What if business intelligence didn't stop at answering what happened, but could finally explain why? In this episode of Tech Talks Daily, I sit back down with Alberto Pan, Chief Technology Officer at Denodo, to unpack how Deep Query is redefining enterprise AI through reasoning, transparency, and context.

We explore how Deep Query functions as an AI reasoning agent capable of performing open-ended research across live, governed enterprise data. Instead of relying on pre-built dashboards or static reports, it builds and executes multi-step analyses through Denodo's logical data layer, unifying fragmented data sources in real time. Alberto explains how this semantic layer provides the business meaning and governance that traditional GenAI tools lack, transforming AI from a surface-level Q&A system into a trusted analytical partner.

Our conversation also digs into the bigger picture of explainable AI. Deep Query reports include a full appendix of executed queries, allowing users to trace every insight back to its source. Alberto breaks down why this level of auditability matters for enterprise trust and how Denodo's support for the Model Context Protocol (MCP) opens the door to more interoperable, agentic AI systems.

As we discuss how Deep Query compares with RAG models and data lakehouses, Alberto offers a glimpse into the future of business intelligence—one where analysts become guides for AI-driven research assistants, and decision-makers gain faster, deeper, and more transparent insights than ever before.

So what does the rise of reasoning agents like Deep Query mean for the next generation of enterprise AI? And how close are we to a world where AI truly understands the why behind the data? Tune in and share your thoughts after listening.

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For years, many businesses believed that Apple devices were inherently secure. That illusion has faded. In this episode of Tech Talks Daily, I speak with Adam Boynton, Senior Security Strategy Manager at Jamf, about why visibility across macOS and iOS is no longer a luxury but a necessity.

Adam explains how Jamf has evolved from device management to full Apple-native security intelligence, protecting over 75,000 organizations and more than 32 million devices. He shares how attackers no longer target individual operating systems but entire ecosystems, exploiting the gaps between how Apple secures its platforms and how enterprises actually monitor them.

From real-world cases to lessons learned at Jamf's annual JNUC conference, Adam describes how telemetry provides security teams with the truth about what's really happening on their endpoints, enabling them to transition from reactive incident response to proactive defense.

Our conversation covers everything from the architectural blind spots that traditional Windows-centric tools can't see to the rise of AI-driven analysis that turns complex forensic investigations into minutes-long processes. We also explore how Jamf's partnerships, such as those with Elastic, are creating an open and integrated future for enterprise security, blending deep Apple signals with cross-platform context.

For anyone still clinging to the myth that macOS or iOS "just work" without attention to security, this episode is a wake-up call. Adam outlines practical advice on patching, mobile hygiene, and zero trust, while revealing how Jamf's latest innovations are quietly making the most secure way the easiest way for users.

Listen to hear how Jamf is redefining modern Apple security, turning management, identity, and protection into a seamless whole, and why accurate visibility—not assumptions—is now the objective measure of cybersecurity readiness.

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There was a time when a computer science degree almost guaranteed a fast track into a well-paid career. But that promise is slipping. In today's Tech Talks Daily episode, I reconnect with Hans de Visser, Chief Technology Officer at Mendix, to discuss why recent graduates are finding it more challenging than ever to secure their first role in technology, and what they can do about it.

Hans brings decades of experience in software engineering and low-code innovation, and his perspective on today's market is both sobering and optimistic. We discuss new research indicating a sharp decline in junior developer openings since 2024 and explore how the rapid rise of AI has altered the hiring equation.

The expectation now is that young developers arrive fluent in automation, generative AI, and multidisciplinary tools —skills that few university programs can thoroughly teach. Yet, as Hans points out, this doesn't mean opportunity has vanished. It just looks different.

Our conversation unpacks what this new reality means for aspiring developers. Hans explains how Mendix evaluates candidates by testing their ability to think critically about AI-assisted code rather than generate it.

He explains why graduates must master both traditional software foundations and modern tools, such as low-code platforms and agile applications. And he offers advice on building a mindset of lifelong learning, staying curious, experimenting with new tools, and understanding how AI can amplify rather than replace human creativity.

For anyone feeling disheartened by the tightening job market, Hans offers balance and hope. He believes that as the definition of software developer evolves, new hybrid roles will emerge at the intersection of business, creativity, and technology. The graduates who will thrive are those who treat AI as a collaborator, not a competitor.

Listen to this episode to hear how Mendix is helping redefine what it means to build software in the age of AI, and why today's tech graduates may need to think less about securing a single job title and more about creating a career that never stops learning.

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