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The Digital Executive

Coruzant Technologies

Best 10-minute, daily tech podcast on emerging technologies, hundreds of Silicon Valley CEOs, Influencers and Celebrities. Hosted by technology executive and creator of Coruzant Technologies.

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Yesterday · 21 min
Daniel Ishag: Who's Paying Your AI Agent's Bills? | Ep 1324
In this episode of The Digital Executive Podcast, host Brian Thomas sits down with Daniel Ishag, Chief Commercial Officer at Bakkt, to explore why the financial infrastructure the world runs on was never designed for the speed, availability, or autonomy that the agentic AI era demands — and what it takes to build the layer that bridges the two. Daniel opens with a career defined by solving old problems through new frameworks: founding Europe's first performance-based ad network and merging it for $183 million, building water technology for underserved utility markets, and moving into digital assets out of fascination with what programmable money could unlock. He explains what Bakkt actually does in concrete terms — owning the licenses, rails, and infrastructure to move stablecoin-denominated value globally, twenty-four hours a day, in minutes rather than days. The use cases he walks through are grounding: a US textile manufacturer paying Vietnamese suppliers instantly and earning four to five percent discounts for speed, a commodities trader cutting days off a vessel's turnaround by eliminating weekend payment delays, a shipping company solving demurrage and bunkering costs through near-instant settlement. The conversation then turns to the bigger structural shift: as AI agents proliferate and begin executing financial transactions autonomously, legacy banking systems built for human-initiated, business-hours-only, correspondent-bank-dependent transfers simply cannot keep up. Bakkt, through its acquisition of DTR, positions itself as the orchestration layer between traditional finance and the agentic economy — not competing with banks, but sitting between them and the new infrastructure the moment requires. Daniel closes with intellectual honesty about the future: he does not know where this goes in ten years, but he is certain that know-your-agent frameworks will need to exist before autonomous spending at scale can be trusted, and that regulations will eventually catch up — because they always do, once someone finds a way to abuse what is new. If you liked what you heard today, please leave us a review - Apple or Spotify. Learn more about your ad choices. Visit megaphone.fm/adchoices
Thursday · 19 min
Mike Lucas: The Science of Staying Active Longer | Ep 1323
In this episode of The Digital Executive Podcast, Brian Thomas sits down with Mike Lucas, co-founder of North Performance, to explore the growing world of performance longevity. Mike shares how decades of surfing, snowboarding, injuries, and recovery led him to build a science-backed wellness brand designed to help active people perform at their best for longer. He discusses simplifying daily supplementation, combining clinical expertise with elite athlete insights, and how wearables, diagnostics, and personalized nutrition could shape the future of recovery and healthy aging. If you liked what you heard today, please leave us a review - Apple or Spotify. Learn more about your ad choices. Visit megaphone.fm/adchoices
Thursday · 20 min
Mike Link: AI That Detects Falls Before They Happen | Ep 1322
In this episode of The Digital Executive Podcast, host Brian Thomas sits down with Mike Link, Chief Operating Officer at KamiVision, to explore how computer vision and AI are quietly transforming the way seniors are protected — not just in care facilities, but at home. Mike opens with a career path that wound through real estate, preventative health work in India, and go-to-market consulting before landing at KamiVision, where a personal connection to aging and loss made the mission feel like more than a business opportunity. He breaks down what makes Kami Care's fall detection different from the rest of the market: a three-layer system that combines edge-based AI detection, cloud filtering, and human verification using blurred, encrypted footage — achieving 99.5% accuracy while protecting the dignity and privacy of the people it monitors. The human-in-the-loop step is not just about catching false positives, it feeds a continuous training loop that makes the AI progressively more accurate over time. The more interesting conversation, though, is what happens before a fall. Mike explains how pre-fall clips, behavioral patterns, time-of-day data, and gait analysis give caregivers and families early warning signals — the kind that make it possible to intervene with a step stool, a schedule change, or physical therapy before a hip fracture ends someone's independence. He closes with a candid look at where senior care technology is heading: toward a world where visual sensors, wearables, vitals, and health records combine into a continuous real-time picture that functions like a remote doctor making daily inferences — and a frank acknowledgment that the biggest obstacle to that future is not the technology, but the privacy and security frameworks that will need to earn people's trust before they let it into their homes. If you liked what you heard today, please leave us a review - Apple or Spotify. Learn more about your ad choices. Visit megaphone.fm/adchoices
