Declarative DSL is a really interesting approach, especially since you’re exposing it directly to the users. There are some applications where throwing the dice in production by having LLM as part of the runtime is not an option.
Yes! Clearly the introduction of LLMs into the mix raises the problem of throwing dice.
The point of view we chose is: how to orchestrate the collaboration between AI, Software and people?
With our aim to have repeatable workflows, this drove us away from building autonomous agents and towards a place where the software is in command of the orchestration. Then the Humans and AI can discuss "what you want to do" and have software run it and use AI where it's needed.
Sorry, I guess I'm not fully understanding what this is exactly. Would you describe this as a low-code/no-code agent generator? So if you can define requirements via a pipelex "config" file, Pipelex will generate a python-based agent?
Hi RoyTyrell,
I guess you could call it low-code, a new kind of no-code where we have natural language in the mix.
But no, Pipelex does not generate a python-based agent: the pipelex script is interpreted at runtime.
Very cool declarative + agent-first is the right direction. Love the “Dockerfile for AI reasoning” analogy. Excited to try composing Pipelex with Codiris workflows.
Declarative DSL is a really interesting approach, especially since you’re exposing it directly to the users. There are some applications where throwing the dice in production by having LLM as part of the runtime is not an option.
Yes! Clearly the introduction of LLMs into the mix raises the problem of throwing dice. The point of view we chose is: how to orchestrate the collaboration between AI, Software and people? With our aim to have repeatable workflows, this drove us away from building autonomous agents and towards a place where the software is in command of the orchestration. Then the Humans and AI can discuss "what you want to do" and have software run it and use AI where it's needed.
Sorry, I guess I'm not fully understanding what this is exactly. Would you describe this as a low-code/no-code agent generator? So if you can define requirements via a pipelex "config" file, Pipelex will generate a python-based agent?
Hi RoyTyrell, I guess you could call it low-code, a new kind of no-code where we have natural language in the mix. But no, Pipelex does not generate a python-based agent: the pipelex script is interpreted at runtime.
Very cool declarative + agent-first is the right direction. Love the “Dockerfile for AI reasoning” analogy. Excited to try composing Pipelex with Codiris workflows.
Waiting for partnership to propose to our users
Thanks, Ronald! Yes, very interested in discussing integrations. Pipelex is super modular and open by design, so it should be a breeze.