start with the idea before the implementation.
the mechanisms you need to reason about.
Schema design
Schema design 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.
Constraints
Constraints 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.
Indexes
Indexes 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.
Transactions
Transactions 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.
Query plans
Query plans 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.
model a learning system
Build the smallest version first. Record the input, expected output, measured result and one failure you discovered.
add unique constraints
Build the smallest version first. Record the input, expected output, measured result and one failure you discovered.
inspect a slow query
Build the smallest version first. Record the input, expected output, measured result and one failure you discovered.
prove you can explain and decide.
normalize intentionally
ask cortex to test me →explain transaction boundaries
ask cortex to test me →pick indexes from workload
ask cortex to test me →what usually goes wrong.
missing constraints
Detect this early by defining a baseline, a measurable signal and a condition that would cause you to stop or redesign the approach.
over-indexing
Detect this early by defining a baseline, a measurable signal and a condition that would cause you to stop or redesign the approach.
N+1 queries
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 PostgreSQL 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.