Tech Talks Daily

• 3513: How Dropbox Is Rethinking Work With AI And Dropbox Dash

  Did you ever stop and wonder how many hours you lose each week hunting for files, tabs, links, or half-written ideas scattered across your apps? It is a familiar frustration, and it sits at the center of today's conversation with Dropbox VP of Engineering, Josh Clemm. Josh has spent two decades building products shaped around scale, personalisation, and clarity, and he brings that mix of experience to Dropbox's push into AI and knowledge management. In this episode, Josh shares stories from his time at LinkedIn and Uber, including the surprising Krispy Kreme promotion that took down Uber Eats across the globe and triggered a major rethink of architecture and resiliency. That experience shaped his belief that chaos often teaches the most. It also sets the stage for why he sees AI fluency as a leadership requirement rather than a trend.  You will hear how Dropbox is approaching internal experimentation, why context rot and work slop are real problems inside companies, and why the empty chat box often creates more anxiety than opportunity. Josh walks through the thinking behind Dropbox Dash, a standalone AI powered knowledge layer that connects all of your cloud apps, understands their content, and turns search into something sharper and faster. He explains why context aware AI is the next leap, how Dash builds knowledge graphs across apps, and why the future of AI might look less like single player workflows and more like tools that sit inside the flow of teamwork. It is a wide ranging conversation that moves from engineering history to the practical steps behind building AI products that feel useful rather than overwhelming. So here is the question that sits underneath everything Josh shared. What would your day look like if your information finally made sense without you having to chase it? Tech Talks Daily is Sponsored By Denodo. To learn more, visit denodo.com

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• 3512: How D2L's Rob Telfer Sees Universities Adapting to an AI First World

  What does learning look like when technology shifts faster than most university systems can adapt? That question shaped my conversation with Rob Telfer, who leads education strategy for D2L across Europe, the Middle East, and Africa. Rob returned to the show with a clear view of how AI is transforming higher education and why so many institutions are struggling to keep pace with expectations from students, employers, and society. Rob opened by laying out the reality universities face today. Financial strain, fluctuating enrolment, employer demands changing at speed, and a generation of learners preparing for roles that may not even exist yet. Against that backdrop, he described AI as the biggest catalyst the sector has seen in decades and explained how it has already reshaped academic policy, assessment models, and daily teaching practice. We explored practical examples of where AI is already creating meaningful change. Rob shared how D2L is helping institutions introduce adaptive learning, on demand student support, and content creation tools that reduce the pressure on educators. These are not speculative ideas. They are used by universities serving tens of thousands of learners, improving accessibility, easing workloads, and giving students faster, more personal support. The conversation moved to employability, a worry at the centre of almost every higher education debate. Rob explained how curriculum design needs to shift from theory first to skill first, and how deeper collaboration between academia and industry can help close widening gaps. He described why AI should be woven through the learning experience rather than bolted on at the end, and how that alignment can shape graduates who are confident with the tools they will soon use in the workplace. A striking theme came from the mismatch between student behaviour and institutional policy. Many students use AI daily, even where guidance is unclear or restrictive. Rob argued that ignoring the reality only pushes students into the shadows. Universities that teach responsible use, clear evaluation methods, and prompt literacy will better prepare their learners for the world they are about to enter. We ended by looking ahead to 2026. Rob believes the institutions that thrive will be the ones that act with intent, create clear AI policies, invest in meaningful technology, and keep human connection at the centre of learning. Those that resist or delay may find themselves struggling to compete in a sector where expectations rise quickly and alternatives for learners continue to grow. If you work in education or care about the future of learning, Rob's insights offer a candid, practical view of what must change. Which of his observations resonates most with your own experience, and how should universities evolve from here? I would love to hear your thoughts. Useful Links Connect with Rob Telfer on LinkedIn Learn more about D2L Follow on LinkedIn, Twitter, and Facebook Tech Talks Daily is Sponsored By Denodo. To learn more, visit denodo.com

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• 3511: BCG on Closing the Gap Between AI Experiments and Real Business Impact

  *]:pointer-events-auto scroll-mt-[calc(var(--header-height)+min(200px,max(70px,20svh)))]" dir="auto" tabindex="-1" data-turn-id= "request-WEB:221c7553-c733-4456-a06c-c66c0626b35b-7" data-testid= "conversation-turn-16" data-scroll-anchor="true" data-turn= "assistant"> How do you guide a workforce through the fastest shift in technology most of us have seen in our careers? That question shaped my conversation with David Martin from BCG, who works at the intersection of talent, culture, and AI. He joined me from New York and quickly painted a clear picture of what is really happening inside global enterprises right now. We started with the widening split between AI fluent teams and those stuck in endless pilots. David explained why the organizations getting results are the ones doing fewer things with far greater ambition. Many others scatter energy across small use cases, save minutes instead of hours, and never reach a scale where value becomes visible. Training surfaced early as one of the biggest gaps. Not surface level workshops, but the deeper hands-on learning that helps people change how they work. David described why frontline teams lag behind, why engineers still miss major capabilities, and how leadership behaviour dramatically affects adoption. Curiosity and communication play a bigger role than most expect. We explored the move from isolated AI experiments to real workflow transformation. David shared examples from engineering, customer service, and operations where companies are finally seeing measurable results. He also explained why agents remain underused, with hesitation, data quality, and unfamiliarity still slowing progress. Shadow AI added another layer, with half of workers already using tools outside corporate systems. The conversation returned often to people. David outlined BCG's 10-20-70 rule, showing why technology is never the main bottleneck. Culture, roles, and process make or break outcomes. Leaders who provide clarity and a sense of direction see faster adoption. Those who remain hesitant create uncertainty that spreads across teams almost instantly. As we looked toward 2026, David shared cautious optimism. He sees huge potential in areas like healthcare and sustainability, along with a wave of workflow redesign that will reshape daily work. His own learning habits are simple, from podcasts to regular reading, and driven by a desire to set a strong example for his children as they grow into a world shaped by AI. If you want a grounded view of where AI is genuinely delivering change, this conversation offers rare clarity. What resonates with you most from David's perspective, and how will you approach your own learning in the year ahead? I would love to hear your thoughts.   Tech Talks Daily is Sponsored By Denodo. To learn more, visit denodo.com

