Don't feel pressured to label every AI-powered enhancement as an "AI feature." For example, using AI to generate CSS for a new dark mode is simply a better way to build. The focus should be on the user benefit (dark mode), not the underlying technology, making AI an invisible, powerful tool.

Public discourse on AI often misses a key dichotomy. While consumer-facing AI products are widely disliked and fail to deliver value, AI has found significant product-market fit within the enterprise for tasks like coding and business process automation. This explains the disconnect between venture capital hype and public skepticism.

In an era of infinite replicability, startups have two viable paths. They can either operate in stealth with a non-obvious, defensible insight ('a secret incantation'), or tackle an obvious problem and win by completely owning the public narrative. The middle ground is no longer viable.

In SaaS, value was delivered through visible UI. With AI, this is inverted. The most critical, differentiating work happens in the invisible infrastructure—complex RAG systems and custom models. The UI becomes the smaller, easier part of the product, flipping the traditional value proposition.

As consumers become wary of "AI," the winning strategy is integrating advanced capabilities into existing products seamlessly, like Google is doing with Gemini. The "AI" branding used for fundraising and recruiting will fade from consumer-facing marketing, making the technology feel like a natural product evolution.

The public readily accepts "invisible" AI in platforms like Instagram or Google Search. The backlash is specifically targeted at generative AI, which is perceived as a direct threat to knowledge work. This highlights a crucial distinction in how different AI applications are perceived based on their visibility and impact on labor.

Kraftful built a complex system with six AI agents but never exposed this to users. Its success came from hiding the AI and focusing relentlessly on delivering simple insights that solved a specific user problem, proving users care about outcomes, not the underlying tech.

Judging consumer AI's success by chatbot user growth is misleading. The real adoption is happening 'invisibly' as generative AI enhances existing popular experiences, like Instagram's recommendation engine and Amazon's product search, rather than in standalone chat apps.

Unlike other tech rollouts, the AI industry's public narrative has been dominated by vague warnings of disruption rather than clear, tangible benefits for the average person. This communication failure is a key driver of widespread anxiety and opposition.