start with the idea before the implementation.
the mechanisms you need to reason about.
Hypothesis
Hypothesis is studied through intuition implementation evidence and trade-offs. The goal is to be able to explain the mechanism and verify it with a concrete test rather than only repeat a definition.
Baseline
Baseline is studied through intuition implementation evidence and trade-offs. The goal is to be able to explain the mechanism and verify it with a concrete test rather than only repeat a definition.
Control
Control is studied through intuition implementation evidence and trade-offs. The goal is to be able to explain the mechanism and verify it with a concrete test rather than only repeat a definition.
Metrics
Metrics is studied through intuition implementation evidence and trade-offs. The goal is to be able to explain the mechanism and verify it with a concrete test rather than only repeat a definition.
Confounders
Confounders is studied through intuition implementation evidence and trade-offs. The goal is to be able to explain the mechanism and verify it with a concrete test rather than only repeat a definition.
turn the lesson into evidence.
write a falsifiable hypothesis
Build the smallest version first. Record the input, expected output, measured result and one failure you discovered.
define a baseline
Build the smallest version first. Record the input, expected output, measured result and one failure you discovered.
pre-register metrics
Build the smallest version first. Record the input, expected output, measured result and one failure you discovered.
prove you can explain and decide.
identify confounders
ask cortex to test me →state rejection criteria
ask cortex to test me →separate exploratory and confirmatory work
ask cortex to test me →what usually goes wrong.
moving goalposts
Detect this early by defining a baseline, a measurable signal and a condition that would cause you to stop or redesign the approach.
no baseline
Detect this early by defining a baseline, a measurable signal and a condition that would cause you to stop or redesign the approach.
selective reporting
Detect this early by defining a baseline, a measurable signal and a condition that would cause you to stop or redesign the approach.
Create a short Experiment design engineering note with one working artifact one metric one failure case and one decision about when you would or would not use it.
Save the result in your portfolio or project repository. A strong learning artifact should make your assumptions, metrics and failure analysis visible.