This AI Was So Bad Users Abandoned It In Record Time
By 813 Staff
Silicon Valley insiders report This AI Was So Bad Users Abandoned It In Record Time, according to Machina (@EXM7777) (on March 15, 2026).
Source: https://x.com/EXM7777/status/2033242082018799764
The difference this time isn't a new feature launch or a performance benchmark; it’s the quiet, mounting evidence of user attrition among the very early adopters who are supposed to be an AI model's most fervent champions. Internal metrics and a growing chorus of developer chatter point to a troubling trend for Google's Gemini 3.1 Pro: a significant subset of power users is quietly walking away, citing a product that has failed to find a definitive use case in a crowded field. This isn't about a single buggy update, but a more fundamental question of fit and utility.
The sentiment was crystallized publicly this week by influential tech commentator Machina (@EXM7777), who stated plainly they had "completely dropped" the model. This single tweet resonated because it echoes private feedback circulating on developer forums and in closed Slack channels. Engineers close to the project say internal documents show concern over user retention metrics for the Pro tier, which sits between the free Gemini 1.5 Flash and the ultra-expensive Gemini 3.1 Ultra. The rollout has been anything but smooth, with users reporting that while the model is competent, it hasn't demonstrated a clear, must-have advantage over existing offerings from OpenAI or Anthropic for specific, demanding workloads. For a cohort that relentlessly optimizes for cost-to-performance, "good enough" often isn't.
This matters because the AI platform war is entering a brutal consolidation phase. It’s no longer about who has the most impressive research demo, but who can build and sustain a loyal developer ecosystem that ships real products. Losing the Machinas of the world—the well-connected early testers whose choices influence entire tech stacks—creates a vacuum that competing models are eager to fill. It signals a potential failure to articulate a compelling reason for builders to invest their time and infrastructure into Google's AI suite, which is critical for the company's broader cloud and services strategy.
What happens next is a period of intense scrutiny on Google's I/O developer conference in May. The company must either unveil a significant, differentiating capability for Gemini 3.1 Pro that addresses the "why this model?" question, or it may need to reconsider its positioning and pricing structure entirely. The uncertainty lies in whether this user drift is a temporary blip or an early indicator of a more serious positioning problem. All eyes are now on the AI division's next move to stem the bleed of its most valuable users before the narrative solidifies into accepted industry wisdom.
