AI Challenge Sri Lanka 2026 : Mindset of an AI Engineer - Workshop 02
August 12, 2026 · 1:30 PM - 3:30 PM @ Online event
Description
Mindset of an AI Engineer was an online knowledge session held online as part of the AI Challenge Sri Lanka 2026, organized by AI Driven Sri Lanka under IEEE Young Professionals Sri Lanka. Aimed at university students, young professionals, and AI Challenge participants, it explored how experienced AI engineers think, work, and solve problems, going beyond tools, libraries, and frameworks. The session focused on the thinking habits that set strong AI engineers apart from those who only know how to use models. It covered how to approach a problem before choosing a technique, how to decide whether AI is the right solution at all, and how to define success in clear, measurable terms. Participants learned why understanding the user, context, and data must come before any modelling, and why many failed AI projects fail because the problem was poorly defined, not because the technology was weak. A large part of the session addressed the practical realities of building AI systems: working with imperfect, limited, or biased data, handling uncertainty, and running structured experiments. It examined everyday engineering trade-offs, such as accuracy versus speed, performance versus cost, and innovation versus maintainability, and explained why simple, reliable, well-scoped solutions often outperform complicated ones. Throughout, the session stressed iterating quickly, learning from failed experiments, and improving step by step rather than chasing perfection on the first attempt. The session also highlighted the human side of engineering: curiosity, continuous learning, adaptability, and clear communication in a fast-changing field. It addressed responsible AI practices, including awareness of bias, reliability, transparency, and the real-world consequences of deployed systems, along with the need to prioritize users and business impact over technical novelty. Participants also received career guidance on building skills, portfolios, and real project experience. Finally, participants were encouraged to apply this mindset to their own AI Challenge projects, focusing on meaningful problems and practical, working solutions. The session gave teams valuable industry perspective as they progressed through the challenge and a clearer view of what it takes to grow as an AI engineer.
Agenda
Time Item 7:00 – 7:10 PM Welcome and speaker introduction 7:10 – 7:35 PM What it means to think like an AI engineer: problem-first thinking and knowing when to use AI 7:35 – 8:05 PM Working with real-world data, experimentation and iteration 8:05 – 8:30 PM Responsible AI, trade-offs and building for real users 8:30 – 8:50 PM Q&A with participants 8:50 – 9:00 PM Closing remarks and vote of thanks