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What's the best programming language for coding agents?

danluu.com

August 10, 2026

53 min read

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53/100

Summary

Dynamically typed programming languages are generally more token efficient in LLMs compared to statically typed languages due to their ability to omit explicit type declarations. This efficiency leads to lower token costs when coding agents.

Key Takeaways

Dynamically typed languages generally have a lower LLM token cost than statically typed languages due to the omission of explicit type declarations, making the code more compact.
Clojure is identified as the most token-efficient language in the comparison, while C ranks as the least efficient, with a gap of 2.6x between them.
Array languages, like J, can achieve high token efficiency, averaging just 70 tokens, nearly half that of Clojure's 109 tokens.
Performance on trivial tasks does not generalize, and the results of evaluations can be misleading if the problems are overly simplistic.

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Community Sentiment

Mixed

Positives

Go is hailed as a top choice for LLMs due to its simplicity and consistency in training data, making it easier for models to generate reliable code.
Commenters note that frontier LLMs excel at picking up various programming languages quickly, which is a promising sign for future applications.
Some users have been pleasantly surprised by how well LLMs handle Gleam and Lustre, suggesting that languages focusing on human-friendly features may also benefit AI models.

Concerns

Many commenters argue that Python's training data is tainted by poor-quality code from non-software engineers, which hampers LLM performance.
One user expresses frustration with LLMs' performance in Gleam, noting they often produce incorrect or irrelevant code due to biases in training data.
There are concerns about evaluating programming languages solely based on token efficiency, as it may overlook how LLMs actually handle real-world programming tasks.