Wednesday · 19 min
Jason Hishmeh: AI Without Security Is Just a Faster Way to Fail | Ep 1321
In this episode of The Digital Executive Podcast, host Brian Thomas sits down with Jason Hishmeh, co-founder of Variance and Aequit, to explore what it actually looks like to deploy AI inside a business responsibly — with security and compliance built in from the start rather than added as an afterthought. Jason opens with an origin story that begins in a corporate accounting department where nobody had a computer, and traces twenty-five years of compounding curiosity through ERP systems, infrastructure, application development, cybersecurity, and eventually AI entrepreneurship. The through line is simple: raise your hand for the interesting problem, figure it out, and make sure the business value is real. He then breaks down why AIOps embeds agents inside tools companies already use rather than asking them to adopt another platform — because application fatigue is real, eighty-eight percent of companies use AI regularly but only about six percent get measurable results, and the fastest path to ROI is automating the repetitive, boring work people already do inside the systems they already know. He addresses the security blind spots directly: employees are giving autonomous AI agents access to production systems without guardrails, sometimes without their employers even knowing it, through shadow IT and browser plugins that leverage the employee's own privileged access. His prescription is to onboard AI agents the way you onboard people — define what licenses, permissions, and access they need, log everything, and make sure a human is always accountable for what the agent does. He closes with a five-year vision where AI is no longer a tool you open and prompt, but something woven into every layer of how a business understands itself, plans, and serves customers — and warns that the companies jumping on every new AI subscription without a strategy will fall behind the ones going deep with a focused set of tools and building real integration from the ground up. If you liked what you heard today, please leave us a review - Apple or Spotify. Learn more about your ad choices. Visit megaphone.fm/adchoices
Wednesday · 22 min
Luis Derechin: Only 1 in 4 Offshore Hires Succeeds. Here's Why. | Ep 1320
In this episode of The Digital Executive Podcast, host Brian Thomas sits down with Luis Derechin, founder and CEO of Nir-Yu and author of The Offshore Team Death Trap, to break down why international hiring fails so consistently — and what it actually takes to get it right. Luis opens with the origin story: a young entrepreneur who raised venture capital for Mexico's first US-funded tech startup, quickly realized American salaries would burn through the runway, and turned to a blended US-Latin America team that cut costs by seventy to eighty percent without sacrificing quality. That necessity became a fourteen-year competitive advantage and, after the company's acquisition, a consulting practice where CEOs kept calling with the same problem — their offshore teams weren't working. What Luis found through those engagements became the seven offshore team death traps: talent mirage, cultural chasm, hidden cost spike, management quicksand, retention revolving door, communication fog, and quality erosion — patterns that explain why only one in four offshore hiring efforts actually succeeds. The antidote is his Remote Intelligence Framework, a six-part acronym that covers rigorous talent selection, expert onboarding and integration, managed support services, optimized team performance, transparent cost-plus pricing, and enhanced scalability — the playbook behind his ninety-five percent success rate and average two-year client retention. He closes with a counterintuitive take on AI's impact: far from making remote teams obsolete, AI is raising the bar on the quality of talent companies need, which means the best candidates are increasingly distributed around the world — in Argentina, Uganda, Israel — and the companies willing to fish outside their local pond will be the ones that win. If you liked what you heard today, please leave us a review - Apple or Spotify. Learn more about your ad choices. Visit megaphone.fm/adchoices
September 15 · 17 min
Vanessa Slowey: If You Need It, You Should Be Able to Get It | Ep 1319
