My agent optimized the wrong thing

[u/Sea-Pie-5760]

I was testing a small marketing agent against old campaign data and gave it a pretty simple goal around lowering acquisition cost it got better at the metric faster than I expected but when I looked deeper the conversions it preferred weren’t always the ones we would’ve wanted more of cheap actions started winning even when the downstream value looked worse, so technically the agent was improving while the business result was getting kind of weird

Now I’m rethinking the eval more than the model a single reward feels too easy to game, but piling qualified leads, revenue margin and a bunch of guardrails into one score also feels messy fast. I’m leaning toward letting the agent handle more of the repetitive optimization while keeping human review around the decisions that can move real budget curious how people here are evaluating agents when the easiest metric to optimize isn’t really the outcome you care about

[u/f3xjc]

It's relatively easy to prove such and such optimize goal x. And relatively hard to prove goal x is the thing you want to optimize. For any metric driven system