The Sunk Cost Trap
Welcome back to Founder Mode!
There is a pattern I keep seeing that has nothing to do with AI models or technology.
It has everything to do with people.
Teams hold onto broken systems long after they stop working. Not because they believe in them. But because they already paid for them.
At Pretty Good AI, we run into this all the time. The hardest part of implementation is not building something new. It is helping people let go of what is not working.
And that is a much more human problem than a technical one.
The System That Would Not Die
One customer we worked with had invested heavily in a record automation tool. On paper, it looked impressive. It promised to reduce manual work and streamline operations.
In reality, it barely functioned.
Staff still had to step in constantly. The data was inconsistent. Workflows were confusing. In some cases, it made things slower instead of faster.
But every time we pointed this out, the team defended it.
They would say things like, “We just need to optimize it” or “We have already put so much into this.”
It was clear what was happening.
They were not defending the system. They were defending the investment.
When Fax Machines Make a Comeback
At one point, we asked a simple question.
“What would happen if you stopped using this tool tomorrow?”
The answer surprised even them.
They said they would probably go back to faxing for some workflows.
Think about that for a second.
A modern system was so ineffective that going back to faxing felt like a safer option.
But even then, they hesitated. Because walking away meant admitting the original decision did not work.
That is the sunk cost trap.
Pride Disguised as Strategy
What looks like a strategy is often pride.
We tell ourselves we are being patient. That we are giving the system time to improve. That we just need one more tweak.
In reality, we are avoiding a harder truth.
This is not working.
At Pretty Good AI, we have learned that emotional resistance is often the biggest blocker. Not budget. Not engineering. Not even data.
It is the reluctance to admit something needs to be replaced.
The New Patient Moment
One conversation stuck with me.
We were talking with a group about improving their intake process. They were struggling to handle new patient volume.
We showed them a simpler approach. Faster routing. Clearer workflows. Less manual effort.
Their response was honest.
“If we cannot solve new patients, we are not going to pay out of pocket for anything else.”
That was the moment everything clicked.
The problem was not technology. It was a priority.
They had been spending time and money maintaining a system that did not solve their most important problem.
Once they saw that clearly, the conversation changed.
Simpler Wins More Often Than Better
There is a belief that the next solution needs to be more advanced. More features. More intelligence. More complexity.
But in many cases, simpler is better.
A clear workflow beats a clever one.
A reliable system beats a sophisticated one.
A solution that works today beats a perfect one that never gets adopted.
At Pretty Good AI, we focus on making things work in the real world. Not just in demos.
That often means stripping things down, not adding more.
Walking Away Is Leadership
One of the hardest things for any team to do is walk away.
Walk away from a tool.
Walk away from a vendor.
Walk away from a decision that felt right at the time.
But that is also one of the clearest signs of leadership.
The faster you can recognize what is not working, the faster you can redirect energy toward what does.
Holding on feels safe. Letting go creates progress.
Why This Keeps Happening
This pattern shows up everywhere.
Not just in healthcare. Not just in AI. In any system where time, money, and effort have already been invested.
We want to believe the thing we chose is still the right thing.
We look for reasons to justify it.
We focus on small improvements instead of big gaps.
We delay the decision to change.
But the longer you wait, the more expensive it becomes.
5 Key Takeaways
- Teams defend investments, not outcomes.
- A system that requires constant work is already failing.
- Pride can slow down necessary change.
- Simpler solutions often outperform complex ones.
- Walking away from what is broken is a leadership decision.
Final Thoughts
Building Pretty Good AI has made one thing very clear to me.
The biggest breakthroughs do not come from adding more. They come from removing what is not working.
Every week, we see teams spend time fixing systems that should have been replaced months ago.
The opportunity is not just to build something new. It is to recognize when the old thing needs to go.
The faster you kill what is not working, the faster you win.
See you on Friday!
-kevin
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