Register or log in to access this video
As leaders we have been tasked to go all-out with AI: both in terms of our products and also our productivity. This talk outlines what you should be thinking of doing for your team, your product, and, importantly, yourself with AI.
The hype surrounding Large Language Models (LLMs) has reached a fever pitch, making it challenging for technology leaders to discern actionable strategies from speculative promises. This talk cuts through the noise, offering a pragmatic operator’s perspective on how to genuinely leverage LLMs within your organisation.
We’ll cover specific, real-world applications for boosting your engineering team’s output, from automating mundane tasks to enhancing code quality and fostering rapid prototyping. You’ll learn how to identify high-impact product features powered by LLMs that deliver quick wins, along with practical considerations for data privacy, model selection, and deployment.
Crucially, we’ll discuss how you, as a leader, can personally leverage AI for better decision-making, thinking and strategic planning, ensuring you leave with concrete steps to implement and see immediate value from AI across your team, product, and leadership approach.
Key takeaways
- Develop a clear, actionable AI strategy for your team: Learn how to assess the readiness of your engineering function for LLM adoption and identify practical tools and workflows to boost productivity and innovation without overwhelming your team.
- Identify impactful LLM applications for your product: Understand methodologies for pinpointing genuine problems LLMs can solve within your product roadmap, moving beyond surface-level integrations to create meaningful user value.
- Navigate the personal leadership shift with AI: Gain insights into how your role as a technology leader evolves with the rise of AI, including strategies for continuous learning, ethical considerations, and fostering a culture of responsible AI experimentation.
