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New York • September 8 & 9, 2027
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A junior engineer on my team shipped a feature in a day that would once have taken much longer. The code looked great.
Then I asked them to explain a few decisions, and things got quiet.
They could describe what the code did. They struggled to explain why it had been written that way, or how they would debug it if it failed in production.
The output looked senior. The understanding was still junior.
That gap is easy to miss because the usual signals, clean PRs, good test coverage, fast delivery, all look healthy. I call this the Confidence Gap.
AI helps people ship better-looking code before they have built the judgment behind it. That is not a reason to ban the tools. It is a reason to rethink mentoring.
I will share three exercises I am using with junior engineers: AI-off sessions, Explain the Machine, and Break It challenges.
The point is not to slow people down or catch them out. The point is to rebuild debugging, explanation, and critical thinking so we do not confuse polished output with engineering growth.
This talk is for leads and managers who want to keep AI in the workflow without losing the apprenticeship part of the job.
Key takeaways
- The Confidence Gap: how AI can hide understanding gaps in junior engineers.
- A practical mentoring toolkit: AI-off sessions, Explain the Machine, and Break It challenges.
- How to reintroduce real learning without making AI use feel punitive.
- Better ways to think about growth when output no longer tells the whole story.
