Are lightweight multi-model workflows a practical alternative to simple agent validation?

One thing I’ve noticed while experimenting with AI workflows is how much time gets spent validating outputs manually.

A lot of agent setups solve this with reviewer/validator agents, but lately I’ve been testing a lighter approach using asknestr to compare multiple model outputs side by side before moving into more complex pipelines.

What’s interesting is that disagreements between models often reveal weak reasoning much faster than relying on a single response.

It obviously doesn’t replace full agent orchestration or evaluation systems, but for early-stage research and ideation it’s been surprisingly useful.

Now I’m curious whether lightweight multi-model comparison could become a common “first-pass validation layer” in agent workflows.

Would love to hear how others here are handling reliability/validation in their own setups.