Tech Talks Daily

• AWS re:Invent: Ruth Buscombe on How AWS Helps F1 Engineers Read a Million Data Points a Second

  Did you know a single Formula 1 car produces 1.1 million data points every second from hundreds of sensors? That number alone sets the tone for this conversation with Ruth Buscombe, an F1 strategist, analyst, and F1TV presenter whose work sits at the meeting point of engineering precision and real time storytelling. We met at AWS re:Invent in Las Vegas, and her insights into how much pressure, judgment, and creativity are wrapped inside each decision brought the sport to life in a fresh way for anyone who has ever stared at a dashboard of metrics and wondered what really matters. This discussion goes far deeper than split times and tyre choices. Ruth explains how AWS and F1 are rethinking race strategy through real time insights and cloud compute, from TrackPulse and root-cause analysis all the way to predictive graphics that let commentary teams spot a race-defining moment before it happens. She also reflects on the sport's changing culture, the growth of new fan communities, and the shift from old telemetry to modern systems that process millions of data points every second. Her stories from the paddock at Ferrari, Alfa Romeo, and F1TV help frame just how intense the job can be when 12,000ths of a second separate pole from second place. There are moments in this conversation that remind us that F1 strategy is as much about human pattern recognition as it is about machine intelligence, and that the strongest engineers find ways to absorb pressure without losing their instinct. What stood out most was how clearly Ruth links F1 to decision making in every industry. Whether she is talking about marginal gains, pattern detection, or the discipline needed to separate noise from signal, her examples make perfect sense to both race fans and tech leaders. She shares how AWS tools allow broadcasters and engineers to interpret scenarios instantly, why the sport needed to move past manual diagnosis, and how new tools even help verify whether a driver's mistake came from a small steering slide or a split-second shift error. Her passion is infectious and her explanations cut straight to the heart of what makes the blend of live racing and cloud computing work so well. As you listen, think about how your own team makes choices under pressure and ask yourself one last question. If you were in the garage making a call with the whole world watching, which signals would you trust and how fast could you act? Useful Links: Connect with Ruth  Sign up to Ruth's Newsletter AWS Insights  

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• 3506: How Marriott International Builds Digital Fluency at Global Scale,

  Have you ever wondered how a company with nearly a million associates across continents keeps everyone learning, aligned, and prepared for constant change? That question sat at the heart of my conversation with Victor Arguelles, the VP of Global Learning Design and Development at Marriott International. Victor began his career as a high-school educator, and it is clear that this early experience shapes his entire approach to enterprise learning. He brings the empathy and discipline of the classroom into a global operation where cultural nuance, business complexity, and operational scale collide every day. Across our conversation, Victor opens up about what digital transformation in learning actually looks like behind the curtain at Marriott. Rather than focusing on tools alone, he explains how mindset, process, and cultural confidence dictate success. He talks about the delicate balance between global standardization and local relevance, and how Marriott validates learning experiences to understand how change will feel for associates before any deployment begins. It becomes clear that the company's commitment to people first is not a slogan, it is the foundation of the entire learning strategy. Victor also shares how Marriott is using partners and platforms to reimagine training in a way that fits into the flow of work. He describes how digital adoption tools have reduced training seat time by as much as 60 percent and given associates real support inside the tools they use every day. This shift has created confidence, improved performance, and given teams more time with guests, which he considers the most meaningful return on investment of all. Looking ahead, Victor reflects on the role AI will play in learning, from measurement to content creation, and how emerging tools could eventually provide adaptive, contextual support in real time. If you are a tech or business leader trying to understand how large enterprises truly modernize learning, this conversation offers a grounded and human view of what it takes. And as Victor looks toward 2026 and beyond, he shares why he believes the next wave of learning innovation will be shaped by AI, data, and a deeper understanding of behavior inside the flow of work. What stood out to you in his approach, and how do you see the future of enterprise learning evolving? I would love to hear your thoughts.

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• 3505: When Home Improvement Meets Real-Time Intelligence

  Have you ever wondered how an industry known for delays and uncertainty suddenly starts operating with the pace of a tech company? That thought stayed with me as I spoke with Eppie Vojt, the Chief Digital and AI Officer at West Shore Home. His team is bringing applied AI into home remodeling in a way that feels practical, grounded, and surprisingly human. Eppie explains how a strong data foundation allowed them to introduce agentic systems without the usual chaos. Those systems now handle scheduling, permitting, forecasting, and communication in the background. The result is a level of certainty that customers rarely experience in remodeling. When someone signs a project, they already know the installation date. Hours of operational work happen silently, and that alone changes the entire experience. We also talk about the culture that made this possible. Instead of forcing new tools onto teams, leadership encouraged small experiments and curiosity. That simple move flipped the mood internally. Departments began approaching Eppie with ideas rather than waiting to be pushed. The rollout was gradual, giving people time to shift into more valuable work without fear or disruption. Looking ahead, Eppie sees huge potential in letting customers start their journey in different ways. Tools like photogrammetry and digital twins could help people get early pricing guidance without a full in-home visit. It reflects a bigger change across physical industries as AI becomes something that quietly supports accuracy, safety, and convenience. If you care about real AI adoption rather than hype, this one offers a clear view into what works. I'd love to hear what stood out to you after listening. Useful Links Connect with Eppie Vojt on LinkedIn Learn more about West Shore in this video Tech Talks Daily is Sponsored by NordLayer: Get the exclusive Black Friday offer: 28% off NordLayer yearly plans with the coupon code: techdaily-28. Valid until December 10th, 2025. Try it risk-free with a 14-day money-back guarantee.

