2 posts tagged with "ai-product-strategy"

You ship an AI-powered summary feature for your document editor. Adoption is great — 40% of users activate it within the first week. Your PM writes a celebratory Slack message. Two months later, average session duration has dropped 25%, collaborative editing is down, and your power users are quietly churning. Nobody connects these trends to the shiny new feature because the dashboard that tracks the summary feature shows nothing but green.

This is AI feature cannibalization: when an AI shortcut solves a user's immediate problem while destroying the engagement loops that make your product worth paying for. It is one of the most insidious failure modes in product development today because every metric that tracks the feature itself looks healthy, even as the product-level metrics decay.

Here's a test every AI startup founder should take: if OpenAI, Google, and Anthropic all shipped exactly what you're building tomorrow, would your users stay? If the honest answer is no, you haven't built a product — you've built a feature on borrowed time.

Between 2023 and early 2025, roughly 3,800 AI startups shut down — a 27% failure rate — with another 1,800 closing in early 2026. Many weren't bad teams or bad ideas. They were thin wrappers around foundation model APIs, and the platform ate them alive. Foundation model pricing collapsed 98% within a single year — the fastest technology commoditization cycle in history — and every pricing drop made the wrapper layer thinner.