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tech 11 July 2026

Scarf Moves Away from Haskell After 7 Years: A Difficult but Necessary Decision

After 7 years in production, Scarf has made the difficult decision to move away from Haskell. Despite the language's robustness and reliability, new dynamics introduced by AI models have shifted the balance.

Article inspired by the original source
After 7 years in production, Scarf has reluctantly moved away from Haskell ↗ avi.press

Introduction

Scarf, a tech company renowned for its commitment to Haskell, recently decided to move away from the language after seven years in production. This decision was not made lightly, as Haskell has played a central role in Scarf's technical success. However, the rapid evolution of technologies, particularly the rise of AI language models (LLM), has redefined development priorities and needs at Scarf.

Why Haskell Was the Ideal Choice

Haskell was chosen for its unique features that make it a reliable and powerful language. Haskell's type system is one of the most advanced, capturing errors at compile time and ensuring code stability in production. Scarf built its backend using libraries like Servant and Beam, allowing seamless integration with PostgreSQL. High-performance services were also developed, proving Haskell's effectiveness in a demanding production environment.

The Challenges of Haskell

However, using Haskell also presented notable challenges. Compilation times and ecosystem friction required constant optimizations of builds, caches, and development environments. Although Scarf's team mastered these tools, the costs in time and resources became significant.

The Impact of AI Models

With the advent of LLMs, the dynamics of software development have changed. These models can generate code quickly and efficiently, altering the relative value of compile-time type checking. If an AI model can produce a working implementation in minutes, but compilation takes significantly longer, the cost of type safety becomes a critical factor.

Use Cases and Recent Figures

Companies like OpenAI and Google have demonstrated that AI can significantly reduce development time. According to a McKinsey study, AI could increase developer productivity by 10 to 50%. For Scarf, the agility and speed of development offered by LLMs outweighed the benefits of Haskell.

Conclusion

Scarf's decision to leave Haskell is emblematic of the changes the software industry is undergoing. While Haskell offers robust type guarantees, the shift towards more agile, AI-assisted development methods is a trend that many companies are likely to follow. If you're looking to navigate these changes, let's discuss your project in 15 minutes.

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