In 1987, Apple released a four-minute vision of computing that was nearly 40 years ahead of its time.
The video, named Knowledge Navigator, showed a professor at his desk talking to a digital agent on a tablet-style computer. The agent surfaced new research, reminded him of an upcoming lecture he was scheduled to deliver, and dialed in a colleague to help with the material. It moved between modes without being asked. Voice when voice made sense. Screen when screen made sense.
Today, work still happens largely from app to app. You open a dashboard to check last quarter’s numbers or fire up a spreadsheet to project this month’s sales. Each is a destination you visit to get something done.
But thanks to agentic AI, work increasingly happens within the tool you’re already using. Ask a question, crunch the numbers, produce a chart, all without opening separate programs to do so.
If you’re working in, say, Slack, WhatsApp, or Telegram, the open-source agents OpenClaw and Hermes carry out their instructions there, where you already are. Claude Code goes further by generating the interface itself. That matters because a machine that builds interfaces on demand can tailor them to an individual, then discard them when the task is done: bigger letters for the visually impaired, an app in someone’s native language, a voice interface for someone whose hands are busy, a simpler view for new hires that fills in as they demonstrate fluency.
This shift changes the app from a stand-alone destination to a capability that can surface wherever and whenever it’s needed. The software still exists. But increasingly it reaches users through agents, conversations, and workflows rather than requiring them to seek it out.
Instead of navigating menus and dashboards, an agent talks straight to the data and the software that runs it.
What that looks like in practice is something every business leader needs to start thinking about now: how employees will talk to machines, where work will reach them, and what it will look like to work a job in the years ahead.
Demoting the interface
Sometimes the deepest value of software is the interface itself. More often, though, it’s the data underneath and the business logic that acts on that underlying information — the algorithms in a spreadsheet, say, that turn numbers into a forecast.
AI agents don’t need the same kind of doorway that humans do. Instead of navigating menus and dashboards, an agent talks straight to the data and the software that runs it. In that scenario, the app’s menus and dashboards slide into the background; the user’s interface is the agent itself, on whatever screen they happen to be looking at. What comes back to you is the completed task or a decision that still needs a human response, delivered through whatever channel you’re already using.
“The interface is melting,” product designer Andrew Sims wrote in a Substack post making the rounds among AI UX designers. Increasingly, the screen becomes a layer for oversight while AI handles execution. What takes its place as the user’s primary interface is the agent itself: knowing what to ask, what it can do, and what to trust it with.
A manager approves an expense report from inside a chat window without opening the expense app. An analyst pulls sales data into a presentation without logging into the dashboard that stores it. The underlying systems still matter. But they increasingly recede into the background while AI handles the navigation between them.
As AI takes over more execution, the interface becomes less the place where work happens and more the place where work is supervised, reviewed, and governed.
Talk as the new interface
Ubiquitous computing is a long-held dream. In the 1960s, a Star Trek officer needed only to speak and the ship’s computer answered. Sensors in Bill Gates’s home, completed in the late 90s, read a pin clipped to each person’s clothing and adjusted the lighting, music, and art accordingly. We have been imagining computers that fade into the background for almost as long as we have had computers.
The difference now is that the pieces are finally showing up in products people use every day, starting with our ability to talk to the machine. Boris Cherny, the creator of Claude Code, has talked about using the voice-to-text AI tool Wispr Flow to communicate with his computer. When he typed a prompt, he tidied his thoughts before hitting enter. When he spoke, however, he rambled, stammered, doubled back — yet the results improved. Freed from the instinct to clean things up, Cherny gave the machine more of his actual thinking, which gave the AI more to work with.
What Cherny noticed on his own is already working in the field. Water treatment inspectors at a Salesforce customer Workdry Group used to spend two to four hours after each plant visit writing up their compliance surveys. Now, while doing their rounds in a noisy plant and wearing safety gloves, they can simply speak what they are seeing, out of order, with pauses, and in industry shorthand. Salesforce’s Voice to Form routes each spoken detail into the proper field. The job can now be finished onsite in 20 minutes.
The next step is real-time conversations. The industry is building models that process speech in real time, the way a colleague in the room would. That’s in contrast to current chatbots, which are turn-based: You talk, the bot responds, you talk again. Real human conversation is messier: People talk over each other, trail off, double back, and throw in false starts and tangents. Continuous voice turns the machine from a tool you must invoke into something simply present, listening, and attending.
Always on, always near
Voice is one factor in the shift. Ambient presence is another. AI can quietly take in your calendar entries, messages, meetings, and the rest of the digital dust you generate in a day. And it can always be near, surfacing what matters on whatever surface you have at hand: a desk monitor, a phone, a smartwatch, eventually earbuds or glasses.
