No one can keep up with the volume of code AI produces.

We wont stop using AI.

We will use AI to check AI.

Of course this is crazy, but it will also unlock pretty insane scaling and productivity and ultimately we will manage it on either end via requirements and tests.

It's mostly (not entirely, but mostly) finding security issues in old human-written code. It'll eventually start running out of those.

From that standpoint, it's not a crazy setup security-wise. Maybe still crazy for development.

You can point AI at any AI produced code and ask it to review it, get back 10 bullet points and a few pages of prose. And the fun part is, you can do that over and over and over again!

This happens all the time. Yesterday, I ran into an especially egregious case.

I had Fable add a new subcommand to our internal CLI tool. I reviewed and tested it locally and had to suggest several fixes that I feel like I wouldn't have had to tell a human senior engineer to do. When it finally submitted the PR, I had it on a loop waiting a few minutes for comments on the PR, then assessing/addressing/replying-to/resolving them, and then repeating again until all AI reviewers were okay with it. It ended up going through dozens of revisions and ended up with 160 comments left on the PR.

You're suggesting that LLMs get better at fixing bugs/vulnerabilities, but at the same time stop getting better at finding them? What if this difference is inherent and essential?

> You're suggesting that LLMs get better at fixing bugs/vulnerabilities, but at the same time stop getting better at finding them?

Are you implying that all code writing by LLMs atm is bug-free?

Absolutely not. By most accounts they're terrible at fixing anything other than trivial bugs in complex codebases e.g. Linux kernel, but they're much better at finding them.

So you put it in a loop and tell it to find the bugs in the code it wrote. What's the issue?

This is a self confession if I ever saw one.

I absolutely do this. It works great.

What value are you providing in this scenario?

Manual testing, and making sure that the AI didn't create so many bugs.

But, to the underlying question, obviously as we automate more and more of our work, of course we provide less and less value. We're heading towards a future where selling thought for money isn't going to work so well.

In fairness at root this has been going on for awhile. No one can keep up with the volume of machine code that modern more abstracted codebases produce.

We didn't stop using syntactic programming languages we used code to check code.

Not sure it's really crazy at all. It's been an abstraction for programmers probably since we stopped soldering transistors to each other.

There is a MAJOR difference between predictable generated machine code and Russian Roulette code generator.

Of course there is.

But if you don’t actually read it…

> it will also unlock pretty insane scaling and productivity

Insane scaling of bloat, bugs, and technical debt I'd say.

> We will manage it on either end via requirements and tests

It is so crazy that this is being touted as a sane strategy. When I was a much worse programmer, I tried to write a big complicated string manipulation function to take two types of scripts in a language and add diacritics. I had the requirements very clear. I had the tests very clearly with all the edge cases. But I didn't have a good and clear picture of how to attack the problem which was quite novel for me. As I got closer to passing all the tests it got exponentially more unruly and confusing. And nearing the end I was frantically changing little bits here and there wincing and praying and hoping the tests would pass. "Please work! Come on!" Then when I got close enough, I could never ever think about touching that mess again.

I was a below average programmer then throwing myself at some novel problem I didn't understand. Throwing LLMs that produce below average code at novel problems and relying on tests and requirements is not where we want to go to make real progress.

(Years later after much learning and coding myself I was able to redo the function in a totally different way. This time I actually understood how to attack the strange problem and made something clean, clear, and robust that just worked. The tests then become a secondary guardrail, not the main force of correction.)

We are seeing such a massive regression from what we've learned over the years of CS.

I'm not so sure LLM code today is below average. There was a time that things posted to dailywtf were normal everyday stuff

Sorry, no, they wouldn't have been WTF's if they were normal

Some WTFs are to be expected: https://www.osnews.com/story/19266/wtfsm/

You shared a story of a novice incompetent human programmer and this should tell us that AI is bad at coding.

I think all code is technical debt in a way. Good code is a necessary evil, bad code is more evil than necessary.

Generating code automatically when you're not even quite sure what it is or even should be doing is insanity.

>Insane scaling of bloat, bugs, and technical debt I'd say.

You just described every legacy codebase. Many of which are widely used and do a lot of sales. You dont need a clean codebase to have a valuable product.

>It is so crazy that this is being touted as a sane strategy.

Re-read what I said. I literally called it crazy.

It is the same dynamic that gave us customer service from some call center in India. Why would companies do this? Customer service got worse. Are they stupid? No, it's just worth it. The quality goes down but the business can scale more so it doesnt matter.

AI will absolutely be good enough at doing things that we'll happily accept some jankiness at times so that we can devote an extra 3000 hours per year per person to other things.

Im not even suggesting its a good thing. I just think the incentive structure dictates it. You're not going to have time to maintain a small slice of some service by hand.

Volume..... <sigh>

It used to be considered a quality of good code that there would be less code, not more.

Some people always tryin to get the highscore on golf.

You can have both less code per problem and more code overall when you make problem solving cheap enough.

