Say I have constructive proof and I want to write a code on Sagemath. I don't know much about coding so I take help from AI. So while publishing the paper what should I do? I'm confused should I add the code or not

If anyone knows how to paint a doomy gloomy future it's /r/math, so here's an open ended question for all of you.

No one can predict exactly to which extent the rise of LLMs will change how the workday of a working mathematician. The only thing that is certain is that the future is rather uncertain. The doomiest comments on this subreddit also show that this uncertainty is particularly tough on people who are early on in their studies, and who would probably like to know to which extent it is useful (in the sense of putting bread on the table as opposed to, say, having fun) to pour a lot of energy into learning how to proof stuff.

Now, for even younger people – kids in elementary school or high school say – the future is even more uncertain.

So my question is: has the rise of LLMs changed how you would advise a younger kid to navigate the future? Chances are that it will always be useful to have a good baseline understanding of maths and logic, but would you be less inclined to advise a skilled high school student to pursue a theoretical career? Or would you have more reservations about enabling a particularly gifted elementary school student, so as to not accidentally set them up for a bumpy course?

Or on a more practical level, have you changed your guidance on which skills are the more useful to acquire given that, for example, software development in particular has have its nature completely changed?

I know that this is adjacent to the “Career & Education” thread, but I'm more interested in the high-level picture than in personal advise.

A consensus is emerging among respected mathematicians that there is a decent chance AI will exceed humans in both brute force verification and complex, creative problem solving at the highest levels. Few frontier theorems will be proven by humans alone, perhaps, in a matter of years.

More controversial, AI may also outpace humans in shaping the correct definitions, building theories, and making connections between disparate areas of mathematics, oft considered the peak of human creativity in mathematics. New areas of mathematics may be created without much human guidance.

Perhaps mathematicians become as helpful to AI as toddlers are to mathematicians. One cannot confidently rule out this scenario - Terrence Tao may find himself completely useless in building a rich, beautiful body of new mathematics.

In such an extreme scenario, humans would still matter in mathematics!

Lockhart's Mathematician's Lament argues for the intrinsic beauty of mathematics as being of primary importance. Humans, as knowledgeable appreciators of beauty, thus play an important a role as spectators and enthusiastic amateurs in mathematics, even if they cannot be world-renowned "competitors" in theorem-proving and theory-building. This mirrors the situation in chess, where the vast, vast majority of human chess players and appreciators will never contribute to the frontier of advanced lines, and arguably even the most skilled like Magnus Carlsen rely on AI to develop their strategies, and would be crushed by such AI in competition. Being completely uncompetitive does not make chess playing and appreciation valueless.

Amateur: from French amateur "one who loves, lover"

But there is more beyond this. Mathematics allows you to understand things that are otherwise impossible to understand. Some of these are important for fairness and justice: Arrow's impossibility theorem, statistical bias, observer relatively and other tricky concepts around coordinate systems (map != territory), locally-trivial globally-nontrivial (global obstructions), forgetful maps to extract the essential structure and remove irrelevant details, limits of computation, etc.

Understanding such mathematical concepts allows you to make moral judgements in ways that would be impossible otherwise. Some super-smart machine might tell you Arrow's theorem is true, but internalizing it yourself gives you the rich understanding of fairness in democracy necessary to consciously shape it. As with humans surpassing the capabilities of their own eyes with optical then radio telescopes, we are not impoverished by using tools that allow us to extend our reach into things we can never directly perceive or understand.

It can be frightening because the life's work of someone of the previous generation can be reproduced and surpassed flippantly. Gauss himself spent a significant amount of time manually factoring prime numbers by hand, a tedious exercise upon which his conjecture on the distribution of primes (the prime number theorem) was based. Gauss died before his conjecture was proven. His notebooks full of rote calculations could be reproduced today in a fraction of a second so short you could not perceive it. Anyone today repeating an endeavor like Gauss by hand would be thought a fool, just as an astronomer who refuses to use a telescope.

That doesn't make the pursuit of understanding pointless. As the limitations of our use of AI will stem from limitations of our own minds, it will still be profoundly rewarding to practice mathematics. Indeed, we may spend less time performing rote exercises and miring in false conjectures. Already the body of mathematics is too large for any single person to understand. One can pessimistically reduce mathematics to mechanics, or optimistically find meaning in your particular path through the mathematical version of the library of babel. Because we shape our minds, our society, and our world with mathematics, we will always matter as sentient beings who reify mathematics by subjecting ourselves to reason, and better ourselves because of it.

AI, for the last year, has been excellent at proving lemmas. I'm beginning to wonder, to what extent hirers should begin to be suspicious as to whether a student/postdoc with good preprints and publications from a minor university - or who had been an unproductive before - is actually talented vs just being early adopter who paid OpenAI $200 in 2025? There are already some young people in my field that I'm a bit suspicious of, as the quality of their publications has no correspondence whatsovever to the ideas they generate during real time discussion. This was historically an issue with collaborations, but we could at least get letters from coauthors there, but now do we need to be similarly suspicious of single author publications?

Is this just eventually going to mean that the only postdocs being hired in 2028 are from the top universities? I believe this is the already the norm in other subjects like English.

In these examples, the numbers seem to melt away. There is a physical tangible conundrum / toy / puzzle that needs abstract mathematics to solve. It's permutation adjacent. Somewhere in discrete maths. What else is there? I know about all the above. Any other cool things? I want a rabbit hole to jump down. I'm not a mathematician, I'm too poor, and I'm also kinda stupid (I blame it on being poor). But I think these are really cool. it's just neat ig.

Math-heads seems to be mainly interested in geometric calculations, calculus, 4d shapes, topology, and logic puzzles. I AM NOT SAYING THIS TOPICS ARE LAME, I simpllyyyy am currently interested in those mentioned above. Any other tricks for puzzles and rabbit holes to jump down?

Thanks in advance for any help. Gracias! Merci!!!!

There is a big hype over LLMs solving problems in some areas of mathematics.

Now, I'm not here to ask whether this will "replace mathematicians" (whatever that means) or not. That's already being done and a post like that is probably being typed as I'm typing this.

What I'm interested in, assuming that LLMs become better at solving problems than humans, how will we train new PhD students?

This seems like something which could drastically lower the general proficiency of mathematicians. Will a mathematician become just a person who checks LLM outputs to see whether they are correct?

Could someone familiar with algebraic geometry give some insights about this?