Recently, the talk of "building AI employees with Claude Code to run a company" has been quite popular in some AI circles.
AI Sales.
AI Marketer.
AI Editor.
AI Researcher.
AI Secretary.
AI Accounting Assistant.
AI Engineer.
AI Business Lead.
You create something like company departments within Claude Code.
You give each AI a role.
You have them read files.
You give them instruction manuals.
You have them learn work procedures.
As needed, you have them handle research, writing, organization, improvement, reviews, code fixes, and document creation.
Hearing just this, it sounds quite futuristic.
And it's not just a delusion.
By actually using Claude Code, you can read files within a project, refer to rules, execute commands in the terminal, and proceed with multiple tasks continuously. If set up well, you can leave a significant portion of the tedious routine work that humans used to do every time to the AI.
For example, you can do things like this:
Have it create article plans.
Have it read past articles to match the writing style.
Mass-produce SNS post drafts.
Draft sales emails for different clients.
Extract tasks from meeting minutes.
Update internal manuals.
Find bugs in code.
Write tests.
Create release notes.
Summarize competitor research.
Create text for inquiry responses.
Organize project progress.
At this point, you certainly want to call them "AI employees."
AI takes over part of the work that humans used to do. Moreover, it's not just a one-off chat; it can operate with a certain amount of context and rules within the project.
This mechanism is simply amazing.
In fact, if used by someone who knows how to use it properly, it's quite powerful.
For sole proprietors and small companies, it has the impact of effectively expanding a small team.
Engineers, editors, marketers, business owners, content creators, and solo founders can significantly change their work speed depending on how they use it.
That's why "AI employees with Claude Code" is not just a buzzword.
It's truly amazing.
It truly has potential.
I think it's a mechanism at a level that changes the way of working for some people.
However.
This is the important part.
Seeing this, there's no need to panic and think, "I have to make an AI employee too."
In fact, most people should probably not go straight to Claude Code.
Because building an AI employee with Claude Code is a story for the much later stages of AI utilization. It's not the first step. It's a place for people who have already understood how to work with AI to move to next, not the starting point.
If you get this wrong, it will be a major detour.
An "AI Employee" is Not About Hiring an AI
The term "AI employee" is quite catchy.
There's a CEO, an AI salesperson, an AI editor, an AI marketer, and an AI secretary, and everyone works autonomously. Humans just give instructions. Then the AIs proceed with the business on their own, and the company runs.
Many people probably have that image.
But the reality behind it is much more mundane.
Building an AI employee is not about giving the AI a personality.
It's not about telling the AI, "You are an excellent employee."
It's not about giving the AI a department name.
The essence is to decompose the business and organize it into a form that the AI can execute.
For example, it's the same when delegating work to a human employee.
Just saying "Do the sales" won't make them move properly.
Just saying "Manage SNS nicely" won't stabilize results.
Just saying "Organize the company documents" won't let them know what to do and how.
Humans can read the room, ask their boss, or judge from the surrounding atmosphere. But AI basically depends on the given context and instructions.
Therefore, what an AI employee needs are things like this:
What is the work for?
Who is the work for?
What information should be used?
What information must not be used?
In what order should it proceed?
What kind of output is the correct answer?
What expressions are prohibited?
At what stage is human confirmation necessary?
How to revert if it fails?
What constitutes completion?
Verbalize these and place them where the AI can refer to them.
Run that within Claude Code.
This is the reality behind AI employees.
In other words, AI employee-ification is not a "mechanism where AI works on its own."
To be precise, it is a "mechanism where human work patterns are decomposed to a state where AI can execute them."
If you try to create an AI employee without understanding this, there's a very high probability of failure.
Why Claude Code is Amazing
Why is Claude Code attracting so much attention?
It's because, unlike ordinary chat AIs, it can enter the work environment itself.
Ordinary chat AIs basically converse on a screen.
You ask a question.
You get an answer.
You have it write a text.
You have it write code.
You have it come up with ideas.
Of course, that alone is convenient enough.
However, Claude Code goes a step further.
It reads files within the project.
It looks at the relationship between multiple files.
It thinks of necessary revision plans.
It actually rewrites files.
It executes commands.
It runs tests.
It reads errors and fixes them.
It refers to configuration files and documentation.
It learns rules for each project.
In other words, it's not just a consultant; it's closer to a worker.
This is quite powerful in the world of development.
Because it can proceed with modifications, confirmations, tests, and improvements while looking at the entire codebase.
And when you apply this thinking to business operations, it becomes "AI employee-like."
