The see-and-point principle states that users interact with the computer by pointing at the objects they can see on the screen. It's as if we have thrown away a million years of evolution, lost our facility with expressive language, and been reduced to pointing at objects in the immediate environment. Mouse buttons and modifier keys give us a vocabulary equivalent to a few different grunts. We have lost all the power of language, and can no longer talk about objects that are not immediately visible (all files more than one week old), objects that don't exist yet (future messages from my boss), or unknown objects (any guides to restaurants in Boston).

The critical research question is, "How can we capture many of the advantages of natural language input without having to solve the "AI-Complete" problem of natural language understanding?" Command-line interfaces have some of the advantages of language, such as the large number of commands always available to the user and the rich syntactic structures that can be used to form complex commands. But command-line interfaces have two major problems. First, although the user can type anything, the computer can understand only a limited number of commands and there is no easy way for the user to discover which commands will be understood. Second, the command-line interface is very rigid and cannot tolerate synonyms, misspellings, or imperfect grammar. We believe that both these deficiencies can be dealt with through a process of negotiation.

The basic principles of the Anti-Mac interface are: The central role of language A richer internal representation of objects A more expressive interface Expert users Shared control

If the user is required to be in control of all the details of an action, then the user needs detailed feedback. But if a sequence of activities can be delegated to an agent or encapsulated in a script, then there is no longer a need for detailed and continuous feedback. The user doesn't have to be bothered unless the system encounters a problem that it cannot handle.

The problem with WYSIWYG is that it is usually equivalent to WYSIATI (What You See Is All There Is). A document has a rich semantic structure that is often poorly captured by its appearance on a screen or printed page. For example, a word may be printed in italic font for emphasis, as part of a book title, or as part of a quotation, but the specific meaning is lost if it is represented only by the fact that the characters are italicized. A WYSIWYG document shows only the final printed representation; it does not capture the user's intentions.

The Anti-Mac principles outlined here are optimized for the category of users and data that we believe will be dominant in the future: people with extensive computer experience who want to manipulate huge numbers of complex information objects while being connected to a network shared by immense numbers of other users and computers. These new user interface principles also reinforce each other, just as the Mac principles did. The richer internal representation of objects naturally leads to a more expressive external representation and to increased possibilities for using language to refer to objects in sophisticated ways. Expert users will be more capable of expressing themselves to the computer using a language-based interface and will feel more comfortable with shared control of the interface because they will be capable of understanding what is happening, and the expressive interface will lead to better explanations.

WYSIWYG assumes there is only one useful representation of the information: that of the final printed report. Although we are not arguing against a print preview function, even when the goal is to produce a printed document, it may be useful to have a different representation when preparing the document. For example, we may want to see formatting symbols or margin outlines, or it may be useful to see index terms assembled in the margin while we are composing.

The One Hypertext done right, I think, is a proto-Metaverse. If we build a Web that feels like a place designed for life, the services and sites on the Web can stretch into the horizons of this hypertext Metaverse. We could meet people on the Web, find entertainment, connect with partners, and build a living online. But aren’t we already building pieces of this Metaverse today? To propel this trend into the Metaverse of 90’s science fiction, I think we need someone thinking more intentionally about building a Web experience from the perspective of an architect, rather than a user interface designer. The Web is increasingly a home more than it is a tool, and our design needs should change to reflect it. I think this work of building a Metaverse requires something different from the iterative engineering the Web industry has engaged in for the last decade. We need more first-principles design, more imagination in what kinds of places the hypertext Metaverse could contain in the future, the way an architect might dream of their next stadium or skyscraper.

I think we’ve barely begun to tap the potential of designing the Web as as built environment and a work of architecture around our digital living spaces. When we design the One Hypertext for people, not just for information, the Web becomes something more than a resource. It becomes the Metaverse.

Today, we find a different set of metaphors for the Web. We don’t go on the Internet as much, or log in and log out anymore. Instead, we’re online or offline, connected or disconnected. “Online” is a state of being, not a place to be. (When was the last time you closed your web browser?) We spend most of our time on the Web not browsing or exploring, but subjecting ourselves to the flow of information that the Internet now levies at our attention.

the Web has lost a sense of place that it used to have. Today’s Web is a condition of being – being online, being connected, being subject to the flow of the feeds. A sense of place is what allows humans to gather and meet and have conversations, and with fewer places on the Web feeling like real spaces we can enjoy, I think we find our conversations pushed out into the few places that retain that metaphor of place.

Twitter’s main user interface, the algorithmic timeline, is bad for using Twitter as a learning tool. It feels like sticking a straw into a firehouse and hoping you’ll suck out enough interesting insights to be worth the effort.

