How I Built 4 AI Agents in OpenClaw Modeled on Real People I Know

This content describes building 4 AI agents in OpenClaw, each modeled on real people (including Tom, head of product). The agents work collaboratively within the platform to simulate real-world team dynamics and decision-making processes. The approach demonstrates how AI agents can be personalized based on actual individuals' characteristics, expertise, and working styles to create more authentic multi-agent systems.

Key Points

• •Create AI agents based on real people's personalities, expertise, and working styles for authentic team simulation
• •Use OpenClaw platform to orchestrate multiple AI agents working together collaboratively
• •Model agents on actual team members (e.g., product heads, domain experts) to replicate real organizational dynamics
• •Design agents with distinct roles and responsibilities matching their real-world counterparts
• •Enable agents to interact and make decisions as a cohesive team rather than in isolation
• •Leverage personal knowledge of individuals to inform agent behavior and communication patterns
• •Test multi-agent workflows by simulating real team scenarios and decision-making processes

Workflow Diagram

Concepts