Building Fast & Accurate Conversational Agents Beyond Function Calling

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Traditional function calling approaches for LLM-powered conversational agents suffer from unpredictable execution, poor debugging capabilities, and the "prompt and pray" problem that kills development velocity. This talk introduces Process Calling - a superior paradigm where LLMs invoke stateful, multi-step processes rather than atomic tools.

Unlike function calling's stateless operations, Process Calling enables agents to maintain context and execute deterministic business logic across conversation flows. Using real production examples, we'll show how Rasa's CALM framework implements Process Calling to build conversational agents that actually work in customer-facing scenarios. Come learn why the future of customer facing agent development isn't about better prompts—it's about better abstractions.

Key Takeaways:

  • Limitations of Function Calling – Understand why traditional LLM function calling leads to unpredictability, poor debugging, and slow development cycles.
  • Introduction to Process Calling – Learn how invoking stateful, multi-step processes improves reliability and maintainability.
  • Rasa’s CALM Framework in Action – See real-world implementations of Process Calling for production-ready conversational agents.
  • Future of Agent Development – Discover why robust abstractions, not just better prompts, are the key to scalable customer-facing AI.

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