1 link tagged with all of: software engineering + liability + ai + llm generated software + robert c. martin
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Mark Seemann argues that fully LLM-driven software engineering could work—producing code as reliable as human-written systems—but legal systems will struggle to assign blame when things go wrong, likely scapegoating whoever signed off on the release rather than the AI that created the defect.
- Code review and human inspection were never foolproof either; the real question isn't whether LLM code is perfect, but whether it's better than human-driven processes, which it plausibly could be.
- Even if LLM-driven systems produce fewer bugs than human teams, courts and liability frameworks aren't equipped to handle a world where no individual "wrote" the problematic code—judges will still need someone to prosecute.
- People will adopt AI-driven systems aggressively (like Tesla FSD drivers ignoring the road) because the odds look good, then face severe legal consequences when rare failures occur, regardless of how robust their quality assurance actually was.
llm generated software
liability
software engineering
robert c. martin
ai