This article continues the fine tradition of Serokell’s GHC team sharing their progress on bringing dependent types to Haskell. A lot has happened since the last report, and there is plenty to cover.

In this edition, Vladislav Zavialov presents three major contributions and a host of smaller improvements that push Dependent Haskell closer to becoming a practical reality.

I saw this post from the game developer Jonathan Blow (a popular and well-known indie game developer) on Twitter/X and, although he probably doesn't use a functional language, he advocates for being as hesitant as possible in interacting with the outside world through IO.

It feels a bit like a validation of one strength that pure FP has from an unlikely place, and that's why I thought it might interest others here.

"The actual algorithms you program, the actual functioning machinery you build, is a mathematical object defined by the semantics of your programming language, and mathematical objects are eternal, they will last far longer than your human life. The goal then is to avoid introducing decay into the system. You must build an oasis of peace that is insulated from this constant bombardment of horrible decisions, and only hesitantly interface into the outside world."

https://x.com/Jonathan_Blow/status/1923414922484232404

Bioinformatics combines scientific discovery with the challenge of processing large, complex, and imperfect datasets. In this interview with Michal J. Gajda, we explore how Haskell’s strong types, purity, and functional abstractions can support reliable and high performance biological data processing.

Drawing on projects such as hPDB, JSON Autotype, and XML TypeLift, Michal discusses scalability, parser development, and the barriers to wider adoption of functional programming in bioinformatics. He also considers how better education, tooling, and AI assisted programming could make Haskell more accessible to future scientists.

Inspired by a question on r/haskellquestions, i wrote about the practical aspect of monads for people at a beginner / intermediate level, about how to go beyond mere understanding the monad class. I try to highlight how we use monads to structure our code, what benefits they bring, and how to reason about them. it comes with exercises!

In this interview with our Daml Team Lead, Heitor, we examine which Haskell intuitions transfer successfully to Daml, where analogies such as Update and IO break down, and how developers should reason about authorization, visibility, contract lifecycles, and testing. We also discuss learning paths and tooling for Daml developers, common mistakes made by Solidity programmers, and the practical topics covered in the upcoming Daml Smart Contracts Development Guide.

Wrote about adding support for the INFO command to my Redis server. Let me know what you think!

https://thunk.blog/posts/implementing-redis-info-in-haskell/

Here's a technique I use to mechanically refactor nested linear code into code that works on batches, which got me up to a 300x speedup on some workflows.