While sometimes the mess is a certifiable inefficient disaster resulting from laziness, the âorganized chaoosâ messy space acts like a mental buffer.
Hereâs computer scientist Jim Gray on the purpose of buffering in a programming context, from his book Transaction Processing:
The main idea behind buffering is to exploit locality. Everybody employs it without even thinking about it. A desk should serve as a buffer of the things one needs to perform the current tasks.
Keeping things âin the bufferâ redounds to productivity (and ideally, creativity). If something is closer at hand, it lowers the transaction costs of retrieval.
Memorization works this way, too. People question the benefits of rote memorization in school, but this is a useful metaphor for understanding its value. Memorizing reusable data keeps it âin RAMâ for faster retrieval.
Faster retrieval reduces friction, which means faster feedback loops, faster learning.
Iâve been looking for a way to use outdoor time as a spur for creativity. Many of us do our best thinking when our brains and bodies are otherwise occupied â we even call them âshower thoughtsâ for a reason. Running and walking for me are incredibly productive for the generative part of my brain. Iâve come up with and connected more dots while running than ever when sitting at the keyboard.
Sometimes Iâll walk with phone in hand, usually reading in the Kindle app, but also burning time on social feeds. Depending on what Iâm reading Iâll even bring a physical book on walks, as long as I can read one-handed. But then I started going with nothing, just a walk with my eyes, ears, and mind to keep me company. And, as is always the case when the mind has nothing to distract it, the brain is racing with thoughts and ideas and things I need to do and stuff I want to look up when I get back home. But thereâs no way to write anything down â fleeting thoughts fleet right out of my head.
So a couple months back I bought a dictaphone. It seemed silly at the time, but I thought âwhat the hell, Iâll try itâ.
Instead of the temptations of my iPhone and the internet in my pocket, I can âtake notesâ, but they have to be free-form, spoken word. There are voice
recorders out there with wifi, AI, transcription. But all of this is irritating ornamentation to me. I wanted the
lowest-tech, least-friction method I could find. Hit record, get mp3 file.
And yes, this means I have an audio file with messy, disorganized thoughts. But so what? I can easily speech-to-text it into the computer (more on that in a minute), and regardless, a driving factor here is to get out of my brainâs way. Half the benefit is the âunlockingâ effect I get of the no-frills, no-barriers talking out loud. Who cares if I say something that makes no sense? Part of the objective here is to kickstart the mental pistons, get through the messy disorganized thoughts, and find the good stuff.
For me, thinking is modal. Sometimes I need a kick to switch my brain from âconsumingâ to âproducingâ mode.
Speaking your thoughts out loud doesnât come naturally to me. Probably not to many people who arenât daily podcasters or radio hosts. Having only done this for a little while, it takes practice to speak coherently off-the-cuff into a microphone.
But the improvisational aspect of dictating is one of the most interesting to me. I find myself 20 minutes into a spontaneous stream-of-consciousness, and along the way encountering 5 tangents of other ideas I didnât even start out riffing on. Itâs a fruitful method for getting these latent ideas in my head to crystallize into something tangible. Iâll fork off on some tangent, then the act of thinking, processing, and trying to articulate out lout helps organize the mess into cohesive thoughts.
These audio files arenât publishable, but maybe one day they might be with practice.
All Iâve been doing after recording is copying the file off the device to my computer, and running a simple command line tool to convert to text locally.
I found this open source tool called hear, which acts as sort of the inverse of the native macOS command say. It uses the OSâs built-in speech recognition APIs to convert mp3 to a simple text file:
hear -d -i voice-note.mp3 > text-note.txt
Itâs not as fancy as the online tools like Rev or Otter, but I like it this way. The bulk of the text is a mess of jumbled thoughts with fragments of useful interestingness I can clip out.
Offline, audible thinking is a helpful tool so far. Iâll keep going with it and see how it evolves.
Visa founder Dee Hock had a great saying: âA belief is not dangerous until it turns absolute.â Thatâs when you start ignoring information that might require you to update your beliefs. It might sound crazy, but I think a good rule of thumb is that your strongest convictions have the highest chance of being wrong or incomplete, if only because they are the hardest beliefs to challenge, update, and abandon when necessary.
Are complex ecosystems like ponds actually smarter than we are? Are they âthinkingâ? Gordon says yes:
Evolution is a pragmatist. It only cares about actual behavior. It is the getting and the doing that matter. The how can be approached in many different ways, through pheromone trails, or trophic networks, or nerve nets, or brains, or symbolic representation. Evolution doesnât care. If you can get information and do something about it, you are thinking.
