Inflearn’s first Grokbot course: turn a one-person company into a 20-person AI organization, with Grokbot enabling 24/7 automated operations that replace every task done on a computer.

What matters now is not the ability to ask AI good questions. It is the ability to delegate tasks to AI, verify the results, and organize multiple Agents to produce outcomes.

Elon Musk identified
digital labor (white-collar work), which involves handling information with a keyboard and mouse, as the area that will be affected first in the AI era.

And now that change is going beyond simply asking ChatGPT questions.

Grokbot is an AI agent that has its own computer,
opens a browser, runs a terminal, edits files, moves between multiple applications,
and can take over real tasks from people.

The more important change comes next.

Rather than using a single Agent,
you can create multiple Agents specialized in roles like Engineer, Manager, Researcher, and Designer
and build an organization that keeps moving by handing work off to one another.

In the recently released official GPT6 Astra video, you can see AI controlling computer tasks through spoken instructions without directly writing prompts.

xAI introduced Grok Bot as an AI teammate that actually operates 24 hours a day, explaining that it had been used internally for tasks such as sales outbound, marketing campaigns, office operations, and bug fixes.

But let’s imagine something a little dangerous.

One day, the colleague sitting next to you not only automates their own work,

What if they analyzed even the repetitive tasks you are performing
and handed them over to Grokbot?

That person may not be working eight hours a day.

An Engineer Agent that codes in your place,

a Research Agent that researches papers and competitor materials,
a Reviewer Agent that validates the results,
and a Manager Agent that distributes tasks,

Create agents for UI/UX, HCI research, design, and more.

You may also be performing multiple tasks simultaneously.

At this point, competitiveness is not simply that...

“I know how to use AI”

가 아닙니다. 앞으로 더 중요해질 능력은

The ability to design which tasks should be done by humans,
which tasks should be delegated to Agents,
which Agents should be created,
how the Agents should collaborate, and
how to verify the results

It is. Everyone will need the ability to orchestrate agents with ownership, while adopting an executive and managerial mindset.

Why Grokbot Now?

Grok’s direction of development also deserves attention.

xAI’s Grok 4.6 is being developed to enhance not only general chat, but also software engineering, knowledge work, tool use, and agentic tasks.

Elon Musk has also mentioned the possibility that xAI could achieve AGI with Grok 5. No one can say for certain whether this will actually lead to AGI.

However, what matters is not the exact AGI release date.

As models continue to become more intelligent,
the proportion of tasks that people must handle themselves will decrease,
while the proportion of work that people define, assign, and verify through AI will likely increase.

So I believe that, going forward, developers too...

Coding Skills + Agent Engineering + AI Management

will likely be required together.

This course doesn’t wait for that change.

Build your own small AI organization directly with Grokbot, available now.

Recommended for people like these

I especially recommend this if you have ever had thoughts like these.

• “Couldn’t I make an Agent work continuously for 24 hours?”

• “I want to build a more autonomous structure than Claude Code or Cursor.”

• “How do I manage multiple Agents running simultaneously?”

• “I want AI to be able to directly use the browser or computer.”

• “How do I connect them if I create separate Development and Manager Agents?”

• “Can’t I make the project continue moving forward while I’m asleep?”

• “How should MCP and external tool plugins be used in an actual Agent architecture?”

• “I want to create a structure where one person manages multiple AI team members.”

If even one of these applies to you, this course is exactly the next step.

After completing the course, you will be able to do more than simply explain Grokbot’s features;

You will be able to design a 24/7 autonomous Multi-Agent system that performs real-world tasks.

Specifically, you will be able to do the following.

• Install Grokbot and delegate real work to Agents

• Designing Prompts / Rules / roles and responsibilities for each Agent

• Have it perform Computer, Browser, Terminal, and File tasks.

• Connecting External Tools with Plugins / MCP

• Operating an Engineer Agent in a Real-World Service Codebase

• Distribute tasks through CEO / Manager Agents

• Designing Agent-to-Agent Task Handoffs

• Managing Context and Shared State Across Multiple Agents

• Turn repetitive tasks into Routines

• Run Agents for extended periods through an Autonomous Loop

• Monitor the status and results of other Agents with a Watcher Agent

• Build a Multi-Agent organization by combining multiple specialized Agents

• Designing an AI Company structure that develops new ideas into real products

Becoming not the person who performs every task, but the person who builds a system that performs the tasks.

Features of This Course

01. Rather than explaining features, we assign real tasks.

Give the Agent tasks based on actual service codebases and projects, let it fail, fix it, and run it again.

We show you the process of operating an Agent like a real team member.

02. Not just a single Agent—we build an AI organization.

Most Agent tutorials end with a single Agent.

However, for complex tasks, rather than having a single Agent handle planning, development, review, research, and management all
at once,

You can design specialized Agents with separate roles to collaborate.

In this course,

Engineer → Reviewer → Manager → Watcher

specialize Agents like this,

We cover the process of connecting them through Context, Shared State, and Handoff
to develop them into a small AI organization.

03. Move beyond a structure where “a person has to keep entering prompts.”

The true leverage of an AI agent
does not lie in merely improving the quality of a single response.

A structure that finds, executes, verifies, and continues with the next task without human intervention creates far greater leverage.

So in the latter part,

Routine
→ Autonomous Loop
→ Watcher
→ Multi-Agent

We expand autonomy in this order.

04. The Course Itself Is an Experiment

The course does not merely create simple examples.

We cover the process of communicating new MVP ideas to Agents
and actually developing them into products.

Not only what can be delegated to Agents,

How far you should not delegate,
where humans need to intervene,
and how to build a validation structure

We’ll cover that together as well.

This is important. The goal of automation is not to create many Agents, but to build a system that can repeatedly produce reliable results with less human intervention.

You will learn about the following topics.

Silicon Valley Survivor | American Snail

Drawing on experience and expertise gained at the forefront of the Global Tech Scene, I show non-majors how to overcome technological barriers and become the owners of their businesses.

• Currently, founder of a Silicon Valley AI coding agent startup

  • Operating the self-developed AI tool 'Snailer CLI' (20K+ downloads)

  • Selected for the Google for Startups Program

• Formerly an engineer at major U.S. tech companies and promising startups

  • Gave up at the final stage with Amazon to start a company

  • Silicon Valley AI Fintech Startup Engineer

  • OpenAI / Meta / Apple / Adobe / Amazon Full-Stack Fellowship

  • Domestic search engine portal, fintech development

  • AI startup AR/B2B/SDK development

• Proven teaching expertise

  • Double major in Computer Science and Business Administration at a four-year university in Seoul, with extensive startup experience

  • Produced over 2,100 students to date, with 4.6K+ followers on SNS threads and 500+ Substack followers.

Do you have any questions?

Notes Before Taking the Course