In this episode of The Digital Executive Podcast, host Brian Thomas sits down with Vanessa Slowey, President and CEO of TelyRx, to explore what happens when a lifetime of lessons about access, infrastructure, and trust finally converge in one mission. Vanessa opens with a story that begins above a small-town pharmacy in Sligo, Ireland, where her father's philosophy was simple: if someone needs medication, you figure out how to get it to them. That instinct followed her through a career building mobile networks across some of the world's most challenging terrain — Papua New Guinea, the Caribbean, 27 markets across Latin America — before bringing her back to healthcare and TelyRx. She draws a sharp contrast between the two industries: in telecoms, the barrier to access was physical and required building infrastructure from scratch; in US healthcare, the infrastructure already exists, but patients still face enormous friction navigating providers, prescriptions, pharmacies, insurance, and delivery. The barrier is friction, not geography, and the solution is the same: build the infrastructure so the patient does not have to connect all the pieces themselves. She is candid about where TelyRx deliberately limits its scope — non-controlled, FDA-approved, everyday medications like inhalers — because clinical integrity and convenience are not in tension when the model is designed correctly, and trust is built by knowing exactly what the platform is and is not for. She closes with a vision of digital health where technology works invisibly in the background and patients experience something deceptively simple: they needed care, they could access it, they understood what it would cost, and they got their medication. That is the standard. And with roughly seventy percent of TelyRx patients returning, she argues the market is already voting for it. If you liked what you heard today, please leave us a review - Apple or Spotify. Learn more about your ad choices. Visit megaphone.fm/adchoices
September 15 · 18 min
Justin & Travis Maderia: Two Brothers vs. the Seafood Mafia | Ep 1318
In this episode of The Digital Executive Podcast, host Brian Thomas sits down with Justin and Travis Maderia, fourth-generation lobstermen and co-founders of Lobster Boys, for a conversation about resilience, integrity, and what it actually takes to fight a broken food system from the bottom up. Justin opens with a story that is equal parts loss and determination — watching his family's fishery collapse over 25 years due to poor regulation, pesticide use, and unsustainable practices, then rebuilding by fishing the waters of Grand Manan, Canada, where better regulations produced visibly better lobster. What started as bringing premium hard-shell lobsters across the border to their existing customer base grew fast — fast enough that they became one of the largest buyers in Canada in just three years, which put them squarely in the crosshairs of the powerful wholesale networks they now call the mafia. Travis picks up the thread, describing the pressure campaign that followed: their boat burned at the dock, banks squeezed, and ultimately a forced bankruptcy right before the start of a season. They fought through it, and what emerged on the other side was a direct-to-consumer model built on something the industry rarely offers — full traceability. Justin explains how Lobster Boys grades each fisherman's catch separately, tracks every lobster from hauling to delivery, and gives individual grade reports back to the fishermen, so the person catching the best quality product is actually compensated accordingly. Travis closes with the bigger picture: a food system that has drifted dangerously far from the farm-to-plate principles that kept Americans healthy, and a call to get back to buying directly from farmers and fishermen before corporate middlemen and compromised supply chains do any more damage. Lobster Boys is starting with lobster — but the mission is much larger than that. If you liked what you heard today, please leave us a review - Apple or Spotify. Learn more about your ad choices. Visit megaphone.fm/adchoices
September 14 · 19 min
Tetiana Aleksandrova: No Surgery, No Keyboard — Just Your Brain | Ep 1317
In this episode of The Digital Executive Podcast, host Brian Thomas sits down with Tatiana Aleksandrova, co-founder and CEO of Subsense, to explore one of the most ambitious bets in deep tech — a non-surgical brain-computer interface that could eventually allow humans to communicate directly with AI, each other, and the digital world using nothing but thought. Tatiana opens by explaining why she founded her second BCI company: her first taught her that fully non-invasive approaches lack the signal precision needed for truly transformative applications, while surgical implants will never scale to healthy everyday users. The answer, she and her team concluded after a year of challenging scientists from chemistry, physics, and engineering to prove them wrong, was nanoparticles delivered intranasally through the olfactory nerve — precise enough to read and stimulate the brain, but requiring no surgery and no permanent hardware. Critically, the system only activates when the user wears the external device, meaning consent is built into the design: take off the hat, and the interface is off. Tatiana is direct about the ethical stakes — access to your brain belongs only to you, not to Subsense, not to employers, not to advertisers, not to the military — and argues that consent in BCI cannot be a one-time signature but must be continuous and revocable. She closes with a vision of three horizons: first, navigating the digital world by thought rather than keyboard or voice; then, seamless integration with AI so that any question is answered instantly without a prompt; and finally, human-to-human communication that transmits not just words but emotions and sensations — a world where knowledge becomes a commodity and empathy becomes transmittable. Her condition for that future to be one people actually want is unchanged: safety first, data protected, and the ability to turn it off whenever you choose. If you liked what you heard today, please leave us a review - Apple or Spotify. Learn more about your ad choices. Visit megaphone.fm/adchoices
