I’ve been a senior SWE (~10 years in backend and infra) and I’d say your observation is partially true.
Juniors often use AI as a “crutch” — they rely on it to fill gaps in fundamentals or recall syntax.
Seniors, on the other hand, use it strategically:
Code review & refactoring assistant: I use AI to sanity-check my design or spot potential edge cases.
Exploration & learning: When evaluating a new library or framework, I ask AI for comparisons or best practices.
Docs summarization: LLMs help me parse long RFCs or documentation quickly.
Prototyping / boilerplate: For scaffolding boring repetitive code.
But not for actual algorithmic thinking or critical code — those still rely on human judgment.
In short: top engineers do use AI, but they use it like they use Stack Overflow — a tool for leverage, not a crutch.
I think AI hasn’t stolen the satisfaction — it just shifted where satisfaction comes from.
Before, we felt proud of solving syntax or logic problems ourselves. Now, the joy is in asking better questions and evaluating better answers. It’s less about typing and more about thinking.
Maybe it’s not coding that feels empty — it’s that our sense of mastery hasn’t caught up with the new workflow.
Code review & refactoring assistant: I use AI to sanity-check my design or spot potential edge cases.
Exploration & learning: When evaluating a new library or framework, I ask AI for comparisons or best practices.
Docs summarization: LLMs help me parse long RFCs or documentation quickly.
Prototyping / boilerplate: For scaffolding boring repetitive code.
But not for actual algorithmic thinking or critical code — those still rely on human judgment.
In short: top engineers do use AI, but they use it like they use Stack Overflow — a tool for leverage, not a crutch.