Expert Panel Rewriting Software with AI Agents, GenAI & What’s Next? | WSO2Con Barcelona 2025
AI Summary
Panel Discussion on AI and Multi-Agent Systems
Panelists Introduced:
- Malit Jing: VP of Research at WSO2, focusing on AI for the past 5 years.
- Victor Dia: Principal Research Software Engineer at Microsoft Research, working on the Autogen framework for building AI agents.
- Yasaman Kazeni: Director of Data Science at Capital One, with experience in AI solutions across retail and finance.
Key Discussion Points:
- Introduction to AI Agents:
- Transitioning from traditional programming to multi-agent systems.
- Importance of programming-level abstractions for building agent systems.
- Development and Production Challenges:
- Challenges of moving AI models from research to production highlighted by Yasaman Kazeni.
- Need for alignment between the AI solution and business needs, including user experience considerations.
- Evaluation Metrics for AI Systems:
- Importance of robust evaluation metrics during development and after deployment.
- Iterative improvements based on user feedback and telemetry data.
- Production Challenges Highlighted:
- Examples of predictive models that required extensive integration into business processes (e.g., personalizing user experiences in retail).
- Multi-Agent System Design:
- Recommendations for using pipelines and workflows for reliability.
- Potential future shift towards more autonomous AI systems.
- Product Development Insights:
- Corporate-level AI teams ensuring best practices and cross-compatibility across business units.
Conclusions:
- Focus on user needs and problems to be solved, beyond just implementing AI technology.
- Need to ensure that AI solutions fit well within existing workflows, emphasizing user experience, and effective metric evaluation to assess real-world performance and improvements.