I have run into this post by John Rush, which I found really interesting, mostly because I so vehemently disagree with it. Here are the points that I wa...

Ayende is a software engineer, blogger, and open-source contributor known for his expertise in software architecture and database development. Readers can learn about database design, NoSQL databases, and domain-driven design (DDD). With blog posts, tutorials, and open-source projects, Ayende shares  insights and best practices for building robust and scalable software systems.

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A critical response to the 'million AI monkeys' hypothesis that AI can rapidly generate production-ready software. Using examples like Cloudflare's vinext (which shipped critical vulnerabilities days after launch), the Claude C Compiler (impressive but architecturally flawed), and the OpenClaw vs NanoClaw comparison, the author argues that generating code quickly is easy but verifying and maintaining it is not. The value of a line of code lies in its battle-tested history, not its speed of generation. Production-grade software still requires the full software lifecycle, and AI-generated code shifts the burden from writing to verification without eliminating it.

The 'Million AI Monkeys' Hypothesis & Real-World Projects

please show this to investors who don’t know how programming actually works

Great read. Sadly only a few management people will read and understand this.
The ones who won’t are the same ones that thing that assigning 10 devs to a problem makes it 10x faster to solve it.