficult than just saying, Hey, we’re just gonna respond to your reviews. I think the biggest challenge and where we had our biggest evolution in the solution was in when we converted what we were doing. So at the time when we started it, we were using third party data. And we were pulling some stuff, but some stuff was being pulled through a third party vendor. And it wasn’t until we launched one view where we controlled the entirety of the dataset. And not just the entire, not just the entirety of the dataset, but the frequency of the dataset, which was insanely important. So this has to do with when it is received from the time that it was published live. And so that in itself sort of opened up this new lane, but in doing so, it also opened up our eyes to this really one like incredible flaw to our system, which was how we were pricing it. But that has to do with how we sort of viewed the, the universe of reviews for a single property. So when we started, we had that 20 Right. The next little jump was, well, maybe we’ll start charging by the room. And this was something we had heard other other vendors doing, and we’re like, oh, this is a good idea. We’ll start charging by the room. What we found immediately was that we were massively overcharging some hotels. And way undercharging other hotels. So a destination 80 room hotel could be doing three or four times the review volume that a 250 room corporate hotel was doing. Like, that’s straight up like extortion on one side and then just us just like.. Ryan Embree: And extended stay sometimes, you don’t have the frequency. Jason Lee: Completely, completely. So, so I think pricing, getting that pricing down. So once we then controlled the universe of reviews, we then, so at, at the time we launched OneView, we had a 360 view of a 365 to be exact, day view of a properties reputation. So we could sort of forecast their total quantity of reviews over a year and then, and then, and then sort of amortize that out to create pricing around review flow. So I believe we were one of the first to do review flow, and I think we might still be one of the only companies that prices that way, where we actually look at quantity of reviews and surveys that a property gets. And then we price knowing exactly what we’re going, what we’re up against, including the 35% ish increase over the summer months that that happens just based on review flow. You know, guest flow. So, so I think those were those big things, kind of those big hurdles, like, internally pricing it the right way, doing it in a way where we could, we could ensure that whatever we said we were going to do, we could 100% do. We had the staff to do it, we had the technology do it, and all the pieces in play. And then I think from there, it was then understanding the sort of undulation of the acquisition of review data. And that is a crazy space because, if you’re scraping the data directly from a site, then you’ve got that whole thing that that’s going on where sites are continually sort of trying to thwart that. You have the API side of that where you can get API but that requires you to get these relationships with these various sites. And so, so our, we were just like, just, just dogged determination To like secure better and better and better and better data sets. And we did that through, eventually through getting partnerships with the major review providers like Expedia, Booking.com and Google. And so inside of doing that, we were able to really secure a data set that then allowed us to respond in a timely manner and efficient manner, and in a way that, you know, could completely solve this issue for a hotel. Ryan Embree: I think some of the biggest learnings or we’ve had is through those challenges, but also through the close relationships that we’ve had with our hotel. Partners and those hotels that we say it all the time when it comes to reputation. I mean, feedback, you want feedback, right? Whether it be from your partners who who travel media group are working with, whether it be from your guests, and you’re a hotelier, you want that feedback. Because that means it’s striking some kind of cord, whether it’s good or bad. ’cause then you can make adjustments. So, the actually hearing what our hoteliers had to, to, to say about our, our reviews and our I’m sorry, what they had to say about our responses helped us. Collaborate or calibrate rather their voice and tone and everything that to kind of get us right in harmony with how they wanted responses. And I think for me at least, it was very surprising to see the spectrum at which people wanted, how they wanted their responses handled. Whether it’s, you know, we don’t want an apology ever to be heard on our responses or, you know, we, we always apologize whether it’s our fault or not. We’re always going to say the customer is always right. And there’s everything in between. We want our voice a little bit more laid back. We want it more of a professional tone. You know, you’ve gone through these patterns and trends of try to use keywords in every single one of your review responses. Aside from the challenges, what have you learned? Maybe talking to hotel partners or hearing them, seeing some of that feedback that comes in about our responses. ’cause I know, although you’re the CTO, you’re very close to that feedback and are in there and seeing what our hotel partners are saying every day about our responses. Jason Lee: That’s a great question. And I think it hits at the evolution of the benefits of this need. And I think that’s what’s so interesting about, about doing this for this length of time. So in the very beginning, I talked about that very complicated setup that we had where we were like approving the response before we sent it to the hotelier, and then we had the hotelier approve the response and edit the response, and then we publish the response. We kept a bunch of that together. So we kept the right approved by the hotelier edit and resolve or audit and resolve, process on our side. And so in doing that, even though it was overkill in the beginning, we had people saying, we don’t wanna approve it. We don’t wanna approve it because we’re, because we’re like, this takes too much time. And because I’m not around on the weekend or whatever. And, but what ended up happening is that as the sort of understanding of what review response was doing, so the review response kind of needs sometimes is hinges on what is the downward pressure to get this done? So is this coming from my management company? Is it coming from the brand? Is it coming from an OTA that says I’ll get better placement if I do this this way? So this becomes this becomes thing. Or like you said oh, I heard that I get better SEO get better placement if I use keywords in my responses. So this becomes this sort of meta benefit. And I think through the through line that we took from the very beginning and way before, I feel like a hoteliers wanted us to do it that way. And maybe today there’s still a few hoteliers that are just like, whatever, man, just get it done. You know, is that we really wanted to communicate with the guest who wrote the review. And we wanted to make sure that whatever we were writing in our response, that that communication was clear. It was clear in gratitude on five stars. It was clear in empathy and resolution in one star reviews. And it was, it was really trying to find that balance when there was no feedback. Even if the get, even if the hotel didn’t care maybe as much about the content of the response that they trusted us to make that response. But what we find is like now, 10 years later, that where, where we have had a complete shift in our property profile at Travel Media Group, where I think we started with a lot of economy properties and select service properties where we’ve, we’ve reached into these incredibly large resorts luxury properties. Some of the nicest properties in the United States are our clients. And I think it’s because we’ve stuck with that. So you talk to the hotelier that has a $200 or $300 a night guest, or even a $1,200 a night guest, in some cases, their feeling about the retention of that guest is very different than a select service, than a select service. But they’re, but they’re also their version of, like, that this activity promotes acquisition of guests. And so the stakes are high. In this space. And I think we’re reaching into like a whole new era where this information, the review and the response are affecting generative search. And we’re reaching a whole new era of economizing the search time with massive amounts of review data. In an individual research session for a guest is really changing the importance of this activity together. So I think, I know I kind of took a windy road on that, but I think the biggest thing is that the evolution of expectation from the guest, but also then from the hotel has changed. And we’ve stayed close to it this entire time. And like, like everything that we do at Travel Media Group, we are sort of singularly focused. So we’re so focused on this as this. We probably, when I talk to hotels sometimes, they’re like, man, you are really exaggerating the importance of this activity. And I’m like, no, it’s everything. This is like, this is about you securing the relationship with this guest. This is everything. But hopefully you want a partner like that has that sort of dogged