The good news is your attention to actually reading and understanding documentation will differentiate you more and more as others (short-sighted, IMO) outsource understanding to an LLM.
The more code writes autonomously, the less intuition the human owners have about that code. Loss of intuition is a seed of technical debt that grows with time. Over a long enough horizon, it can make looking at your own codebase feel like the first day on the job (sometimes at a company you started).
Luckily, there are ways to mitigate this and essentially translate those human intuition of how the codebase “should” be into guardrails for the agents. But without that, your setting your sails in a stochastic sea where each wave looks nothing like the last.
I think this has as much to do with how hard software became to understand as with the new shortcut to refusing to understand it and the shortsightedness in willing to take it.
We lost a lot of traction in the name of ease of staffing and speed. Using LLMs to generate more code that is harder to understand it catalyzes it but the root of the problem, in my opinion, was letting go of great design and deep understanding for short term profit.
I've been thinking about this lately - is it like using 3rd party libs to achieve stuff faster? As much as I would lovr to hand craft the datetime logic in my app, I might as well use luxon and invest this time somewhere else. Only now with llms, you get virtually infinite 3rd party libs you can use, you create them on the fly. So if you have strong engineering values, I would say simply it boils down to "contracts over programs", you can still be in touch with the logic that glues it all together and treat some logic as a blackbox the same way we do with 3rd party libs?
It's not just about it feeling like a 3rd party library but it's a library that's at risk of changing significantly after every 'update' without warning.
Atleast with a well built library you know the contours and how it fits into your larger system
It's not because with libraries you have a boundary somewhere and can decide to not care what's inside as long as the interface is stable and well designed. The problem of course you need to prioritise building well designed interfaces and decouple components from each other, and that's a skill most developers aren't good at.
Models are getting better. Astra for example refactored some code GPT-5.6 Sol wrote and extracted some related functionality in a separate file without prompting.
The models are also becoming very capable of suggesting architecture simplifications, but you need to ask for that, and you probably need some taste in picking from the suggestions, although the default ones are quite decent.
Considering how many compromises and problems third party libraries have caused recently, I would say the comparison is apt - if you don't know what you're shipping one day it might explode on you
Isn’t this also counting on the AI company faithfully reproducing the contents of the book, and no hallucinations or shenanigans occurring? How will we ever know what the book actually said if people wanted to argue its contents later?
This is actually how Jeff Dean, Chief Scientist at Google recommends doing thought exercises to challenge assumptions (watch is recent YX Startup School talk). The end goal isn’t “128GB of RAM”, the goal is “useful effective software”. If for whatever reason RAM was an immovable constraint, a different tech tree would emerge.
The tech tree where we develop tech to have tons of RAM is better and leads to more opportunities than the tech tree where everything is built for only a handful of GB of RAM. We may never have had LLMs if we didn’t go down the first path.
Or maybe we’d have LLMs that fit in a handful of GBs (and we technically already do). It’s hard to tell without completely going down that parallel universe and simulating all the milestones in it, but it’s a fun thought experiment.
I live near Plum Island. Just look at the Google Map reviews to get an idea of the sentiment. Camp Hero, Plum Island…lotta material for Netflix series coming out of Long Island.
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