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As someone who loves Haskell more than any other language, some challenges are

- the tooling is decades behind, say, Rust or Go

- finding the right library in looks very different in Haskell--you frequently start with the signature on Hoogle. Agents can learn this but it's not the same as "web search"

- creating the right solution also looks different. It's usually borne out of thinking about the types and coming up with the correct algebra. Again models can probably learn to create the right types and orient the solution around that, but it's not automatic

- same today as yesterday, laziness is a blessing and a curse. The runtime can do unpredictable things when you suddenly evaluate a deep thunk

- GHC directives effectively mean there are multiple "Haskells"

Some of those are a result of the "avoid success at all costs" mantra. You can't shake that off in a day. It will take a concerted effort to make it more amenable for seamless adoption.

Haskell continues to be my favorite language to write and read, but Rust is the more practical language with a rich type system. If you're looking for something approaching Haskell's expressiveness but with fewer of these issues, check out PureScript.

As an intermediate Haskell programmer, I’ve found that using AI to debug or learn Haskell is a better use of time than generating a lot of code with it.

Even without AI most of my Haskell time is spent thinking.

Also, I hand writing Haskell is one of my small after work pleasures.

There are lots of people successfully using agents with Haskell, for example

* https://github.com/digitallyinduced/ihp/ is mainly written with Claude now

* https://jappie.me/haskell-vibes.html is gushing over agent-written Haskell

* https://discourse.haskell.org/t/anti-llm-sentiment-considere... huge thread about the divisiveness of LLM's from some person who loves using them with Haskell

I can see how agent coding is a nice fit for Haskell, since LLM's tend to be best at tasks where you can easily verify the output – and GHC lets you easily verify much more of your domain than say Python (sure you can test some of what dynamic typing doesn't catch, but LLM-written tests do not always do what you think they should[0]). At the same time, the LLMs tend to not code golf unless asked to, and they don't care if they have to wait for dependencies to compile, so that takes away the two major Haskell time sinks.

[0] https://haskellforall.com/2026/05/type-out-the-code#:~:text=...

I think you may find helpful this [1] almost 20 years old [2] agent.

  [1] https://github.com/augustss/djinn
  [2] http://lambda-the-ultimate.org/node/1178

"no global state" sure but sprawling monad constraints mean you're jumping around more than other languages.

The terseness of Haskell just hides the inherent complexity of the problem. The AI (or human) still needs to uncover that complexity in order to do non-trivial things.

I suspect that the compact nature of the syntax would require more tokens spent "thinking" to get decent results. It might be more efficient for simple code though. Either way worth testing. Surely someone must've set up a "how well LLMs handle Xlang" benchmark suite.

Yup, it was mostly pleasure AI coding a company codebase in Scala. I'm considering it for next projects for this reason although my understanding and intuition for Scala code is much weaker than for Python.

I was a little disappointed with the results I was seeing in F#. I thought the .NET + GPT-5.* pull through would be sufficient but it never seemed to work out. Maybe I just wasn’t approaching it correctly.

That only scales to a point. When there gets to be enough work, making it everyone's job ensures that it becomes nobody's job. Usually because one person was doing anyway in an informal capacity, and now they're overloaded.

Source, seen it play out in a non-technical nonprofit that after years of stagnation, went the other way of hiring executive staff to run the day to day stuff. And from currently being part of another organization that is flailing that way presently.

He doesn't have a role at Facebook anymore AFAIK, although I can't find the source now. I remember hearing it was mostly due to filtering engine at Facebook being rewritten in Hack, so they don't have the need for Haskell people anymore.

We're always happy to hear about pain points!

For example, one thing that is a friction point at my own job is knowledge of tooling for performance tuning and optimization. It's not that Haskell doesn't have this tooling, it's just not well-known.

Is there anything in particular you would need?

What do you find about bringing it into production? Is it the actual language patterns or the tools? I've done Haskell in production for over a decade now so I am not sure what challenges newcomers face.

I like it too. It's underrated because the learning curve is very high

You can use the GHC musl container: benz0li/ghc-musl:9.8.4 to create static binaries. I've specialized that into -arm64 and -amd64 containers for forgejo actions.

Anytime I push to my Haskell repos my actions automatically create static binaries for installation on my nodes.

Cross compilation could definitely be easier :-/ I tend to just use github actions and compile from whatever architecture it should run on, so that's a workaround. I long for a day when I can just `cabal build --platform=amd64` etc. and it Just Works without having to download and compile a horde of foreign libs or set up a vm

> Deployment is pain specially on commodity VPS.

Oh? Why is that?

Chair of the HF here -- things are going quite well, actually. We have great sponsors who come back year after year, the HF has been spending more to make infrastructure more reliable (e.g. for Hackage), and we've started a new event series focused on North America (https://haskell.foundation/events/2026-amerihac.html), which has been a great success!

Our metrics are also showing that Haskell usage is actually growing. So overall, can't complain!

It is just a runtime, no? I have only ever heard about it as something to run their own bend programming language.

Are people targeting it as a runtime for Haskell as well?

I don't mean to sound elitist, but in a way, Haskell's difficulty is kind of the point of the language.

The thing that's so elegant about Haskell is that it allows you to express programmatic constructs at a very abstract level. Abstraction is almost by definition difficult to grasp. That's why it takes a decade and a half for (most) people to go from arithmetic to calculus.