We're drowning in AI product launches, and most of them are solving problems that don't exist.
This week alone, we've watched companies sprint toward complexity like it's a virtue. New toggles, new integrations, new AI layers bolted onto existing products. The pitch is always the same: "We added intelligence." The result? Users who are more confused, not less.
Here's the uncomfortable truth that venture capitalists and product teams don't want to hear: The winners in this AI cycle won't be the companies that add the most features. They'll be the ones brave enough to subtract.
Look at what's actually working right now. Users are paying for a $9 physical key that locks their phones. Why? Because simplicity is a luxury good. In a world of infinite options and algorithmic rabbit holes, the ability to just turn something off is genuinely valuable. That's not sexy. That's not an AI story. But it sells.
Meanwhile, we've seen what happens when companies get too clever too fast. Google launched an Earth AI feature and yanked it within 24 hours because it was generating misinformation. That's not a failure of AI technology. That's a failure of asking "should we?" instead of just "can we?" It's the product management equivalent of moving fast and breaking things, except the thing you broke was user trust.
The real opportunity isn't in piling on capabilities. It's in curation. It's in saying no to 90 percent of the ideas so the 10 percent that matter can actually work.
Consider the state of app ecosystems globally. India is an interesting case study here. Markets that aren't saturated with legacy software have different expectations. They're starting to pay for apps not because those apps do everything, but because they do one thing well. That's a signal we should all be reading.
The AI products that will actually matter are the ones that make your workflow simpler, not smarter. Make your decision-making faster, not fancier. Make your life easier, not more optimized.
Instead, we're getting the opposite. We're getting AI chatbots bolted onto every platform. We're getting recommendation systems trained on recommendation systems. We're getting products that require their own instruction manuals to understand what they're actually for.
This isn't a technology problem. It's a discipline problem. Product teams are operating under the assumption that more features equal more value. That might have worked in the 2010s when the competition was other humans trying to build software. But when the competition is simplicity itself, you need a different playbook.
The operators who will win this decade are the ones who understand that artificial intelligence doesn't mean artificial complexity. They're the ones who'll look at an AI capability and ask hard questions: Does this actually solve a customer problem? Does it make the product easier to use or harder? Am I adding this because it's necessary or because it's possible?
That's not cynicism. That's realism. The market is already shifting. Users are voting with their attention, and they're choosing products that respect their time. They're choosing the reading apps that work. They're choosing the tools that do one job and do it well.
The hype cycle will continue. More features will ship. More layers will be added. But when the dust settles, the companies standing will be the ones that resisted the urge to build everything and chose to build something instead.