The missing part of this is that verifying the bug with LLMs is also easy, and so is adversarially reviewing the proposed fix with LLMs.

The only thing left for you to do should be directional decisions. The LLMs should pause and rope you in if the fix involves directional/invariant changes.

> LLMs do find bugs, do save time

They find bugs but whether they save time is nowhere near as clear as you try to insinuate here.

They save time in finding bugs.

And for me they also save time in fixing bugs.

Unless it's finding a bug it added then it's time wasted x2

This is where I believe strong typing (like, Haskell-strong or stronger) and functional programming in general will be a win. The confidence I have that my fixes are localised when fixing Haskell code is infinitely stronger than fixing even Java, not speak about C, code.

Haskell's type system would not easily prevent this bug. It's not good at numeric/logic issues like that. When people say "Haskell makes it impossible to write bugs" they mean "Haskell has enums" (ADTs).

Liquid Haskell might require you to prove that the divisor is nonzero, but even in standard Haskell there's common idioms for ensuring that a list is non-empty (data NonEmpty a = a :| [a]) or that text is non-empty (newtype NonEmptyText = NonEmptyText Text, with non-exported constructor, helpers like make :: Text -> NonEmptyText, or more advanced tricks like https://exploring-better-ways.bellroy.com/haskell-koan-type-... ).

The big problem preventing this approach from working for numbers is that it's just so cumbersome there. Most of this is because all the arithmetic operators are bundled into a single Num typeclass, and `fromInteger :: Num a => Integer -> a` has a type that's impossible for a "non-zero number" wrapper to satisfy.

Definitely room for improvement on Haskell's standard library when it comes to the number-related type classes. Modern Haskell could do very well in this area with a good type-class redesign in this area. The issue I think is that this would invalidate a lot of existing code, relying upon that. But you can already replace Prelude with something else in your own code if you want to.

I think Idris has a better chance there.

OOP has those too, and they're very annoying.

In Haskell they are a little less annoying. It is just easier to reason about (including proving) pure functions.

I meant the constrained types by hiding the constructors. Super annoying, not automatically convertible, in Haskell you have to remember what the fake constructor is called, and write it every time you use it, but at least it's efficiently implemented with newtype, unlike the Java OOP version. Think about writing a value with several nested constrained types, like NonEmptyListOne (makeNonZeroNumber 42, 'h' `NonEmptyString` "ello world"). It's just really annoying.

The blog link I mentioned avoids this cost with literals, by providing using a required type argument to check the string length at compile time without TH. It requires a relatively recent GHC:

    make :: forall symbol -> (IsNonEmptySymbol symbol) => NonEmptyText

    type family IsNonEmptySymbol symbol :: Constraint where
      IsNonEmptySymbol "" = Unsatisfiable (Text "Expected a non-empty string")
      IsNonEmptySymbol _ = (()::Constraint) -- empty constraint is always satisfied

I am not claiming you cant write buggy code in Haskell! But following good functional style, your bug will more likely be compartmentalised, and fixing it will not break some other part of your program.

You can write good functional code in many languages. (Even C++!)

Sure! I have done my fair share of pretending Java and C++ support my functional style. But at the end of the day, you have better support for writing that style in a real functional programming language. And I wonder how well one can enforce a functional style in say Java or C++ upon the LLMs. Who knows, they might be great at it?

People don’t say "Haskell makes it impossible to write bugs"! You may have heard "if it compiles it works" which is somewhat tongue in cheek, but also true for a sufficiently loose interpretation of "works" in a way it is not true for languages with a less strong and flexible type system.

Imo, formal methods like more expressive/stricter type systems are key to making LLM generated code successful. Of course models will get better, but trusting the output will become much easier with a type system that proves more properties.

What's stronger than Haskell?

Dependent types is one possible direction. Not sure when a language with dependent types will arise which will be useful for making real programs.

Agda is the most mature dependently typed programming languae (having been around since the 90s – it is basically Haskell on steroids), but has a more proof-assistant flavor than an actual programming language flavor. Opus & Fable write Agda quite well, so LLMs can understand dependent types.

Anything with ranged numeric types. Like everyone's favorite functional programming language, Ada.

This issue raises SIGFPE. Ada would raise Constraint_error, which is easier to catch than a signal, but still occurs at runtime.

You need range proofs to be 100% safe, and then you can as well use the regular type because invalid values will not occur.

Or Liquid Haskell.

Lean 4, Idris 2.

Perhaps coq/agda/idris/etc.

Even Lean 4 strong typing

You haven't mentioned the dynamic typed languages that I believe should die -- Python and Javascript. The only good use case for dynamic typing is notebooks (niche of R lang) where you're throwing out the code you just wrote after getting the result you wanted from it.

If finding the bugs with LLMs is easy. Then making sure it doesn't break something else is just LLMs finding no bugs. Easy.

That hasn’t been that bad. My real issue has been the time sink involved in following along with the maintainer and jumper through their hoops. Even after I demonstrate a flaw and a potential fix. My schedule is just so busy I need to pencil in time to deal with them.