September 10 · 20 min
Jerry Zhang: Your AI Agents Are Silently Failing. Here's How to Fix That. | Ep 1316
In this episode of The Digital Executive Podcast, host Brian Thomas sits down with Jerry Zhang, co-founder of Lemma, to explore one of the most underappreciated problems in enterprise AI deployment — agents that appear to work but silently degrade the moment they hit real-world production. Jerry opens with the founding story: two college friends who met as freshmen at USC's startup incubator, went off separately to build AI agents at companies on opposite ends of the industry — healthcare and chip design — and came back together after realizing they had been solving the exact same frustrating problem. The pain point that crystallized Lemma came from co-founder Cole's internship experience: spending an entire summer manually throwing prompts into Claude over and over again until an eval set passed, a process so repetitive it begged to be automated. That frustration became the first internal prototype of Lemma, built inside the company where Cole was interning. Jerry then describes the critical lesson from their earliest customers: engineers do not care about finding failures, they care about resolving them. The first version of Lemma surfaced issues well but just gave engineers more homework, which they resented. The breakthrough was closing the loop — not just detecting the root cause but automatically proposing a fix and opening a pull request, so the engineer becomes the reviewer rather than the detective. He closes with Lemma's larger vision: deploy once, learn forever. Today's agents do not just plateau in production — they actively degrade through prompt drift and model drift. Lemma is building the observability and self-identification layer that becomes the foundation for truly self-improving agents, where the system can eventually recognize where it is failing, pull the relevant context, and fix itself with minimal human intervention. If you liked what you heard today, please leave us a review - Apple or Spotify. Learn more about your ad choices. Visit megaphone.fm/adchoices
September 10 · 17 min
Shenbo Xu: Your AI Is Confident. That Doesn't Mean It's Right | Ep 1315
In this episode of The Digital Executive Podcast, host Brian Thomas sits down with Shenbo Xu, MIT PhD and co-founder of Kapnova, to make a distinction that most business leaders have heard but rarely internalized — and that costs companies millions when they get it wrong. Shenbo opens by tracing his path from MIT's AI lab through quantitative research at Point72 and foundational model training at Scale AI, explaining that each stop sharpened the same core insight: prediction tells you what will happen, but causal inference tells you what happens if you actually do something about it. Those are fundamentally different questions, and almost every AI system in deployment today is only built to answer the first one. He illustrates the danger with two vivid examples. First, a retail CEO who copied Apple's no-discount strategy without understanding that Apple's customers and his own were nothing alike — the sales crashed, and he lost his job. Second, eBay's discovery that years of spending on branded search ads — the ones triggered when someone literally types "eBay" into Google — produced almost no incremental value, because those customers were already going to the site anyway. The model said the ads were working. The experiment proved otherwise. This, Shenbo argues, is the gap that lives inside almost every ROAS number ever reported: prediction models get credit for outcomes that would have happened regardless. Causal AI builds an actual model of what drives what, so executives can ask what will happen if we do this before committing the budget. He closes with a forward-looking take on where causal reasoning is heading — pointing to recent DeepMind research suggesting that any AI capable of generalizing across new environments must have learned something causal — and argues that the next generation of decision-making tools will be built on mechanism, not just pattern, making them more honest, more durable, and genuinely trustworthy when the world changes. If you liked what you heard today, please leave us a review - Apple or Spotify. Learn more about your ad choices. Visit megaphone.fm/adchoices
September 8 · 19 min
Katrina Purcell: Great Strategy Means Nothing Without Execution | Ep 1314
