The term “App-Killing AI” sounds like something out of a techno-thriller, but it actually describes a massive shift in how we interact with technology. We are moving away from an era of “there’s an app for that” and toward one where “the AI just does that.”
This transition marks the end of the fragmented app economy and the beginning of the agentic workflow era.
1. The Death of the Interface
For the last 15 years, our digital lives have been dictated by icons on a grid. To book a flight, you open a travel app. To order food, you open a delivery app. To check your budget, you open a banking app. Each of these requires you to learn a specific user interface (UI), navigate menus, and manually move data between them.
AI kills apps by making the UI invisible.
When you can tell a Large Language Model (LLM), “Book me a flight to Tokyo for under $800 and find a hotel near a subway station,” the AI interacts with the APIs (Application Programming Interfaces) behind the scenes. You no longer need to see the airline’s app or the hotel’s website. The app becomes a “dumb pipe” for data, while the AI becomes the primary interface.
2. Large Action Models (LAMs) and Agents
The “killer” aspect of AI comes from the evolution of LLMs into Large Action Models (LAMs). While an LLM can tell you how to bake a cake, a LAM can actually order the ingredients from a grocery store.
How it works:
Decomposition: The AI breaks a complex request into smaller tasks.
Tool Use: The AI identifies which “apps” or services are needed to fulfill those tasks.
Execution: The AI performs the clicks, types the text, and processes the payment.
In this scenario, the app is no longer a destination for the user; it’s just a tool for the AI. If the AI can bypass the app’s frontend entirely, the “app” as we know it effectively dies.
3. The Economic Threat to the App Store
The “App-Killing” trend poses a systemic threat to the business models of tech giants like Apple and Google.
Discovery is dead: If users stop browsing the App Store because their AI assistant handles everything, developers lose their primary way of finding new customers.
Ad Revenue: Apps like Instagram or Yelp rely on users scrolling through their interface to show ads. If an AI scrapes the data and presents it to you in a clean text summary, those ad impressions disappear.
SaaS Consolidation: Many “single-feature” apps (like PDF editors, basic note-takers, or simple photo filters) have already been rendered obsolete. Why pay for a specialized PDF-to-Word converter when ChatGPT or Claude can do it for free in the chat window?
4. Hardware and the “Post-App” Devices
We are seeing the first attempts at hardware specifically designed to kill the app-centric smartphone model.
Rabbit R1: Designed around a “Large Action Model” to perform tasks across various services without opening apps.
Humane AI Pin: A screenless wearable that relies entirely on voice and laser projection, bypassing the grid-of-icons entirely.
OpenAI/Apple Integration: With the integration of Apple Intelligence, Siri is evolving from a voice-activated timer into an agent that can look at your screen, understand context, and take actions across apps.
While the first generation of these devices has been rocky, the intent is clear: The phone should be a personal assistant, not a tray of icons.
5. The Survival of the Fittest (Apps)
Not every app will die. To survive the “AI Apocalypse,” apps are being forced to pivot in two directions:
The “Data Moat” Strategy
Apps that own unique, proprietary data that AI can’t easily scrape will survive. For example, Uber survives because it owns the physical network of drivers. AI can book the ride, but it still needs Uber’s infrastructure to move the car.
The “Extension” Strategy
Instead of fighting the AI, developers are turning their apps into AI Plugins. They are making their services easily “readable” for AI agents, ensuring that when a user asks their AI to “find a plumber,” that app’s database is the one the AI chooses to use.
6. The Risks: Privacy and Monopolies
If AI “kills” apps, it creates a massive centralization of power. Currently, your data is spread across 50 different apps. In an AI-first world, a single entity (like OpenAI, Google, or Apple) might see everything you do.
Security: If you give an AI agent the power to “kill” apps by acting on your behalf, you are giving it your credit card info, your home address, and your passwords.
Bias: If an AI “kills” the travel app and chooses your flights for you, how do you know it isn’t prioritizing the airline that paid the AI company the biggest commission?
7. The Future: A Conversational OS
The ultimate conclusion of “App-Killing AI” is the Conversational Operating System. We are moving toward a world where the OS isn’t a layer of software that runs apps; it is an intelligent layer that understands your intent.
Imagine an OS where:
There are no downloads.
There are no updates.
There are no logins for individual services.
You simply speak or type, and the world’s digital infrastructure responds.
Conclusion
“App-Killing AI” isn’t about the literal deletion of software; it’s about the demotion of the app. Apps are being moved from the “front of house,” where they interact with humans, to the “back of house,” where they serve as specialized workers for a central AI manager.
The era of human-to-app interaction is ending. The era of human-to-AI-to-service is beginning.
The character in the uploaded image should replicate the exact motions, expressions, and steps shown in the reference video.