determination to make sure that it’s done correctly. But I feel like, so to kind of wrap this up, I do feel like that that is what we’ve done, that’s been the through line is like focusing on the need and like you said, focusing on the voice make, altering account by account. So now you’re talking about a few thousand hotels. That we’re scaling, you know, we’re where we’re like in the off months, we’re doing somewhere, you know, around 20,000 – 25,000 reviews. And we’re able to then inside of that still create personalization, still create a voice of a hotel. Still be able to hit the right kind of policies, the right kind of renovation details, the right kind of care to each individual review, or each individual guest as we see that to make this thing work. Ryan Embree: I mean, every hotel we have found out is so drastically different from the way they want thing hand handled, but also, just their properties are different, right? Their locations, their markets, occupancy drivers, the type of traveler that they bring in that they want to attract. There’s so many different elements. That speak to that. And it’s with the, Jackie and her team do a fantastic job to the point to the precision, we want to be completely aligned with that hotel partner. And what you were talking about was some of the newer luxury properties that we’re now partnering with. I mean, the stakes are high in the sense of they’ve had decades long reputation. They have built that. And it is no longer a negotiable for them to make sure that that reputation is protected. And a solution like this, like respond and resolve, really can help solidify that and also just serve as such a foundation and a security blanket in case some of these, Jackie had a couple examples of these things right now that can go wrong at a property. We hate to see it, but it happens every single day in a trusted partner like Travel Media Group and Respond & Resolve™ team behind you can really help give you a little bit of peace of mind for a hotelier. And you’re absolutely right. Obsessed is a great word to put it and passionate about review response. I mean, this is something that we’ve done for 10 years, but I think it’s been a little bit longer that we’ve been in the reputation game. And you know, you can’t, in 2026, you know, we, I had a podcast episode, late last year where it was actually with the co-founders of ILHA and they were talking about how you cannot in 2026 cannot be a complete expert at every aspect of hospitality. You just can’t. It’s just, it’s one of those unique industries where you can’t know everything about everything. You will never be the expert of chemicals for your hotel pool. But it’s important to know those things, and it’s important and critical to have a valuable partner that knows those things. So you think about that as one element, chemicals in a pool, curtains, flooring, review response is a very important element to your digital and online reputation there. And we talked with Jackie about, you know, obviously AI and how that has certainly changed in the last 10 years. And it’s how it’s come in, talk to us, because I think a lot of times people might hear us and think that we are anti AI or anti-technology, and it’s actually the exact opposite. It’s an incredible piece of technology that we can use in elements of reputation, but not necessarily for the actual response. So how are you kind of using AI? And we do have an AI solution, not 10 years old yet. We’ll be doing that in in several years. But talk to us about how you’ve used technology and AI kind of hand in hand with Respond and R™esolve for the past 10 years. Jason Lee: Yeah. I mean, I would say in the last 18 months we have evolved our core platform probably more than we did maybe in four years. So we’ve done a lot recently. And a lot of it is that a, like a whole new world of data analytics has been opened up. By this, so something that I would needed maybe two or three data scientists to help me with. I can do, can do with, with an API through anthropic, or through Open AI. And working with members of my team and putting some data together, we’re able to find like really interesting insights. And so the first thing we launched last year was the guest experience snapshot. And that was an a completely AI driven report. And the sort of origin of that was to show the hotel the top things that was that a guest was experiencing great. And then the top things that they, that was going wrong, and some of that was to show them multiples of the things that we were responding to. So the things that, so using this data to kind of, to shine a little light on like, Hey, we can only say sorry for this so many times. You know, but also to show them the other side of it where it’s like, Hey, this is where you guys are winning. You guys are winning in these very, in these areas. And this feedback isn’t always a negative. There’s a bunch of great stuff in here. And I think, so we’ve then continued that by continuing to analyze trends to continue to analyze, review flow, to analyze the sentiment data. And it just continues and continues and continues, as we sort of unlock the use cases of these tools. But for us, I think like the big pieces of the tools that are really exciting coming forward are the ways that we can scale personalization, in a way that we couldn’t do without major data science. And, and so we’re able to scale personalization, so taking the personalization that a hotelier gives us about very specific things about their property, and not writing the response based on that, but sort of confirming the response against the voice. So I can take a response and confirm then the voice, you know, and it says, yeah, this, this matches what they’re, what they asked us to do. And so that can get very, that in our world, that’s probably one of the more complicated pieces of it, especially where you have a very lengthy voice note, you have a massive policy note. You have a massive amenity amenity note. So these are these these spaces where a writer could get turned around on something. But where this could verify, hey, the response you just wrote is missing this one piece. Ryan Embree: Notes are changing seasonally based on restaurant menus, based on programming that the resort is conducting out. And its amenities classes that it has timing. I mean, all of those elements are notes that that can be provided and are so important. I mean, we think of it as oh, well, if we get a date wrong or if we get an item wrong, I mean, that has a pure, such a big impact on the guest experience and their impression of your hotel. And the care that you’re taking, so it’s just one of those elements, again, we talked about it with Jackie of, you have to prove essentially at this time that you’re not AI and that you do care and that, it’s so important to these guests and hoteliers, all this. Jason Lee: I think that’s where it all boils down to is that when I get that email from Booking.com as a guest that’s from the hotel, and I open that up and I read the response to the review that I wrote, does it feel authentic? Does it feel like it came from them? Does it mean anything to me? Is there any kind of meaning to that at all? Or is this like, or does this intensify, does this intensify my advocacy of this property, or does this intensify my anger? And you or does this turn me around? Does this make me wanna and I think these are these opportunities you have in this space that does make a huge difference. And I think AI will help us enhance the personalization of our individual properties and help help us, like put that really, like that perfect response together that helps the guests know that they’re cared for. Ryan Embree: It’s a feeling. I mean, Jackie talked about it getting that feedback from our partners about, this was a repeat guest, this is someone that stayed with us and they talked about our response back to them. They thanked us. And those are the moments that we strive here at Travel Media Group for, and we’ve seen so many over the last decade of doing this review response. And here we are at 10 years as you look towards the future, the landscape ever changing, you know, what do you see kind of for the future of Respond and Resolve™? And maybe we can open it up just to guest feedback management. I mean, were really at a inflection point I feel like right now. Jason Lee: Yeah. I mean, I think, I think it’s kind of more of the same in terms of what this has been about all the all along, which is the guest experience. And how do we react to the guest experience react to the specific experience the guest is giving us in a response, but act then multiple guest having similar experiences. How do we react to that? How do we improve the guest experience over time? And I think that that’s where the opportunity is right now, is that there are so many tools available to us to understand this in a much more granular level, in a much more specific level. So the old way of, of asking questions, I think of guests, I think is gonna go away at some point us sort of like, asking guests the same questions over and over again. You know, would you recommend, how clean was your room? What was the breakfast like? You know, rate that, I think we’re gonna get to a spot where we sort of understand these elements, but we can take broader textural, data points and start to really dial in to, so what does a 3 in