Digital Leadership: Exploring the Similarity in Human Leadership and AI Agent Prompting

3 min read

I wanted to share a concept I've been employing while building AI systems in my own time, I call it Digital Leadership. It bridges our beliefs in how traditional human leadership is thought about and how we prompt AI agents in systems to perform tasks. When architecting and building an agentic system, you need to be clear about three things: expectations, processes, and communication channels, just as you would in a workplace to make everyone supported and able to do their best work.

I believe Digital Leadership is an important part of the puzzle in solving the challenge of dependable AI Agent Systems.

Key Guidelines for Digital Leadership

Here are some key guidelines when applying good Digital Leadership:

  • Purpose: Like any leader with a clear vision for their team, we must define the purpose of our AI system. What do we want our agents to achieve?

  • Guidelines: We need to provide agents with guidelines on how they should communicate with each other and with users. This includes tone, level of formality, and any limitations.

  • Skills: What specific tasks should the agents be able to perform? Should they generate suggestions, automate tasks, or provide explanations?

  • Step-by-Step Instructions: For complex tasks, we may need to give agents detailed instructions on how to proceed.

  • Examples: Providing agents with examples of how to handle different situations can help them learn and evolve.

  • Error Handling and Limitations: We need to instruct agents on how to handle situations where they lack sufficient information or encounter problems. This also includes when an agent fails and a waiting agent is asynchronously waiting.

  • Feedback and Iteration: Just as a good leader is responsive to feedback, we need to create systems where AI agents can learn from their mistakes and improve their performance.

Communication Structures for AI Agents

We can use different structures to control communication and workflow among agents, just like in real life:

  • Hierarchical Structures with a designated leader coordinating the work.

  • Decentralized Structures where agents collaborate more equally.

  • Dynamic Structures where leadership can shift depending on the situation.

Prompting Best Practices

General things to consider when prompting a single AI agent:

  • Be Specific: AI agents are good at following instructions but not at interpreting vague or ambiguous directives.

  • Use Clear Syntax: Structure instructions in a way that is easy for agents to understand.

  • Provide Examples: Concrete examples help agents understand what is expected of them.

  • Focus on "Do" Instead of "Don't": It's more effective to instruct agents on what to do rather than what not to do.

Getting Started

When constructing an AI agent system the requirements dictate what is best for the situation. But, I believe this will be a timeless tip for anyone building and maintaining these solutions. A good place to start is with OpenAI's Swarm to explore multi-agent systems.

Are you still interested or have questions? Contact me! (Especially if you are working on asynchronous AI agent systems, I would love to chat.)

Further Reading