For an article production project, you place past articles, structure templates, writing style rules, prohibited expressions, and product information.
For a sales project, you place customer information, negotiation notes, proposal materials, email templates, and FAQs.
For a recruitment project, you place job descriptions, candidate evaluation criteria, interview questions, scout texts, and company briefing materials.
For a business planning project, you place KPIs, meeting minutes, business plans, competitor research, and financial notes.
Then, you ask Claude Code:
"Read this material and prepare for the next negotiation."
"Match the style of past articles and create a new article structure."
"From these meeting minutes, organize decision items and assigned tasks."
"Provide improvement plans for this LP, including competitor comparisons."
"Investigate the cause of this code error and provide a fix plan."
Then, it becomes a very practical movement.
This is certainly powerful.
It becomes a significant weapon for those who can use it.
So, "AI employees with Claude Code" is not something to be ridiculed.
Rather, it's highly likely that part of future work will move in this direction.
However, the problem starts here.
The fact that this mechanism is amazing and whether everyone should do it right now are completely different things.
The More Amazing the Mechanism, the Heavier the Prerequisites
The story of building AI employees with Claude Code is complicated because, despite its flashy appearance, the necessary preparation behind the scenes is quite mundane.
To build an AI employee, you need at least the following:
First, you need a work pattern.
What is the flow of work every time?
What are you looking at to make judgments?
Where do you get lost?
What kind of output is a passing grade?
What kind of mistakes are likely to occur?
Without this, you can't hand it over to the AI.
Next, you need to organize information.
Where is the product information?
Where is the customer information?
Where are past success stories?
Where are the internal rules?
Are old and new information distinguished?
Is information that the AI can read and information that it must not read separated?
This is also necessary.
Furthermore, you need judgment criteria.
Why is this text good?
Why does this sales email hit home?
Why does this proposal pass?
Why is this design weak?
Why is this code fix dangerous?
Why is this customer response rude?
You must verbalize what humans judge intuitively to the extent that you can convey it to the AI.
And permission design is also necessary.
Files the AI can read.
Files the AI can edit.
Files the AI must not touch.
Commands the AI can execute.
Things the AI must not send on its own.
Tasks that always require human approval.
If you are sloppy here, it's dangerous.
Because Claude Code operates in a place closer to the work environment than ordinary chat. As much as it is convenient, if used sloppily, sloppy changes and sloppy automation will also occur.
With ordinary chat, even if it fails, it ends with the text on the screen.
But with Claude Code, depending on the settings and operation, it can proceed to file changes, command execution, and integration into workflows.
Therefore, building an AI employee with Claude Code is not just about "bringing in a convenient AI."
Business design.
Information organization.
Instruction design.
Permission management.
Review system.
Recovery in case of failure.
These mundane tasks come as a set.
If you skip this and jump in thinking "AI employees are amazing," you usually won't be able to master it.
Most People are Bad at Chatting Before Building AI Employees
Here, I'll say something quite blunt.
Most people haven't even mastered ordinary chat AI, let alone Claude Code.
They ask ChatGPT or Claude questions somewhat vaguely.
They ask it to "make it nice."
They say "make it easier to understand."
They say "make it professional."
They look at the resulting answer and think, "Something's not right."
But they can't explain what's different.
They can't say how to fix it next.
In the end, they fix it themselves.
And then they think, "AI is kind of subtle."
This is not because the AI is weak, but because the instructions are weak.
For example, suppose you have it write an article.
"Write an article about Claude Code."
With just this, the AI will write a plausible general theory.
But that's likely not the article you want.
In reality, this kind of information is needed:
Who is the article for?
Is the reader a beginner, a business owner, or someone knowledgeable about AI?
Is the purpose education, sales, enlightenment, or aiming for a viral hit?
Is the tone calm, somewhat provocative, or like a real-life experience?
Do you give the conclusion first or pull them along?
What misunderstandings do you want to clear up?
What kind of after-reading feeling do you want?
Which expressions do you want to avoid?
Which claims do you want to strengthen?
Just by giving this, the output changes significantly.
Sales emails are the same.
"Write a sales email" is weak.
Who is the recipient?
Is it the first contact, after a negotiation, or after a lost deal?
What is the recipient's challenge?
Is our purpose a reply, setting up a negotiation, or document confirmation?
What is the word count?
How much should the salesy feel be suppressed?
How many characters should the subject line be?
What is the next action?
If you say this much, the AI is quite usable.
Conversely, if someone who can't say this much proceeds to Claude Code, their AI utilization won't suddenly become good.