breakfast mean? What does, what does it mean when somebody says that they would recommend at a 7? Or a thumbs up or a thumbs up or a thumbs down. I think this is where, you know, this is where these kinds of scales get a little funky. And so AI could help a guest actually articulate themselves in a response in a survey, for example. AI could also obviously take this data and take patterns of data and help a hotel understand the fail points of their service. And I think those are these really amazing opportunities for hotels that want to engage there. And, but all of this together is also doing something really interesting in the generative search world. So, we’re seeing people flock generative search more and more and more because it economizes that effort. I can read hundreds of reviews, I can have hundreds of reviews read for me and summarized, based on a very specific question. So I can ask about the breakfast, for example. And I get this summary. So none of that is gonna come through a three on a guest experience survey a guest satisfaction survey is not gonna affect that. But the 25 Expedia reviews that you’ve gotten in the last 90 days will. And I think those are those things that start to inform the traveler are going to be the quantity of signals. Whether they’re positive or negative and then the sort of inference of that signal, it’s not binary, it’s not good or bad, it is this other thing. Which is sort of the feeling of a guest. And I think a AI is getting better and better and better, and is getting to a point where it can sort of relay the feeling that multiples of guests have had about your property to a prospective guest. And that either should thrill you or it should scare you. Because this part of technology that I think get that we are all enjoying in some ways, right? Because it’s saving us time, it’s saving us effort, but in other ways, there is no place to hide. So you can’t hide behind, the first 200 reviews that you received at your hotel anymore. Where you got that, the first 200 reviews, you netted out a 4.4, and you’ve sort of been riding on that for the last like five, six years, more and more. That’s score is going to be irrelevant. Ryan Embree: That’s what I was gonna say, that I think the historical data is just gonna become less and less vital and critical. And it’s gonna be a moving type. It’s what you want. It’s absolutely something in the now what is the guest doesn’t care about what your hotel was like five years ago. When somebody at the front desk had a great, was really personable and friendly to them. They want to know what that front desk agent is doing today. What that room looks like today. So it’s going to be this living almost a living reputation. Jason Lee: And it is today. Yeah, it is now. But it’s different because, because a guest won’t research that deeply. It is today, I think it’s living today. And I think the hotels that are winning today will continue to win. Because it means that you’re doing the right thing by your guest. And I think that continues this cycle of sort of looking at the guest experience and finding your fail points and fixing ’em, finding ’em, fixing, finding and fixing is the real key. But it’s also empowering your front desk. It’s, it’s making sure that nobody leaves your property upset. It’s all of the things that we should be doing anyway that affect thhis. This is true hospitality. At its core but I think, what’s interesting about what AI is doing is it’s kind of shining a light into the, I guess, residual needs here. But I think this also gives you an unprecedented opportunity at your hotel to share this information with your staff, to, to take this back and, and really like, like dig in and make it work. The other thing I was gonna say, the other thing I was say on that, what I think on the future of guest feedback management will be the number of companies coming in an AI play today is crazy. There’s a lot of new companies that are coming in there, and there’s, and then there’s like long-term companies like Medallia, and Qualtrics and other companies that are offering AI responses inside of their platforms. And I think this all economizes that activity, but it does not remove our obligation to have authentic voice at our property and to communicate with guests that need to be communicated with. And the guests that needs to be communicated with. If you communicate well there, and I’ve said this over and over and over, if you communicate with the guest who wrote the review, well that will impact guest acquisition a hundred percent. Ryan Embree: Absolutely. Jason Lee: So the authentic voice is gonna be at a premium. The canned voice, the canned templated voice of AI, I think will end up, will end up being able to spot it. I mean, I think in some ways it, nothing changes, right. In other ways, everything changes. Ryan Embree: Yeah. Yeah. I absolutely agree with you on that, Jason. I think it is going to be a priority for hotels that truly care to rise above the sea of sameness. And as your response and the templates, you know, that was kind of that first tide, was that the templates you wanted to show your guests that you actually cared, write something that looked better than a template. Better than a thank you for your feedback. ’cause that’s what all you were getting. Now, the, the reputation response ecosystem is even more ingrained because more and more people are coming in and using AI to respond. You’re going, it’s going to be a premium to show that you’re going to be looking for those edges and places that you can show guests that you care differently from the hotel next to you. And authentic review response, caring review response is gonna be one of those. Jason Lee: But authenticity all the way around, I mean I saw this I saw a video of the CEO of Marriott talking about specifically saying, use this technology to give yourself more time with the guest. Give yourself a few extra minutes with the guest to create relationship to create authenticity in person. Ryan Embree: The general manager of the future might look closer to the general manager of the past than it does right now. Interesting times. Here to celebrate, again, 10 years of Respond and Resolve™. Congratulations, another milestone, another chapter. Congrats to you and your team, and thanks for celebrating with us here on the Suite Spot. Jason Lee: Thanks, Ryan. Ryan Embree: To join our loyalty program, be sure to subscribe and give us a five star rating on iTunes. Suite Spot is produced by Travel Media Group. Our editor is Brandon Bell, with Cover Art by Bary Gordon. I’m your host Ryan Embree, and we hope you enjoyed your stay.

Olathe Unified School District: Cisco Helps K-12 Build Secure, Resilient, AI-Ready Infrastructure, Podcast, Umphrey brings a distinctive perspective to the CTO role. Before moving into technology leadership, he was a high school history and government teacher at Olathe East High School, where he also coached football and boys golf By Doug Green “For partners, the message is simple: don't bring a cookie-cutter approach. Understand the district, understand the mission, and tailor the solution.” At Cisco Live, Technology Reseller News spoke with Joshua Umphrey, Chief Technology Officer for Olathe Unified School District in Kansas, about how one of the state's largest school districts is building a secure, resilient and AI-ready digital foundation for K-12 education. Olathe serves nearly 30,000 students across 51 schools. Like many school districts, Olathe faces enterprise-level technology challenges in a public-sector environment: protecting students and staff, keeping systems available, managing limited resources and preparing for emerging demands such as AI in education. Umphrey brings a distinctive perspective to the CTO role. Before moving into technology leadership, he was a high school history and government teacher at Olathe East High School, where he also coached football and boys golf. “Definitely an atypical route,” Umphrey said, reflecting on his move from the classroom into IT leadership. That background still shapes how he views technology. For Umphrey, the network is not simply infrastructure. It is part of the learning environment. Technology has to protect students, support teachers, keep learning moving and help the district plan for what comes next. In the podcast, Umphrey discusses how Olathe is using Cisco networking, security, Splunk, Cisco UCS, Call Manager and Cisco CX offerings to improve visibility, cybersecurity and resilience across the district. The goal is to move from reactive support to a stronger model of operational control, where IT teams have better insight into what is happening across the environment and can respond more effectively. The conversation also turns to what Cisco Partners and technology providers should understand about serving K-12. School districts are not interchangeable. They have different budgets, facilities, staffing models, security needs and educational priorities. For partners, Umphrey's message is clear: K-12 customers need practical, secure and manageable solutions that are aligned with the mission of education. The sale is not simply about products. It is about helping schools protect learning time, reduce risk and build a technology foundation that can support students, teachers and staff over the long term. Learn more about Cisco education solutions at cisco.com.

