Presentation: The Ladder Is Missing Rungs: Engineering Progression When AI Ate the Middle
Alasdair Allan discusses empirical research from METR and Anthropic on AI coding adoption. He explains the "supervision paradox," where reliance on AI tools disrupts junior skill development, risks institutional context loss, and threatens the long-term engineering pipeline needed to oversee autonomous systems effectively. By Alasdair Allan
Alasdair Allan discusses research by METR and Anthropic regarding the impact of AI on software development. He highlights the "supervision paradox," where reliance on AI tools can hinder junior skill development and threaten the long-term engineering pipeline needed to oversee autonomous systems. Allan, a former astrophysics researcher and ex-Head of Documentation at Raspberry Pi, argues that the focus should shift from AI writing code to how software engineering functions without the need for engineers to write code themselves.
He points out that a Reuters study found experienced developers using AI tools took 19% longer to complete tasks, contradicting initial claims that AI would make developers 24% faster. The dependency on AI has become too strong for developers to participate in controlled studies, indicating a significant shift in the professional landscape.
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