I have come to the same conclusion. You can outsource your thinking but you cannot outsource your understanding https://t.co/puRjwUSJaZ
— kache (@yacineMTB) March 22, 2026
Every time I come back to this, it just feels more true. Exactly what is happening right now.
For a long time, my relationship with AI tools was simple. Hit a problem, ask the AI, read the answer, apply it, move on. Fast. Felt productive. I thought I was being smart about it.
Then I started building a chatbot at work. And something shifted.
What I Used to Do
Before the chatbot, I had a pattern. I would hit a bug or a tricky piece of logic and go straight to the AI. Get an answer. Apply it. Done. I never really asked why something worked. I just needed it to work.
Looking back now, I was completely outsourcing my thinking. Not just the tedious parts, but all of it. The reasoning, the diagnosis, the understanding. I handed it all over and moved on.
What Changed When I Built the Chatbot
When I started building the chatbot, I made a deliberate decision: whenever the AI gave me an answer, I was going to try to understand it before I applied it.
That meant reading it carefully. Asking myself why this particular approach worked. Trying to explain it back to myself in plain words. If I could not do that, I would dig deeper before moving on.
It was slower. But it was completely different from what I had been doing before.
The result was that when the chatbot broke, and it did break, I could actually debug it. I knew what was happening because I had chosen to understand it as I built it. I was not searching through old AI conversations hoping to find something I had applied six weeks earlier without understanding.
Thinking and Understanding Are Not the Same Thing
That experience made me see something clearly. Outsourcing thinking is fine. AI is genuinely useful for that. But thinking and understanding are not the same thing.
Thinking is the process. Understanding is what stays after the process ends.
You can hand the process to an AI. You cannot hand over the staying part. That is entirely on you.
The GPS Problem
There is an analogy I keep coming back to. When GPS navigation became universal, something quietly changed. People stopped building mental maps of their cities. You would get in a car, plug in a destination, follow the voice, arrive. But ask someone to drive the same route without their phone and they would be lost.
The thinking got outsourced to the device. The understanding never happened.
AI is GPS for ideas. It will get you to the right answer. But if you never do the driving yourself, you will not know the roads.
What Happens When You Skip It
I have seen this pattern a lot now. Someone asks an AI to explain a concept, gets a good explanation, feels good about it, and then gets into a meeting where someone asks them to go deeper. And they cannot. Because they read the explanation, they did not build the model.
Or someone uses AI to write a piece of code they do not fully understand. It works. Gets merged. Three months later there is a production issue and nobody can debug it because nobody actually understood what it was doing.
The output was correct. The understanding was absent. And when things went sideways, there was nothing to fall back on.
This is not an AI problem. It is a human behavior problem that AI makes much easier to fall into.
Understanding Is Built Through Friction
The uncomfortable truth is that understanding does not come from reading the right answer. It comes from being wrong first. From sitting with confusion long enough to find your way through it. From asking "but why?" three more times after you think you get it.
When you outsource your thinking before doing any of that, you skip the friction. And the friction is the whole point.
Building the chatbot the way I did, making myself understand each answer before applying it, was slower. But that understanding is mine now. No one can take it away. And next time I see those patterns, I will recognize them instantly.
This Does Not Mean Avoid AI
I am not saying do not use AI for thinking. I use it constantly. For research, for drafts, for debugging, for talking through decisions at 11pm when there is nobody else around.
The point is not to avoid outsourcing. The point is to be conscious about what you still need to own.
Use AI to explore faster. Use it to get unstuck. Use it to handle the repetitive cognitive work that does not require deep comprehension. But when something genuinely matters, when you will need to make decisions about it, teach it, build on it, or defend it later, do the work yourself. At least once.
Let AI be the thinking partner. Do not let it be the understanding substitute.
What I Am Actually Trying to Say
There is a version of the AI future that looks great on the surface. Every question answered instantly, every problem solved efficiently, every confusion smoothed over. And then there is the version where people can access any answer but cannot actually think about anything.
The tool is neutral. What matters is whether you use it to go deeper or to avoid going deep at all.