In this episode, Tessa Burg talks with Stephen Trammell, Vice President of New Business Models at Nestlé Purina North America, about what it really takes to build stronger customer relationships in a digital world.  Instead of focusing on the point of sale, Stephen explains how brands can create value across the full pet ownership journey by understanding real needs, solving real pain points and showing up in ways that feel natural and helpful.  The conversation dives into how teams can decide when to build, buy or partner, what makes a pilot worth scaling and why loyalty is a better goal than short-term conversions. This is the conversation for marketers and business leaders who want to think bigger about growth, innovation and the customer experience.  Leader Generation is hosted by Tessa Burg and brought to you by Mod Op. About Stephen Trammell: Stephen Trammell is an experienced marketing leader who bridges traditional marketing with digital innovation.  His career in consumer products spans over two decades.  He currently serves as Vice President of New Business Models at Nestlé Purina North America, leading Purina's portfolio of digital-first brands.  He has worked in marketing research, led billion-dollar brands like Fancy Feast and is currently pioneering digital platforms and apps including myPurina, Petfinder and Petivity's portfolio of IoT-connected pet care devices and health kits.  Stephen can be reached on LinkedIn. About Tessa Burg: Tessa is the Chief Technology Officer at Mod Op and Host of the Leader Generation podcast. She has led both technology and marketing teams for 15+ years. Tessa initiated and now leads Mod Op's AI/ML Pilot Team, AI Council and Innovation Pipeline. She started her career in IT and development before following her love for data and strategy into digital marketing. Tessa has held roles on both the consulting and client sides of the business for domestic and international brands, including American Greetings, Amazon, Nestlé, Anlene, Moen and many more. Tessa can be reached on LinkedIn or at Tessa.Burg@ModOp.com.

The Credit Repair Cloud State of the Union from Credit Repair Expo 2026 reveals the full roadmap, including AI-assisted disputing, the new Credit Hero Marketplace, mobile client app, and the tools built to help credit repair business owners get more clients and scale faster. Join Our FREE Start Repairing Credit Challenge: HERE Daniel Rosen takes the Credit Repair Expo stage with Keenan Jones, the new CEO of Credit Repair Cloud, and Tanmay Andhe, Chief Technology Officer, to walk through what's live in your account right now and what's coming next. From the Secure Client Access mobile app and PDF attachments to faster re-imports and CRC Billing with zero revenue share, this is everything credit repair specialists need to know about the platform that powers their business. You'll also hear how the CRC Marketing Hub gives you a built-in white-label of GoHighLevel for free, how Credit Hero Score has grown into the highest-paying credit monitoring in the industry, and what rent reporting will mean for your clients' scores. Daniel and Keenan share real numbers from the community: 20,000 Credit Heroes, 181 million point increases, and $229 million processed inside the system. Then they unveil the Credit Hero Marketplace, a new way for consumers and affiliates like mortgage brokers, realtors, and loan officers to discover and connect with you. Plus a look at AI-assisted disputing, custom client game plans, and where the platform is headed over the next year. If you run a credit repair business, this is the inside view. Tune in!  P.S. Join the #1 event to grow your credit repair business: http://creditrepairexpo.com/   Key Takeaways: 00:00 Intro  01:36 The Numbers Behind 20,000 Credit Heroes  05:26 What's Live Now. The Secure Client Access Mobile App  06:56 PDF Attachments and Faster Re-Imports  08:34 CRC Billing. Keep 100% of Your Revenue  11:06 How to Sell and Onboard Clients While You Sleep  11:52 The CRC Marketing Hub Explained  22:24 Credit Hero Score. What's New and What's Coming  26:06 Rent Reporting. A New Way to Boost Client Scores  28:28 Introducing the Credit Hero Marketplace  32:04 AI-Assisted Disputing. The Future of Credit Repair  34:42 New Awards to Celebrate Every Milestone  40:34 Final Thoughts Additional Resources: Grow Your Business Faster With CRC Billing Activate the FREE CRC Marketing Hub Get the highest payout with Credit Hero Score Join the Credit Hero Marketplace Share your feedback - we're listening Become a Credit Repair Cloud affiliate Get a free trial to Credit Repair Cloud Get my free credit repair training   How Credit Repair Millionaires Get Clients on Autopilot Make sure to subscribe so you stay up to date with our latest episodes.

