HR Leaders Summit

In 2030, we don’t "write" code anymore, we orchestrate it. The massive adoption of agentic AI has transformed the SDLC into a high-fidelity assembly line. We have "Architect Agents" drafting design docs, "Reviewer Agents" enforcing linting and security, and "Coder Agents" generating 99% of production PRs. In this "dystopian" (or utopian?) future, the role of the Software Engineer has evolved into a conductor. To get these agents to work perfectly, together the human must possess a god-tier level of experience, knowing exactly when to demand an interface over a class, how to prevent leaky abstractions in generated code, and how to debug logic they didn't technically type. But there is a catch: if the machines do all the typing in the world of proprietary software, where does the next generation of senior conductors come from? In this session, we will explore: - The Agentic SDLC: A technical deep dive into a multi-agent world, where specialized agents handle specific lifecycle stages. - The "Expert Paradox": Why AI-driven development actually raises the bar for seniority and architectural knowledge, making "Junior" a disappearing job title in proprietary software. - Open Source as the training ground: Why FOSS is becoming the only place where humans still "hand-craft" code, not out of necessity, but for mastery and passion, and how this makes Open Source the ultimate training ground for future engineers.

AI has huge potential in recruiting - but implementations vary widely. This talk breaks down what worked, what didn’t, and why, across both office (professional) and volume (high-velocity) hiring environments. In this practical session, you’ll hear real, data-backed lessons from multiple AI introductions we led at Redcare Pharmacy and evaluated in both office hiring and volume recruiting. I’ll cover: - Successful patterns - where AI improved work of the recruiters / candidate experience. - Unsuccessful rollouts - where tools underperformed and what were the reasons. - Human + machine workflows - what roles remain human-centric, and where AI delivers the most leverage. - Ethics and bias safeguards - real examples of how bias surfaced, and practical guardrails to address it. - Metrics that matter - what to measure when you deploy AI so you know you’re improving, not guessing.

Software teams spend enormous effort on codes - yet many of the biggest productivity issues are not technical at all. They come from miscommunication, mismatched expectations, and avoidable friction between equally capable engineers. In this talk, I will explore how MBTI - a 16 personality assessment - can be used as a practical communication framework for engineer teams - not as a personality label or hiring tool, but as a shared language to understand different working and communication preferences. I will share how small adjustments in communication can dramatically improve team effectiveness. This session focuses on actionable, engineer-friendly techniques to reduce friction, improve collaboration, and build high-performing teams.

Only 23% of employees globally are engaged in their work. Burnout has hit 66%, and the average age for experiencing it is now just 32. On top of that, only 44% of managers have ever been trained in how to lead people, despite being directly responsible for 70% of team engagement outcomes. We don’t have a productivity crisis, we have a leadership crisis. In this 20-minute keynote, I share how the Process Communication Model (PCM), a behavioural tool originally developed for NASA, helps founders and managers lead people the way they’re actually wired. This is not a PCM training session. It’s a practical, story-led talk designed to shift how leaders think about performance: not as something to push for, but something to unlock through smarter communication, deeper understanding, and earlier stress recognition. Using PCM as a lens, I’ll walk the audience through: Why people disengage (and how to see it coming) Why one-size-fits-all motivation fails modern teams How to recognise when a communication style is misfiring Audience members will reflect on their own teams in real-time, explore the gap between how they lead and how people want to be led, and leave with a clear insight: you don’t manage performance, you manage people.

Most career advice tells you to climb the ladder linearly. I’m going to tell you why I jumped off it - and how that "demotion" generated the highest returns of my career. I was a Startup IC who jumped into a large organization management, only to realize I lacked the technical "scale" to lead effectively. I will walk you through my decision to swing the "Manager Pendulum" back to an IC role, and how each swing compounded my skills: The Investment: I swung back to IC to learn "Operational Reality." Because of my management background, my impact compounded - I knew exactly which battles to pick and which to ignore, navigating large company politics better than my peers. The Cost: It wasn't free. I faced the "Mentorship Vacuum," the "High-Performance Trap," and a job market that viewed my non-linear path with suspicion, making offers harder to get. The Dividend: When I swung back to Big Tech management, I wasn't starting from scratch. I was starting with Compound Interest -armed with technical confidence and high-fidelity empathy that only a recent IC possesses. I will show you why the pendulum isn't a back-and-forth motion - it's an exponential curve upwards.

