The first wave of GenAI adoption often followed a simple pattern: take a frontier LLM, throw all available data into its context, and ask it to reason. But real-world applications are now proving that this approach quickly hits hard limits in scale, cost, accuracy, and reliability. This keynote explores the emerging architecture patterns that are replacing monolithic “all-in-one” prompting with modular, specialized systems:

• Right Tool for the Right Job. Complex domains require pipelines that combine information extraction, structured representations, reasoning modules, and conversational layers, instead of a single model trying to do everything at once.
• Multi-Agent Collaboration. Recent research shows that agents coordinating across smaller, specialized models outperform single-agent LLMs for reasoning and decision making – mirroring real-world teamwork.
• Domain-Specific Models. Tailored models continue to deliver superior accuracy and safety compared to general-purpose ones, particularly in regulated or knowledge-heavy domains.
• Governance and Trust. As systems grow in complexity, governance frameworks and domain-specific red teaming are becoming essential to ensure safe, unbiased, and compliant deployments.

We’ll illustrate these trends with the case study of longitudinal patient journeys, where success requires moving beyond “stuff the chart into an LLM” toward modular, multi-agent, domain-specific architectures. Attendees will leave with a clear map of the architectural trends shaping GenAI in 2025 and practical insights into how to apply them across industries.