--- title: How Artificial Intelligence Disrupts Engineering Progression description: Alasdair Allan's QCon London talk argues that AI is disrupting the career progression pipeline for software engineers by removing the learning opportunities... canonical: https://daily.dev/posts/how-artificial-intelligence-disrupts-engineering-progression-3oilsnrwc twitter:card: summary_large_image twitter:site: @dailydotdev og:type: website og:site_name: daily.dev og:title: How Artificial Intelligence Disrupts Engineering Progression | daily.dev og:description: Alasdair Allan's QCon London talk argues that AI is disrupting the career progression pipeline for software engineers by removing the learning opportunities... og:url: https://daily.dev/posts/how-artificial-intelligence-disrupts-engineering-progression-3oilsnrwc og:image: https://api.daily.dev/og/posts/3OILSNrwC.png og:image:alt: How Artificial Intelligence Disrupts Engineering Progression og:image:width: 1200 og:image:height: 630 og:locale: en --- > ## Documentation Index > Fetch the complete documentation index at: https://daily.dev/llms.txt > Use this file to discover all available pages before exploring further. # How Artificial Intelligence Disrupts Engineering Progression **[InfoQ](https://daily.dev/sources/infoq)** · 5 min read · 0 upvotes · 0 comments ## Summary Alasdair Allan's QCon London talk argues that AI is disrupting the career progression pipeline for software engineers by removing the learning opportunities junior developers traditionally relied on, while also enabling people to perform above their actual skill level. He notes fewer junior developers are being hired, not because they're being fired but because AI has slowed entry-level hiring. In an interview, Allan cites research showing experienced developers were measured 19% slower with AI despite believing they were 20% faster (METR study), and Anthropic found junior engineers using AI scored 17% lower on mastery tests without finishing faster. He argues programming is becoming supervisory work, with Anthropic engineers using Claude in 59% of daily work but only able to fully delegate around 20%. Allan suggests structured learning paths with deliberate rotation through fundamentals, similar to medical residencies, and measuring understanding rather than velocity. ## Full article daily.dev links to this article rather than hosting it. Read it at the original source: ## Questions this post answers ### Does AI actually make experienced developers faster at coding tasks? Not necessarily. A METR randomized controlled trial found experienced developers were 19% slower when using AI tools, despite believing they were 20% faster. The perceived productivity gain did not match measured reality, suggesting self-assessment of AI-assisted coding speed can be unreliable, particularly for complex tasks where AI's usefulness collapses. _Developers weighing AI tool adoption track studies like this on daily.dev before trusting perceived speed gains._ ### How does using AI coding assistants affect junior developers' skill development? Junior engineers using AI scored 17% lower on mastery assessments without completing tasks any faster, according to Anthropic research cited by engineering consultant Alasdair Allan. The incidental learning that comes from struggling through problems with a mentor gets bypassed when AI supplies answers without the journey, stunting the pattern recognition and intuition that traditionally develops through hands-on debugging and legacy code work. _Engineering leaders shaping mentorship programs follow research on AI's effect on skill formation via daily.dev._ ### What percentage of Anthropic engineers' work is done with Claude and how much can be fully delegated? Anthropic's own engineers use Claude in 59% of their daily work, but can only fully delegate around 20% of tasks to it. The gap between generation and judgment is where human oversight remains essential, with programming increasingly becoming supervisory rather than purely code-writing work. _Teams defining how far to delegate to AI agents track findings like this on daily.dev._ ## Similar posts on daily.dev - [AI Is Killing Entry-Level Programming Jobs. 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A METR randomized controlled trial found experienced developers were 19% slower when using AI tools, despite believing they were 20% faster. The perceived productivity gain did not match measured reality, suggesting self-assessment of AI-assisted coding speed can be unreliable, particularly for complex tasks where AI's usefulness collapses. Developers weighing AI tool adoption track studies like this on daily.dev before trusting perceived speed gains."}},{"@type":"Question","name":"How does using AI coding assistants affect junior developers' skill development?","acceptedAnswer":{"@type":"Answer","text":"Junior engineers using AI scored 17% lower on mastery assessments without completing tasks any faster, according to Anthropic research cited by engineering consultant Alasdair Allan. The incidental learning that comes from struggling through problems with a mentor gets bypassed when AI supplies answers without the journey, stunting the pattern recognition and intuition that traditionally develops through hands-on debugging and legacy code work. Engineering leaders shaping mentorship programs follow research on AI's effect on skill formation via daily.dev."}},{"@type":"Question","name":"What percentage of Anthropic engineers' work is done with Claude and how much can be fully delegated?","acceptedAnswer":{"@type":"Answer","text":"Anthropic's own engineers use Claude in 59% of their daily work, but can only fully delegate around 20% of tasks to it. The gap between generation and judgment is where human oversight remains essential, with programming increasingly becoming supervisory rather than purely code-writing work. Teams defining how far to delegate to AI agents track findings like this on daily.dev."}}]} ```