The "Apparent Productivity" Syndrome
You might be manufacturing motion ... not value.
You open your editor.
Your AI assistant suggests something.
You click “accept”.
Then again.
And again.
A test appears.
An endpoint exists.
A UI loads.
A deployment passes.
You close the laptop thinking:
“Wow… I got a lot done today.”
But did you?
We’ve entered a strange phase in software engineering.
For decades, producing code was expensive.
It required understanding systems, remembering APIs, fighting syntax and debugging endlessly.
Because of that, code production itself became our proxy for productivity.
More code → more effort → more value.
AI quietly broke that equation.
Today, code is cheap.
Tomorrow, it will be almost free.
And when something becomes cheap, it stops being a useful metric.
Lines of code are no longer proof of progress.
Commits are no longer proof of impact.
Even shipped features are no longer proof of value.
You can now build an entire feature without once having a clear thought about why it should exist.
That’s the Apparent Productivity Syndrome:
The feeling of high productivity created by low-friction output.
You are active.
You are shipping.
But you may not be moving anything meaningful forward.
This changes the job.
The limiting factor is no longer implementation.
The limiting factor is judgment.
In the past, engineers were paid to translate ideas into software.
In the near future, engineers will be paid to decide which ideas deserve to exist.
Because adding value to the business will become more necessary than ever.
Not writing code.
Not shipping features.
Changing outcomes.
So the question becomes:
If AI can build almost anything — how do we guarantee what we build matters?
Below are three simple steps I’ve been thinking, developing and applying more and more on a daily basis before accepting the next 200 green suggestions:
1) Define the Business Change — not the Feature
Before writing a single line (or accepting a single suggestion), answer this:
What behavior in the real world will change if this succeeds?
Not system behavior.
Human behavior.
A bad example in this situation would be:
“Add caching to the service”
A good example:
“Reduce user’s waiting time enough so checkout drops are reduced 10x”
If you can’t point to a measurable change outside the codebase, you are probably manufacturing motion, not value.
AI accelerates building. It does not accelerate thinking.
2) Create a Failure Condition First
Every valuable feature has a way to prove it failed.
Before implementation, write down this sentence:
“After release, we will consider this feature unsuccessful if there is _____”
Examples:
No decrease in support tickets
No change in conversion rate
No latency improvement perceived by users
still the need for engineers to manually intervene
If a feature can’t fail, it also can’t succeed — it only exists.
This step is powerful because it removes emotional attachment.
It forces you to think about expectations and how those should be met.
You stop defending the implementation and start evaluating the outcome.
3) Delay Optimization Until Impact Exists
AI makes it dangerously easy to polish and build irrelevant things.
You can:
refactor endlessly
improve naming
add abstractions
increase test coverage
make it elegant
All before knowing if the feature should go exist or not.
Instead:
Ship the smallest version that can trigger the business change.
Then improve only if the change appears.
Optimization after validation multiplies value.
Optimization before validation multiplies waste.
The New Skill
We are moving from:
“Can you build it?”
to
“Should it exist?”
AI did not remove the need for engineers.
It removed the need for mechanical engineering effort.
The remaining work is direction, judgment and restraint.
Because in a world where building is effortless,
deciding not to build becomes the highest leverage action.
And maybe the real productivity of the future
is measured not by how much code you ship…
…but by how much unnecessary software never gets written.
Final thoughts
As always, keep building, keep working towards your goals and all of those things that brings more meanings to your life, while remembering your values and what takes you closer to your next horizon.
Stay safe,
Juan.