Computer use is one of the most interesting capabilities in AI right now, but I do not think its long-term importance is exactly what it appears to be. The obvious interpretation is that AI is learning how to use computers the way we do. Models can look at a screen, understand an interface, move a cursor, click buttons, fill out forms, and navigate software that was never designed for them. That is impressive, and it is already useful.
But I increasingly think computer use is best understood as a bridge between two eras of software rather than the final interface between AI and computers.
Today, computer use is especially valuable when an agent needs to navigate a messy or unfamiliar workflow that does not have clean machine-native rails. Imagine I need to generate an API key on a developer platform I have barely used. I know the outcome I want, but I may not know which menu contains the right setting, what sequence of pages I need to move through, or how the product has chosen to organize that workflow.
An agent with computer use can inspect the interface, reason about what it sees, and figure it out for me. A surprising amount of modern work is difficult not because the underlying task is complicated, but because every piece of software has its own structure that we have to learn.
There is also an important distinction between speed and autonomy. If I am already sitting at my computer and all I need to do is click a button, it may still be faster for me to do it myself than to delegate it to an agent. But that is different from asking whether I should have to perform the task at all. A thirty-second action that needs to happen every day can be far more valuable to automate than a complicated task I only perform once a year.
The value of computer use is not necessarily that an agent can move through an interface faster than I can. The value is that I can leave the loop entirely.
At the same time, there is something strange about the way computer use works. For decades, software has been designed around humans. We created buttons because humans can click them, menus because humans need to visually discover available actions, and dashboards because humans need information arranged spatially in order to understand it. Now we are teaching AI systems to look at those same interfaces and imitate us.
A model takes a screenshot, interprets what it sees, finds the visual element that corresponds to the action it wants, moves a virtual cursor, clicks, waits for the screen to change, and repeats the process. It works, but it is an incredibly indirect way for two computers to communicate.
If an agent wants to create a calendar event, it should not fundamentally need to find the right button, open a window, identify several fields, fill them out, and click save. The underlying software already knows how to create the event. What the agent really needs is direct access to that capability.
APIs, MCP servers, skills, and other machine-readable interfaces provide a much cleaner path because they allow agents to invoke actions directly rather than visually interpreting a representation of those actions that was designed for a human.
That is why I see computer use as a compatibility layer. It solves the problem of the enormous amount of software that exists today but was never built with agents in mind. Not every legacy application is going to expose a clean API. Not every internal enterprise tool will get an MCP server. Not every website will become agent-native overnight. Computer use gives an agent a universal fallback. If a structured tool exists, use it. If there is an API, call it.
If neither exists, look at the screen and figure it out.
In that sense, computer use does not really compete with APIs or agent-native interfaces. It fills the gaps between them. As more software becomes designed for agents, the visible importance of computer use may actually decline, but its usefulness will remain. There will always be software that has not been rebuilt for agents, obscure workflows without clean integrations, and situations where navigating the interface is simply the easiest available option.
Computer use allows agents to operate across all of them.
I also do not think this transition means graphical interfaces disappear. Humans still need visual software because not every decision is objective. There are plenty of situations where I do not just want something done. I want to inspect, compare, judge, or develop a preference. E-commerce is an obvious example. If I want to reorder the same toothpaste I have bought for years, an agent should probably just do it. I do not need to look at a product page.
But if I am buying a new couch, I absolutely want to see it. I want to compare materials, proportions, colors, and options I may not have known how to describe before I saw them.
That distinction applies far beyond shopping. Some tasks are fundamentally about execution, while others involve taste, trust, exploration, inspection, or subjective decision-making. Agents are exceptionally useful for the first category. Human interfaces remain extremely useful for the second. I do not think software becomes interface-less. Instead, I think software increasingly develops two interfaces at once: one optimized for humans and another optimized for agents.
The human layer will remain visual, explorable, and designed around perception and judgment. The agent layer will be structured, machine-readable, and optimized for execution. Sometimes I will use the human layer. Sometimes my agent will use the machine layer. Often, we will move between the two in the same workflow. I might visually compare several options, make a subjective choice, and then hand the objective execution to an agent.
This is where I think the web is ultimately heading. For most of its history, software has been built around a single type of user: a person operating a computer. Agents introduce a second type of user with completely different needs. A human may need a beautifully designed dashboard containing twenty metrics. An agent may simply need structured access to the underlying data. A human may need navigation. An agent needs discoverable capabilities. A human interface communicates visually what can be done.
An agent interface needs to communicate those capabilities programmatically.
Computer use matters because it allows those two worlds to coexist while the transition is happening. It gives AI access to software that was built for humans while the software industry gradually creates cleaner ways for machines to interact directly. Eventually, the most advanced agents may spend far less time clicking through interfaces than they do today. But they will still need the ability whenever no better path exists.
That is why I think computer use is so important. Not because clicking buttons is the future of AI, but because computer use is the bridge between the software we have today and the software we are building next.