Name: TechLead Conference 2025: AI in Orgs
Start: 2025-09-18T14:00:00.000Z
End: 2025-09-19T19:00:00.000Z

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.

Supercharging Agile Teams with Generative AI

Kanika Tolver

Technical interviews are struggling to keep pace with the reality of modern software engineering in a time of AI agents. LLMs and their offshoots can now easily solve take-home assessments, and traditional DSA formats reward memorisation over real-world skills. So how can we accurately and fairly assess the technical abilities of engineers as part of a standardised hiring process? In late 2024, I began a redesign of the technical interview process at HelloBetter, a mental health tech company in Berlin. The aim was to create a format that actually reflects day-to-day engineering work, while also being time-conscious, inclusive, and accepting of the presence of AI in developer workflows. In the process, we created "The McDougall Method": a new and emerging framework for better interview processes which is quickly forcing technical leaders to rethink their AI mitigation strategies.

Transforming Your Tech Interviews in the AI Agent Age: The McDougall Method in Detail

Anna J McDougall

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.

Leadership Insights From Growing 2X in 8 Months

Swizec Teller

"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.

Entropy Tolerance: The Most Important Software Question You Aren't Asking

Tony Alicea

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.

I Don’t Know Everything, and That's the Job

Maya Shavin

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 AI is Impacting Engineering Leadership

Gregor Ojstersek

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.

Prompt-Driven Operations: COO’s Playbook

Anastasiia Zvenigorodskaia

Overview:        AI adoption brings system complexity, especially when autonomy, orchestration, and cloud-native microservices collide. Based on my published research and enterprise experience, this workshop breaks down the complexity of deploying agentic systems responsibly. This workshop is aimed at senior engineers who are navigating cloud-native architectures while introducing autonomous AI components, without a clear blueprint.Contents:1. The New Complexity Stack    a) Microservices, AI, and third-party code generators    b) Where system chaos starts and why it escalates 2. Understanding Agentic AI Behavior    a) Autonomy, memory, and hallucination risk    b) Real-world examples from financial decision support 3. Design Patterns for Clarity    a) Guardrails for system observability    b) Tradeoffs: orchestration vs code generation 4. Scalability Without Burnout    a) What senior engineers must lead: governance, ethics, reliability     b) Designing systems that scale safely under load 5. Takeaways    a) Agentic adoption roadmap    b) How to test and monitor non-deterministic AI    c) Alignment with team velocity and business outcomes

From Chaos to Clarity: Managing Agentic System Complexity in Cloud-Native FinTech

Sibasis Padhi

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.

The Intent-Driven Web: How AI is Reshaping Frontend Development

Shaundai Person

I have watched well-meaning programmers, technical leaders, and their managers pour their hearts and souls into managing so-called "technical debt" and I worry that they're not getting very far. I believe that a fundamental misunderstanding from the very beginning has led almost everyone down a dark, painful road towards bitter disappointment, endless bickering, failed projects, mounting Imposter Syndrome, and debilitating learned helplessness. Fortunately, I think we can reverse these trends, at least for ourselves, with a combination of techniques from Extreme Programming and general psychology. No, really! You might be surprised to learn that everyone truly wants the same thing, but that some complexities of the human mind have made that difficult to see. Overcoming this fundamental misunderstanding fits squarely into the category of "simple, not easy", so if we want to make progress, then we'd better start now!

Overcoming the Fundamental Misunderstanding About Technical Debt

J. B. Rainsberger

Most teams are still using AI as a glorified autocomplete, but the future is already here. I'll show you how engineering teams work when coding agents handle implementation while humans focus on guidance and oversight.I have built coding agents that have our team guidelines embedded - no more style guides or coding standards docs. You'll see agents that automatically follow our Next.js 15 patterns, Nx monorepo structure, shadcn/ui conventions, and more of our tech stack, while humans make small corrections that improve all future work.This isn't about replacing engineers - it's about scaling the possibilities of your team through agent multiplication instead of hiring and restructurizations. I'll demonstrate the workflow where the agent implementation is followed by human refinement, creating consistent quality that doesn't depend on human variability.

The Future of Engineering Teams: Humans Guide, Agents Code

Konrad Bujak

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.

From Access Control to AI Control: Why Identity Governance Is Key to Scaling AI in the Enterprise

Cynthia Akiotu

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.

Vibe Coding at Enterprise Scale: What Happens When AI Joins Your Dev Team

Wesley Fuchter

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.

Rethinking Engineering Roles in the Age of AI Disruption

Keren Fanan

TechLead Conference

I'm attending TechLead Conference 2025 – get your free remote ticket and join me there

In this edition of TechLead Conf we will focus on two pressing topics in 2025: adopting AI in organizations and challenges around it from tech leadership perspective, and how Senior engineers and leaders can work on reducing systems complexity. Learn directly from industry practitioners and real case studies ranging from startups to The Big Tech.

TechLead Conference 2025: AI in Orgs

FocusReactive

Hygraph

TechLead Conference 2025: AI in Orgs

Event about leadership and seniority