Free sample lesson · Is This Actually Working?
Feeling Faster Is Not Evidence
In one controlled study, experienced developers were measurably slower with AI and reported feeling faster.
Lesson 1 of the Wondering course Is This Actually Working?
What You Will Explore
- Perception Gap
- Fixed Tests
Discover why the feeling of speed can be misleading when using AI and learn how to implement objective fixed testing.
The Illusion of Speed
Using AI often feels like a massive shortcut. You skip the painful blank page and see results instantly.
However, your feelings are not reliable evidence of actual productivity.
In a study of experienced open-source developers, participants believed AI tools made them faster. In reality, their measured completion times actually increased. There was a 40 point gap between how fast they felt and how fast they were.
- Perceived Speed: Developers believed AI made them significantly faster.
- Actual Speed: Measured completion times actually increased.
Why Our Senses Fail
AI shifts where you spend your effort. It removes the vivid struggle of starting a task.
Because the start feels easy, you assume the whole process is better. You do not notice the time spent later on.
Reading carefully, correcting errors, and fixing contradictions takes time. This effort is diffuse and harder to track than the initial excitement of generating text.
- Easy Start: Removing the blank page creates an initial feeling of speed.
- Hidden Struggle: Time spent reading carefully and correcting errors goes unnoticed.
- Diffuse Effort: Fixing contradictions takes more time than generating text.
The Power of Fixed Tests
To see the truth, you need a fixed test set. This is a small collection of 10 to 30 real cases you save in a document.
Instead of testing whatever arrives next, you run every new prompt against these same examples.
This allows you to compare versions fairly. You do not need complex software or thousands of data points to do this effectively.
- Test Cases: A small collection of real cases saved in a document.
- Method
Testing the Awkward Cases
Do not only use easy examples for your test set. Easy cases always look good.
Include at least three awkward cases. Use the email that went wrong or the one with missing information.
Include a case where the correct answer is to ask a human for help. If your workflow handles these difficult spots, you have real evidence that it works.
Putting It All Together
- Collect Test Cases: Gather 10 to 30 real examples including both easy and awkward scenarios.
- Run Both Versions: Process the exact same fixed test set through both the old and new versions.
- Measure Real Results: Evaluate completion time and correctness instead of relying on gut feeling.
Check yourself
A subjective feeling that an AI workflow made a task faster is _____ that productivity actually improved.
- not reliable evidence
- conclusive proof
Answer: not reliable evidence
Studies show that workers often report feeling faster even when measured completion times increase. Feeling faster is the perception being tested, not the objective evidence.
AI tools eliminate the friction of the _____, creating an illusion of speed while hiding the effort required later for _____.
Answer: AI tools eliminate the friction of the initial start, creating an illusion of speed while hiding the effort required later for error correction.
Because skipping the blank page feels fast and easy, users tend to overlook the diffuse time spent later on reading carefully and fixing mistakes.
When constructing a fixed test set of 10 to 30 cases to evaluate a prompt, why should you include awkward or difficult cases?
- They expose hidden errors and test how the prompt handles difficult edge cases.
- They guarantee that the AI will complete all future tasks without needing human review.
- They eliminate the need to measure completion time during testing.
- They automatically increase the dataset size so specialist software is required.
Answer: They expose hidden errors and test how the prompt handles difficult edge cases.
Easy cases almost always look good. Including awkward cases—like missing information or situations requiring escalation—tests whether the workflow actually handles real-world difficulties.
Keep going
This is lesson 1 of 5 in Is This Actually Working?. Next up:
- Write Down What Good Means
- Count The Rework
- What Churns And What Holds
- A Routine You Will Actually Run
Wondering turns any topic into short lessons you can read, watch, or listen to, with practice questions and an AI tutor.