Prominent Haskell defector pilloried by anti-AI purists

Jump to main content

Search

REG AD

DEVOPS

Prominent Haskell defector pilloried by anti-AI purists

Haskell adherents revisit the language's tongue-in-cheek 'avoid success at all costs' mantra

Joab Jackson

Joab<br>Jackson

SOFTWARE DEVELOPMENT AND CLOUD REPORTER

Published<br>wed 15 Jul 2026 // 21:37 UTC

Another day, another programming language feels the heat from AI.<br>A prominent Haskell-based software platform is shifting new development to Python, with its founder arguing that Haskell's tooling and ecosystem have been slow to adapt to AI-assisted development.<br>“Haskell is in real danger,” warned Scarf founder Avi Press, in a post entitled “After 7 years in production, Scarf has reluctantly moved away from Haskell.”

REG AD

“AI is here to stay. The people and ecosystems that use it well are going to move much faster than the people and ecosystems that do not.”

REG AD

Press’ post set off a firestorm of controversy within the Haskell community, which is small but vocal, and likely felt the sting of one of its most prominent users defecting to the comparatively toy-like Python to better serve the needs of agents.<br>“Trying to change the language to work better for some metric of ‘better’ with AI is foolish for many many reasons,” wrote one user on Reddit. “It's foolish to try to change to LLMs in a kneejerk fashion because no one knows what's on the horizon.”<br>Putting the fun into functional programming<br>Haskell, a functional programming language that debuted in 1990, may not appeal to fast-moving startups. It ranks No. 46 in the latest TIOBE index of programming language popularity, with a rating of less than half a percent.<br>Favoring recursion and immutable data over conventional imperative loops and mutable state, the language's mathematical underpinnings can intimidate even experienced developers. Nevertheless, it has attracted a highly dedicated following, particularly within academia.<br>Press has been one of Haskell’s most vocal proponents, and has even served on the language’s foundation board. “Learning it made me a much better programmer,” he admitted. Press used Haskell to build Scarf, which provides usage analytics for open source software.<br>In a 2023 talk entitled “Why Haskell is a Terrible Choice for Startups (and why we picked it anyway),” Press admitted it was difficult to find Haskell programmers, yet the language’s rigorous type safety comes with other benefits. Refactoring is a cinch, which is valuable as business priorities change. Also, documents can be auto-generated from data types.<br>Plus, once you get the hang of it, programming in Haskell is downright fun, Press argued.

REG AD

Because AI<br>But going forward, Scarf’s new features will be added in Python instead.<br>“At Scarf, we started doing all new API work in Python,” he wrote. “New API routes go into Python, existing Haskell code keeps running, and over time the new server becomes the main path and our Haskell footprint will shrink.”<br>Press said Python plays better with AI, which is the direction he sees development heading.<br>A huge part of the problem is Haskell's sluggish compilation times.<br>“If an LLM can produce a working implementation in a few minutes, but your compile step takes dramatically longer, then your language and build system have become a bottleneck in the development loop,” he wrote.<br>Long compilation times, once a minor annoyance, become prohibitive when running multiple coding agents at once. Caching can help, but incurs its own overhead to manage.<br>“I want to spin up multiple worktrees, fork off different lines of work, let agents try things, review the results, and keep the useful ones. In that world, cold start time matters a lot,” Press wrote.

REG AD

MORE CONTEXT

Linus Torvalds tells AI haters to fork off

Microsoft chief turns hostile on frontier AI labs, warns companies to guard their IP

Java's Project Valhalla finally lands a preview in JDK 28

HTTP gets a QUERY method so complex searches can stop pretending to be POST

Rigor for runtime<br>Using Python with AI practices immediately improved the Scarf production team’s workflows, allowing them to fix bugs with minimal oversight, Press noted. In some cases, AI can fix a bug “before I get off the call with a customer,” he noted.<br>“Resisting this kind of productivity is not an option anymore,” Press wrote.<br>Yet, Press doesn’t feel that the Haskell ecosystem is addressing the shift to agentic-led development. Many of the language’s maintainers focus more on restricting the use of AI, or restricting its use on Haskell entirely, rather than looking for ways Haskell can better serve AI, or vice versa, he argued.<br>Agents have different bottlenecks than human code jockeys, he noted. “They are cheap at generating code and expensive when blocked. They benefit from fast feedback, clear examples, low setup friction, and errors that help them repair the code quickly,” he wrote.<br>Press listed ways Haskell could be made easier for...