Claude Code is not a magic spell that turns sloppy instructions into perfection.
Rather, there is a risk of expanding the work range while keeping the instructions sloppy.
Therefore, before an AI employee, you should first master ordinary chat.
This is not a detour.
Rather, it's the shortest route.
Mastering Ordinary Chat Doesn't Mean Becoming a Prompt Artist
When I say "master chat," it might sound like I mean learning prompt tricks.
But that's not it.
Mastering ordinary chat means acquiring the way of working with AI.
Don't try to make the AI produce a finished product in one go.
First, brainstorm.
Next, have it create a structure.
Fix that structure.
Next, have it write the first draft.
Point out weak parts.
Have it provide improvement plans.
Organize it into the final draft.
Finally, have it check it.
People who can create this flow are strong.
For example, for article production, proceed like this:
First, convey the reader and the purpose.
Next, have it provide multiple introduction plans that the reader would be interested in.
Choose the best flow from among them.
Next, have it create a heading structure.
Confirm the role of each heading.
Next, have it write the body.
In the middle, correct it by saying "the conclusion is too early here," "make this part more expectant," or "reduce technical terms here."
Finally, polish the title, beginning, and ending.
If used this way, the AI is quite strong.
Conversely, if you only ask it to "write an article with 10,000 words" from the beginning, the AI will produce a plausibly long text, but it's likely to deviate from the goal.
This is not the AI's fault.
It's a problem with the way of working.
AI is stronger when used as a partner for thinking and production rather than as a finished product manufacturing machine.
And this "way of working with AI" is needed just as it is in Claude Code.
Even in Claude Code, instead of suddenly saying "do everything,"
First, read the current situation.
Don't edit yet.
Provide a work plan.
Identify risks.
Tell me which files you will touch.
Separate parts that require human confirmation.
Execute after that.
Finally, summarize the changes.
Such a way of proceeding is important.
People who don't have this sense in ordinary chat are also dangerous in Claude Code.
If You Automate Without Knowing Claude's Characteristics, You'll Usually Have an Accident
What's important in using AI is knowing the quirks of each model.
Claude has its strengths.
ChatGPT has its strengths.
Gemini has its strengths.
It's not a story of which one is absolutely superior.
There are fits and misfits depending on the work.
Claude often feels strong in organizing when given a long context, naturalness of text, tone adjustment, polite summaries, and output based on multiple conditions. In particular, it is compatible with tasks such as reading existing documents and improving them to match that atmosphere.
On the other hand, since it returns quite natural text even with sloppy instructions, it can sometimes look like the degree of completion is high.
This is the scary part.
The output is plausible.
The text is beautiful.
The structure is also organized.
So, at first glance, it looks good.
But if you read it carefully, the business premises might be off, customer understanding might be shallow, or judgments might be too safe.
This is not a story about Claude being bad.
It's a story common to AI in general.
Therefore, before automating, you first need to know Claude's quirks.
What kind of instructions make it strong?
How much context should be passed to increase accuracy?
When is it likely to give a safe answer?
When should you have it ask confirmation questions?
What kind of work can be left to it?
What kind of judgments should humans still look at?
Experience this in ordinary chat.
If you suddenly automate with Claude Code, you will be integrating it into your business without understanding these quirks.
That's like suddenly entrusting important business to a newcomer whose personality, strengths, and weaknesses you don't know.
Even an excellent newcomer needs onboarding at first.
You need to teach them the company rules.
You need to teach them the characteristics of the customers.
You need to share past failures.
A boss's review is also necessary.
AI is the same.
Before Creating an "AI Employee," First Have the AI Reproduce Your Work
What you should do before going to Claude Code is quite simple.
First, have the AI reproduce your work in an ordinary chat.
For example, if you are writing an article, have the AI write an article.
However, instead of completing it in one go, proceed while decomposing how you usually think.
What kind of reader are you assuming?
Why are you handling that theme?
What do you want them to feel first?
Where do you create a sense of expectation?
Where do you introduce a sense of discomfort?
Where do you show your true feelings?
Where do you urge the reader to take action?
Convey this to the AI.
And for the resulting text,
The conclusion is early here.
The explanation is light here.
The reader's emotions don't move here.
More specific examples are needed here.
This part is too provocative.
This part is conversely too weak.
This expression doesn't sound like me.
This heading is too ordinary.
Correct it like this.
This interaction itself becomes preparation for AI employee-ification.
Because in order to have the AI reproduce your work, you must verbalize your work's judgment criteria.
