Why doing agents with go?
Python is way more ergonomic when dealing with text than go. Go's performance advantages are basically irrelevant in an AI agent, as execution time is dominated by inference time.
Python is way more ergonomic when dealing with text than go. Go's performance advantages are basically irrelevant in an AI agent, as execution time is dominated by inference time.
Go is the sweet spot in expressive concurrency, a compile time type system, and a strong standard library with excellent tooling as you mentioned.
My hope is that, similar to Ruby in web development, Python's mind share in LLM coding will be siphoned to Go.
Inference time is only the bottleneck if you are running a single agent loop, for a single consumer, with a single inference call being made at a time.
If you are serving a bunch of users, handling a bunch of requests, not all of which result in inference calls, some of which may result in multiple inference calls being made in parallel in independent contexts, you start to understand that concurrency matters a lot.
Might as well start with a language that helps you handle that concurrency instead of a language that treats it (asyncio) as a bastard edge case undeserving of first-class support.
Fwiiw I noticed that colleagues using other languages like Java and JS with Claude Code sometimes get compile errors. I never get compile errors (anymore) with Go. The language is ideal for LLMs. Cant tell how CC is doing lately for Python.
Personally I could see Go being quite nice to use if you want to deploy something as eg a compiled serverless function.
I'm assuming the framework behaves the same way regardless of language so you could test using Python first if you want and then move over to eg Go if needed.