In the CYME booth at NAB in Las Vegas, Matthieu Kopp, Chief Technology Officer, previews the next Peakto release, highlighting support for much larger media libraries, expanded collaboration, guest sharing, and secure on-premise access without cloud uploads. He also discusses other features such as new culling tools, improved ingest control, subclips for video workflows, and how AI agents may shape future media asset management.  Show Notes: Chapters: [0:03] Introduction from NAB 2026 [0:43] CYME previews the next Peakto release [0:58] Supporting millions of media assets and larger archives [1:23] Expanded collaboration, access rights, and web interface features [1:53] Guest sharing, downloads, comments, and local Frame.io-style workflows [2:40] Access privileges for studios, reviewers, and outside guests [3:23] Security, peer-to-peer access, and avoiding cloud uploads [4:54] Library size limits, video indexing, and upcoming benchmarks [6:06] Working with multiple libraries and large content collections [8:06] New culling tools for photographers [8:36] Improved ingest control and pausing [9:17] Streamlined interface and differences between photo and video workflows [10:05] Subclips, fast editing needs, and support for Premiere or DaVinci workflows [10:44] Different creative personas and media asset management expectations [11:57] AI agents and future workflow possibilities [12:45] Where to learn more about CYME and Peakto [13:10] Closing from NAB in Las Vegas Support:      Become a MacVoices Patron on Patreon      http://patreon.com/macvoices      Enjoy this episode? Make a one-time donation with PayPal Connect:      Web:      http://macvoices.com      Twitter:      http://www.twitter.com/chuckjoiner      http://www.twitter.com/macvoices      Mastodon:      https://mastodon.cloud/@chuckjoiner      Facebook:      http://www.facebook.com/chuck.joiner      MacVoices Page on Facebook:      http://www.facebook.com/macvoices/      MacVoices Group on Facebook:      http://www.facebook.com/groups/macvoice      LinkedIn:      https://www.linkedin.com/in/chuckjoiner/      Instagram:      https://www.instagram.com/chuckjoiner/ Subscribe:      Audio in iTunes      Video in iTunes      Subscribe manually via iTunes or any podcatcher:      Audio: http://www.macvoices.com/rss/macvoicesrss      Video: http://www.macvoices.com/rss/macvoicesvideorss

https://youtu.be/gS7aHfIiXjQ Preetha Pulusani, CEO of DeepTarget, is passionate about helping people realize their potential and leveraging technology to create meaningful business growth. After spending 25 years in corporate America and learning hard lessons from an early entrepreneurial failure, Preetha built DeepTarget into a bootstrapped fintech growth company that helps banks and credit unions acquire, engage, cross-sell, and retain account holders through advanced data analytics and intelligent marketing. In this conversation, Preetha shares the DeepTarget Bootstrap Framework, a leadership and innovation model built around five principles: Combine Pros with Fresh Graduates, Think Big but Start Small, Be Agile with a Flat Structure, Fail Quickly, and Keep a Tight Customer Feedback Loop. She explains how blending experienced professionals with emerging talent creates powerful teams, why rapid experimentation outperforms large-scale product launches, and how customer feedback should guide innovation. Preetha also discusses using data to drive growth, selling outcomes instead of technology, and building a successful SaaS company without outside funding. — Pull 5 Levers to Bootstrap Your Firm with Preetha Pulusani  Good day. Steve Preda here with the Management Blueprint, and my guest today is Preetha Pulusani, the CEO of DeepTarget, a company that helps hundreds of financial institutions increase loan demand, promote product adoption, and support intelligent marketing through advanced data mining and analytics. Preetha, welcome to the show.  Thank you, Steve. Thank you for having me. Thank you for inviting me. I’m looking forward to it.  Yeah. You have a very interesting business and very interesting profile, so I can’t wait to jump in. But let me ask you my favorite question. What is your personal ‘Why’, and how are you manifesting it in your business?  I guess you could say that my personal ‘Why’ has evolved over several years. I spent 25 years in corporate America, and that was the best business education I could have ever received. My first failure as an entrepreneur, though, added to that significantly, and that was right before I started DeepTarget. Luckily, it was a quick failure, but that doesn’t mean it was not a difficult one. And in every way, the lessons learned have come in handy today. So I believe that I’m in my final chapter of my career, so I can speak from years of experience. And my personal ‘Why’ is—it’s always been about people for me. I’ve never believed in the lone genius.  I believe that every person has some spark of genius in a different way. And I have always been inspired by pulling out that spark and weaving a tapestry of people.Share on X And that happened even in my job in corporate America, but it happens even more with my team today as an entrepreneur at DeepTarget. So it’s about empowering people to use that spark rather than focusing on something that they may not be as good at. It’s pulling out that strength and making it the collective strength of a solution, of how we serve customers, and of the business itself. Does that make sense?  Oh, yeah. This is great. I love that. My experience is that nearly none of the companies I talk to—or basically none of them, literally none of them—capitalize on the maximum talent of their team. Because it’s impossible to maximize it completely, but you can work on it, and that is wonderful.  Yeah.  So do you have a process for how you do that? Is there a mental process? Is it just an awareness? Is it a curiosity? Is it a natural thing that you do, or do you actually have a way of doing this?  So I have found that I think I read people. I think I’m intuitive in that way. And so I see myself as being the orchestrator of whatever it is, whether I’m working on today’s problem or whether I’m working on the big vision. I don’t know that it’s a process so much, but I have used it over and over again. It’s become a very natural thing for me.  So you talk about the big vision. What is that big vision?  So as a company, my focus is on making our clients successful. What that means is helping them grow their financial institutions.Share on X We work with credit unions and banks, and it’s all about growth. And we use innovation to leverage that growth for them. How do you acquire new account holders? How do you cross-sell to them? How do you communicate with them? How do you retain them? I’m a techie at heart, so it’s been about how do I leverage data? How do I leverage—today, of course—AI, kind of a combination of data and AI, to make sure that they are able to see the growth they need for their financial institutions? And that’s kind of become the mission that we have adopted for the company.  Yeah. I noticed that on your website you have this map of, I think, seven or eight different ways that you’re driving adoption and contact with people and—  It’s highly data-driven. It’s not wishy-washy. We’ve evolved from being a marketing company to a growth company. And when you take anything that’s data-driven into marketing, yeah, it’s something that people like to do. But what we like to do is use the technology to get to the human—to get to the individual. So we are helping our credit unions and banks reach individuals, understand each account holder, and understand what their financial needs are. And the only way you can do that at scale is by using technology and data. So we’ve built a platform that enables them to do that. That’s why the front end is all data, right? We can accept as much data as they want to give us so that we can do the right things to help them grow and engage their account holders.  Yeah. I like that you’re very techy, as you say—techy and data-driven. So I wonder, what is your mental model when you think about the end customers of your financial institution clients? What’s your mental model for how you innovate this process? So what are the major elements? If you had to synthesize it down to maybe three to five elements—your levers that you can pull—what are those?  Great question. So I’m going to start with the people because, for me, everything revolves around people. What I’ve been able to do is combine very seasoned pros with fresh graduates from local universities, and that has been a potent combination. Okay? That’s number one. Whether I’m talking about development, customer success, or sales, that’s been the combination that has worked for me. And as a bootstrapper, that has also helped me financially. You have a very seasoned pro that I’ve worked with for years, and you know exactly what their strengths are.  