In this episode of The Digital Executive Podcast, host Brian Thomas sits down with Katrina Purcell, growth operations consultant and former chief of staff, to explore the messy, often overlooked work that actually makes scaling companies succeed. Katrina opens with a career that wound through media, project management, and an executive MBA before landing her in the chief of staff role at IAS — where guiding a company through its IPO taught her that her real gift was bringing people along for the ride, not just building the strategy. She explains why she took that skill set independent: companies only IPO once, but dozens of founders need exactly this kind of help right now. She then tackles the most common failure mode she sees in leadership: keeping strategy behind closed doors until it is polished, then rolling it out to a team that never had a chance to shape it and therefore never truly owns it. Her prescription is consistent — involve people early, listen to the perspectives that complicate your plan, and recognize that your business has grown beyond just you the moment you hired a team. On goal-setting, she is equally direct: OKRs fail not because the framework is wrong but because companies copy what Amazon does today without remembering that Amazon did not start there, and because nobody owns the process or adjusts it as the company grows. She closes with a sharp observation about AI and operations — automation sounds appealing until you realize most teams have never documented their processes well enough for a machine to follow them. Her prediction is that AI will actually force the documentation discipline that most startups have always skipped, and that the founders who build durable companies will be the ones who invest in that foundation before they try to automate on top of it. If you liked what you heard today, please leave us a review - Apple or Spotify. Learn more about your ad choices. Visit megaphone.fm/adchoices
September 3 · 15 min
Adam J. Schwartz: Trust AI, But Verify Everything | Ep 1313
In this episode of The Digital Executive Podcast, host Brian Thomas sits down with Adam J. Schwartz, founder and CEO of DocumentReview.law, to explore what happens when a practicing attorney gets frustrated enough with existing tools to teach himself JavaScript and build a better one. Adam opens with the breaking point that sparked everything: a case with a few hundred documents where every existing platform was built for millions, making it both overkill and cost-prohibitive for the client. So he sat down in his converted garage in Los Angeles, dusted off his JavaScript knowledge, and spent two years building a prototype that eventually made professional developers chuckle — before they rebuilt it into a modern, browser-agnostic platform attorneys can use from any device. He then makes a clear-eyed case for where AI belongs in legal work and where it does not. AI can triage documents, surface the relevant ones faster, and eliminate the redundant early review passes that drive up billable hours — but until AI can stand in a courtroom, argue before a judge, or sit across from an opposing party in mediation, lawyers still need to know the case inside out. His governing principle is simple: trust but verify. He then pulls back the curtain on why document review consumes roughly seventy-five percent of discovery costs — the combination of hundreds of attorney hours and expensive vendor storage infrastructure — and explains how DocumentReview.law attacks both. He closes with a vision of legal practice where AI handles the ministerial work so attorneys can spend more time on the two things only humans can do: building the case and building the relationship with the client. If you liked what you heard today, please leave us a review - Apple or Spotify. Learn more about your ad choices. Visit megaphone.fm/adchoices
September 2 · 19 min
Aidan McCarty: The Signup Form Is Dying. Here's What Replaces It. | Ep 1312
In this episode of The Digital Executive Podcast, host Brian Thomas sits down with Aidan McCarty, co-founder and co-CEO of Verified, to make the case that the way we prove who we are on the internet is about to look as dated as the fax machine — and that a phone number is the identity primitive that survives what comes next. Aidan opens with the Stripe analogy at the heart of Verified's thesis: Stripe didn't make payments better, it made payments disappear, and that is exactly what Verified is doing for signup. Where a typical fintech onboarding flow takes 161 seconds, 16 clicks, and loses forty percent of users along the way, Verified does it in 9.3 seconds — a user enters a phone number, confirms their first name, and their real identity fills itself in from authoritative sources. He then flips the intuition that speed and security trade off against each other: autofilling data from trusted sources is dramatically more secure than letting anyone type whatever they want into a form, because forms are exactly how fraudsters construct fake identities with dark web Social Security numbers. Regulators are catching up, with FinCEN, OCC, and FDIC jointly