> I say the tools are better and reading than writing.

No way, models are much, much better at writing code than giving you true and correct information. The failure modes are also a lot easier to spot when writing code: it doesn't compile, tests got skipped, it doesn't run right, etc. If Claude Code gave you incorrect information about a system, the only way to verify is to build a pretty good understanding of that system yourself. And because you've incurred a huge debt here, whoever's building that understanding is going to take much more time to do it.

Until LLMs get way closer (not entirely) to 100%, there's always gonna have to be a human in the loop who understands the code. So, in addition to the above issue you've now got a tradeoff: do you want that human to be able to manage multiple code bases but have to come up to speed on a specific one whenever intervention is necessary, or do you want them to be able to quickly intervene but only in 1 code base?

More broadly, you've also now got a human resource problem. Software engineering is pretty different than monitoring LLMs: most people get into into it because they like writing code. You need software experts in the loop, but when the LLMs take the "fun" part for themselves, most SWEs are no longer interested. Thus, you're left with a small subset of an already pretty small group.

Apologists will point out that LLMs are a lot better in strongly typed languages, in code bases with lots of tests, and using language servers, MCP, etc, for their actions. You can imagine more investments and tech here. The downside is models have to work much, much harder in this environment, and you still need a software expert because the failure modes are far more obscure now that your process has obviated the simple stuff. You've solved the "slop" problem, but now you've got a "we have to spend a lot more money on LLMs and a lot more money on a rare type of expert to monitor them" problem.

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I think what's gonna happen is a division of workflows. The LLM workflows will be cheap and shabby: they'll be black boxes, you'll have to pull the lever over and over again until it does what you want, you'll build no personal skills (because lever pulling isn't a skill), practically all of your revenue--and your most profitable ideas--will go to your rapacious underlying service providers, and you'll have no recourse when anything bad happens.

The good workflows will be bespoke and way more expensive. They'll almost always work, there will be SLAs for when they don't, you'll have (at least some) rights when you use them, they'll empower and enrich you, and you'll have a human to talk to about any of it at reasonable times.

I think jury's out on whether or not this is bad. I'm sympathetic to the "an LLM brain may be better than no brain", but that's hugely contingent on how expensive LLMs actually end up being and any deleterious effects of outsourcing core human cognition to LLMs.