Tech Talks Daily

*]:pointer-events-auto scroll-mt-[calc(var(--header-height)+min(200px,max(70px,20svh)))]" dir="auto" tabindex="-1" data-turn-id= "request-WEB:b0120523-17fc-4d94-97d7-97b3e135ed14-3" data-testid= "conversation-turn-8" data-scroll-anchor="true" data-turn= "assistant"> What does autonomous IT really look like when you move beyond the slideware and start wiring systems together in the real world?
At Dynatrace Perform in Las Vegas, I sat down with Pablo Stern, EVP and GM of Technology Workflow Products at ServiceNow, to unpack exactly that. Pablo leads the teams focused on CIOs and CISOs, building the workflows and security products that sit at the heart of modern IT organizations. From service desks and command centers to risk and asset management, his remit is clear: enable AI to work for people, not the other way around.
We began with ServiceNow's deepening multi-year partnership with Dynatrace. While the announcement made headlines, Pablo was quick to point out that the real story starts with customers. This collaboration is rooted in a shared goal of helping joint customers reduce outages, improve SLA adherence, and shrink mean time to resolution. The vision of autonomous IT operations is not about hype. It is about connecting observability data with deterministic workflows so that insight can evolve into coordinated, system-level action.
Pablo walked me through the maturity curve he sees emerging. First came AI-powered insight, summarizing data and surfacing signals from noise. Then came task automation, drafting knowledge articles, paging teams, triggering predefined playbooks. The next step, and the one that excites him most, is orchestrated autonomy. That means stitching together skills, agents, and workflows into systems that can drive end-to-end outcomes. It is a journey measured in years, not months, and it depends as much on digitizing process and building trust as it does on technology.
We also explored root cause analysis, still one of the biggest time drains in IT. By combining Dynatrace's AI-driven observability with ServiceNow's workflow engine, enterprises can automate forensic steps, correlate events faster, and shorten the time spent on major incident bridges where teams debate ownership. Even incremental improvements in accuracy can save hours when incidents strike.
Trust, of course, remains central. Pablo was candid that full self-healing systems are still some distance away. What we will see first is relief automation, controlled failovers, scripted actions suggested by machines but approved by humans. Over time, as confidence grows and processes become fully digitized, the balance will shift.
Beyond the technology, a consistent theme ran through our conversation. Outcomes have not changed. Enterprises still want higher availability, faster resolution, better employee experiences. What is changing is the how. ServiceNow is reimagining its platform to deliver those outcomes at a much higher standard, not through incremental tweaks, but through rethinking workflows for an AI-first world.
From design partnerships with banks building pre-flight change checks, to internal teams acting as the toughest customers, this was a grounded, practical conversation about where autonomous operations are headed and what it will take to get there.
If you are a CIO, CISO, or IT leader wondering how to move from theory to execution, this episode offers a clear-eyed look behind the curtain.

What happens when nearly half of organizations admit they have no AI-specific security controls, yet AI-driven data leaks are accelerating at the same time?
In this episode of Tech Talks Daily, I spoke with Aayush Choudhry, CEO and co-founder of Scrut Automation, about what he sees as a blind spot in the cybersecurity industry. While much of the market continues to design tools for Fortune 500 enterprises with deep pockets and large security teams, Aayush argues that the real existential risk sits with the 99 percent of businesses that cannot survive a serious breach.
Aayush brings a founder's perspective shaped by firsthand pain. Before launching Scrut, he and his co-founder experienced the grind of managing compliance and security as a cloud-native startup trying to sell into enterprises. They were outsiders to GRC and security at the time, forced to learn from first principles. That experience became the foundation for Scrut Automation, a modern GRC platform built specifically for small and mid-sized companies that cannot afford six-month implementations, armies of consultants, or half-million-dollar tooling budgets.
We explore why treating compliance and security as separate functions increases risk for smaller organizations. In the mid-market, the same small team is often responsible for both. When compliance is handled as a box-ticking exercise and security as a separate technical discipline, gaps emerge. Scrut's approach converges governance, risk, and security signals into a unified layer that translates hundreds of technical alerts into context-aware risks that actually matter to the business.
Our conversation also tackles AI complacency. Using the classic confidentiality, integrity, and availability framework, Aayush outlines what minimum viable AI security hygiene looks like in practice. That includes ensuring AI agents are not over-privileged compared to the humans they represent, placing guardrails around sensitive data fed into models, and extending supply chain security thinking to agentic integrations. For resource-constrained teams, these are not theoretical concerns. They are daily realities.
Perhaps most compelling is his view that AI can act as a force multiplier for small teams. By embedding accumulated expertise into agents trained on anonymized patterns and edge cases, Scrut aims to democratize security know-how that would otherwise require multiple full-time analysts. The goal is simple but ambitious: make enterprise-grade security outcomes accessible without enterprise-grade headcount.
If you are leading a small or mid-sized business and wondering how to balance growth, compliance, and AI risk without breaking the bank, this conversation offers a candid look from the trenches.

