TechLead Conf Amsterdam 2026: Adopting AI in Orgs Edition

The speaker emphasizes the importance of engineers becoming multipliers in the AI era, highlighting the evolution of tools and methodologies in software development. The shift towards engineering leadership necessitates essential skills like feedback, delegation, and project leadership. The changing landscape of engineering roles reflects a rise in tech leads and product engineers. Adaptability and the ability to learn fast are crucial in the evolving demands of the industry. Strategies for career growth include showcasing skills, embracing AI adoption, and fostering a culture of continuous learning and adaptation.

Tech leads play a crucial role in AI value creation. Global AI spending in 2026 to reach $2.5 trillion. A Kinsey report reveals low impact on profits despite massive AI investments. More than 90% of organizations adopt AI, yet lack real value creation. AI initiatives often lack global impact due to local focus on metrics, not end value. Misunderstanding the value creation akin to Toyota's success. Freddy Ballet discovers Toyota's secret in Europe. Taichi Ono's unconventional methods for value creation in France lead to significant productivity gains and quality improvements. Realizing significant value through collective problem-solving and innovative strategies at Toyota. Focusing on Lean principles to create value through collective problem-solving and adapting learnings for AI integration. Lean Tech Manifesto emphasizing value for customers and creating a continuous learning system for AI transformation, driving value creation through customer-centricity and daily learning opportunities. Addressing bottlenecks in project delivery through AI, Achieving quality with one-shot prompting, Fostering a learning organization with Kaizen approach in AI environment. Utilizing blueprints to streamline code review processes, Embracing a holistic approach to AI value creation, Importance of metrics in evaluating organizational and product performance.

The Talk delves into the challenges faced with polyrepos, emphasizing issues with managing multiple apps and dependency hell. It highlights the benefits of monorepos in efficient code sharing and version management, advocating for their simplicity and effectiveness. The advantages of monorepos include atomic changes, large-scale refactoring, and strong code reuse culture. Monorepos offer benefits such as simplified dependencies, unified CI-CD, enhanced collaboration, and efficient refactoring. The impact of monorepos on legacy code bases includes reusability, traceability, early issue detection, and enhanced CICD processes. The discussion also touches on the challenges of context switching in a polyrepo environment, the limitations of AI in polyrepo versus monorepo settings, and the importance of building context layers for enhancing AI capabilities in monorepos.

Richard Rodenkemper, senior software engineer at Sentry, discusses ensuring quality with AI. GitHub data shows exponential growth in coding. Concerns arise about the reliability of coding agents versus human engineers. Impact of AI and Cloud on code production and app quality is questioned. Challenges in code reliability despite increased production are highlighted. AI as a quality tool in software development. Importance of reliability for product success highlighted. AI's strengths in handling data and searching code base discussed. Examples of AI usage in code reviews and quality assurance at Sentry shared. AI efficiency in endpoint deprecation and system updates highlighted. AI's assistance in migrating design systems and reducing notifications using Cloud Code emphasized.

The speaker delves into code editor development, emphasizing collaboration between humans and AI. Discussions revolve around adapting to technological changes while facing persistent cognitive limitations. Balancing cognitive load in software development is crucial for optimal task completion. Focus and alignment in software development are essential for effective problem-solving. Addressing challenges of team alignment in AI-driven environments is crucial to avoid creating legacy code bases. Pair programming enhances collaboration, accountability, and learning within development teams. Valuing collaboration, trust, and autonomy fosters speed and efficiency in software development. Leadership strategies focus on promoting autonomy, mastery, and purpose while addressing burnout. AI impact on productivity and collaborative coding practices are reflected upon, emphasizing the benefits of pair programming. Effective onboarding and encouraging pair programming adoption contribute to better problem-solving and team collaboration.

Shifra, founding developer relations engineer at Render. Render is the cloud for builders. How to relate to users who are not people? Company growth challenges with AI recommendations affecting signups. The challenges of AI recommendations in contrast to traditional SEO. Impact on team operations and product development. Need for a strategic shift towards agent-centered developer experience. Developing interface design for agents, content portfolio importance, and human gate validation. The evolving role of agents in product consumption and the necessity for a fundamental shift in development focus. Facing challenges head-on, emphasizing agentic experience, and prioritizing system self-correction for productive agent and human interactions at Render.