[Basic Part 2.5] OpenClaw.AI Master Class: Fundamentals of Multi-Agent Team Design and Role Separation

If you follow OpenClaw Parts 1 and 2, you eventually end up making a single agent do everything. As you do this, there comes a moment when prompts get tangled, memory gets mixed up, folders get messy, and you feel stuck, not knowing how to organize things anymore. This lecture is the "Introduction to Multi-Agents (Part 2.5)," designed to help you move one step further from that point. While maintaining a single bot, we will separate roles into two agents—planner and editor—and connect each agent to different workspaces and Telegram forum topics. You will personally build a structure where "different agents respond depending on which room you speak in." By following the hands-on practice, you will have the following in your environment: - A configuration file defining two agents: `content_planner` and `content_editor`, - A content folder structure where planning and drafting are separated, - A Telegram group chat where different agents are attached to specific forum topics, - And one actual draft of an Inflearn course introduction created through the collaboration of the two agents. In short, this is a practical class that helps you design the first step of upgrading your Telegram bot from a "single AI assistant" into a "small AI team with divided roles."

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49 learners

Level Basic

Course period Unlimited

Kevin

Business Productivity

orchestration

multi-agent

AI Agent

openclaw

Business Productivity

orchestration

multi-agent

AI Agent

openclaw

News list

kevin

Notice of minor changes in the Openclaw onboarding stage.

Hello.

OpenClaw is still undergoing frequent version updates. There are about two changes that would be good for you to know, so I am sharing them with you.

Regarding the system configuration files automatically generated in the config folder before onboarding
1. In our lecture, the config folder was completely empty before OpenClaw onboarding, and the OpenClaw system configuration files were automatically generated once onboarding was complete. However, after the update, even before onboarding, running the docker-compose.yml file just once will cause OpenClaw to generate the basic required system configuration files in the config directory. Even if files generated before onboarding exist, you can proceed with the practice following the sequence shown in the lecture.
Regarding changes to the options selected by users during the onboarding stage
There are some options where the names or other details selected by users during the onboarding stage have been slightly changed or removed, so I will list the changes below.
1. Section 3 > Lesson 11: Hello OpenClaw First Boot and System Check
  - Changes in the OpenClaw Onboarding Hands-on Practice
    - 4 minutes 40 seconds
      - Config handling configuration option
        (Existing) Select Update values -> (Changed) Select Review and update
      - How do you want to provide this API Key? configuration option
        (Changed) This option itself has been removed, so you can ignore it in the lecture video.
      - Default model configuration option
        (Previous) You could select directly from all models -> (Changed) Select Browse all models, then manually enter the text 'google/gemini-2.5-flash' in the next step
      - How do you want to hatch your bot configuration option
        (Existing) Select Do this later -> (Change) Select Hatch later

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