authorizing autofill as a compliant onboarding method. The conversation then turns to the bigger existential case: as AI agent traffic on the internet rounds up toward one hundred percent, the question of whether someone is actually a human — and which human — becomes the scarcest and most valuable signal on the web. A phone number, with its tenure, carrier data, activity history, and real-world cost, is almost impossible for an AI to fake and almost impossible for a human not to have, making it the missing identity primitive of the twenty-first century. Aidan closes with a prediction: forms will disappear the way fax machines did — not because someone built a better form, but because an obviously superior alternative already exists. If you liked what you heard today, please leave us a review - Apple or Spotify. Learn more about your ad choices. Visit megaphone.fm/adchoices
August 25 · 22 min
Jen Grogono: Every Company Is Becoming a Media Company | Ep 1311
In this episode of The Digital Executive Podcast, host Brian Thomas sits down with Jen Grogono, founder and CEO of uStudio, to explore why the future of enterprise training and internal communications looks a lot more like Spotify than a company intranet. Jen opens with the founding story of ON Networks in 2006, where the challenge of syndicating original content across a hundred different endpoints — each with different metadata, formats, and technical requirements — planted the seed for what would become uStudio. When she saw enterprises building massive libraries of training and marketing content with no infrastructure to manage or measure them, the pivot was clear. She breaks down why the measurement layer is so critical to enterprise buyers: it is not enough to send a message, leaders need to know what is landing, who tuned out at the twenty percent mark, and what is actually changing behavior. That feedback loop, built on a secure instrumented platform inside corporate networks, is what separates content that moves people from content that gets ignored. She then addresses AI's role in two directions simultaneously — as the subject of urgent workforce change management that demands better communication, and as the engine making content creation, personalization, and discovery faster and more targeted than ever. Her product AutoCast turns corporate documents and knowledge bases into audio, so AI can surface the right three-second clip or five-minute deep dive exactly when a worker needs it. She closes with a vision of the enterprise as an always-on Spotify-like network — personalized to each worker's role, consumption habits, and learning needs, delivered through their phone at any idle moment — and makes the case that the companies that build that infrastructure now will be the ones whose messages actually land when it matters most. If you liked what you heard today, please leave us a review - Apple or Spotify. Learn more about your ad choices. Visit megaphone.fm/adchoices
August 24 · 21 min
Kevin Pickhardt: Your Printer Is a Security Hole | Ep 1310
In this episode of The Digital Executive Podcast, host Brian Thomas sits down with Kevin Pickhardt, Executive Chairman of Pharos Systems International, to make the case that one of the most overlooked vulnerabilities in enterprise IT is sitting right there in the corner of every office floor — the printer. Kevin opens with a career that began at Xerox forty years ago and traces the surprisingly consistent thread through every transformation since: printing never went away, but the infrastructure managing it never kept up. He explains why printing has been uniquely resistant to modernization — historically owned by facilities rather than IT, split across drivers, print servers, endpoints, and physical documents with no single accountable owner, and architecturally built on trust rather than zero trust. A printer today accepts any file from anyone who can reach it on the network, which is precisely the opposite of how modern security is supposed to work. He then walks through how hybrid work and COVID fundamentally changed print behavior — breaking the personal relationship between employee and device, driving printing into home networks enterprises couldn't control, and forcing organizations to rethink printing not as a connection from desk to nearby printer but as a cloud-based queue accessible from anywhere. He closes with a clear vision of what modern printing infrastructure has to become: cloud native, user-centric and identity-first, integrated with broader IT systems rather than siloed, and secured end-to-end with data loss prevention that can flag when someone suddenly starts printing sensitive financial documents. The paperless office, Kevin notes, was a prediction made forty years ago and still hasn't arrived — and the organizations that accept print as a permanent fixture and modernize it accordingly will be the ones that close the security gap before someone else exploits it. If you liked what you heard today, please leave us a review - Apple or Spotify. Learn more about your ad choices. Visit megaphone.fm/adchoices
August 20 · 21 min