All we really need to say a system is âintelligentâ is that it incorporates feedback. Loops generate reactions, learnings from past iterations:
What else? Suddenly, we see that we embody many forms of intelligence outside of our brains. Our DNA, for example, encodes the memory of millions of years of experience within our environment. Every life lived by our ancestors, all the way back to that first single cell. Each recursive step in the game of life, a gift to us.
I also loved this quote from cyberneticist W. Ross Ashby:
âTo some, the critical test of whether a machine is or is not a âbrainâ would be whether it can or cannot âthink.â But to the biologist the brain is not a thinking machine, it is an acting machine; it gets information and then it does something about it.â
New Metaphors is a project to help spur creative thinking through metaphor. Itâs a deck of cards you can use in exercises to help stimulate new perspectives on an existing idea:
A metaphor is just a way of expressing one idea in terms of another. This project is a nightmare. The city is a playground. You are a gem. Creating new metaphors could help us design new kinds of product, service, or experience, and even help us think about and understand the world differently.
New Metaphors (buy a printed pack, or download for free) is a set of 150 cards (two different kinds) and some fairly simple methods for running workshops, brainstorming (individually or in groups), discussions, and other creative activities.
Iâm reminded of something from David Epsteinâs Range, where he writes about the importance of analogies to creative, connective thinking. Astronomer Johannes Kepler was known to use analogies to reframe problems he was working on:
Kepler was facing a problem not just new to himself, but to all humanity. There was no experience database to draw on. To investigate whether he should be the first ever to propose âaction at a distanceâ in the heavens (a mysterious power invisibly traversing space and then appearing at its target), he turned to analogy (odor, heat, light) to consider whether it was conceptually possible. He followed that up with a litany of distant analogies (magnets, boats) to think through the problem.
Most problems, of course, are not new, so we can rely on what Gentner calls âsurfaceâ analogies from our own experience. âMost of the time, if youâre reminded of things that are similar on the surface, theyâre going to be relationally similar as well,â she explained. Remember how you fixed the clogged bathtub drain in the old apartment? That will probably come to mind when the kitchen sink is clogged in the new one.â
When working through problems, the most impressive creators to me arenât those that divine an entire solution in their brain for an hour, then slam out a perfect result (spoiler: this doesnât exist outside of the occasional savant). I love to watch people who are great at avoiding the temptation to overcomplicate. People who can break problems down into components. People who can simplify complex problems by isolating parts, and blocking and tackling.
I enjoyed this, from an interview with Ward Cunningham (programmer and inventor of the wiki):
It was a question: âGiven what weâre trying to do now, what is the simplest thing that could possibly work?â In other words, letâs focus on the goal. The goal right now is to make this routine do this thing. Letâs not worry about what somebody reading the code tomorrow is going to think. Letâs not worry about whether itâs efficient. Letâs not even worry about whether it will work. Letâs just write the simplest thing that could possibly work.
Once we had written it, we could look at it. And weâd say, âOh yeah, now we know whatâs going on,â because the mere act of writing it organized our thoughts. Maybe it worked. Maybe it didnât. Maybe we had to code some more. But we had been blocked from making progress, and now we werenât. We had been thinking about too much at once, trying to achieve too complicated a goal, trying to code it too well. Maybe we had been trying to impress our friends with our knowledge of computer science, whatever. But we decided to try whatever is most simple: to write an if statement, return a constant, use a linear search. We would just write it and see it work. We knew that once it worked, weâd be in a better position to think of what we really wanted.
The most impressive software engineers Iâve worked with have a knack for this type of chewing through work. The simplest thing usually isnât the cleanest, fewest lines of code, fewest moving parts, or the most well-tested. Simple means âdoes a basic functionâ, something you can categorically check and verify, something a collaborator can easily understand.
Sometimes you just need to first do the Simplest Thing before you can find the Correct thing.
Some solutions rely on convoluted chains of logic that are strictly dependent on every single statement being true. They are more likely to have hidden âdivide by zeroâ problems that may be easily noticeable to the experienced practitioner but are invisible to the layman. Simple solutions might have errors too, but they will be much more obvious. Also, complicated chains of logic âfeelâ correct because a lot of the steps will be verifiably true; people sometimes forget that all of the steps have to be true for the entire argument to have any truth.
