AI coding assistants now produce production-ready code with light review
Simon Willison describes how Claude Code and similar tools blend casual vibe-coding with agentic engineering. Engineers increasingly accept AI-generated code without line-by-line inspection, treating it like any external service. Reported productivity jumps from roughly 200 lines per day to 2000. The new constraints appear at the design and deployment stages rather than raw implementation. Willison flags the risk that teams normalize lower scrutiny, creating quality debt when AI output drifts from actual requirements.
Solo founders previously spent weeks writing and debugging core features by hand, which at least forced some reflection on whether the work served paying users. The new workflow removes that friction entirely. Design decisions and deployment pipelines now determine success, yet nothing in the tooling forces founders to validate demand before the AI begins generating the next module or micro-course.
Analysis
This development will accelerate your existing habit of refining code and cloud settings instead of building automated funnels. Set a non-negotiable rule: run a full prompt-chain simulation of 50 customer interviews and extract explicit willingness-to-pay signals before any new vibe-coded feature reaches production.
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