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The AI coding trap
If you ever watch someone “coding”, you might see them spending far more time staring into space than typing on their keyboard.
The real work usually happens alongside coding, as the developer learns the domain, narrows down requirements, maps out relevant abstractions, considers side effects, tests features incrementally, and finally squashes bugs that survived this rigorous process. While the LLMs get to blast through all the fun, easy work at lightning speed, we are then left with all the thankless tasks: testing to ensure existing functionality isn’t broken, clearing out duplicated code, writing documentation, handling deployment and infrastructure, etc. Good tech leads expose their engineers to work at the limit of their capabilities, using processes and practices that minimise delivery risk while also enabling each team member to grow their skills, knowledge, and domain expertise.
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