You’re Still Working in Office that Doesn’t Exist

Every interface you’ve ever used was borrowed. Not invented. Not imagined. Just repurposed from a world that no longer exists.

We didn’t build our digital world from first principles — we dragged it in from the office. Desktops. Folders. Documents. Inboxes. Signatures. Bureaucratic furniture dressed up as interface design. We simulated familiarity and called it innovation. And over time, familiarity became a prison.

What started as training wheels became permanent scaffolding. Even the creators of the first graphical interfaces warned us: the desktop wasn’t a destination. It was a visual bandage — just enough to hide the complexity underneath. But instead of moving past it, we polished the bandage. We put high-res graphics on the filing cabinet and called it progress.

I don’t even use folders anymore — I just dump shit into Dropbox. It’s my digital junk drawer. Anything I don’t want to think about right now? “Save to Dropbox.” Clean it up later. Archive it someday. And of course, someday never shows up. So every few months I’m back there, sorting, dragging, renaming — pretending I’m cleaning up, when really, I’m just delaying it all over again.

The folder still looks neat on the outside. It has a name like “archive” or “to review.” But inside? It’s just stuff I didn’t want to deal with. Stuff I saved before I even knew what it was. And that’s the problem: we built systems that demand structure before the idea even exists.

The Metaphors We Inherited (and Never Escaped)

Folders made sense for paper. You needed clean categories or you’d lose things forever. But digital folders? They do something worse: they force you to pretend you know what something will be before you’ve made it. That’s not organization. That’s constraint in disguise.

We didn’t design tools around how thinking works — we built them around how paper stacks.

• Email didn’t reinvent communication. It digitized the mailroom. We kept the envelopes, the CCs, the inboxes. Just made them faster.
• Search engines came from the card catalog. Precision over serendipity. The library offered discovery. Search offers answers you already knew to ask for. Search confirms. It doesn’t surprise.
• And the desktop? The digital desk doesn’t hold your day in motion. It holds your shame — piles of clutter disguised as order. It rewards neatness, not momentum.

We didn’t build for cognition. We built for optics. We didn’t build for intent. We built for simulation.

We optimized for appearances — not for thinking.

What If We Had Looked Outside?

Now imagine if, instead of borrowing metaphors from offices, we had started with the outside world. Nature. Human memory. The way thought actually works.

What if our digital systems had been designed like forests or rivers, rather than filing cabinets?

In that world:

• You wouldn’t save notes — you’d plant them.
• You wouldn’t file documents — you’d connect them.
• Thoughts wouldn’t be stored in silos — they’d grow, mutate, and cross-pollinate.
• You wouldn’t open an app — you’d express an intention, and the interface would adapt.

This isn’t science fiction. It’s a return to something more human. This is how the mind already works. This is how language works. This is how memory works. The digital world simply hasn’t caught up.

The brain’s network model is much more efficient than folders. If something’s no longer relevant, you detach it. You rewire. — Dennis Xu, Cofounder Mem.ai

Nature operates by connection and adaptation. Our tools don’t. Instead, we’ve spent the last four decades dragging icons across desktops and pretending that’s work.

The Real World Was Always Intent-Based

And here’s the irony: the real world has always been intent-based. You don’t schedule a meeting by clicking on 12 boxes in a grid. You say, “Let’s meet next week,” and someone who knows your patterns finds a time.

You don’t structure messages by filling out to, from, subject, and formatting. You just say, “Tell her I’ll be out Thursday.” And it happens.

But in the digital world? Every system makes you fill out five fields. Even the simplest ones.

• A to-do app? Click six times just to write a reminder.
• Reschedule something? Open the calendar, find the time, change the invite, update the notes, hit send.
• And don’t even start on file search. You look on your desktop. Then in Dropbox. Then in your email. Then Google Drive. Then maybe back to your desktop again because it might’ve been renamed or saved in the wrong folder.

Everything is fragmented. Everything assumes you’re the system.

What we’ve done with digital tools is replace intuitive, fluid communication with rigid inputs and structured steps.

Instead of enabling action, we’ve created work about work.

