u/ApartmentHappy9030

I’ve been working on multi-agent workflows for real use cases (not just chat), and built a small demo around customer operations.
Instead of a single LLM, this uses multiple agents with defined roles (analysis, decision, execution), coordinated through an explicit workflow.
It’s built on Spring AI, but the focus is on orchestration — managing execution flow, retries, and state between agents.

What it does:
routes requests across specialized agents

enforces a structured execution flow

keeps state across steps instead of relying on a single prompt

The main challenge I’ve seen isn’t the models — it’s orchestration:
keeping execution predictable when agents interact

handling retries and partial failures without breaking the flow

managing shared state without turning everything into implicit prompt context

Curious how others are handling this in practice:
are you using explicit orchestration (graphs / workflows), or keeping it implicit in prompts?

how do you deal with failure handling across multi-step agent pipelines?

do you keep state externally, or rely on the model context?

Interested in real-world approaches , especially beyond toy demos.

I’ve been working on RAG setups recently, and something keeps coming up.

Simple pipelines work fine:

query → retrieve → generate → done

But as soon as things get more complex, it starts breaking down:

- multiple retrieval steps

- retries when retrieval fails

- combining different sources

- keeping track of intermediate state

- validating the final answer

Most examples stay linear, but real workflows aren’t.

I ended up experimenting with a graph-based approach to orchestrate the flow:

- separate agents for retrieval, reasoning, validation

- shared state across steps

- retries and recovery when something fails

It’s not a RAG tool per se, more like a way to structure non-linear, stateful workflows around RAG.

Example flow:

User query

→ retrieve (vector DB)

→ refine query

→ retrieve again

→ synthesize answer

→ validate output

Curious how others are handling this.

Are you sticking with linear pipelines, or moving toward something more structured?