Is there a reason why so many of these agent harness are written in node.js?
1. it's built for async 2. runs everywhere 3. interpreted, making it fast to iterate on 4. decent performance 5. most popular language, llms are decent at writing it
Probably for the ease of coding extensions — which strikes me as outdated thinking: if it’s open source and you’re outsourcing the coding to LLMs, why not use a compiled, safe language?
There’s an interesting counter example for DeepSeek called CodeWhale, though:
I'm not sure why specifically Javascript instead of something like Python or other options, but using an interpreted environment minimizes the friction for implementing extension systems, which are an important feature in AI harnesses.
codex is written in rust fwiw
smol has implementations in Go, Python, Clojure, PHP
https://github.com/smol-env/smol
out of the box an agent only needs to be able to do http requests and call tools (which might again be just http requests or shelling out)
there is no inherent reason for why an agent has to be in JavaScript or Typescript
but they are popular languages and come with runtimes and libraries for http requests, steaming, TUI (terminal ui) and so on which can help
TypeScript is great and its ecosystem is easy to work within.
Because that hammer is their only tool!
I gotta same problem.
Might be easier to do cross platform.
npm as a distribution tool works well and typescript has types.
Any reason why it should not be written in nodejs?
Nothing better for UI than React. Electron/tauri or node kinda falls from it.
Skill issue. Their models don't work for serious programming so everyone just copies Electron apps from each other.
Because:
1. The first significant agentic harness was made by Anthropic.
2. One of the most senior developers of client-side software at Anthropic is Felix Rieseberg, one of the original creators of Electron. [1]
3. After Claude Code blew up, everyone else copied Anthropic.
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1: https://daringfireball.net/2026/07/claudes_criminally_bad_ma...