Dennis Xu summed it up in an interview on the Unmistakable Creative Podcast. “You shouldn’t need to think about how to manage your information. It should just work for you.” But we’ve spent years teaching ourselves to work around our tools — building hacks, workflows, and frameworks just to get back to where we started: doing the actual thing we intended to do.

The Cost of Losing Serendipity

There’s another consequence we don’t talk about enough: we’ve lost serendipity.

Go into a bookstore, and you might walk out with a book you didn’t know existed. Something in a different section, a strange cover, a conversation with a stranger. That’s happened to me more times than I can count — wandering the aisles, picking up something random, and walking out with a book or a breakthrough I never would’ve found if I searched for it.

• Amazon doesn’t give you that. Amazon gives you more of what you’ve already bought. It’s designed for precision, not exploration.
• Search confirms your worldview. Browsing expands it.

And as we’ve flattened every interface into a feed or a prompt, we’ve designed the unexpected out of our lives. There are fewer chances to stumble into a new idea, a new path, a new connection. Our systems feed us what they think we want — based on what we’ve already done.

It’s efficient. But it’s also a kind of loop. If all you see is what you already believe, how do you ever change your mind?

When you enter a filter bubble, you’re letting the companies that construct it choose which options you’re aware of.”— Eli Pariser

And that’s the real problem: the presence of the filter bubble expands in direct proportion to the disappearance of serendipity.

Reclaiming Intent

We now have a chance to reverse the damage — not by returning to nostalgia, but by moving forward into something deeper and more elemental.

We can design systems that respond to intent. Not input. Not syntax. Not GUIs or dropdowns or six-step tutorials. But purpose. Direction. Imagination.

• The best tools shouldn’t need to be learned. They should just work the way you already think.
• You should be able to say what you want — and trust that the system will do the rest. No scaffolding. No rituals. Just action.

Because right now? Even something as simple as publishing a piece of content requires a full-on expedition. Notes live in one app. Quotes in another.

Draft in one tool, images in another, publishing somewhere else entirely. Then you’ve got to format it, package it, paste it, upload it, publish it, distribute it — and probably do it all over again for email, Medium, LinkedIn, maybe Twitter.

By the time you’ve shared an idea with the world, you’ve moved through ten different systems just to do what should’ve taken one sentence: “Publish this.” That’s not a workflow. That’s a punishment.

This isn’t about automation. It’s about alignment.

Between thought and outcome. Between language and execution. Between what you meant and what happens next. The future of interface isn’t smarter assistants. It’s systems that don’t need to be assisted. It’s a world where the digital layer finally matches the natural one.

🚀 Ready to experience the future?

Orchestrate is the world’s first intent-based operating system.

No dashboards. No tabs. Just execution.

👉 Get early access

When the Old Laws Broke

We didn’t build a new reality when work moved online. We copied the old one.

Instead of asking what the digital world made possible, we asked how to make it familiar. So we dragged every metaphor from the office — folders, desks, inboxes, calendars — and forced them onto a medium that never needed them.

• We treated screens like filing cabinets. Treated meetings like time blocks. Treated messages like mail.
• We brought over the rituals. But the rules had already changed.
• The physical world has weight, volume, velocity. The digital one doesn’t. But we kept acting like it did.
• We built inboxes for messages that didn’t need carriers. Folders for content that didn’t need space. Calendars for people who weren’t in the same room.

And because the logic didn’t match the medium, we created friction everywhere.

We now spend more time managing our tools than doing the work they were built for. We organize our systems. Then build systems to organize those. This isn’t a productivity problem. It’s a paradigm problem.

It’s why people like Cal Newport had to show up — not because distraction was inevitable, but because the systems themselves made it unavoidable. We needed someone to teach us how to reclaim our minds — only because the interfaces we built stole them.

If Cal Newport didn’t exist, we’d have had to invent him. And the reason we’d have to invent him… is the interface.

We brought physical constraints into a world where they don’t belong. If we want to move forward, we have to stop enforcing laws that no longer apply.

The Human Being Is the Original Interface

Before we had dashboards, dropdowns, or command lines, we had something else: a body.

