If You Don’t Want to Be Replaced by AI, Stop Acting Replaceable

By Kristi Short, CEO · CH2 Solutions

There is a lot of anxiety about AI replacing jobs. I understand why. We are watching these tools do work that not very long ago, we assumed required a person.

Lately I’ve been thinking about the issue from a different direction.

If you are worried about being replaced by AI, you should probably be asking yourself what value you are adding after AI does its part.

I ask that because I’m starting to see some concerning behavior. People are using AI to produce work and then passing that work along without really reviewing it, questioning it, or in some cases even understanding it.

I recently saw documentation prepared for a client about a project. It looked finished. There were links throughout the document to supporting information. Except when someone actually clicked on them, the links were empty.

We’ve also heard stories about engineers using AI to generate code and then being asked what the code does.

“I don’t know. Claude wrote it.”

I have no problem with Claude writing the code. In fact, I think engineers who aren’t learning how to use AI effectively are going to find themselves at a disadvantage.

“I don’t know” is the part that bothers me.

If you are the engineer responsible for putting code into a product, you need to understand what that code does. You need to know why it’s there, how it interacts with the rest of the system, and what might happen if it fails. AI can help you get there faster, but it doesn’t eliminate that responsibility.

The same applies to almost every profession.

If your involvement in a piece of work amounts to asking AI to do something, copying the result and sending it along, you have removed most of your own professional value from the process. If you consistently demonstrate that your judgment isn’t necessary, you probably shouldn’t be surprised when someone eventually asks whether you are necessary either.

That may sound harsh, but I think it’s an important distinction in the conversation about AI and jobs.

Think of your AI agent as a very talented new hire

I’ve started thinking about AI agents a little like extremely capable college graduates in their first jobs.

Imagine you hired someone who was incredibly smart, had read more than any person possibly could, worked at extraordinary speed, and could turn around an assignment almost immediately.

You’d be thrilled to have that person on your team.

But would you give them an assignment on Monday morning and send their work directly to a client Monday afternoon without looking at it?

Probably not.

You would give them context. You’d explain what you were trying to accomplish and why. You’d review what they produced. When they made a bad assumption, you’d correct it. When something didn’t make sense, you’d ask questions.

As they learned, you’d give them more responsibility.

That isn’t micromanagement. It’s management.

So why would we treat an AI agent differently?

One of the mistakes I think we're making right now is assuming that because AI can produce sophisticated work, it should automatically be trusted to produce finished work.

Those aren't the same thing.

AI can give you an impressive answer while missing context that would be obvious to someone who has worked with a particular client for five years. It can confidently head down the wrong path because the original question contained a bad assumption. It can produce something polished enough that no one thinks to check whether the links actually work.

And perhaps most importantly, it doesn't have to answer for the result.

You do.

The opportunity isn't to do less. It's to do higher-value work.

This is where I think the AI productivity conversation sometimes goes off course.

Let's say something used to take you three hours and AI can now get you 80% of the way there in 30 minutes.

What should happen to the other two and a half hours?

Obviously, some of that time should become productivity. We should be able to do more. That's one of the reasons these tools are so exciting.

But I also think some of that time should make the work better.

If AI writes the first draft, you have more time to improve the thinking behind it. If it generates routine code, an engineer has more time to think about architecture, security, and edge cases. Remember the 80/20 rule? Human behavior and user attrition fall in the 20% more often than we would like. If it produces the initial analysis, a business leader has more time to question whether the assumptions are right.

That is where experience becomes valuable.

A senior professional isn't valuable simply because they can produce a document, write code, or build a spreadsheet. They are valuable because they have enough experience to recognize when something isn't right.

They know which questions haven't been asked. They understand the history behind a decision. They recognize the client concern that isn't written in the project brief. They have seen enough things go wrong to know where to look before something does.

AI can make that person dramatically more productive.

But only if they stay involved.

The standard should be going up

This is the part I find most frustrating about some of the careless mistakes we're beginning to see.

AI is giving us an opportunity to produce some of the best work of our careers. We have access to tools that can research, analyze, draft, code, organize, and iterate with us at a speed that would have seemed impossible a few years ago.

So why would our standards go down?

If AI saves you two hours on an assignment and you submit it two hours earlier with mistakes you could have caught in ten minutes, I'm not sure we've accomplished much.

That's not really productivity. It's just faster production.

The people I think will benefit most from AI aren't the ones who figure out how to hand off the most work. They'll be the ones who figure out where AI makes them better and where their own experience still needs to take over.

Because as AI gets better at producing things, simply being able to produce something will become less valuable.

Knowing whether it is good will become more valuable.

Knowing whether it solves the right problem will become more valuable.

Knowing when the answer doesn't make sense will become more valuable.

And being willing to take responsibility for the final result will become more valuable.

I'm a big believer in AI. I want people using it. I use it myself every day. I want our teams experimenting with it. I want an engineer to figure out how to do in 30 minutes what used to take three hours. I want them to become the architects to incredible products.

But if AI does 80% of the work, don't assume your contribution is the remaining 20%.

Your contribution is knowing whether the entire 100% is right.

Your AI agent may be extraordinarily capable. Let it do the work it's good at. Give it context. Guide it. Question it. Check its work.

Then add the part it can't provide on its own: your experience and professional judgment.

You're still the experienced professional in the room. Act like it.

Kristi Short is CEO and Co-Founder of CH2 Solutions, a technology consulting and nearshore firm that builds high-performing engineering teams for technology companies. She has served as CTO, COO, and CPO across multiple organizations and brings an operator's perspective to every client engagement.

Learn more at ch2solutions.com