It's the same with sales.
What are you looking at before a negotiation?
Which of the customer's statements do you consider important?
At what timing do you propose?
What kind of person do you not push hard against?
What kind of person do you show examples to?
What kind of counterargument do you respond to and how?
Explain this to the AI.
It's the same for recruitment.
It's the same for accounting.
It's the same for marketing.
It's the same for customer support.
Entrusting work to AI means verbalizing the tacit knowledge of your work.
If you proceed to Claude Code without doing this work, the AI employee will just be an "atmospheric employee."
Once You Have a Winning Pattern in Chat, It's Finally Time for Claude Code
Suppose some business starts to go well to some extent in ordinary chat.
For example, weekly article planning.
Daily SNS post creation.
Drafting follow-up emails after negotiations.
Extracting tasks from meeting minutes.
Summarizing research results.
Improving existing materials.
Code review.
README updates.
FAQ maintenance.
Here, for the first time, it's Claude Code's turn.
Because what you are doing every time in chat has the potential to be systematized.
You are explaining the same context every time.
You are referring to the same files every time.
You are having it output in the same format every time.
You are doing the same checks every time.
You are making the same corrections every time.
These things can be moved to the Claude Code side.
For example, write the rules within the project.
Decide on the output format.
Organize the files to be referred to.
Clarify prohibited items.
Create a checklist.
Document the necessary work procedures.
Make a folder structure that is easy for the AI to work with.
Only then does Claude Code show its true potential.
In other words, the order is like this:
First, try it in chat.
Find instructions that work.
Create a work pattern.
Use it repeatedly.
The pattern solidifies.
Move it to Claude Code.
Semi-automate it.
Make it AI employee-like as needed.
This flow is natural.
Conversely, you must not suddenly automate a business that has never succeeded in chat with Claude Code.
That's like suddenly putting a business that you don't know if it will work or not onto a factory line.
AI Employee-ification Should Be Thought of in "Business Units" Rather Than "Employees"
Another important point.
It's better not to be pulled too much by the term "AI employee."
If you try to create an "AI Sales Manager" or "AI Marketing Lead" from the beginning, the abstraction is usually too high.
If you're going to leave it to AI, you should first think in business units.
Instead of an "AI Sales Manager,"
An "AI that creates follow-up emails after negotiations."
Instead of an "AI Marketer,"
An "AI that reads past posts and provides 10 post themes for the next week."
Instead of an "AI Editor,"
An "AI that only improves the introduction of an article."
Instead of "AI Accounting,"
An "AI that organizes receipt filenames according to rules."
Instead of an "AI Recruitment Lead,"
An "AI that reads candidate information and creates questions to be confirmed in an interview."
It can be this narrow at first.
In fact, narrower is better.
Because if the business range is narrow, the input, output, and evaluation criteria all become clear.
Don't make the work you leave to the AI large from the beginning.
Start small.
Humans confirm.
If there are no problems, expand a little.
Keep only what worked.
Discard what was subtle.
Beyond this accumulation, as a result, something "AI employee-like" is created.
You don't create an AI employee from the beginning.
As a result of accumulating small AI tasks, it starts to look like an AI employee.
This order is important.
What Most People Should Do First
Looking this far, I think the mechanism of building AI employees with Claude Code looks quite attractive.
In fact, it is attractive.
It's an amazing mechanism.
It's quite powerful for those who can use it properly.
But what most people should do at this stage is not to tinker with Claude Code.
First, master ordinary chat.
ChatGPT is fine.
Claude is fine.
Gemini is fine.
Anyway, train your ability to ask AI to do work in an ordinary chat.
What should you give the AI for a good output?
How much background should you explain?
In what order should you ask to increase accuracy?
Where should you insert confirmations?
How should you give correction instructions to make it better?
How do you verbalize your work's judgment criteria?
How do you template good instructions?
Do this.
What you can't do in an ordinary chat, you can't do in Claude Code either.
Rather, only those who have increased what they can do in an ordinary chat will grow all at once when they use Claude Code.
In sports terms, this is like basic training.
Before doing flashy plays in a match, you need the basics of running, stopping, kicking, throwing, seeing, and judging.
Claude Code is close to a quite advanced match environment.
But chat is basic training and, at the same time, a real battle.
If you underestimate this, you will become a person who just has flashy tools.
What to Do to Master "Ordinary Chat"
So, specifically, what should you do?
You don't need to do anything difficult.
First, try giving the work you do every day to the AI.
Writing emails.
Fixing text.
Coming up with ideas.
Summarizing materials.