Shannon Flanagan: Your Soft Skills Are Now Your Superpower | Ep 1309
In this episode of The Digital Executive Podcast, host Brian Thomas sits down with Shannon Flanagan, founder and CEO of Retail Women in Tech, to make a case that the most important thing missing from most AI transformation efforts isn't better technology — it's the right people in the room. Shannon opens with a career that started at 18 folding jeans and evolved through merchandising, consulting at Accenture, and leadership roles at Gap, Lands' End, and Macy's, shaped throughout by a single question she discovered at 25: what does it take to create the conditions where people love what they do every day? That question led her to organizational design, change management, and eventually to founding a nonprofit she describes as the hardest, poorest, and most fulfilling chapter of her life. She built Retail Women in Tech not to create another exclusive senior women's network, but to get more women — at every level, function, and age — into the rooms where AI decisions are being made, because she believes the qualities women have historically been told to downplay are exactly the ones the AI era will reward most. On change management, Shannon introduces a framework as simple as it is powerful: potential minus interference equals performance, and argues that most AI transformations fail because leaders lead with technology and ROI instead of starting with human readiness, trust, and psychological safety. She closes with a forward-looking vision of what success will look like in retail and beyond — not functional expertise, but judgment, discernment, ethics, and connection — and a challenge to women entering the field to stop waiting until they feel ready for AI roles and start recognizing that what they bring is exactly what the future needs. If you liked what you heard today, please leave us a review - Apple or Spotify. Learn more about your ad choices. Visit megaphone.fm/adchoices
August 20 · 19 min
Allen Dine: ER-Level Care, Delivered to Your Front Door | Ep 1308
In this episode of The Digital Executive Podcast, host Brian Thomas sits down with Allen Dine, Chief Business Officer at Care2You, to explore what it actually takes to deliver emergency and hospital-level care inside someone's home — and how AI is making that possible at scale across one of the most complex urban environments in the world. Allen opens by tracing a career defined by a refusal to wait for someone else to solve the problem, from learning SQL to build his own data warehouse to deploying AI voice agents for patient intake — because in home care, if you want change, you have to build it yourself. He then walks through how Care2You uses voice AI for the highest-stakes first contact in healthcare: patient intake screening. The agents collect vitals, demographics, and recent history, cut a five-minute clinical call to under two minutes, and flag red flags — but they never make clinical decisions. Every conversation is fully audited so clinicians can review exactly what happened before stepping in, keeping the human always in the loop and the process never a black box. The dispatch and routing challenge gets equal attention: matching the right clinician to the right patient across New York City's five boroughs in real time, accounting for traffic, acuity, and a patient load that isn't fully known until the day unfolds. AI compresses what used to take ten minutes of dispatcher judgment into seconds, presenting ranked options that humans can override and adjust. Allen closes with a vision of hospital-at-home that goes beyond just moving the site of care — arguing that the real opportunity is educating patients about what conditions can be safely and comfortably treated at home, so that recovery happens surrounded by family, pets, and familiar routines rather than hospital walls, at lower cost to everyone involved. If you liked what you heard today, please leave us a review - Apple or Spotify. Learn more about your ad choices. Visit megaphone.fm/adchoices
August 19 · 17 min
Furkat Kasimov: Don't Copy Success. Learn From Failure Instead. | Ep 1307
In this episode of The Digital Executive Podcast, host Brian Thomas sits down with Furkat Kasimov, London-based entrepreneur, angel investor, and author, to explore what it takes to build and invest wisely in the AI era — before the crowd figures it out. Furkat opens with a origin story that predates the current AI boom by a decade, tracing his first investment to an InsureTech conference where he spotted a deepfake detection company called PinDrop Security and recognized that every dangerous technology creates a market for its antidote. That insight became the founding logic of Applayerai, a venture studio built around predicting what solutions large corporations will need in five to ten years — and building them before those corporations think to ask. He then unpacks the philosophy behind his book Don't Do This, explaining why he focused on cataloguing over 150 business mistakes rather than celebrating success stories: timing and luck can't be replicated, but someone else's mistakes can be avoided. He closes with sharp advice for executives navigating the AI stack: treat foundation models like cloud providers and build for model independence so you can swap them out without rebuilding everything; match model cost to task complexity rather than defaulting to the most powerful option for everything; and always measure the cost of completing a workflow so you can actually optimize it. His parting message cuts through the noise simply — don't lose sight of what makes your business great, treat AI as a utility, and build the knowledge base that lets your agents keep improving over time. If you liked what you heard today, please leave us a review - Apple or Spotify. Learn more about your ad choices. Visit megaphone.fm/adchoices