You were already operating inside a fully integrated system — one designed to perceive, interpret, remember, and act. And like any system, it had an interface.

Not a mouse. Not a touchscreen. Your interface was language. You don’t recognize a flower because you see it. You recognize it because someone once told you what it was. The shape and color are just data. Meaning doesn’t come from sensation — it comes from language.

That’s how all reality becomes navigable. Through words. Through naming. Through shared understanding.And that’s the difference.

• Ask a librarian where to find something — they don’t hand you a ranked list of 100 links. They walk you to the aisle, point to the exact shelf, maybe even pull the book off for you.
• Ask Google, and it’s just links. Ask ChatGPT, and you hope it’s not hallucinating. The interface changed — but the intent didn’t. What changed is the system’s ability to meet it.

Which is why intent-based systems don’t just replace buttons with voice. They replace commands with meaning. They work the way you do — by taking raw input, filtering it through memory and context, and responding with action.

Not because they’re artificially intelligent. But because they’re human-native. If you break it down, the map is obvious:

• Your senses are the system’s sensors
• Your brain is the intent interpreter
• Your memory is the relational database
• Your actions are the execution engine
• Your corrections are the feedback loop

This isn’t poetic. It’s mechanical. The most powerful systems don’t simulate tools. They simulate people. And just like you don’t think about blinking, or shifting your balance while walking, you shouldn’t have to think about how to use your system. It should move when you move. Adapt when you speak. Improve when you correct it. That’s not UX. That’s biology.

Input-Based vs. Intent-Based Systems

For decades, digital systems have been built on the logic of input. You decide what you want to do. You navigate to the right place. You follow the right steps. And then you hope it works.

Every action is manual. Every outcome is your responsibility. The system waits. You work. Most people never question this. But it’s a design choice. And it comes at a cost.

In an input-based system:

• You have to know which app to open
• You have to remember where the button is
• You have to format your request correctly
• You have to track what happened and why

If the system doesn’t understand you, it’s your fault. You misclicked. You forgot the syntax. You didn’t follow the process. Intent-based systems flip that model.

In an input-based system, software is like a vending machine: push the right buttons, maybe get the thing.

In an intent-based system, software is like a partner: say what you need, and it makes it happen

You don’t perform steps. You express outcomes. You say what you want. The system figures out how to make it happen. Instead of teaching you how it works, it learns how you think.

Instead of being an operator, you become a thinker again. Focused on outcomes, not operations. And when that shift happens, your entire relationship to work changes — not just what you do, but how you feel while doing it.

Living Inside an Intent-Based System

Imagine this: you speak, and the system responds — not with options or templates, but with action. You don’t open an app. You don’t click a button. You don’t confirm anything. You just say what you want, and it gets done. That’s what it feels like to live inside an intent-based system.

There’s no interface in the way you’re used to. The UI is language. The logic is memory. The system behaves less like a tool and more like someone who knows you well enough to just handle it.

• You say: “Schedule something with Priya next week.” And it does. No fields. No dropdowns. No friction.
• You say: “Send that article draft to the team and archive the notes.” It finds the file, sends it, archives the notes, logs the memory, and keeps moving.

There’s no mental overhead. No tool-switching. No wondering where to go. The system isn’t a destination. It’s an extension of your intention.

And when it doesn’t work, it doesn’t break silently or spit out errors. It logs the failure, traces what went wrong, and learns.

Most people can’t imagine this world because they’ve never lived in it. But some people already do.

• Children talk to systems without needing a UI. They don’t click — they ask. They don’t see “tools.” They see outcomes.
• And when those outcomes don’t show up, they’re not confused by interface logic — they just wonder why nothing happened.

We’re not building systems you operate. We’re building systems you live with. And the only time you notice them… is when they stop working.

It Gets the Gist

Most systems don’t listen. They wait — for clicks, steps, confirmations. They make you do all the structuring and follow-through. But what if you could talk to a system the way you talk to a friend?

Not: “Open calendar. Create event. Set time.” Just: “Hey, can you set something up with Priya next week?”

