AI has made building things ridiculously fast.
You can describe an idea and have a working prototype in minutes.
Need a landing page?
AI can build it.
Need an API integration?
AI can write most of it.
Need a database query?
Ask AI.
Need a blog post?
Done.
And honestly, it's pretty incredible.
But there's a weird side effect I've noticed.
AI doesn't just make you faster at building things.
It can also make you faster at building the wrong thing.
The Old Problem Was "I Don't Know How"
For a long time, one of the biggest barriers to building software was technical knowledge.
You had an idea, but maybe you didn't know how to:
- Build the frontend
- Create an API
- Connect a database
- Deploy the application
- Set up authentication
- Integrate another service
You had to learn those things or find someone who could.
AI has lowered that barrier dramatically.
That's a huge win.
But it creates a new problem.
Now the Problem Is "Should I?"
AI can give you an answer to almost any implementation question.
But it doesn't necessarily tell you whether you should be doing it.
You can ask:
"How do I connect these two APIs?"
And AI will happily explain it.
A better first question might be:
"Do these two systems actually need to be connected?"
That's a completely different question.
And it's one AI can't always answer for you.
I Think We're Entering the "Too Easy to Build" Era
There's a strange thing happening with software.
Some ideas used to be too expensive to build.
Now they're cheap enough that you can build them on a weekend.
That's great.
But when building becomes cheap, deciding what to build becomes more important.
You can spend a Saturday creating:
- A dashboard
- An automation
- A Chrome extension
- An AI chatbot
- A content generator
- A CRM integration
And by Sunday evening, realize you didn't actually need any of them.
I've definitely been guilty of this.
The Prototype Feels Like Progress
This is probably the dangerous part.
You build something.
It works.
You see the result.
And your brain immediately goes:
"Nice."
But a working prototype doesn't necessarily mean you've solved a problem.
It might only mean you've successfully created a new thing to maintain.
There's a difference.
AI Makes This Especially Obvious
I've used AI for everything from writing code to debugging integrations to figuring out weird API behavior.
It's incredibly useful.
But I've found that the best results usually happen when I already understand what I'm trying to accomplish.
For example:
Bad:
"Build me an automation that processes leads."
Better:
"When a lead submits this form, check whether the phone number is valid, create the contact if it doesn't exist, notify the sales team, and don't create duplicates if the webhook fires twice."
The second request isn't necessarily better because it's longer.
It's better because the problem has been thought through.
AI is much better at implementation when the human has already done some thinking.
This Applies to Content Too
The same thing is happening outside software development.
AI can create content extremely quickly.
At Colab Content, for example, we work with AI-assisted content workflows.
But the interesting question isn't:
"How quickly can we generate an article?"
It's:
"Do we actually have something useful to say?"
That's becoming a universal AI problem.
More output doesn't automatically mean more value.
The same applies to code.
More code doesn't automatically mean a better application.
AI Is Becoming a Multiplier
I've started thinking about AI less as a replacement for skill and more as a multiplier.
If you have a good idea:
AI makes it easier to execute.
If you have a bad idea:
AI makes it easier to execute that too.
If you understand the problem:
AI can save you a ridiculous amount of time.
If you don't understand the problem:
AI can help you confidently build something you don't need.
That's why judgment is becoming more important, not less.
The Most Useful AI Skill Might Be Knowing When Not to Use It
This sounds strange considering how much everyone talks about AI.
But sometimes the best solution is incredibly boring.
You don't need an AI agent.
You need a form.
You don't need a complicated automation.
You need a notification.
You don't need another dashboard.
You need a spreadsheet.
You don't need another SaaS product.
You need someone to answer the phone.
Technology should solve the problem.
It shouldn't become the problem.
I Still Love How Fast Things Are Now
None of this is an argument against AI.
Quite the opposite.
I love being able to go from:
"I wonder if this would work..."
to:
"Here's a working version."
in an afternoon.
That's something developers didn't always have.
The trick is not letting that speed convince us that every idea deserves to become a product.
Sometimes the best thing you can build is the thing you decide not to build.
Final Thought
The biggest change AI brings to technology might not be that fewer people need to code.
It might be that more people can build things than ever before.
And when building becomes easier, thinking becomes more valuable.
What problem are we actually solving?
Who needs it?
Is there a simpler way?
What happens when it breaks?
Do we need this at all?
AI can help answer some of those questions.
But the responsibility for asking the right ones is still ours.
And honestly, that's probably a good thing.
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