Complicated stories seem more likely to be logically sound to a midwit, but simple strategies are actually far less likely to have hidden land mines.
Iâm a big fan of looking for simple explanations for problems, or at least starting with simple explanations and testing them before overcomplicating your rationale. The midwit memes seem like unrealistic parody, but you see these situations in the wild all the time. Self-proclaimed âexpertsâ desperately want to have complex solutions to problems with complex systems â hell, one very well may be required. But at least invalidate the Pareto-fitting, more-likely simple solutions first.
This resignation letter from former Philadephia 76ers GM Sam Hinkie is full of gems. Here are a couple.
On contrarianism in a short-sighted league when youâre always under the microscope:
To develop truly contrarian views will require a never-ending thirst for better, more diverse inputs. What player do you think is most undervalued? Get him for your team. What basketball axiom is most likely to be untrue? Take it on and do the opposite. What is the biggest, least valuable time sink for the organization? Stop doing it. Otherwise, itâs a big game of pitty pat, and youâre stuck just hoping for good things to happen, rather than developing a strategy for how to make them happen.
On traditions, conventional wisdom, and the limits of advanced statistics in basketball:
Maybe someday the information teams have at their disposal wonât require scouring the globe watching talented players and teams. That day has not arrived, and my Marriott Rewards points prove it from all the Courtyards I sleep in from November to March. There is so much about projecting players that we still capture best by seeing it in person and sharing (and debating) those observations with our colleagues. What kind of teammate is he? How does he play under pressure? How broken is his shot? Can he fight over a screen? Does he respond to coaching? How hard will he work to improve? And maybe the key one: will he sacrificeâhis minutes, his touches, his shots, his energy, his bodyâfor the ultimate team game that rewards sacrifice? That information, as imperfect and subjective as it may be, comes to light most readily in gyms and by watching an absolute torrent of video.
Shane Parrish on the power of second-order thinking:
Second-order thinking is more deliberate. It is thinking in terms of interactions and time, understanding that despite our intentions our interventions often cause harm. Second order thinkers ask themselves the question âAnd then what?â This means thinking about the consequences of repeatedly eating a chocolate bar when you are hungry and using that to inform your decision. If you do this youâre more likely to eat something healthy.
Those that excel at second- or third-order thinking spend a lot more time running these simulations in their heads, playing out various scenarios and weighing costs/benefits of each unique pathway. It seems like an obvious thing to attempt with any decision; but I see cases regularly where it doesnât appear that a person is playing out their chosen path beyond the next immediate step and likely outcome.
Iâm reminded of the business concept of the âpre-mortemâ, wherein a team sits down collectively to look ahead at a decision about to be made or a project about to be tackled, and attempts to predict the contents of the post-mortem saying why the project failed or succeeded.
See also Annie Dukeâs Thinking in Bets, a whole book on orienting your critical decision-making capacity on thinking in probabilities.
If a note is an idea, we want to make the idea as atomic as possible, so we can find and stitch them together into an interconnected web of ideas. We want composable building blocks.
Composability helps us stack, mix, and repurpose ideas. To correlate them and find the relationships between them. Prose is an excellent medium for consumption, for diving deep on a particular topic. But with a prose format for documenting ideas (through notes), itâs harder to relate shared ideas across domains. Prose makes ideas easy to expand on and consume, but difficult to decompose into reusable parts. Decompose too far, though, say into individual words and letters, and the information is meaningless. We want a middle ground that can effectively convey ideas, but is also atomic enough to be decomposed and reused. We want idea Legos.
In Self-Organizing Ideas, Gordon Brander contrasts the linear, difficult to break down expansiveness of prose with something more like an index card. With index card-level division, ideas can now be expounded on at the atomic level, but also cross-referenced and remixed more easily than long-form prose. With the Zettelkasten, Luhmann devised a system of just that: numbered index cards that could reference one another. If you use a system like this for note taking, itâs a fun exercise to actually take a batch of 3-5 permanent notes at random and look for relationships. When Iâve done this, pulling out 2 arbitrary permanent notes, it often sparks new thoughts on them, and in the best cases, entirely new atomic notes.