Organizing meeting notes.
Creating SNS posts.
Creating inquiry replies.
Brainstorming sales talks.
Improving product descriptions.
Providing perspectives for competitor comparison.
It's fine to start from around here.
At that time, don't seek a finished product all at once.
First, explain the background.
Next, convey the purpose.
Next, convey the output conditions.
Next, have it provide plans.
Look at those plans and correct them.
Finally, template it.
For example, for an article, ask like this:
"I want to write an article on this theme. The readers are sole proprietors and business owners who are interested in AI but haven't touched Claude Code yet. If I give the conclusion first, they will drop off, so first I want them to think 'this mechanism is amazing.' After that, I want to show the mundaneness of the reality behind it, and finally land on 'most people should master ordinary chat first.' First, just create the structure."
At this point, don't have it write the body.
Next, look at the structure and,
"Make the beginning more exciting."
"Don't suddenly deny it here."
Acknowledge the greatness of Claude Code first."
"After that, bring it to 'but the prerequisites are heavy.'"
"In the end, make it a realistic roadmap, not a lecture."
Correct it like this.
When you do this much, the AI gets quite close to the goal.
Do this interaction many times.
And save the instructions that worked.
This becomes the basic physical strength for AI utilization.
People Who Will Truly Make a Difference with AI Employee-ification
In the future, I think the number of people who master AI employees and AI agents will increase.
However, what will make a difference is not "people who know the latest tools."
What will make a difference are people who can delegate work to AI.
People who can decompose work.
People who can verbalize the purpose.
People who have judgment criteria.
People who can show good and bad examples.
People who can review.
People who can improve when it fails.
People who can template the same work.
People who can separate the range that can be left and the range that must not be left.
Such people are strong when they have Claude Code.
Conversely, for the following people, it's still too early:
They don't know what to ask the AI.
They can only say "make it nice" every time.
They can't explain the quality of the output.
They can't put their business flow into words.
They haven't organized past success stories.
They try to use the AI output as it is without reviewing it.
They think everything will become easy if they automate it.
If you build an AI employee in this state, it probably won't go well.
An AI employee is not an existence that will save the company on its own.
Under an excellent boss, it becomes a strong subordinate, but under a boss who can only give sloppy instructions, it becomes just an output machine.
In other words, before creating an AI employee, you first need to become an AI boss.
The Correct Order from Now On
"AI employees with Claude Code" is certainly amazing.
However, it's not the first thing you should do.
The correct order is this:
First, use AI to the fullest in ordinary chat.
Next, know the characteristics of Claude.
After that, create your work pattern.
Template the instructions that worked.
Find business that you use repeatedly.
From there, semi-automate with Claude Code.
Finally, make only the necessary parts AI employee-like.
This flow is the most solid.
If you try to build an AI employee all of a sudden, most people will get frustrated.
But if you start from ordinary chat, anyone can improve little by little.
And people who have acquired the ability to ask AI to do work in chat will grow all at once when they proceed to Claude Code.
Because what you do in Claude Code is, after all, the same.
Convey the purpose.
Pass the context.
Create rules.
Decide on procedures.
Confirm the output.
Improve.
Make it into a reusable form.
Make what you were doing in ordinary chat easier to automate, more continuous, and in a place closer to the work environment.
That is Claude Code.
Finally
The mechanism for building AI employees with Claude Code is incredibly amazing.
There's no doubt about it.
If designed properly, the way of working for solo founders and small teams will change significantly.
Various tasks such as article production, development, sales preparation, document organization, research, and internal document maintenance will become faster.
You will be able to use AI in a form closer to a worker rather than just a consultant.
However, that is the advanced version.
For many people, what is needed right now is not "building an AI employee."
First, master ordinary chat.
Ask the AI to do work.
Brainstorm with the AI.
Have the AI create a structure.
Have the AI draft.
Have the AI improve.
Have the AI check.
In that process, verbalize your work's pattern.
When you can do this, you will also see the characteristics of Claude.
What kind of writing is Claude good at?
What kind of instructions increase accuracy?
When does it become safe?
How much can be left to it, and from where should humans look at it?
Once you understand that, you can proceed to automation.
There's no need to rush to build an AI employee.
First, become a person who is good at asking AI to do work.
After that, expand the range you leave to the AI.
"AI employees with Claude Code" certainly feels like the future.
But the entrance to that future is surprisingly mundane.
Chatting normally.
Asking normally.
Correcting normally.
Patterning normally.
Only those who have mastered that will truly become strong with Claude Code.
