Conversation Routines: A Prompt Engineering Framework for Task-Oriented Dialog 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 sophisticated behavioral patterns and decision logic while preserving natural conversational flexibility.
Results show that CR enables domain experts to design conversational workflows in natural language while leveraging custom enterprise functionalities (tools) developed by software engineers, creating an efficient division of responsibilities where developers focus on core API implementation and domain experts handle conversation design.
While the framework shows promise in accessibility and adaptability, we identify key challenges including computational overhead, non-deterministic behavior, and domain-specific logic optimization. Future research directions include enhancing system robustness, improving scalability for complex multi-agent interactions, and addressing the identified limitations across diverse business applications.
The full article is freely accessible on my blog:
It’s a detailed read that requires some attention, but I hope you’ll find it insightful! I’d love to hear your thoughts or any experiences you’d like to share—feel free to comment!
UPDATE - 18/02/2025
The original article has been published on arXiv! The updated version submitted to arXiv includes experimental results, minor refinements and formatting adjustments: https://arxiv.org/abs/2501.11613
#ConversationAgenticSystems #ConversationRoutines #LargeLanguageModels #LLM #AIAgents #PromptEngineering #ConversationDesign #WorkflowAutomation #Automation #NaturalLanguageProgramming #Programming #SoftwareDevelopment #ArtificialIntelligence
Conversational LLM-based Applications Specialist
1 个月My latest article has been published on arXiv! Compared to the version available on my blog, convcomp.it, the version submitted to arXiv includes minor refinements and formatting adjustments. Thank you all for your valuable feedback and support! https://arxiv.org/abs/2501.11613
Data Scientist and Generative AI Engineer.
2 个月This is a great read! Conversational routines seem an important way to create a competent system with enough flexibility to interact with us humans
Technology Leader, Entrepreneur, and Educator | CTO of oTTomator | YouTube Influencer
2 个月Lot of great insights here, thank you for this Giorgio!