To be honest lots of developers think they don’t need to learn machine code. They just need to learn a language which once compiled will produce machine code.
To be honest lots of developers think they don’t need to learn machine code. They just need to learn a language which once compiled will produce machine code.
I wonder if a probabilistic compiler would be fine for the people arguing this. One that sometimes produces machine code that does something else, and sometimes produces machine code that is just broken and does nothing useful. From the same source code.
What if your compiler could be fooled by some other developers into spending thousands of dollars, and still not produce the desired machine code in the end?
I've run into compiler bugs before.
There are compiler bugs (rarely) which will be fixed. That's different from fundamental flaws in the technology, which cannot be fixed.
Compilers are deterministic and, luckily, not agentic.
But yes, it's not obvious (or perhaps even likely) that it just happens that current high-level languages are the "correct" optimal level of abstraction at which you can ignore the sausage-making details at the lower levels. Ultimately, of course, it depends on the use case. Something like Python is so far removed from machine instructions that knowing assembly hardly gives the programmer any additional value.
(Also, obligatory reminder that assembly and even numeric machine code are also abstractions, an "API" provided by the CPU. Instructions get split or fused into micro-ops, named registers are a backwards-compatible abstraction over a much larger register file, instructions get reordered and executed in parallel depending on their data dependencies, a large fraction of the total transistor budget is spent on multi-level caches and cache logic to maintain the illusion of fast access to a single, uniform memory space...)
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This is different.
Understanding assembly/machine code is optional but helpful. The programming language semantics are enough to reason about what the program is doing. Other tools also help, but are optional for learning how to program.
Using an AI, there is no semantic model that can be used to reason through. You're left without any mental model of the proglblem at all.
I've been arguing for years that is isn't optional and treating it like it is is how we ended up with Electron and 400MB JavaScript websites.
When you have no mental model of the machine running your code or what the physical implications of code mean, you fundamentally lack the ability to reason or care about performance. "Works on my machine" is the original vibecoding.
I take it you listen to Casey Muratori's talks? He talks about this a lot.
I mean I don't disagree, but there's still a difference in the kind of disconnect you get. The disconnect is harmful in the high-level language case, but it's dangerous and irresponsible with vibe coding/LLMs.
Also, I would argue that a good enough understanding of computer architecture and a mental model of a process' memory layout gets you there, without knowing how to write assembly. That's still a mental model.
LLMs these days seem to have no problem using language semantics to conceptualize what’s happening in a program. This is my favorite use of an LLM, “why is this library doing x” and then it digs through the library itself in my venv to find an answer.
Yep, super-duper-google is an unequivocally good use case for LLMs.
That's not what the LLM is doing. It is guessing at what is happening by regurgitating some docs. It's a more expensive web search.
You also don't have a mental model if you need to ask the LLM about it. This is stuff you should be internalizing.
You internalize the inner workings of all the libraries in your venv? Impressive! My current project’s uv.lock has ~60 packages in it already, reading and comprehending those tens to hundreds of thousands of lines of code must be time consuming.
You’re also just confidently wrong about the model reading the code. It quotes file paths and line numbers and I open and read those files at those line numbers. For me, hallucinations are much more frequent when it references the docs rather than code because docs are more subjective than code.
This is a normal thing I’ve been doing since at least December.
I have to ask — do you actually use LLM coding tools? Your knowledge on this topic seems really out-of-date.
Developers can change their minds.