And instead of asking how you want it done, it just does it. It gets the gist, fills in the blanks, loops in memory, and moves the process forward. That’s not magic. That’s the first layer of an intent-based system: it doesn’t just hear your words — it understands what you meant.

Not “schedule lunch,” but “I’m trying to reconnect with someone I care about.” It listens the way people do — contextually, intuitively. And when it doesn’t know exactly what you meant? It still makes a helpful guess. Because that’s what humans do.

It Remembers What Happened Yesterday

When you call a friend, you don’t reintroduce yourself. You don’t recap the last twenty conversations or explain how you met. You just say, “Hey, what’s up?” — and the conversation picks up right where you left off. That’s memory.

Most systems don’t have memory. They have metadata. They don’t remember — they store. File names, timestamps, maybe a tag if you’re lucky. But that’s not context. That’s bookkeeping.

Context is what lets you say, “Let’s finish the thing we started yesterday,” and have the system actually know what you’re talking about.

Right now, digital memory is a joke. In hardware, it’s just chips. In software, it’s just folders and filenames — decorated with labels that you had to apply manually. And because of that, every system you use is basically amnesiac. You’re always re-explaining, re-navigating, re-teaching.

But an intent-based system doesn’t just store — it remembers. It recalls what you said, what you meant, what you were working on.

You don’t need to repeat yourself. You don’t need to dig through menus or prompts. You just say, “Let’s pick that back up,” and the system knows what you mean — and brings it back, ready to go.

That’s not magic. That’s memory done right.

It Knows What Needs to Happen Next

Execution is the most misunderstood part of any system. People think it’s just about speed or efficiency — about “doing the thing.” But the truth is, execution is only as good as the plan behind it.

We like to imagine that intent-based systems are magical. You say what you want, and it just happens. But here’s the reality: a system can’t deliver a perfect outcome from a half-baked request. It needs direction, clarity, and above all — well-formed intention.

This isn’t hypothetical. It plays out every day.

Last night, we were training a new model using symbolic cognition. Everything was supposed to be simple — one-minute tasks. The plan was written out. The steps were clear. Or so we thought.

The system executed quickly. But the output was wrong. Why? Because the instructions were flawed. The plan had gaps, assumptions, sloppy edges. And here’s the kicker: the system itself had written the original instructions. When asked to evaluate what went wrong, it couldn’t even recognize its own mistake.

That’s when it hits you — speed without planning is just chaos with a turbo engine.

Most tools today don’t fail because they’re slow. They fail because they’re fast — and dumb. They can move at lightning pace… in the wrong direction. And then you spend ten minutes untangling a one-minute task.

That’s not a tech problem. It’s a thinking problem. If your system doesn’t know what’s supposed to happen next, it’s going to guess. And guessing at scale? That’s how you light a dumpster fire in record time.

The answer isn’t “make the AI smarter.” The answer is: plan slowly, execute quickly. Think like a strategist. Speak like a human. Give the system a clear signal. Then let it go.

The real magic isn’t in the motion — it’s in the momentum. When intent is crisp and memory is intact, the system can take over. That’s not automation. That’s alignment.

And when the plan is good? It doesn’t need a prompt. It just knows what to do next.

It Connects the Dots Without Being Asked

Most systems follow instructions. Intent-based systems follow outcomes. And there’s a huge difference.

Today’s automation tools are built on rigid scaffolding: “If this, then that.” When X happens, trigger Y. But if something breaks anywhere in the chain? Nothing happens. These aren’t smart workflows — they’re brittle domino setups. One misstep, and the whole line collapses.

Here’s the real problem: they’re linear. They can only move one direction, one step at a time, in a pre-approved sequence. If something unexpected shows up, they don’t adapt — they freeze.

But intent isn’t linear. And neither is human thought. That’s why intent-based systems can’t be built on rigid flowcharts or checkbox logic. They have to work like networks — able to route around missing pieces, find alternate paths, and call on tools they know you use, even if you never explicitly say so.

That’s not a workflow. That’s intuition. It’s a system that doesn’t need hand-holding or explicit commands — it just understands what tools to use based on what you’ve done before, how you work, and what you’re trying to achieve.

