What is wrong with using LLMs to analyze and explain code? Am I missing something? Before writing code, this is an even easier task to accomplish using AI.

I think a huge gap in the market today is documentation that is both easy for humans to navigate and understand, but also readily ingestible for agents.

There is something to this, but to the concluding paragraph: I think these tools already are extremely good at helping us understand code, in addition to helping us generate it.

The context of when that previous experience - Heartland outsourcing to India – happened would be helpful. The 90s? The 00s? The 10s?

Coding agent to me, means shifting my brain from memory-bound to compute-bound

>The cost of producing code has collapsed. AI tools can generate functional, adequate, perfectly average code at a speed and cost that would have been unimaginable even five years ago. And like the outsourcing wave of the early 2000s, the economics are real and rational. Nobody is wrong for using these tools. The code they produce is often fine. It works. It passes tests. It might ship as-is.

After using AI for months (Claude, Gemini, ChatGPT) it is extremely rare for their code to work 'as is' first shot and almost always requires several iterations and cleaning up edge-cases.

When it does work 'first shot' it's usually when it's transferring existing working code to a new project which is slightly different.

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