And then you put some fresh graduates under them. I’m telling you, there’s nothing better. That combination is second to none. The second thing is, I believe in thinking big, but starting small and scaling quickly. I learned that over time. There was a time when we used to have the big-bang theory of creating products.Share on X We have moved so far away from that. So think big, start small, and be agile. And as a small company, that’s a big advantage for me. We have a very flat structure. And so we’re able to have the agility we need to move markets, frankly. If you’re going to fail, fail quickly.  Have a tight customer feedback loop. And if something isn’t going to work for your customer, just abandon it. Abandon it quickly. I can’t say, in all honesty, that I’ve done that every time, but it’s always on my mind: “Should we really even pursue this?” I know we’ve had projects that we thought would be very successful, but they weren’t. But when you’ve only made a small investment, it’s easier to set it aside. “Okay, it’s not working. This is not what we need to do. Let’s move on.”  Yeah, I love that. Can you give an example where you invested in a process and really believed in it, and it turned out not to work, and then you had to pivot from it?  So the way we help banks and credit unions engage and cross-sell to their account holders is primarily through digital banking. We put up very personalized offers using data in the digital banking environment and use that real estate very effectively. It works like a charm. That’s what we do today. We did get a little sidetracked by expanding that into email, and we didn’t see the kind of growth we expected. So we tried to understand that. We did kind of an autopsy. And the difference is that when you log into digital banking, you’re being served something. The difference with email is that you’re pushing something out. It has its uses, for sure, but the particular aspect of what we had done in the product didn’t take off like we expected. So we just said, “Okay, let’s do more of what we can do within the digital banking environment.”  But that works for farming existing customers of the banks, right? Do you also help banks acquire new customers?  Yes. And that’s where email works, by the way. And so does direct mail, and so do digital ads. When you’re cross-selling to existing account holders, you have a lot of information about them. For example, if they rent a home, you would never give them a HELOC offer, right? But on the other hand, what we’re doing for new account acquisition is still using data. We’re looking at who the most profitable customers are that your credit union or bank has, and using that as the model to find more likely customers within a particular radius of their branches. So we are still using data, but in a different way and using different channels to reach them versus digital banking.  That’s fascinating. So what drives growth in your business?  Well, if you had asked me that question 10 years ago, I would have said innovation drives growth. But what we have found and learned over time is that innovation is an engine.Share on X Innovation, in a way, actually causes friction because when you innovate, you’re creating something new. So you first have to go out and educate the market. You have to make them understand that there’s a new way of doing things, and not everybody is open to change.  So if I go talk to a marketing professional and say, “Hey, here’s a new way of doing things. We’re using data.” I put myself in the place of that marketing person who is already constrained by bandwidth, who is already doing so many things, saying, “You’re bringing another new tool for me to learn and use? For what purpose?” While innovation is the engine, what we have learned is not to focus on the innovation, but to focus on the impact. And we do that by really working hard to get into the C-suite. So we are talking to the CEO, the COO, the Chief Digital Officer, or the Chief Technology Officer of these banks and credit unions, helping them understand the outcomes. What is it we do? We acquire new customers. We cross-sell to existing customers. We help you retain them. I receive these direct-mail solicitations from mega banks like Chase and Wells Fargo.  They’re paying me $900, $1,500 to open a checking account. It’s expensive to acquire new accounts. That’s just an example, right? So we are helping you grow through new account acquisition, but we also have a whole playbook for how you retain those new accounts that you acquire. So when you talk at the C-suite level, all of a sudden they’re not seeing a tool. What they’re seeing is an outcome. “How soon can we see results?” is the question we get asked. So we grow through a different way of selling what we do to these institutions.  So people don’t care how you achieve the result. They just want you to talk about the result?  Exactly. Especially the CEO. I mean, they don’t really care. They do care about things like data privacy, and we’ve addressed all of that. We’ve been doing this business for so long that data security is table stakes. But they care less about how you do it and more about why. So we have to talk to the individuals who care about the why rather than the how, although the how plays such a big part in building a business, right? But that’s what we focus on.  That’s behind the wall. That’s your problem, basically.  That’s right. That’s the secret sauce. We used to take great pains to explain the secret sauce at one point in time, but not anymore.  That’s interesting. So why do they listen to you? I mean, why do they believe that you can get these results? Do you show them testimonials, or how do you prove it?  We have over 200 customers now—customer contracts. It’s actually closer to 300. So we have a lot of testimonials and references that we can show them. We also let them know that there are barriers to using software like ours, such as, “Do I need to have somebody operate the software?” No, because part of what we offer is a managed service. We will operate the software for you using your branding and everything else that you have. So we’ve kind of removed all of the barriers. The biggest barrier today is creating awareness in the broader market, because this is a huge market.  And on my bootstrapping budget, I have to make sure people know that such a solution exists. What we find is that once we reach the decision-maker, it’s a fairly straightforward sale. I would say that if I’m constrained by anything when it comes to growth, it’s because I’m a bootstrapper. I watch every penny carefully, and I have built the company funded entirely by revenue. And one of these days that’s not going to be enough. But so far, so good. Yeah. Okay. So basically you create broader awareness of your products. You have all these testimonials and references. When you get in front of these decision-makers, you talk about the outcome and show them the results you can get.  And we have direct sales, right? I mean, we do call on, we have a couple of people. All they do is work the phones, emails, and LinkedIn to get us meetings in front of the right people. You know, also, Steve, in this day and age of everything digital, what we have found with banks and credit unions is that first important meeting with the CEO—we’re finding that doing it in person makes a huge difference. So that’s another thing that we do.  That’s interesting. So does that limit you geographically?  We’re having so much success with that model that it only helps us. More revenue means I can invest more in sales. So we are limited to the United States. We have customers on both coasts, a pretty good map of customers on both coasts, and in the Midwest. And there are some blank spaces, and we’re trying to address those blank spaces.  So you actually have people fly all over the country to meet with CEOs?  Yes. And it’s making a big difference. This is a change that we made not too far back. I would say maybe about 18 months ago or so, and it’s made a big difference for growth.  That is so interesting because after the pandemic, a lot of companies kept doing video sales calls.  As did we. As did we.  As probably you did as well. But the assumption was that there’s no point in traveling. It’s an extra expense and doesn’t make a huge difference. But you’re saying it’s the opposite—that it does.  Yes, it makes a huge difference. You’re talking to the CEO of a bank. Banks still have a more traditional generation of leaders. Even I didn’t believe it when I was first sold on this whole concept, but I’ve become a believer now. That meeting—the CEO not only is in the room with you, but brings in his or her key executives to talk to you. When you’ve made the trip all the way to Sacramento, they’re going to do that, right? So it’s made a difference.  So there’s a reciprocity involved. They see that you’re making the trip. Okay, then we might as well put more into it. And it’s kind of a self-fulfilling process.  