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Apache Burr: Build reliable AI agents and applications

burr.apache.org

41–50 of 125 posts

Re: Apache Burr: Build reliable AI agents and applications

#41

I think the marketing copy probably needs to focus on differentiating features vs any myriad of agent frameworks. I took one look at the sample and immediately said "This is literally just langgraph with a builder pattern"

Right -- possible it's slightly out of date https://github.com/apache/burr#-comparison-against-common-fr.... Good point on differentiating.

Re: Apache Burr: Build reliable AI agents and applications

#43
On a tangent, can anyone recommend good coding agent orchestration tools or platform? Something to launch, manage and monitor codex or claude agents in multiple machines

Ideally self-hostable/open source

I know claude code has a lot of that internally built in already, but it’s claude-only

Re: Apache Burr: Build reliable AI agents and applications

#44
post #4

First time I hear about Burr, curious why it was incubated in Apache.

Cause I submitted it. Learning the Apache process and cranking on other things has been a slow process. But we've got some momentum and beginning more regular releases.

Re: Apache Burr: Build reliable AI agents and applications

#45
post #6

I'm still on the fence about agent frameworks, they have their place, and it depends on the nature of the agent: e.g. "Low latency, return a good enough response in 3 seconds, vs. working for 3 hours on a problem." BUT, if you boil it down, an agent really is context building, making an LLM call, executing requested tool calls, parsing the final model output, returning it to some frontend. There's extensions like mem…

Right I think this is why we made it unopinioated to a fault. Burr doesn't really do these things rather it just provides an orchestration framework. So it's pure BYO functions, classes, components, etc...

Re: Apache Burr: Build reliable AI agents and applications

#48
post #6

I'm still on the fence about agent frameworks, they have their place, and it depends on the nature of the agent: e.g. "Low latency, return a good enough response in 3 seconds, vs. working for 3 hours on a problem." BUT, if you boil it down, an agent really is context building, making an LLM call, executing requested tool calls, parsing the final model output, returning it to some frontend. There's extensions like mem…

It’s painfully obvious that you can just open your coding harness and… tell it you’d like to make an agent. They’re simple to write.

This is where it's nice to have some guardrails -- coding agents work etremely well with limitations.

Re: Apache Burr: Build reliable AI agents and applications

#50
post #12
post #2

I couldn't find an explicit reference for the naming, but for anyone wondering there is a Hamilton example: https://github.com/apache/burr/tree/main/examples/multi-agen...

Burr is named after Aaron Burr, founding father, third VP of the United States, and murderer/arch-nemesis of Alexander Hamilton. What's the connection with Hamilton? This is DAGWorks' second open-source library release after the Hamilton library We imagine a world in which Burr and Hamilton lived in harmony and saw through their differences to better the union. We originally built Burr as a harness to handle state be…

Right it was a bit of a joke. Originally stefan and I presented frameworks when we were at stitch fix -- stefan called his "hamilton" and I called mine "burr". His was better for the use-case. But then we wanted to build something for state machines as opposed to DAGs, so we called it Burr. I wanted the git tagline to be "make your agents go burr..."
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