TechLead Conference 2025: AI in Orgs

Agile isn’t just a methodology—it’s a mindset. And in the era of Generative AI, that mindset is evolving. This session explores how Agile teams can integrate GenAI to boost collaboration, speed, and innovation across the software development lifecycle. Learn how AI can assist with user stories, sprint planning, retrospectives, and more—acting as a tireless team member. Real-world examples, prompt engineering tips, and the top tools to supercharge your stand-ups, backlogs, and burndown charts will be shared.

How does it feel when your team more than doubles in less than a year? Like your brain was put in a blender and someone kept pressing the button. I joined a 7-engineer, 40 employee, startup in August, by May we were 14 engineers, 100 people, and I was a manager. These are my lessons.

"Entropy Tolerance" is an original idea to help technical leaders navigate AI adoption decisions. This concept measures how much AI-generated uncertainty your systems and processes can handle before they break. Learn this decision-making framework to guide your teams on when to embrace AI and when to proceed with caution.

Becoming a Lead or Staff Engineer doesn’t mean having all the answers—it means knowing how to ask better questions, how to support others, and how to make smart decisions in ambiguity. In this talk, I’ll share what I’ve learned (and unlearned) stepping into IC leadership roles: how to grow influence without managing people, how to admit “I don’t know” with confidence, and how to use AI tools to save time, focus in where it's important and scale my impact. It’s less about being the expert, and more about enabling others—and yes, that’s the job.

While AI tools excel at generating code, they can't navigate the human complexities that make or break technical decisions. As senior engineers, our value increasingly lies not in what we code, but in how we lead teams through technical choices that reflect our values and culture.Through real examples of how values conflicts disguise themselves as technical disagreements, this session explores what tech leaders need to preserve and strengthen as AI reshapes our industry. You'll discover practical tools for uncovering team values and learn to make technical decisions that account for both code and culture in an AI-driven world.

Gregor will be sharing both positive and negative trends that he's seeing, speaking with many engineering leaders across the industry. He'll also share how the role of engineering leaders is evolving, and tips on what to do to be a successful engineering leader in the age of AI.

How a tech COO uses prompt engineering to run financials, manage teams, and scale operations with clarity.I’ll share practical use cases of prompt engineering from inside Epicmax, a growing dev agency. I’ll walk through how I use LLMs for:- Financial reporting, forecasting, and margin control- Managing team capacity and delivery risks- Tracking KPIs and creating short-term and long-term strategy- Sales proposals, launching new products, finding market fit- Open source products management- Communicating with the company owner, pitching and validating ideas
You’ll get real prompts, workflows, and decision-making strategies to make AI a true part of your leadership toolkit - not just another tool on the shelf.

Advancements in AI have brought us to the cusp of a major shift in how we interact with the web. The future of frontend will no longer be about just rendering pixels; it will be about rendering intent.In this keynote, we'll dive into how AI will further close the gap between human intent and digital experience. AI is moving us beyond static components, empowering developers to create deeply personalized and intuitive web applications with a level of efficiency we've only ever dreamed of. Join me to explore how AI empowers frontend developers to craft richer user experiences through more thoughtful customization, smarter user-experience testing at scale, and accelerated innovation.

AI is changing the game - fast. Designers, PMs, and even non-technical teams can now prototype, build and ship without touching a line of code. Tools like Lovable, Figma AI, Copilot and other AI agents are blurring the boundaries between design, implementation and deployment. So where does that leave developers?It’s tempting to say our jobs are being replaced. But maybe we’re just entering a new phase.As AI handles more of the visible, repetitive tasks, UI layouts, boilerplate code, even connecting APIs—the complexity doesn’t disappear. It moves. The real work is shifting behind the curtain: into orchestration, logic, validation, governance and performance. This talk explores how engineering is evolving in a world of AI-generated everything. It asks: with great power (of automation) comes what kind of responsibility? How do we maintain control, accountability and quality when anyone can “build” something that runs?You’ll walk away with a clear view of what AI can and can’t (yet) replace, why human judgment is more critical than ever and how developers can reclaim ownership, not over pixels, but over systems. If you’ve ever wondered, “What’s my role when everyone’s a builder?”—this talk will help you answer that.

AI is no longer just a tool, it’s becoming an active participant in our systems. From autonomous agents making decisions to AI models accessing sensitive data, the question is no longer “Can we adopt AI?” but “How do we control what AI can do?”In this session, I will show how Identity Governance is the missing link between responsible AI adoption and system complexity management.- Why AI adoption introduces new identity risks and hidden   attack surfaces- How to simplify AI system complexity through strong governance models- What tech leads must know about governing AI-powered systems and machine identities- Real-world patterns for controlling AI access using tools like Microsoft Entra ID and Privileged Identity Management (PIM), Security Co-pilot, DSPM for AI and more This talk blends strategy with practical examples, offering a clear pathway for leaders who want to scale AI securely without increasing risk or complexity. Whether you are navigating AI integration, leading tech teams, or scaling enterprise platforms, this session will arm you with actionable insights to build trust in your AI-driven ecosystem. AI is here to stay. The leaders who govern it wisely will define the future.

What if you let AI code alongside your devs—would it speed things up or slow them down? At Modus Create, we ran a 3-month internal experiment to find out. Two squads were tasked with building the same app: one squad had full access to AI coding agents like GitHub Copilot and Cursor, while the other worked with zero AI assistance. The results? Surprising, nuanced, and extremely relevant for any enterprise thinking about bringing AI tools into their software delivery process. In this session, we'll share productivity metrics, insights on code quality, cultural impact, and what we learned about pairing developers with AI. You'll walk away with a real-world perspective and a practical guide on how to scale AI-powered development across your engineering org—without the hype.