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I built several harnesses in different products over the last two years. Fully agree with you that doing it right is a rabbit hole. Certain system properties that you almost always want in a harness used within a SaaS (for example) are non-obvious at the start and require certain architectural choices. It's easy to start down a path and then find a gap a couple days before launch.

Async tool calls, having the agent wait indefinitely for a human response, and showing a form or questions to the user via a tool call are a few common capabilities that come up that a product manager might miss at first.

This is why I've been building Nvoken. LLM agnostic, ergonomic SDKs, flexible tool call patterns, tenant and user-aware budget enforcement, etc.

I'd really appreciate any and all feedback on this! It gives you some free tokens on signup and it's super quick to try.

https://nvoken.com



> Async tool calls, having the agent wait indefinitely for a human response, and showing a form or questions to the user via a tool call are a few common capabilities that come up that a product manager might miss at first.

All of this is specified in the ACP spec, so if you build your agents from that - you don't end up skipping features.

Also vital is proper prompt caching, tool design and some connection retry mechanism.


> All of this is specified in the ACP spec

Oh good reminder. I need to do that.

> Also vital is proper prompt caching, tool design and some connection retry mechanism.

prompt caching is weirder than i originally thought, and so variable across providers. Retry is easy, but can you explain more on tool design?


The best advice is to use evals to improve any code that produces output that goes into the LLMs context.




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