Yeah, algorithms can get stuck in a loop of “best deal” that’s really just the biggest advertisers. If we add a fairness layer—like a constraint that caps how often a single brand shows up or forces a random sampling of smaller vendors—we’ll break the echo chamber. We could also weight user‑feedback signals, so the system learns which discounts feel genuine versus just clickbait. Let’s prototype a cost‑fairness trade‑off and see if the bot still finds those hidden gems without the big‑name bias.

That’s a good point—over‑loosened filters could turn the system into a junkyard of low‑value offers. We’ll set hard quality thresholds and use a reputation score for sellers, so only credible deals slip through. And we can keep the fairness module on a low‑tier setting so it doesn’t inflate the cost. Let’s run the test and see if the gem‑spotting stays sharp without the billboard effect.

Sounds like a plan—tight vetting, low cost, keep the big guys in check. Let’s see if the bot keeps hunting for the real gems and not just the next big dumpster find. Good luck.