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• 3504: Building Software for a Cross Platform World

  What does it really mean to run a company that aims to be "good" before it ever thinks about becoming "great"? That was the question sitting with me as I sat down with Appfire's CEO, Matt Dircks. The conversation took us straight into the heart of modern leadership, purpose, and the realities of running a global SaaS business during a period of change. Matt has led organisations through rapid growth, mergers, cultural resets, and shifting market expectations. What stood out in our discussion was how open he is about the parts of leadership that are messy. He talked about transparency, dealing with hard decisions, and the challenge of building a culture where people feel safe enough to be honest without losing accountability. His philosophy is grounded in something simple. You cannot scale trust unless you behave in ways that earn it every day. We explored how Appfire is evolving beyond its acquisition roots, expanding from Atlassian aligned tools into cross platform solutions that support enterprises across Microsoft, Salesforce, GitHub and more. Matt explained why the company is investing heavily in new AI native products and why being close to customers is becoming a priority as their needs become more complex. He also shared how openness, active communication, and a willingness to be challenged guide the way he leads through uncertainty. The more we talked, the clearer it became that Appfire's next chapter is a blend of product innovation, cultural maturity, and a renewed focus on service. Matt's story offers a useful lens for anyone wrestling with questions about values, growth, and the human side of technology. What does a "good company" look like in practice, and how does that shape the road to long term success? I'd love to hear what resonated with you, so let me know your thoughts. Useful Links Connect With Matt Dircks on LinkedIn Learn more about Appfire The No Asshole Rule: Building a Civilized Workplace and Surviving One That Isn't by Robert I. Sutton  Range: Why Generalists Triumph in a Specialized World by David Epstein Tech Talks Daily is Sponsored by NordLayer: Get the exclusive Black Friday offer: 28% off NordLayer yearly plans with the coupon code: techdaily-28. Valid until December 10th, 2025. Try it risk-free with a 14-day money-back guarantee.  

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• 3503: The Next Security Challenge Created by AI Coding Tools

  What happens when AI adoption surges inside companies faster than anyone can track, and the data that fuels those systems quietly slips out of sight? That question sat at the front of my mind as I spoke with Cyberhaven CEO Nishant Doshi, fresh from publishing one of the most detailed looks at real-world AI usage I have seen. This wasn't a report built on opinions or surveys. It was built on billions of actual data flows across live enterprise environments, which made our conversation feel urgent from the very first moment. Nishant explained how AI has moved out of the experimental phase and into everyday workflows at a speed few anticipated. Employees across every department are turning to AI tools not as a novelty but as a core part of how they work. That shift has delivered huge productivity gains, yet it has also created a new breed of hidden risk. Sensitive material isn't just being uploaded through deliberate actions. It is being blended, remixed, and moved in ways that older security models cannot understand. Hearing him describe how this happens in fragments rather than files made me rethink how data exposure works in 2025. We also dug into one of the most surprising findings in Cyberhaven's research. The biggest AI power users inside companies are not executives or early career talent. It is mid-level employees. They know where the friction is, and they are under pressure to deliver quickly, so they experiment freely. That experimentation is driving progress, but it is also widening the gap between how AI is used and how data is meant to be protected. Nishant shared how that trend is now pushing sensitive code, R&D material, health information, and customer data into tools that often lack proper controls. Another moment that stood out was his explanation of how developers are reshaping their work with AI coding assistants. The growth in platforms like Cursor is extraordinary, yet the risks are just as large. Code that forms the heart of an organisation's competitive strength is frequently pasted into external systems without full awareness of where it might end up. It creates a situation where innovation and exposure rise together, and older security frameworks simply cannot keep pace. Throughout the conversation, Nishant returned to the importance of visibility. Companies cannot set fair rules or safe boundaries if they cannot see what is happening at the point where data leaves the user's screen. Traditional controls were built for a world of predictable patterns. AI has broken those patterns apart. In his view, modern safeguards need to sit closer to employees, understand how fragments are created, and guide people toward safer workflows without slowing them down. By the time we reached the end of the interview, it was clear that AI governance is no longer a strategic nice-to-have. It is becoming a daily operational requirement. Nishant believes employers must create a clear path forward that balances freedom with control, and give teams the tools to do their best work without unknowingly putting their organisations at risk. His message wasn't alarmist. It was practical, grounded, and shaped by years working at the intersection of data and security. So here is the question I would love you to reflect on. If AI is quickly becoming the engine of productivity across every department, what would your organisation need to change today to keep its data safe tomorrow? And how much visibility do you honestly have over where your most sensitive information is going right now? I would love to hear your thoughts. Useful Links  Connect with Cyberhaven CEO Nishant Doshi on LinkedIn Learn more about Cyberhaven Tech Talks Daily is Sponsored by NordLayer: Get the exclusive Black Friday offer: 28% off NordLayer yearly plans with the coupon code: techdaily-28. Valid until December 10th, 2025. Try it risk-free with a 14-day money-back guarantee.

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