And by the way, when you have more people in the room, you get more objections, but you’re able to address those in person. Yeah. Even if you have a video call with the CEO, if the CEO goes and talks to the CTO and brings up the objection, “You really need to worry about these guys and their data security,” we never hear about that. We just hear silence. We don’t know what’s going on behind the scenes. So you get that opportunity to address all of that kind of in person. And I think it actually works out more cost-effectively, surprisingly. Yeah, as long as those are resulting in deals.  Yes. So maybe that’s an inside thing, but I’m just wondering, what is the upside of something like that? If you convert one of the CEOs and they start using the system—maybe that’s a business secret—but what is the value of that conversion? Let’s say the 12-month value of that conversion that makes you want to do that trip.  So let me give you an example. We sell annual subscriptions with five-year terms. That’s a big deal, right? And when we sell five-year terms, it can become very significant. So we price based on the asset size of the financial institution because that kind of determines how large they are, how many branches they have, and how many account holders they have. So let’s take an institution that’s, say, a billion dollars. I’m just going to give you some rough numbers, right? For a five-year contract, you’re talking about $300,000 or so.  Okay. That makes sense. It’s definitely worth the trip.  Yes, it’s worth the trip.  Yeah.  The other way to have that personal interaction, which we have found to be very effective, is conferences—focused conferences. Many of these banks and credit unions have state leagues, regional leagues, or certain technology-focused groups that meet. And those are kind of the best venues to do our prospecting.  And then do you sponsor these conferences?  Well, we do. We’re very selective, but we have booths, and in addition to that, we may do some other sponsorships. Yeah.  Yeah. That’s great. So switching gears here, I’m really curious. What is something that you’re actively trying to figure out in your business? So if you had a magic wand and you could wave it, what would you want to fix in the next 12 months?  I’ve kind of told you that I’ve been a bootstrapper, and I’ve been a bootstrapper very intentionally. Because one of the things that I said I would do is that I wouldn’t be so stubborn as to never take any outside capital. But the thing that I wanted to figure out before taking external capital was what would give me a multiplier effect. So if I took a dollar in, how would I be able to multiply that? And I’m getting very close to figuring that out on the sales and marketing side. So if I had more dollars, and if I have a sales formula that I know works—that I’m confident works—then I should be able to take that formula, add those dollars, and simply add salespeople, right, to grow.  Scale it up, yeah.  So that’s kind of been the biggest issue I’ve had for the past, say, five years. But I would say that over the past 12 to 18 months, a lot of that has become clearer to me. And so I think I’m getting close to having that solved—to having that formula where I can say, “Okay, if I put in more dollars, I’m going to get X return.”  Yeah. Some people call this the coin-operated marketing and sales system. You keep dropping the coin and—  Yeah. Yeah. It’s taken me years to figure it out. I spent a lot of my early years at the company building a very robust technology platform because without that, everything else becomes secondary. And then I had this focus on, how do I get sales and marketing? And I’ve tried many things, and they haven’t necessarily worked, right? I’ve built up a customer base by slogging over time, but then you want that formula if you want to throw money at it.  Yeah. And that’s where I think I’m getting closer to getting there.  Yeah. And then marketing media is changing all the time. Different platforms come and go. Then you have different advertising formulas, and they burn out. So it’s actually difficult to stabilize it and make something that’s permanently coin-operated, so to speak. Yeah. And when we say everything is data-driven, it’s not just on the front end that everything is data-driven. We are able to tell the credit union or bank how many products we actually sold. What loans did you sell? How many auto loans? How many mortgages? How many HELOCs? How many credit cards? How many deposit accounts did you open each month that were influenced by our campaigns? We’re able to go back and tell them that. And what are the new balances you generated as a result of that? So it’s not about impressions and clicks. On the back end, we actually give them very deep data analytics so they can see, “This is the revenue I generated last month, and these are the new balances I generated last month.” And so that makes a difference, too.  Yeah. I saw on your website that many customers get a 500% ROI on their investment.  Yeah. Which only says that I’m charging them too little.  Yeah. Yeah.  No, but I mean, if you look at the balances and how they measure, we’re almost afraid to put the actual numbers out there. But we show them a growth grid that shows, month by month, here’s what you made using these campaigns. We can even show them what happens when they turn off the campaigns and what the impact is.  So in terms of bootstrapping, is that a strategy? Let’s say you figure out your scalable sales formula. Would you then go raise money, or would you still want to bootstrap?  If the revenue that I’m generating can be used toward growth, I won’t have to go raise money. But I won’t be so stubborn and silly that I wouldn’t take outside capital. I get calls all the time from investment bankers and capital firms. In fact, I was talking to one just yesterday, and I said, “I’m probably getting a bit closer to being open to capital. Give me another six months. By the end of the year, I should know.” So yes,  I would raise money if I had that sales formula, if I knew for sure. And I think part of this, Steve, is because I talked about my first failure as an entrepreneur. It was a very quick failure, but it was a hard one because I had taken money from friends and family, and it was used up, and they didn’t get much in return. When I had to shut down that company, I actually gave them shares in this company. I guess I got a bit burned, so I’m more resistant to taking outside capital until I’ve figured out what the solution is. But I think I’m getting very close. You get to a point where it’s silly not to take capital.  Yeah, because someone might copy it. You figure out a formula, and someone might copy it. Then they put more money behind it, they dominate the market, and you lose. Yeah. So that’s the only concern.  Yeah.  Yeah. If there are listeners who hear this and say, “Wow, I’d like to learn more because I’m involved with a financial institution, and we need to improve our sales, get more customers, and upsell more customers,” where can they find out more, and how can they reach you?  So our website has, I think, a wealth of information. So certainly they can go to our website just to learn more about the solution. They can contact us at success@deeptarget.com. That’s probably the easiest way to get a deeper dive into what we do and have that one-on-one meeting. And I think that’s the best way to learn more. Whether you’re interested in going forward or not, that’s the best way to learn.  Yeah. Okay. Well, definitely. I checked out the website, and it’s pretty informative. You get good visuals of what Preetha’s team is doing, and it’s pretty complex, I would say. There’s a lot of nuance to it, so I found it fascinating. So definitely check out deeptarget.com if you’d like to learn more. Preetha is also on LinkedIn, and you can email them at success@deeptarget.com. Any famous last words for the audience? Something that would help an entrepreneur who wants to bootstrap their business? What would you recommend they do?  I think starting a business is no easy feat, and I don’t believe in overnight success. It’s a journey. It’s been one of the most inspiring and interesting journeys, and probably the greatest learning journey, that I’ve been through. So I think you shouldn’t focus just on the end result or overnight success. Instead, come for the journey.  Yeah. You have to love the journey in order to reach the destination, right?  It’s tough, right? Yeah. It can be tough at times, but then you reach a point where it’s just the best thing.  Yeah. Well, that’s great inspiration for the founders listening to this. And if you enjoyed the podcast, then definitely follow us on LinkedIn, subscribe on YouTube, and give us a review on Apple Podcasts. And Preetha, thanks for coming. That was an eye-opening discussion. I don’t recall having many bootstrapper tech companies on the show, so this is definitely a new element for us and a really good perspective. So thanks for coming, and thank you for listening. Important Links: Preetha's LinkedIn Preetha's website Preetha's email: success@deeptarget.com

