> Overall, our Rust rewrite and following performance hillclimbing has made Prime Agent significantly faster and more resource efficient. With time to input roughly 14x faster than TypeScript and using over 80% less memory after startup
I'm interested in their Planner -> Implementer -> Reviewer -> Verifier process they used for this transition to Rust. I've see similar but curious how they actually implemented this.
Curious how this could be applied to greenfield coding rather than just making a copy in a new language or performance optimizing.
So they used Prime Agent and GLM 5.3 to swarm and rewrite the code in Rust. This also shows Prime Agent doing what it preaches by rebuilding itself. Since Prime Agent is Pi under the hood, will they push a Rust rewrite to Pi? Pi extensions use Typescript so I wonder if they will work.
I don’t see many people talk about Prime Agent, I always wondered if it could just be a Pi extension cause it seems to be a subagent orchestration agent.
Kinda wish people break down token usage into input (cache hit), input (cache miss) and output when talking about it. Giving a total 200B tokens number doesn’t help gauge costs.
I know people tend to hate on rust rewrites. But having something that compiles to a single binary that you can just copy over and get started has its advantages especially when working with sandboxes etc.
The real win is cold starts: a single static binary beats dragging Node into thousands of ephemeral sandboxes every time.
We already knew TypeScript was the wrong language for many use cases from the start as an excuse to not learn Rust.
Now there is no excuses to not use Rust and it just shows in raw performance alone.
> Overall, our Rust rewrite and following performance hillclimbing has made Prime Agent significantly faster and more resource efficient. With time to input roughly 14x faster than TypeScript and using over 80% less memory after startup
very nice outcome of this port
I'm interested in their Planner -> Implementer -> Reviewer -> Verifier process they used for this transition to Rust. I've see similar but curious how they actually implemented this.
Curious how this could be applied to greenfield coding rather than just making a copy in a new language or performance optimizing.
So they used Prime Agent and GLM 5.3 to swarm and rewrite the code in Rust. This also shows Prime Agent doing what it preaches by rebuilding itself. Since Prime Agent is Pi under the hood, will they push a Rust rewrite to Pi? Pi extensions use Typescript so I wonder if they will work.
I don’t see many people talk about Prime Agent, I always wondered if it could just be a Pi extension cause it seems to be a subagent orchestration agent.
If anyone wants a 100% parity Rust port of v1.0 DeepSeek Harness, I have one here: https://github.com/trevorprater/SeekDeep-Harness
What benefits have you seen from using the DeepSeek Harness? What were you using before?
Kinda wish people break down token usage into input (cache hit), input (cache miss) and output when talking about it. Giving a total 200B tokens number doesn’t help gauge costs.
Does anyone have experience to share about their Prime Agent harness? Does it do anything that regular harnesses paired with a memory plugin can't do?
I know people tend to hate on rust rewrites. But having something that compiles to a single binary that you can just copy over and get started has its advantages especially when working with sandboxes etc.
Convenient yes, but also not just a rust thing!