After a 30-year hiatus, I returned to playing Dungeons & Dragons (D&D), this time with AI companions like ChatGPT and Claude. This experience offered a unique insight into agentic AI and its applications in enterprise software. D&D’s complexity—with its character creation, spell lists, and intricate rules—parallels that of enterprise systems. My hypothesis is that if AI can adeptly play D&D, it could navigate the complexities of enterprise software just as effectively.
The AI Dungeon Master, or ChatDM, has significantly improved over time. Initially, its understanding of D&D mechanics was rudimentary, but it has since enhanced its grasp of the rules and storytelling. However, success with these AIs requires effort in prompt crafting and feedback. The AI often relies on clichés due to its training data, which raises the concern of redundancy in enterprise tasks if generic models are used.
Significantly, the app’s architecture surrounding the AI model is crucial for achieving unique outcomes. The Model Context Protocol (MCP) provides a framework for embedding AI into applications, allowing for more dynamic interactions. By defining tools, resources, and prompts, MCP enables AIs to execute tasks with reasoning capabilities. My coding efforts revealed that while tool functionality is vital, the way they are described and instructed holds greater importance for effective reasoning.
In conclusion, the experience with D&D underlined that context and creativity are essential when deploying AI in enterprise environments.
Source link
