September 18 - 19, 2025

Online

TechLead Conference 2025: AI in Orgs

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

Event about leadership and seniority

Full remote ticket included with Multipass.

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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.

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English versionEN

Supercharging Agile Teams with Generative AI

28 min

Supercharging Agile Teams with Generative AI

Kanika Tolver

Career Rehab LLC

Kanika Tover discusses supercharging agile teams with AI, emphasizing an agile mindset, adaptability, and collaboration. Generative AI tools enhance productivity gains, development speed, and efficiency in agile teams. AI integration improves planning, development, testing processes, feedback facilitation, and communication efficiency. Core AI platforms like OpenAI and Chat GPT-5 are crucial for text generation. Future trends include AI evolving into team assistants and agents for tasks. Real-life AI applications focus on efficiency and productivity enhancement. AI collaboration improves meeting efficiency, technical debt management, and customer focus.

team productivity artificial intelligence

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

18 min

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

Anna J McDougall

Author "You Belong in Tech: How to Go from Zero Programming Knowledge to Hired"

Anna McDougall discusses transforming tech interviews in the AI agent age and the flaws in traditional technical interviews due to lack of control in remote settings. Addressing challenges in technical interviews with AI integration and the need for adapting traditional assessment methods to combat AI influences. Balancing technical interview difficulty, focusing on psychological safety, and using a modern, realistic, and indicative approach in the McDougall method. Organizing engineer for meetings, pairing engineer for interactions, and use of all tools allowed in the McDougall method. AI tools are essential in development. McDougall method: Intro, warmup, pair programming, reflection, wrap up. Shorter interviews save candidate time. Intro warmup: 10-15 mins. Pair programming checks for implementation, 35-45 mins. Create repository based on a real codebase for pair programming. Create Mimic codebase for testing. Send repository with failing tests. Tasks represent different levels: fresh junior to senior plus. Start candidates one level under. Psychological safety in tasks. Levelling based on task difficulty. Reflecting on candidate understanding and feedback. Emphasizing timeline in wrap up. Encouraging McDougall Method adoption and experimentation.

career artificial intelligence

Leadership Insights From Growing 2X in 8 Months

15 min

Leadership Insights From Growing 2X in 8 Months

Swizec Teller

Plasmidsaurus

Product-market fit is like being pushed by the market, needing more. A game analogy illustrates teamwork dynamics in handling tasks. Communication is key in team growth, allowing delegation for collective success. Experienced team members focus on clarity, delegation, and accountability. Prioritize assigning tasks to team members based on expertise. Embrace the role of a side quest specialist for long-term or short projects. Engage in mentorship and explain reasoning to foster team independence and growth. Mentorship occurs organically between tasks, influencing work approaches. Trust your team to make decisions by explaining your rationale. Mentor one skill at a time to ensure effective learning and application. Focus feedback, encourage newbies, address weak points of experts to enhance performance. Focus on feedback for beginners and experts, emphasize outcomes and timely feedback to enhance performance. Realize the importance of quick utility, user stories, and outcome-focused work. Utilize user stories, documentation, and flexible roadmaps for effective planning and decision-making. Embrace change, document ideas, focus on user stories, and leverage backlogs for effective planning and adaptation.

scalability team productivity

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

20 min

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

Tony Alicea

Tony is a bestselling Udemy and Pluralsight author, known for his online courses such as "JavaScript: Understanding the Weird Parts"

In software development, the discussion focuses on understanding determinism vs. non-determinism and its impact on reliability and trustworthiness. The examples provided highlight the implications of non-deterministic behavior, especially in critical systems like language model autopilots on planes. Technical leaders are advised to consider entropy tolerance when integrating AI and LLMs into business processes using a decision framework. Different entropy tolerance levels exist, influencing the need for AI-human collaboration based on the process's value and tolerance. The decision-making framework for AI integration emphasizes the importance of human involvement in processes with varying levels of entropy tolerance.

best practices

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

21 min

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

Maya Shavin

Published author, international speaker and an open-source library maintainer of frontend and web projects

Maya Shavin's tech journey, the importance of collaboration and growth, asking quality questions for problem-solving, prioritizing root causes, embracing uncertainty, admitting uncertainty and growing influence, influencing team growth, smart prioritization, building trust, efficient task management, smart delegation, mastering prioritization with AI assistance, empowering learning, and scaling impact.

career artificial intelligence

Staying Human in the Age of AI: What Tech Leaders Need to Preserve

20 min

Staying Human in the Age of AI: What Tech Leaders Need to Preserve

Amy Dutton

RedwoodJS

The speaker reflects on the evolution of AI, its impact on coding accessibility, and the value of understanding human complexity in decision-making. Leadership challenges with junior developers highlight the importance of human dynamics and autonomy. Teamwork involves exploring values and navigating conflicts, emphasizing the significance of aligning team values in decision-making processes. Implementing human-centered technical decisions and fostering value alignment within teams are key strategies for successful adaptation and community building.