Salesforce’s chief scientist calls this “ambient intelligence”: software that watches the work continuously, understands the context, and “reaches you before you reach for it.”
In fact, most of the conversation so far about the UI of AI has centered on devices. Big shifts in computing have typically launched a new gadget, and plenty of companies are betting this one will, too. Smart glasses. Earbuds. Lapel pins. Pendants on a chain.
Maybe Star Trek called it decades ago: You speak to the air or tap a badge pinned to your chest. And yet, don’t bet against the device that arose out of the last great platform shift: the smartphone. The phone is not going anywhere soon. It’s too good and too entrenched, as the thing already in everyone’s pocket. The likelier future is all of the above, with the phone still at the center.
The interface reorganization runs deeper than gadgets, though. A new generation of operating systems for phones, laptops, and tablets is being built around AI agents rather than apps so that the home screen will be a conversation with an assistant rather than a grid of icons. Nvidia, for instance, unveiled the RTX Spark, a PC chip designed to run agents locally. The shift is happening not just at the UI level. The silicon and operating systems beneath are reorganizing around agents, too.
The bigger question is where the work shows up, whatever you’re carrying. You stop going to the app and instead the software comes to you.
Silvio Savarese, Salesforce’s chief scientist, calls this “ambient intelligence”: software that watches the work continuously, understands the context, and, as he stated it, “reaches you before you reach for it.” That could be the sales rep who gets the customer detail she needs mid-call or the operations manager who is nudged to focus on the one alert that matters pulled from a flood of noise. The app matters less when the work flows toward you instead of the other way around.
What will work in the near future actually look like for…
Sara, a Customer Success Specialist: Picture a desk three or four years from now. Sara is a customer-success specialist who formerly closed support tickets one at a time. Now she starts her morning perusing a board her agent built overnight, showing which clients are slipping toward churn, which are ready to expand, and which require a call before lunch. The agent surfaced the patterns. She decides which to act on.
Jaden, a Strategic Seller: Jaden asks his agent to game out a deal before every customer meeting. What happens if the customer balks at the price? What happens if the customer commits to the larger tier? What do the numbers look like if this or that feature is dropped? The seller walks into the meeting without having to do the hard work of mapping out every contingency. Simulation has become a first-class mode of work, not an optional exercise if someone finds the time.
Kiran, a Service Manager: Kiran oversees not a team of people but a fleet of agents. A command-center surface shows what the agents handled overnight, what they escalated, and what they flagged for human review. Kiran’s job is to spot what they missed and coach the ones that drifted off-policy.
The common thread: less doing, more directing. Less time inside the software, more time floating above it.
The interface comes to you
At Salesforce, we’ve implemented Headless 360, which lets an agent, with permission, reach into the platform and act on a customer’s full history without entering through one of our front doors. As company co-founder Parker Harris said when Headless was announced, “Why should you ever log into Salesforce again? Maybe you never will. Maybe you will go into Slack.”
The broader answer is that increasingly you won’t have to log into specialized apps where the work used to live. An agent surfaces what you need inside the collaboration layer your team already uses, like Slack, and handles the navigation between systems on your behalf. Multiply that across every tool a company runs and the workday starts to look different.
Four decades ago, Apple’s Knowledge Navigator got plenty wrong. It imagined a single assistant on a single device at a single desk, talking in turns. What is actually arriving looks more dispersed: multiple agents with dedicated specialties working on our behalf, orchestrated by a chief of staff that manages traffic and judges importance, on whatever surface is at hand, anticipating rather than answering.
Yet, is the general goal of software that comes to you rather than the other way around finally within reach? Or is this one more tomorrow that seems forever around the next corner? Nobody can say. The pieces are real and shipping, but not yet a whole. Forty years on, the dream is closer than it has ever been, yet still not here.
There is a trade-off in the transition. The old UI was something everyone could see. New users learned what was possible by exploring menus, buttons, and screens. The new UI is whatever an agent renders for whoever happens to be asking. Features that once sat in plain sight may now be hidden. The menu that taught new hires what the software could do. Those become harder to find. The shared screens that let a team align around the same information may become harder to find as well.
For executives, the questions are stacking up faster than the answers. What does an interface-less workplace mean for hardware procurement, when the gadget that actually does the work might be a phone, a watch, or eventually a pendant? What about the apps your company has already bought, the ones that may soon become plumbing nobody opens? And what about the connective tissue beneath all of it: the IoT sensors, the communication protocols, the security frameworks, the basic question of trust between an always-watching system and the people whose data feeds it?
And what about the work itself, when the human’s day shifts from getting things done to deciding what to do with the work their agents have already completed?
None of these has a settled answer yet. But what’s clear is the direction. The interface will become less a place you go and more something that meets you wherever you are.