For me, Twitter serves two purposes. First, it’s a learning tool. There are lots of smart folks talking to each other and sharing what they’re thinking about on Twitter from software to economics to writing, and I can find on Twitter opinions or perspectives I can’t find on blogs or books. Second, it’s a place for me to share whatever I’m working on on my blog or on my side projects with my audience. Lucerne is designed around these two primary workflows: learning and sharing.

With Lucerne, I can search for interesting conversations happening on Twitter by experimenting with these filters. When any filter seems particular useful, I can save it to check again later, by adding it to the left sidebar with a name. As I use the app, I end up curating an ever-changing personalized collection of these channels in my sidebar that provide multiple different views onto the firehose of Twitter.

The biggest change I’ve noticed from using the client is that it turns Twitter from a consumption experience into an exploratory experience.

Lucerne isn’t meant to be a Twitter replacement. Twitter’s web app is still great for writing and following threads, for example, and I don’t want to have to re-create something that’s already fine for my use. But for my two main workflows of learning and tracking my progress on Twitter, Lucerne works better for me.

What if curating things for your audience was radically easier? A company like Pocket or Instapaper, who already have a substantial user base clipping and collecting reading material they like, may be in a good place to launch an experiment in this space. But those most avid readers and curators may also already have started newsletters, and may not want something lower maintenance. Another minimal viable product may be a kind of a filter for Twitter that aggregates just the links and good reads that people you follow have shared. People are already curating and sharing – a good first step may be to simply slide into where people are already curating, and make the processes of curation and discover easier and higher-reach.

If we were to build a medium for better thinking on top of the web browser, it’s reckless to expect the average user to manually connect, organize, and annotate the information they come across. Just as the early World Wide Web started out manually-curated and eventually became curated by algorithms and communities, I think we’ll see a shift in how individual personal landscapes of information are curated, from manual organization to mostly machine-driven organization. Humans will leave connections and highlights as a trail of their thinking, rather than as their primary way of exploring their knowledge and memory.

However, to build an enabling medium that’s more than a single-purpose tool, it isn’t simply enough to look at existing workflows and build tools around them. To design a good creative medium, we can’t solve for a particular use case. The best mediums are instead collections of generic, multi-purpose components that mesh together well to let the user construct their own solutions.

The current state web browsers is particularly damning from this perspective. Web browsers have access to such a treasure trove of valuable, often well-structured information about what we learn and how we think, what interests we have, and who we talk to. Rather than trying to take that information and let us build workflows out of them, browsers remain a strictly utilitarian tool – a rectangular window into documents and apps that play dumb, ignorant of the valuable information that transits through them every day.

The vision of the web browser that excites me the most is one where the browser is a medium for creativity, learning, and thinking deeply that spans personal and public spheres of knowledge. This browser will be fast and private, of course, but more than that, this browser will let me explore the Web from the comfort of my own garden of information. It’ll break the barriers between different apps that silo our information to help us search and remember across all of them. It’ll use a deeper machine understanding of language and images to summarize articles, highlight important ideas, and remind me what I should remember. It’ll let me do it all together with other people in a way that feels like real presence, rather than just avatars on screen.

Most existing tools and browsers treat web pages and pieces of notes like complete black boxes of information. These tools know how to scan for keywords, and they have access to the metadata we use to tag our information like hashtags and timestamps, but unlike a human, most current tools don’t try to peer into the contents of our notes or reading materials and operate with an understanding of our information. With ratcheting progress in machine understanding of language, I think we have good high-quality building blocks to start building thinking mediums and information systems that operate with some understanding of our ideas themselves, rather than simply “this is some text”.

So, what are the building blocks of a powerful thinking medium that can actually help us think, more than just recall? For a tool that has such broad access to information like a web browser, I think a critical piece of the puzzle is better machine understanding of language.

If we want to organize information that flows through our lives, we simply can’t restrict our design space to be a single product or app. No matter how great a note-taking app is, my emails are going to live outside of it. No matter how seamless the experience in my contacts app, my text conversations are going to live outside of it. We should acknowledge this fundamental limitation of the “note-taking app” approach to building tools for thought, and shift our focus away from building such siloed apps to designing something that lives on top of these smaller alcoves of personal knowledge to help us organize it regardless of its provenance. If we want to build a software system that can organize information across apps, what better place to start than the one piece of software that has access to it all, where most of us live and work nearly all the time? I think the browser is a rich place to build experiments in this space, and my personal experience building Monocle and Revery support this idea so far.

In the browser of the future, the boundary between my personal information and the wider Web’s information landscape will blur, and a smarter, more literate browser will help me navigate both worlds with a deeper understanding of what I’m thinking about and what I want to discover. It’ll remind me of relevant bookmarks when I’m taking lecture notes; it’ll summarize and pick out interesting details from long news articles for me; it’ll let me search across the Web and my personal data to remember more and learn faster.