In the CYME booth at NAB in Las Vegas, Matthieu Kopp, Chief Technology Officer, previews the next Peakto release, highlighting support for much larger media libraries, expanded collaboration, guest sharing, and secure on-premise access without cloud uploads. He also discusses other features such as new culling tools, improved ingest control, subclips for video workflows, and how AI agents may shape future media asset management.  Show Notes: Chapters: 0:03] Introduction from NAB 2026 [0:43] CYME previews the next Peakto release [0:58] Supporting millions of media assets and larger archives [1:23] Expanded collaboration, access rights, and web interface features [1:53] Guest sharing, downloads, comments, and local Frame.io-style workflows [2:40] Access privileges for studios, reviewers, and outside guests [3:23] Security, peer-to-peer access, and avoiding cloud uploads [4:54] Library size limits, video indexing, and upcoming benchmarks [6:06] Working with multiple libraries and large content collections [8:06] New culling tools for photographers [8:36] Improved ingest control and pausing [9:17] Streamlined interface and differences between photo and video workflows [10:05] Subclips, fast editing needs, and support for Premiere or DaVinci workflows [10:44] Different creative personas and media asset management expectations [11:57] AI agents and future workflow possibilities [12:45] Where to learn more about CYME and Peakto [13:10] Closing from NAB in Las Vegas Support: Become a MacVoices Patron on Patreon      http://patreon.com/macvoices      Enjoy this episode? Make a one-time donation with PayPal Connect: Web:      http://macvoices.com Twitter: http://www.twitter.com/chuckjoiner      http://www.twitter.com/macvoices Mastodon:      https://mastodon.cloud/@chuckjoiner Facebook:      http://www.facebook.com/chuck.joiner MacVoices Page on Facebook:      http://www.facebook.com/macvoices/ MacVoices Group on Facebook:      http://www.facebook.com/groups/macvoice LinkedIn:      https://www.linkedin.com/in/chuckjoiner/ Instagram:      https://www.instagram.com/chuckjoiner/ Subscribe:      Audio in iTunes      Video in iTunes      Subscribe manually via iTunes or any podcatcher: Audio: http://www.macvoices.com/rss/macvoicesrss      Video: http://www.macvoices.com/rss/macvoicesvideorss

Weave Brings AI Into the Front Office for Healthcare Practices, Podcast, Rather than replacing the human relationship between patient and provider, AI can help practices respond faster, capture missed opportunities and manage routine communications more efficiently. The result is a better experience for patients and a more sustainable operating model for busy practices By Doug Green “Healthcare always has this very interesting intersection between human care and technology,” says Doug Green, Publisher of Technology Reseller News, opening a conversation with Abhi Sharma, Chief Technology Officer at Weave, about how AI is changing the way small and medium-sized healthcare practices communicate with patients. In this Technology Reseller News podcast, Sharma outlines how Weave is helping healthcare providers use AI to reduce administrative burden, improve responsiveness and create a more connected patient experience. For many practices, the front office remains one of the most pressured parts of the business, balancing phone calls, appointment reminders, payments, follow-ups and patient questions while also trying to deliver a personal experience. Sharma explains that Weave's approach is focused on practical AI that supports the daily workflow of healthcare offices. Rather than replacing the human relationship between patient and provider, AI can help practices respond faster, capture missed opportunities and manage routine communications more efficiently. The result is a better experience for patients and a more sustainable operating model for busy practices. The conversation also explores how AI can help healthcare organizations modernize without losing the personal touch that matters so much in care delivery. For technology resellers and service providers, the discussion points to a growing opportunity around communications, automation and workflow tools designed specifically for vertical markets such as dental, medical, veterinary and other appointment-based healthcare services. Learn more at https://www.getweave.com/

Geothermal energy has long been seen as a promising, but challenging, clean energy resource. Unlike wind or solar, geothermal requires finding heat hidden deep underground, often with little surface indication of where to look. Joel Edwards, co-founder and Chief Technology Officer of Zanskar, joins Climate Rising to explain how advances in geoscience, data science, and machine learning are transforming geothermal exploration. By combining publicly available geologic data with modern modeling techniques, Zanskar is working to reduce the risk and cost of finding new geothermal resources. The conversation explores how geothermal systems work, why exploration has historically been challenging, and how Zanskar's approach is enabling “blind discoveries”—finding viable geothermal resources that lack surface expressions such as hot springs or geysers. Joel also discusses the economics of geothermal, the role of data centers as a potential catalyst for growth, and what it will take to scale the industry.

In this podcast episode, Dr. Jonathan H. Westover talks with Shea Belsky about neurodiversity in the workplace.Shea Belsky is an autistic self-advocate. He is a Tech Lead II at HubSpot, and the former Chief Technology Officer of Mentra. Shea brings several unique perspectives to the discussion on neurodiversity: He is the manager of neurodivergent & neurotypical employees, has reported to neurodivergent & neurotypical managers, and has advocated for the needs and wellbeing of all who seek to be heard and understood in the workplace. Shea has championed neurodiversity for organizations like Novartis, the College Autism Summit, Northeastern University, in addition to being featured in Forbes and the New York Post. He also hosts his own podcast, Autistic Techie, empowering neurodivergent self advocates to feel more confident in the workplace and ready to take on the day to day challenges of their job. He's excited to share his perspectives on neurodiversity and how to be a meaningful ally and advocate!https://www.amazon.com/Brainstorm-Guide-Neurodivergent-Talent-Future/dp/1394388772https://autistic-techie.com/https://www.linkedin.com/in/sheabelsky/See Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

In this episode, Keith speaks with Anthony Vinci, CEO of VICO, about how AI is changing decision-making for founders, investors, governments, and financial institutions.Anthony's background spans intelligence, national security, investing, and artificial intelligence. Before founding VICO, he worked at Cerberus Capital Management, Bridgewater Associates, and served as the first Chief Technology Officer at the National Geospatial-Intelligence Agency.The conversation explores how AI is moving beyond chatbots and becoming a real decision-making layer for businesses.Anthony explains why the future is not about replacing human judgment, but improving it through better frameworks, probability forecasting, and scenario planning.They discuss:Why AI alone is not enough without human judgmentHow VICO combines LLMs with mathematical forecastingThe difference between information and decision intelligenceWhy founders need better frameworks for uncertaintyHow AI is reshaping risk assessment and strategic planningThe future of building companies in the AI eraThis episode is a thoughtful look at what happens when AI moves from generating answers to helping people make better decisions.Connect with Anthony Vinci: Website: https://vico.io/ LinkedIn: https://www.linkedin.com/in/anthony-vinci/Book: https://www.anthonyvinci.com/ Sponsor Info: We are strategic business advisors with decades of leadership experience and a proven track record of driving businesses' growth. We specialize in creating custom-tailored strategies to introduce your company, drive growth, build leadership teams, and ensure companies implement appropriate compensation programs. Our mission is to utilize our expansive network to benefit your company https://www.compass-strategic-advisors.com/ Subscribe for more founder insights and hit the bell for notifications! Follow us on our channels for exclusive startup content and behind-the-scenes insights from interviews like this one. Spotify: https://open.spotify.com/show/3cFpLXfYvcUsxvsT9MwyAD?si=f5a14e779777487d Apple Podcasts: https://podcasts.apple.com/ca/podcast/liftoff-with-keith-newman/id1560219589 Substack: https://keithnewman.substack.com/ Newman Media Studios: https://newmanmediastudios.com/ LinkedIn: https://www.linkedin.com/company/liftoffwithkeith For sponsorship inquiries, please contact: sponsorships@wherewithstudio.com#ArtificialIntelligence #AI #DecisionMaking #Leadership #Entrepreneurship #RiskManagement #FounderMindset #MachineLearning #StartupGrowth #FutureOfWork