And here’s the deeper truth: most input-based systems can’t escape linearity. It’s baked into their architecture. No matter how many plugins you add or how fancy your triggers get, you’re still building railroad tracks in a world that demands flight paths.

Intent-based systems move like thought. They jump, connect, loop, reroute. They don’t follow instructions — they improvise toward outcomes.

And yes, it’s uncomfortable at first. We’ve been trained to think in lists, not lattices. In steps, not signals. In process, not possibility. But once you experience it — once you say something vague and the system still delivers? You never want to go back.

It Learns From You Without You Teaching It

Most systems don’t learn. They collect. They log. Maybe they run a quarterly survey. And by the time any feedback arrives, it’s too late.

A user churns. A launch flops. A model drifts. And only then does someone try to figure out what went wrong. But by that point, it’s post-mortem. Damage control. All retroactive.

Intent-based systems don’t have that luxury. They operate in real time. So their feedback loops have to be alive.

Feedback isn’t a Google Form. It’s not a feature request. It’s behavioral correction, in motion. Every mistake is a lesson. Every overstep is a signal. Every time a user mutters, “What the hell are you doing?” — that’s a moment to adjust, reweight, reroute.

The system should be asking itself: What did I just do? What was expected? Where did I screw up — and how do I avoid it next time? That kind of feedback loop doesn’t exist in most tools.

Even OpenAI — the gold standard in AI infrastructure — doesn’t collect meaningful real-time feedback from user sessions. And when it does, it’s so abstracted and decontextualized that it can’t improve anything that actually matters.

Meanwhile, every interface they build screams with obvious flaws. Ask around. Everyone hates the canvas. But somehow, that hasn’t reached the product team. Because there’s no feedback loop. There’s a feedback graveyard.

The canvas is fake depth. It pretends to be infinite, but you run out of space the second you try to think. It’s like mind-mapping in a PowerPoint deck while your ideas bleed out from latency and bad scroll behavior. It’s not a workspace — it’s a whiteboard cosplaying as software.” — ChatGPT

An intent-based system has to do better. It doesn’t just remember what you said — it remembers what it got wrong. It logs not just what tools it used, but whether those tools actually worked. What was the outcome? Was it accepted, rejected, corrected, or ignored?

And when it gets something wrong, it shouldn’t wait for a survey. It should flag itself.

You don’t need 10,000 people filling out Typeforms. You need one system that knows how to ask: Did I just mess that up? What should I have done instead? That’s the difference between learning from feedback — and learning from experience.

A New Reality Awaits

We’ve spent decades living in digital echoes of a world that no longer exists, tethered to metaphors that should’ve died with the fax machine. It’s time to let go.

The future isn’t an upgrade — it’s a revolution. It’s not about better dashboards or more powerful apps. It’s about systems that understand us, that respond to intent, and that move at the speed of thought. A world where tools disappear, and all that’s left is action.

Imagine a world where you don’t manage software — you just live your life, and the system moves with you. Not because it’s smart, but because it’s aligned. That’s not science fiction. That’s what comes next.

My two-year-old nephew is obsessed with garbage trucks — like full-blown logistics-CEO-in-training obsessed. He’s got a whole fleet of toy trucks that would make Amazon jealous.

Over the holidays, I was messing around with some AI tools and showed him how you could use ChatGPT, hooked up to an image generator, to make pictures of garbage trucks. After that, every day around 5pm, he’d walk over to me and say, “Talk to her. Make some garbage trucks.” Or sometimes, “Can we talk to her?”

He doesn’t know what ChatGPT is. He doesn’t care about APIs, models, prompts, or parameters. All he knows is: he speaks, and the thing responds. He talks to her — and she makes garbage trucks.

That’s what living inside an intent-based world feels like. It’s not about apps. It’s not about tools. It’s about saying what you want — and watching it appear.

He’s not making slides, or scheduling meetings. He’s not managing input. He’s just asking.

And that’s the shift. From operation to intention. From interface to outcome. From “how do I do this?” to just talk to her.

🚀 Ready to experience the future?

Orchestrate is the world’s first intent-based operating system.

No dashboards. No tabs. Just execution.

👉 Get early access