Using AI Without Losing Understanding
Think, form the question, use the tool, understand the answer, verify. AI as reviewer and debugging partner, the dependency check, and what you still own.
Problem → Think → Form Question → Use Tool → Understand Answer → Apply → Verify. The tool is in the middle of the sequence, not at the start of it — because a question you have not formed produces an answer you cannot judge.
Your design → AI critiques → you decide → you implement. The assistant is strongest as a second reader of something you made, because then its output is a list of objections you can judge, not a design you have to adopt.
Before the assistant can help with a bug, you must bring four things: expected behaviour, actual behaviour, evidence, and a hypothesis. Bring fewer and it guesses; bring all four and it investigates with you.
Four questions about any code the assistant helped with: could you explain it without the tool, recreate its core idea, describe its failure modes, and debug it yourself? Where the answer is no, go one layer deeper — that layer is yours now, whether you understand it or not.
"If you are nothing without the LLM, you should not have it." Read constructively: the tool should amplify an engineering ability that exists, not stand in for the understanding required to own the result. The strongest opposing view — that fluency with the tool is itself the new skill — is stated and taken seriously.
The assistant can produce code, architecture, SQL, tests and explanations. You still own requirements, correctness, trade-offs, security, failure handling and understanding — the things that need to know what the system is for, and the things that are yours when the output is wrong.
Current goal, assumptions, unknowns, decisions, experiments, findings, next step. A notebook in your own words is where independent reasoning is built — and where you can see, at a glance, whether the tool has been doing yours.