Despite the renewed focus I see in the community of people and companies trying to build better tools for thought, I think much of our work is still confined to tool-making. That is, most of our efforts are about creating more automatic, more efficient ways to do what we already know how to do – spaced repetition, Zettelkasten, journaling, and so on. We are busy making more effective command-line apps for thought, rather than dreaming up graphical interfaces.

Designing a medium for thought requires that we discover what these primitive components of a thinking medium should be. Should there be some sense of geometry and space? How important should text be, against drawings and images? How should people collaborate and share their thoughts? I propose that the solution to these questions are not an opinionated tool with a “Share” button and a rigid way to use an image in a project, but something with a collection of capabilities that happen to include inserting and positioning text and images, sharing and collaborating on those objects on the page, and connecting ideas.

Participation inequality plagues the internet. Only 1% of people on any given platform create new content. 99% only consume.Many think that's just what happens when human communities scale. But maybe it's just what happens in an internet built for advertising. Consider that:All of the internet's interfaces—social feeds, search bars, news sites—are optimized for consumption.Interfaces for creating new content, particularly knowledge, are antiquated. Word-processors look like they did forty years ago, disconnected from the internet and any content you might write about. Which means: writing requires hours of searching and sorting. Knowledge creation is painful for the people best at it, and inaccessible to most others. What would it take to make writing accessible? Maybe: a totally new kind of interface. Ideally: a word-processor that pulls in the information you need as you type. And what would that take?Unprecedented NLP to make connections as you type,A word-processor redesigned around links, andA highly technical team focused on a non-technical market.If achieved, it would:save writers hours,make knowledge production accessible to anyone who knows how to type, andlay the groundwork for a mainstream knowledge economy.

So we’re starting out with a tool focused on those two core jobs we have: capturing ideas in the moment, and making sense of them as you grow your web of ideas.

But both of these issues are trivially solved if we simply begin with today's lightly hyperlinked documents, and let the reader's computer generate links on-demand. When I'm reading something and don't understand a particular word or want to know more about a quote, when I select it, my computer should search across everything I've read and some small high-quality subset of the Web to bring me 5-10 links about what I've highlighted that are the most relevant to what I'm reading now. Boom. Everything is a hyperlink.

One interesting observation about these markets is that the upper-limit for value creation of individual ventures here, one creator, one community, etc, is smaller than startups. There are only a handful of trillion-dollar communities in the history of humanity, and no trillion-dollar influencers or entertainers. Scale will come more from breadth, not just making one good bet, as is the case in startups.

The next Y Combinator will identify an industry where most people are under-valuing a certain class of talent in an industry poised to grow rapidly, gather a community to commoditize tribal knowledge, and over time scale it into a self-sustaining flywheel that helps them grow their gravitational field. As for which industry, my guess is as good as anyone else’s – unpredictability is a core element of disruption, almost definitionally – but I think there’s a good chance it’ll come from one of these areas: The creator economy – people who can independently grow an audience and monetize them sustainably. Entertainment, as an old, bureaucratic industry adjacent to this space, is also an interesting target. Communities – I’ve written extensively about my bullishness on communities elsewhere. Higher education – what replaces Harvard and Stanford?

In the real world, we don't want anyone rearranging the mess on our desks, but we don't mind if someone puts a Post-It note on our computer screen, empties the wastebasket overnight, or refills the newspaper stand with the latest edition.

Similarly, computer interfaces must evolve to let us utilize more of the power of language. Adding language to the interface allows us to use a rich vocabulary and gives us basic linguistic structures such as conditionals. Language lets us refer to objects that are not immediately visible.

Most of us don’t realize just how much the “app-centric” mindset is ingrained into us, until we get a chance to think in a “problem-centric” way free from the limitations of apps.

Every productivity app company these days seems to embrace the phrase “second brain,” as in “make X app your second brain.” One of my big takeaways from using Monocle on a daily basis for the last week has been that no single app can be my second brain. There are going to be parts of my life that are inherently spread out across different apps.

This kind of an annotation layer could also create more intimate contexts for conversation. If I’m doing a deep-dive research into the Faroe Islands, an annotation layer might let me know that someone else had recently visited the page in a similar frenzy of research. We might meet each other in this meta-layer in the same way we might bump into each other at a library while poring over the same row of books.

Most people have both a “Collector” and a “Librarian” inside them when they keep track of their ideas. The Collector wants to capture every idea you get, from shower thoughts to ideas that hit you on a long drive home. If you capture all your disparate ideas, maybe they’ll add up to something. The Librarian inside you wants to grow an organized, structured, clean library of ideas you can understand and browse. If you know how to find any idea you keep, you’ll be able to make the most of it when you need it. Often, these two needs are in conflict. It’s difficult to organize every idea you capture, because most ideas don’t start out with a solid form. The result is that you might let most of your ideas slip away in the moment, or you might end up with pages and pages of notes of ideas that you’ve captured and are afraid to throw away, but you can’t make sense of, much less learn from.