When a user's goal is purely transactional (e.g., booking a flight), they have little loyalty to the app's UI. AI agents can directly fulfill these tasks, making such apps obsolete because their primary value is intermediation, not a unique, loyalty-building experience.
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As AI makes it easy to generate 'good enough' software, a functional product is no longer a moat. The new advantage is creating an experience so delightful that users prefer it over a custom-built alternative. This makes design the primary driver of value, setting premium software apart from the infinitely generated.
Generative AI primarily changes an app's user interface, but agentic AI can bypass UIs entirely to complete tasks. This makes transaction-fulfillment apps, which constitute a huge portion of the market, vulnerable to being replaced by agents that act directly on a user's behalf.
The review of Gemini highlights a critical lesson: a powerful AI model can be completely undermined by a poor user experience. Despite Gemini 3's speed and intelligence, the app's bugs, poor voice transcription, and disconnection issues create significant friction. In consumer AI, flawless product execution is just as important as the underlying technology.
AI is becoming the new UI, allowing users to generate bespoke interfaces for specific workflows on the fly. This fundamentally threatens the core value proposition of many SaaS companies, which is essentially selling a complex UX built on a database. The entire ecosystem will need to adapt.
The "DoorDash Problem" posits that AI agents could reduce service platforms like Uber and Airbnb to mere commodity providers. By abstracting away the user interface, agents eliminate crucial revenue streams like ads, loyalty programs, and upsells. This shifts the customer relationship to the AI, eroding the core business model of the App Store economy's biggest winners.
The most durable moat for enterprise software is established user workflows. The current AI platform shift is powerful because it actively drives new behaviors, creating a rare opportunity to displace incumbents. The core disruption isn't just the tech, but its ability to change how people work.
The most effective application of AI isn't a visible chatbot feature. It's an invisible layer that intelligently removes friction from existing user workflows. Instead of creating new work for users (like prompt engineering), AI should simplify experiences, like automatically surfacing a 'pay bill' link without the user ever consciously 'using AI.'
Despite the hype, AI's impact on daily life remains minimal because most consumer apps haven't changed. The true societal shift will occur when new, AI-native applications are built from the ground up, much like the iPhone enabled a new class of apps, rather than just bolting AI features onto old frameworks.
Similar to how mobile gave rise to the App Store, AI platforms like OpenAI and Perplexity will create their own ecosystems for discovering and using services. The next wave of winning startups will be those built to distribute through these new agent-based channels, while incumbents may be slow to adapt.
The existential threat from large language models is greatest for apps that are essentially single-feature utilities (e.g., a keyword recommender). Complex SaaS products that solve a multifaceted "job to be done," like a CRM or error monitoring tool, are far less likely to be fully replaced.