How do you build enterprise software for the companies that keep the world turning, while also building a leadership culture where people can actually thrive?
In this episode of Tech Talks Daily, I spoke with Kerrie Jordan, Group VP of Product Management at Epicor, about her journey from studying literature to helping shape cloud ERP strategy at a global software company serving more than 20,000 customers worldwide. Kerrie's story is a reminder that there is no single path into technology leadership. Sometimes the foundations are laid in unexpected places, through storytelling, creativity, and a deep curiosity about people.
Kerrie shares how her early career in product lifecycle management opened her eyes to the human side of software. Interviewing customers and writing case studies showed her that behind every system implementation is a personal story, a career milestone, or a business trying to survive and grow. That perspective still shapes how she approaches product and marketing today at Epicor, a company recently recognized as a Leader in the Gartner Magic Quadrant for Cloud ERP for Product-Centric Enterprises for the third consecutive year.
But this conversation goes far beyond market recognition. We talk openly about burnout, resilience, and the reality of leading through pressure. Kerrie reflects on the importance of protecting time, creating space to reconnect, and building a culture where empathy is practiced, not just discussed. Her view of leadership is grounded in communication, psychological safety, and being tough on problems rather than people.
Mentorship is another thread running throughout our discussion. Kerrie explains why powerful mentorship is not passive. It requires vulnerability, preparation, and a willingness to hear difficult advice. A single phrase from a mentor early in her career, "stick-to-itiveness," continues to shape how she approaches hard problems today.
We also explore the future of women in manufacturing and technology. Kerrie highlights the need for intentional change across education, early career development, and leadership visibility. She believes technology, particularly AI, can expand access, enable upskilling, and introduce flexibility that supports long-term career growth. At the same time, she makes a simple but powerful point. Women in tech want the same thing as anyone else: the space and autonomy to do their jobs well.
From customer co-innovation and community-driven product roadmaps to inclusive leadership under commercial pressure, this episode offers a candid look at what it really takes to lead in enterprise technology today.
If you are building products, leading teams, or questioning your own next career step, I think you will find something in Kerrie's story that resonates.

Why do so many of us feel busy all day, yet struggle to point to the meaningful work we actually completed?
In this episode of Tech Talks Daily, I sit down with Tomás Dostal Freire, CIO of Miro, to unpack a challenge that quietly drains modern organizations. Tomás brings experience from companies like Google, Netflix, and Booking.com, and now leads both IT and business acceleration at Miro. His focus is simple but ambitious. Move beyond AI experimentation and rethink how work itself gets done.
We explore new research revealing that for every hour of creative work, employees lose up to three hours to meetings, admin, emails, and maintenance tasks. That ratio is more than an inconvenience. It affects decision-making speed, employee satisfaction, and ultimately a company's ability to compete. Tomás argues that future candidates will choose employers based on how much unnecessary internal work they are expected to tolerate. In other words, reducing busy work is quickly becoming a talent strategy.
One of the biggest culprits? Context switching. With dozens of browser tabs open and information scattered across tools, teams spend more time stitching together fragments than making decisions. Tomás describes how duplication of work, outdated systems, and a lack of shared context quietly erode momentum. AI, he believes, should not create more noise or another standalone tool. It needs to be embedded where collaboration already happens.
We discuss the difference between single-player AI moments, where individuals use tools in isolation, and multiplayer AI collaboration, where shared context allows teams to move faster together. At Miro, this philosophy has shaped what they call an AI Innovation Workspace, a shared canvas where human insight and AI assistance coexist in real time.
Tomás also shares practical advice for leaders who want to reclaim creative time. Start by identifying tasks you dislike doing that could easily be handled by someone junior. That list often reveals what AI can already automate. Then focus on building transferable skills like cognitive agility and first-principles thinking, rather than chasing every new tool.
If you are wrestling with burnout, fragmented workflows, or wondering how AI can genuinely improve collaboration without overwhelming teams, this conversation offers a grounded, optimistic perspective. And yes, we even add a Beatles classic to the Spotify playlist along the way.

How do you protect millions in revenue during your busiest hour of the year when your entire business depends on digital performance?
At Perform 2026, I caught up with Alex Hibbitt, Engineering Director responsible for the customer platform at Storio Group, to unpack what happens when observability moves from an engineering afterthought to a board-level priority. Storio Group was formed from the merger of Photobox and Albelli, bringing together multiple brands and five separate e-commerce platforms into one unified customer journey. That consolidation created opportunity, but it also exposed risk, especially during peak trading from Black Friday through Black Sunday and into the Christmas rush.
Alex shared what it really looks like when downtime is non-negotiable. At peak, Storio's platform can generate up to 1.5 million euros per hour. A single poorly timed incident is not simply a technical problem, it is a direct threat to revenue and customer trust. Before partnering with Dynatrace, the team was relying heavily on centralized logging, processing over a billion log lines a day and depending on engineers to manually interpret signals. It was reactive, labor intensive, and left too much to chance.
What stood out for me was how cultural change led the transformation. Rather than imposing a new tool from the top down, Alex and his team built a maturity model engineers could relate to, created internal champions, and framed observability as risk management and business protection. The result was a reported 65 to 70 percent reduction in log costs, a 50 percent drop in mean time to detect overall, and up to 90 percent improvement for the most severe incidents.
We also explored how unifying logs, metrics, and traces into a single AI-driven platform helped Storio move from reactive firefighting to proactive detection. During one Black Sunday alone, three major issues were identified early enough to avoid an estimated 4.5 million euros in potential impact.
This conversation goes beyond tooling. It is about protecting customer experience, safeguarding revenue during peak demand, and building an engineering culture that embraces change. If your organization is wrestling with cloud costs, fragmented monitoring, or the pressure to deliver flawless digital performance under load, there are some powerful lessons here.