August 19 · 21 min
Edwin Miranda on Business Singularity: Where Human Judgment and AI Become One | Ep 1306
In this episode of The Digital Executive Podcast, host Brian Thomas sits down with Edwin Miranda, founder of Konsultora, to explore what it actually means to build an organization for the AI era — not just one with more tools, but one with less distance between a signal, a decision, and an action. Edwin opens by tracing the common thread across his career in advertising, political strategy, and customer experience: competition and decision-making. Every domain is ultimately about understanding what is changing, making better decisions faster, and adapting before your competitors do. AI, he argues, is the first technology that can sit inside that process and accelerate every step of it. He then addresses the economic pressure bearing down on traditional agency and consulting models — research that took weeks now takes minutes, media buying is increasingly algorithmic, content scales infinitely, and reporting can be automated — meaning businesses built on selling hours to produce those outputs are facing an existential reckoning. The answer is not to resist but to rebuild: moving from selling execution to building the systems, workflows, and decision-making capabilities that let organizations operate differently. Edwin then tackles the accountability question head-on, arguing that as AI moves from answering questions to taking actions, agents need identities, permissions, and audit trails just like any employee — because autonomy without accountability is not transformation, it is risk. He closes with a nuanced take on the human-versus-AI debate, rejecting the framing entirely. The goal is not to remove humans but to remove friction around them, freeing up human capacity for the judgment, creativity, and trust that machines cannot replicate. The companies that thrive will not be those that simply bought AI first — they will be the ones that learned to signal, decide, act, and adapt faster than the world around them changes. If you liked what you heard today, please leave us a review - Apple or Spotify. Learn more about your ad choices. Visit megaphone.fm/adchoices
August 18 · 24 min
Antonio Mallia: AI Agents Need a Different Kind of Search | Ep 1305
In this episode of The Digital Executive Podcast, host Brian Thomas sits down with Antonio Mallia, founder and CEO of Seltz.ai, to explore one of the most overlooked infrastructure questions in the AI era: what happens to web search when the user is no longer a human? Antonio opens with a career that runs from the University of Pisa's information retrieval tradition through a PhD at NYU to research roles at Amazon, Pinecone, and Bloomberg — and traces the moment the idea for Seltz crystallized while building Alexa's question answering engine, when it became clear that the next consumer of search results was not a person but a machine. He then explains why Seltz took the harder path of building its own full retrieval stack from scratch rather than wrapping Google or Bing like most AI search products — and why that distinction matters deeply. Traditional search engines were optimized for human patience: ranked lists, short snippets, spell correction, ambiguous queries refined over multiple attempts. LLMs need something fundamentally different — full paragraphs without truncation, long and specific queries that nail the topic on the first attempt, and above all, freshness, because the one thing a model cannot learn in training is what happened after its cutoff date. Seltz also focuses its index on the content LLMs struggle most with — tables, financial records, SEC filings, and structured data that traditional crawlers skip and models cannot reliably memorize. Antonio closes with a prediction that reframes the entire stakes of what he is building: human search queries have plateaued, but machine queries are growing exponentially, and as people spawn multiple specialized agents to handle their knowledge work, the query load on web infrastructure will reach a scale never seen before. The companies that build for that future — with efficiency and freshness at their core — will define the next twenty years of the web. If you liked what you heard today, please leave us a review - Apple or Spotify. Learn more about your ad choices. Visit megaphone.fm/adchoices

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