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• 3510: Orange Business and the Rise of Digital Innovation Across IMEA

  Did you know that when many people hear "Orange," they still ask if it involves SIM cards? That was the perfect place to begin my conversation with Sahem Azzam, President for IMEA and Inner Asia at Orange Business. Once we cleared that up, it opened the door to a much richer story about what enterprise innovation looks like across one of the fastest-moving regions on the planet. Sahem joined me from Dubai, a city that has become a living case study for what happens when a region refuses to think small. As we compared notes from Gitex Global, it became clear that what is happening across the Middle East is not a short burst of enthusiasm. It is a deliberate long-term shift driven by young populations, bold government ambition, and a willingness to adopt new technologies before anyone else. Sahem explained how this appetite for speed is shaping the region's digital transformation and how Orange Business is supporting it through cloud, connectivity, cybersecurity, digital integration, and large-scale smart city programmes. He shared practical stories that peeled back the curtain on cognitive city design, energy optimisation, and the pressure on enterprises to simplify sprawling hybrid IT environments. What stood out was how often the conversation returned to value. Better user experiences, lower costs, and new revenue paths. Everything Orange Business builds must deliver one of those outcomes. Sahem talked through platformization, why unified infrastructure matters, and how enterprises can reduce complexity in an age where cloud, security, networking, and AI all collide at once. We also discussed the growing focus on responsible AI and the shared need for transparency. Sahem spoke about data ownership, trusted models, and the careful guardrails that must sit behind every AI deployment. The rise in cyber threats is making this more important than ever, and he offered a candid look at how Orange Cyberdefense approaches modern security through an integrated view of infrastructure, operations, and risk. What gave this conversation a personal edge was Sahem's final reflection on learning. After years at Stanford, London Business School, and Harvard, he still sees human experience as the most valuable teacher. Listening to people, sharing problems, comparing perspectives. Events like Gitex remind him that optimism is contagious and that the future of the region will be shaped by collaboration as much as technology. If you want a grounded view of digital transformation from someone living it every day, this conversation is a rare window into both the opportunities and the tension behind innovation at scale. Have you seen the same momentum in your own region, and how do you stay ahead of the pace of change? I would love to hear your thoughts.   Tech Talks Daily is Sponsored By Denodo. To learn more, visit denodo.com/aws

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• 3509: What AWS re:Invent Revealed About the Acceleration of Agentic AI

  Did you ever walk into a conference session thinking you were ready for the week, only to realise the announcements were coming so fast that you almost needed an agent of your own to keep up? That was the mood across Las Vegas, and it was the backdrop for my conversation with Madhu Parthasarathy, the general manager for Agent Core at AWS. He has spent the week at the centre of AWS's wave of agentic AI news, working on the ideas that are already moving from keynotes and demos into the hands of real enterprise teams. Sitting down with him offered a rare moment of clarity among the noise, and his calm take on what actually matters helped bring the bigger picture into focus. Madhu talked through the thinking behind Agent Core and why he believes 2026 will be the year enterprises finally begin shifting from prototypes to production-scale agents. He walked me through the two areas customers keep coming back to, trust and performance, and why the new policy framework and agent evaluations could remove long-standing barriers to deployment.  His examples were grounded in real behaviour he is seeing inside large companies, whether that is internal support workloads, developer productivity, meeting preparation, or customer-facing flows designed to reduce the friction between intent and outcome. We also explored the deeper shift introduced by Nova Forge, including the idea of blending enterprise data with model checkpoints to create domain-specific agents that can work with greater accuracy and context. Madhu explained why there will never be a one-size-fits-all model and how choice remains central to AWS's agentic AI approach. My guest also reflected on how infrastructure changes, such as Trainium three ultra servers and expanded Nova model families, are shaping the pace at which companies can experiment, evaluate, and adopt emerging capabilities. Trust surfaced again and again in our conversation. Madhu was clear that non-deterministic systems also introduce concerns, which is why action boundaries and guardrails are becoming as important as model quality. He described the excitement he is seeing from customers who now feel they have workable ways to give agents responsibility without handing over the keys entirely.  As he put it, this is the moment where confidence begins to grow because the guardrails finally meet the expectations of enterprise leaders. We closed with the topic many people have been whispering about all week, modernization. Madhu reflected on AWS Transform, the push to help organisations move away from legacy architectures far faster than before, and the impact that agentic systems will have as they support full stack migrations across Windows environments and custom languages.  Madhu cuts through the noise with a grounded view of reliable autonomy, multi-agent orchestration, policy-driven safety, and the shift toward agents as true collaborators. The question now is where you see the biggest opportunity. How might these agent-based systems change your workflows, and what would it take for you to trust them with the tasks you never seem to have time for? I would love to hear your thoughts. Tech Talks Daily is Sponsored By Denodo. To learn more, visit denodo.com/aws    

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