Comment by bitwize
19 hours ago
But LLMs have proven themselves better at programming than most professional programmers.
Don't argue. If you think Hackernews is a representative sample of the field then you haven't been in the field long enough.
What LLMs have actually done is put the dream of software engineering within reach. Creativity is inimical to software engineering; the goal has long been to provide a universal set of reusable components which can then be adapted and integrated into any system. The hard part was always providing libraries of such components, and then integrating them. LLMs have largely solved these problems. Their training data contains vast amounts of solved programming problems, and they are able to adapt these in vector space to whatever the situation calls for.
We are already there. Software engineering as it was long envisioned is now possible. And if you're not doing it with LLMs, you're going to be left behind. Multimodal human-level thinking need only be undertaken at the highest levels: deciding what to build and maybe choosing the components to build it. LLMs will take care of the rest.
A bit optimistic I'd say. It's put some software engineering within reach of some people who couldn't do it prior. Where 'some' might be a lot, but still far from all.
I was thinking the other day of how things would go if some of my less tech savvy clients tried to vibe code the things I implement for them, and frankly I could only imagine hilarity ensuing. They wouldn't be able to steer it correctly at all and would inevitably get stuck.
Someone needs to experiment with that actually: putting the full set of agentic coding tools in the hands of grandma and recording the outcome.
It's still going to take a knowledgeable person to steer an LLM. The point is that code written entirely by humans is finished as a concept in professional work—if you're writing it yourself you're not working efficiently or employing industry best practice.
I think it's dramatic to say it's the end of hand written code. That's like saying it's the end of bespoke suits. There are scenarios where carefully hand written and reviewed code are still going to have merit - for example the software for safety critical systems such as space shuttles and stations, or core logic within self-driving vehicles.
Basically when every single line needs to be reviewed extremely closely the time taken to write the code is not a bottleneck at all, and if using AI you would actually gain a bottleneck in the time spent removing the excess and superfluous code it produces.
And my intuition is that the line between those two kinds of programming - let's call them careful and careless programming to coin an amusing terminology - I think that line may not shrink as far back as some think, and I think it definitely won't shrink to zero.
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That is akin to saying if you aren't using an IDE you are not working efficiently or employing industry best practice, which is insane when you consider people using Vi often run rings around people using IDEs.
AI usage is a useless metric, look at results. Thus far, results and AI usage are uncorrelated.
Actually I will argue. Complex systems are akin to a graph, attributes of the system being the nodes and the relationships between those attributes being the edges. The type of mechanistic thinking you're espousing is akin to a directed acyclic graph or a tree, and converting an undirected cyclic graph into a tree requires you to disregard edges and probably nodes as well. This is called reductionism, and scientific reductionism is a cancer for understanding complex phenomena like sociology or economics, and I posit, software as well.
People and corporations have been trying for at least the last five decades to reduce software development to a mechanistic process, in which a system is understandable solely via it's components and subcomponents, which can then be understood and assembled by unskilled labourers. This has failed every time, because by reducing a graph to a DAG or tree, you literally lose information. It's what makes software reuse so difficult, because no one component exists in isolation within a system.
The promise of AI is not that it can build atomic components which can be assembled like my toaster, but rather that it can build complex systems not by ignoring the edges, but managing them. It has not shown this ability yet at scale, and it's not conclusive that current architectures ever will. Saying that LLM's are better than most professional programmers is also trivially false, you do yourself no favours making such outlandish claims.
To tie back into your point about creativity, it's that creativity which allows humans to manage the complexity of systems, their various feedback loops, interactions, and emergent behaviour. It's also what makes this profession broadly worthwhile to its practitioners. Your goal being to reduce it to a mechanistic process is no different from any corporation wishing to replace software engineers with unskilled assembly line workers, and also completely misses the point of why software is difficult to build and why we haven't done that already. Because it's not possible, fundamentally. Of course it's possible AI replaces software developers, but it won't be because of a mechanistic process, but rather because it becomes better at understanding how to navigate these complex phenomena.
This might be besides the point, but I also wish AI boosters such as yourself would disclose any conflict of interests when it comes to discussing AI. Not in a statement, but legally bound, otherwise it's worthless. Because you are one of the biggest AI boosters on this platform and it's hard to imagine the motivation of spending so much time hardlining a specific narrative just for the love of the game, so to speak.