That said, they can potentially get you a speedup if you have a neatly separable task, and can parallelize the work. But it doesn't lead to some quantum leap in what agents are able to accomplish unsupervised.
I do think some form of multi-agent workflow is going to become important over the next few years, but more because it fits our mental model of the world rather than being some big technological unlock.
I think the theoretical value of multi-agents is collaboration with external agents (outside your code base). Other than that, there is a very little use cases where it make sense (e.g. https://www.anthropic.com/engineering/built-multi-agent-rese... ), and building it / debugging them take much much longer and is much harder. So unless you have the ressources, not worth the trouble
I agree that multi-agent doesnt work in practice. But this isnt that.
Using different models for different things isn’t new at all. The article seems like an excuse to get some marketing out there (and it’s poor at that - they got me looking at what was built with their product but I can’t see the actual code. Feels scammy.)
2. Creating single agent systems is already quite tricky. The best practices and LLMOps workflows are far from mature. Jumping to multi-agent systems is very early imo. My suggestion to any builder in this space is to start simple, very simple, and then add complexity, instead of building a house of cards.
Agentic AI definitely works for software engineering because we have suitable mitigations for its limitations. It is unclear what those mitigations might be in other fields of application.
