Conversation Routines: A Prompt Engineering Framework for Task-Oriented Dialog Systems
Giorgio Robino

TL;DR
This paper presents Conversation Routines, a prompt engineering framework that enables the development of task-oriented dialog systems with LLMs, allowing domain experts to design workflows naturally while developers implement core functions.
Contribution
The paper introduces a systematic prompt engineering framework for task-oriented dialog systems that combines natural language specifications with custom functions, improving workflow design and behavioral consistency.
Findings
CR effectively encodes complex behavioral patterns.
CR allows domain experts to design workflows in natural language.
Framework demonstrates flexibility in two proof-of-concept systems.
Abstract
This study introduces Conversation Routines (CR), a structured prompt engineering framework for developing task-oriented dialog systems using Large Language Models (LLMs). While LLMs demonstrate remarkable natural language understanding capabilities, engineering them to reliably execute complex business workflows remains challenging. The proposed CR framework enables the development of Conversation Agentic Systems (CAS) through natural language specifications, embedding task-oriented logic within LLM prompts. This approach provides a systematic methodology for designing and implementing complex conversational workflows while maintaining behavioral consistency. We demonstrate the framework's effectiveness through two proof-of-concept implementations: a Train Ticket Booking System and an Interactive Troubleshooting Copilot. These case studies validate CR's capability to encode…
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Taxonomy
TopicsSpeech and dialogue systems · Multi-Agent Systems and Negotiation · AI in Service Interactions
MethodsFocus
