Two years ago, the most interesting sentence you could say in a developer forum was "I'm building an AI tool." Now it's the default assumption - so expected that developers are actively looking for conversations about everything else.
That shift is showing up in questions circulating through developer communities: what are people building that isn't AI-related? The people asking aren't hostile to AI. They say so directly. They've just noticed that technical forums have been absorbed almost entirely by model announcements, agent framework launches, and wrapper app pitches - and they find it exhausting.
This is a familiar pattern. Every technology wave produces this moment - the point where the dominant topic crowds out almost everything else. It happened with mobile apps around 2011 to 2013, blockchain in 2017 to 2018, and no-code platforms in 2020 to 2021. The AI wave has lasted longer because the underlying technology keeps delivering genuinely new capabilities rather than stalling after the initial excitement.
What the Overcrowding Actually Costs
The concrete effect for developers building non-AI projects: reduced visibility and weaker peer feedback. Developer forums have self-selected around AI topics. A well-built compiler, data visualization tool, hardware project, or game engine can struggle to get traction in a community where a new AI benchmark post or "I built X with Claude in 3 hours" story consistently pulls more engagement.
This isn't a complaint about AI coverage being invalid - most of it covers legitimate news. The problem is ratio. When the vast majority of technical conversation clusters around one category of tools, the feedback loops that help non-AI projects improve get weaker. Fewer eyes, fewer useful critiques, slower iteration.
What the Fatigue Doesn't Mean
AI fatigue in conversation is not the same as AI declining in usefulness. ChatGPT, Claude, and developer tools like Cursor are adding users, not losing them. The fatigue is about discourse saturation - what gets discussed publicly versus what people actually use day to day.
The more accurate read: AI is becoming infrastructure. Like databases in the 2000s or cloud hosting in the 2010s, it's shifting from being the story to being a component inside other stories. When that transition happens, conversations naturally fragment - some people focus on the AI layer, others move back to what they're building on top of it.
For companies building AI tools, the saturation has a practical consequence: differentiation is harder. A year ago, "we use AI" was a meaningful claim. Now it's table stakes. The products likely to pull ahead are the ones where the AI is invisible to the user - where someone describes it as a great writing tool or a great code reviewer, not a great AI tool.
Developers asking what else people are building aren't rejecting the technology. Most are probably using AI somewhere in their stack without making it the headline. That's what mature adoption looks like.