Show HN: Jido 2.0, Elixir Agent Framework

I really like the focus on “data and pure functions” from the beginning of the post.

I’ve read a lot on HN about how BEAM execution model is perfect for AI. I think a crucial part that’s usually missing in LLM-focused libraries is the robustness story in the face of node failures, rolling deployments, etc. There’s a misconception about Elixir (demonstrated in one of the claw comments below) that it provides location transparency - it ain’t so. You can have the most robust OTP node, but if you commit to an agent inside a long running process, it will go down when the node does.

Having clear, pure agent state between every API call step goes a long way towards solving that - put it in Mnesia or Redis, pick up on another node when the original is decommissioned. Checkpointing is the solution

Yep - BEAM has great support for audio workloads - would love to chat

GP is just spamming a bunch of threads with comments about their product. They aren't actually here for the discussion, check their comment history.

Fair enough! My comment is about agentic-focused libraries in general, it’s inaccurate of me to call all such libraries “LLM-focused”

Speaking of inaccuracies, BEAM does provide pretty good location transparency - but resource migration between nodes in particular is not part of the built-in goodies that OTP brings

cool

Although... the agent orchestration is really the easy part. It is just a loop. You can solve this in many different ways and yes some languages are more suitable for this than others. But still - very straightforward.

The hard part is making sure these agents can do useful things which requires connecting them to tools. Although just adding bash might seem like checking that box the reality is more complex when it comes to authentication (not only). It is even more problematic when you need to run this in some sort of distributed way where you need to inject context midway, abort or pause and do so with all the constraints in mind like timing issues for minted urls and tokens, etc. Btw, adding messages to the context while LLM is doing some other job (which you might want to do for all kinds of reasons) does not always work because the system is not deterministic. So you need to solve this somehow.

Even harder is coming up with useful ways to apply the technology. The technical side of things can be solved with good engineering but most of the applications of these agents are around pretty basic use-cases and the adoption is sort of stagnated. 99% of these agents are question/answer bots, task/calendar organisers, something to do with spam and the most useful one is coding assistants.

And so frankly I think the framework is irrelevant at this point unless one figures out how to do useful things.