Large or fast-growing engineering organizations often foster silos, separating teams, hindering collaboration, and reducing the impact of collective knowledge and opportunities for technology sharing. But you don’t need a management mandate or a big budget to start breaking them down. I’ll share five approaches I’ve successfully used that can be used by individual contributors and managers to bridge gaps between different parts of your organization. From fostering intrinsically driven grassroots communities of practice and running internal tech conferences or hackathons to encouraging cross-team code contributions and rotating engineers between products, each approach is designed to be flexible, scalable, and low-cost. I’ll also share personal experiences and the impact these approaches had on the organization. Whether you're an experienced individual contributor or a manager, this talk will offer practical ideas and inspiration to drive change and encourage you to not give up, even when you experience setbacks.

Session Abstract Nearly three-quarters of IT professionals in Europe report burnout or work-related stress, with similar patterns emerging globally, but here's the uncomfortable truth: While we're automating code, we're atrophying our brains. This talk bridges neuroscience and software engineering to reveal a paradox threatening every developer's career: Chronic stress doesn't just make you tired, it physically shrinks your hippocampus, reduces neuroplasticity, and destroys the cognitive flexibility that makes you valuable in an AI-saturated job market. Drawing from cutting-edge 2025-2026 research in neuroplasticity and my work at the intersection of psychology and organizational systems, I'll demonstrate: - The Cognitive Flexibility Crisis: How elevated cortisol from chronic stress impairs working memory and cognitive flexibility; exactly the skills AI can't replace - The "Use It or Lose It" Reality: When chronic stress disrupts neuroplasticity, it leads to cognitive inflexibility, emotional dysregulation, and poor decision-making; passive AI dependency accelerates this decline - The Brain Training Protocol: Concrete, science-backed interventions that reverse stress-induced brain damage and build cognitive resilience Participants will walk away with: - A Neuroplasticity Audit: Self-assessment tools to measure your cognitive load and brain health risk factors - The 3R Recovery Framework: Results → Responses → Responsibility for active AI collaboration that strengthens neural pathways - Practical Brain Hacks: From strategic deep work blocks to meditation techniques that develop more gray matter in the hippocampus and reduce it in the amygdala This isn't wellness theater, it's career survival. In 2026, the most successful developers won't be those who write the most code. They'll be those who've trained their brains like elite athletes, building the cognitive endurance to thrive alongside AI, not be displaced by it.

The recruitment market is changing dramatically — again — and those of us in HR are barely noticing. Rather than addressing and adapting to these significant changes, we are ignoring them completely. The shift to conversational job searching alone is turning our recruitment process on its head. With the addition of AI agents, we must rethink our processes and our technological setup. In this lecture, I would like to draw attention to the underestimated changes and highlight the dramatic nature of the situation, so that no one is caught unawares.

Many companies and startups are looking to hire AI Native talent, but only few are experienced how to interview them. If you struggle to define approach and your interview starts with “Have you used Github Copilot?” question – welcome to my talk, where I will share experince I earned in 2025 after interviewing over 100 team members globally for enterprise IT projects. You will learn real-world lessons on how GenAI has reshaped the hiring criteria for developers, QAs, architects and managers, and what are the best practices (including questions and practical tasks) to distinguish vibe-coders from AI-Native software engineers.

Alternative title - Hiring Technical Leaders: Build or Buy? When it comes to (technical) people leaders, should we nurture and promote from within the organization or hire from the outside? What is the not-so-hidden cost of both of those approaches (fresh ideas, different approaches to people and technical leadership, leadership maturity vs organization maturity); technical leadership - building credibility within a team; leading at different sizes and different maturity of organization - the role of a leader in a start-up vs scale-up vs large organization.