artificial intelligence

How AI is Impacting Engineering Leadership

23 min

How AI is Impacting Engineering Leadership

Gregor Ojstersek

Engineering Leadership newsletter

Gregor discusses the impact of AI on engineering leadership, addressing concerns and sharing insights from industry discussions. Teams are feeling less motivated due to sensationalistic AI predictions causing fear of missing out. Company leaders face challenges managing unrealistic AI expectations and beliefs. Guidance is provided for leaders to avoid FOMO, start with small AI experiments, and prioritize good culture. Developing AI strategy involves aligning with engineering, embracing skill convergence, and educating on AI tools.

artificial intelligence

Prompt-Driven Operations: COO’s Playbook

23 min

Prompt-Driven Operations: COO’s Playbook

Anastasiia Zvenigorodskaia

Epicmax

Anastasia Zmiengorodzka discusses using GPT as a strategic partner, leveraging her tech background at EpicMax. She outlines enhancing tech leadership skills with GPT, emphasizing clear communication, trend identification, and business integration.

team productivity

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

36 min

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

Shaundai Person

Netflix

The speaker recounts a frustrating drive-through experience on a family road trip, showcasing the challenges of AI implementation in noisy environments. Emphasis is placed on user-centric software development and the importance of strategic AI application. The discussion delves into user navigation difficulties, data collaboration hurdles, and the potential of generative UI for personalized experiences. Leveraging LLM for dynamic UI generation based on user intent is highlighted, along with its capabilities in contextual understanding and task orchestration. The use of varied prompts to enhance LLM performance and the significance of AI integration in user-centric testing are also explored.

web development

Overcoming the Fundamental Misunderstanding About Technical Debt

19 min

Overcoming the Fundamental Misunderstanding About Technical Debt

J. B. Rainsberger

jbrains.ca

JB Rainsberger discusses the impact of technical debt, emphasizing the cost of delaying essential work and its implications on feature delivery. Reflecting on past attempts to address technical debt and the diverse interpretations of its meaning, highlighting the challenges in managing technical debt and the resulting dysfunction in teams. Exploring the true nature of technical debt as a reflection of current understanding and the ongoing risk of a mismatch between programmers and code. Managing technical debt without specialized techniques or tools, addressing distortions, and collaborating to face ongoing risks. Improving code alignment and understanding reduces future regrets. Embracing regular code realignment reduces resistance to necessary changes. Test-driven development ingrains managing technical debt in daily programming.

team productivity

Rethinking Engineering Roles in the Age of AI Disruption

14 min

Rethinking Engineering Roles in the Age of AI Disruption

Keren Fanan

MyOp

Discussing the impact of AI on engineering and the role of developers. Keren Fanan, CEO of MyApp, shares insights on AI's potential to empower engineers and reduce dependency on manual coding. AI's role in development: balancing AI automation with human expertise. Engineers post-AI: orchestrating human-AI code interaction, with examples from Uber and Netflix. Balancing ownership of AI-generated code with different ownership assignments and connecting AI and developer-generated code. AI as a teammate, organizational shift to AIR, tips for management: creating AI squads, having weekly AI rituals, prioritizing transparency, and determining code ownership by the creator.

career

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

22 min

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

Wesley Fuchter

Modus Create

The discussion covers the integration of AI tools in software development and the productivity gains observed in an experiment at Modus Create. AI significantly enhanced productivity and code quality, with a Python engineer successfully adapting to TypeScript with AI assistance. Human oversight is crucial for optimal results in AI coding, ensuring quality and complementing human expertise. Clear communication with AI, contextual feeding, effective task management, and workflow optimization were highlighted as key factors in leveraging AI tools for software development.

tooling

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

15 min

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

Cynthia Akiotu

A bank faces fraudulent transactions caused by a poisoned prompt from an AI co-pilot. AI plays a vital role in sectors like health, retail, and enterprise, but its integration poses challenges in identity and access management. Generative AI vulnerabilities lead to shadow AI emergence, with independent agents creating access control and data security challenges. Identity governance is crucial for managing AI, with a playbook emphasizing Identification, Security, Governance, and Auditing. Microsoft's Entra Agent ID ensures visibility and policies for AI agents to prevent disclosure of sensitive information.

artificial intelligence

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

Recording pending

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

Workshop

Sibasis Padhi

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

design systems

The Future of Engineering Teams: Humans Guide, Agents Code

Recording pending

The Future of Engineering Teams: Humans Guide, Agents Code

Workshop

Konrad Bujak

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.

team productivity

TechLead Conference 2025: AI in Orgs

Event about leadership and seniority

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