When someone claims their system "navigates the explore/exploit tradeoff," they're not saying anything meaningful — that phrase has become table stakes in conversations about agentic systems. But that doesn't make the underlying challenge any less important.
Think of it this way: if you only explore, you're like a mountaineer who says "I don't care which mountain is highest, I'll just keep climbing." You'll never settle on the best path. If you only exploit, you're the climber who summits a handful of peaks, points to the highest of that handful, and declares it to be the highest mountain in the world. Both approaches fail at the actual goal: finding the true highest peak of customer engagement.
The critical question isn't whether a system balances exploration and exploitation — practicaly any system nowadays claims to do that — but rather how it achieves that balance. And when you start digging into the "how," you'll encounter two major red flags that reveal superficial implementations.
Our agents analyze past user behavior to determine the best times (or channels, or copy, etc.) to engage.
Translation: “We’re 99% focused on exploitation, with any exploration being undocumented and probably accidental.
These systems lean entirely on historical data. They'll use terms like "predictive modeling" while fundamentally just replaying past patterns. It's better than nothing, but it just leaves so much value unrealized - you never find that highest peak because you stopped climbing new mountains.
We explore dozens of different messages and pick the ones that work best.
Translation: “Our exploration is so limited it provides no lasting value.”
Frankly, any time someone actually specifies the number of messages or the number of winners, you should be skeptical. There should be nearly as many winners as there are users, and the number of message variants should be even higher than that. Testing a handful of subject lines might pad your numbers in the short term but it's not going to shift your customer experience. And there is no “best” message — only different bets with varying success.
If you don’t understand how a system balances exploration and exploitation, you can’t trust what outcomes it’s optimizing for — and that’s not a technical detail, it’s a business risk.