Within our knowledge systems, we should strive for that right altitude of scope for a particular note or idea. Andy Matuschak says âevergreen notes should be atomic.â In my system, I make atomic notes that are concept-based, with a declarative format that prompts me to keep the note focused around a specific idea. Just scrolling through the list now, I see ones like:
âTraditions are storehouses of trial and errorâ
âNovelty in startups is higher than predictedâ
âKnowledge is the biggest constraint in product managementâ
With a format like this, each note is structured as a claim or idea, so itâs densely linkable inline within other notes. So when reading a note, the cross-link to another idea can appear seamlessly within the text. Using a concept-based approach, we might find serendipitous connections we werenât looking for. Andy says:
If we read two books about exactly the same topic, we might easily link our notes about those two together. But novel connections tend to appear where theyâre not quite so expected. When arranging notes by concept, you may make surprising links between ideas that came up in very different books. You might never have noticed that those books were related beforeâand indeed, they might not have been, except for this one point.
Novel ideas spring from concocting new recipes from existing ideas. Composable, atomic ideas make it more manageable to toss several disparate ones together to experiment with new combinations.
Gordon has been writing lately about his work on Subconscious, and the possibility of software-assisted self organization of ideas. This is a super intriguing idea, and exactly the sort of reason Iâm interest in computers and software â for their ability to help us think more creatively, do more building, and less rote information-shuffling.
He differentiates what the âwakingâ mind and âbackgroundâ mind are good at, which Iâd interchangeably refer to as the âat the deskâ mind and the âaway from the computerâ mind:
Waking mind:
Good at critical thinking; analysis, tactics
Prone to finding local maxima
Can feed work to the background mind
Background mind:
Good at making connections
Synthesis; strategy; abstractions and analogies
You can only feed it, not direct it
For anyone in a critical thinking-based market, Iâm sure this rings accurate. Think about how we refer to eureka moments popping into our heads â âshower thoughtsâ. This idea that we can âonly feed it, not direct itâ does feel true. For me the most interesting ideas donât result from me saying âokay, itâs time to think about thingsâ and writing down the result.
When Iâm working on something, itâs challenging to get âunstuckâ while sitting at my desk. Some days I can get in the zone, but most of the time the zone eludes me. Itâs not even the active distractions of Slacks, meetings, and email (though those are never-ending), but temptation from the no-kidding thousands of individual little shiny threads to follow.
But then when Iâm out for a walk, a run, or driving somewhere, thoughts and ideas abound. And of course Iâm never in a good position to take notes or jump right into writing or doing anything about them at the time. My post from last year on Downtime Thinking looked at my experience with this phenomenon. Iâve experimented with techniques for bringing these modes closer together. Too many interesting ideas are lost in the transition between waking and background brain modes.
Hammock-driven creativity helps the mind jar loose from its normal working context. Environment is a strong contributor to controlling your behavior. For myself, my ânormalâ work environment â sitting at my desk, keyboard and mouse in hand, multiple monitors available â is associated in my brain with dozens of activities other than creative or critical thinking. Iâve experimented lately with âmorning pagesâ as a mechanism working on the writing habit. Start a timer and do nothing but write free-form for 25 minutes. Iâm having mixed success with it much of the time, but occasional sessions lead to solid ideas, and Iâll blow past my time commitment promise.
If I can combine the intentionality of morning pages with a minor change of scenery, the forces could combine into a productive combo.
In a recent interview, Jerry Seinfeld described his writing sessions, a brilliantly simple practice:
I still have a writing session every day. Itâs another thing that organizes your mind. The coffee goes here. The pad goes here. The notes go here. My writing technique is just: You canât do anything else. You donât have to write, but you canât do anything else. The writing is such an ordeal.
I love that: âYou canât do anything else. You donât have to write, but you canât do anything else.â
Setting the table for the writing session triggers the Pavlovian mode: âthis is writing time.â Then youâve got the intention, that you canât do anything else. And I love how he gives himself the leeway to not even write! But in exchange for the freedom for work-avoidance, your only other option is staring at the wall.
Of the hundreds of posts Iâve written here over the past few years, I would guess that 80% of the topics spawned in my head while exercising. Running is my primary regular means for alone time to think in silence. I usually listen to audiobooks while Iâm out, but constantly pause to dictate notes to myself into a scratchpad document. Reviewing this occasionally is like a stream of consciousness chain of observations and ideas that I can usually peg to an origin of what triggered the idea, then can take it and run with it when back home. There may even be some science behind this; perhaps a more active heart rate or increased blood flow increases brainpower. Wild speculation, but running certainly feels mentally invigorating sometimes.
When we sit at our desks, we have access to all of our resources â apps, tools, websites, Wikipedia â youâd think that an environment like that would be a boon to creative thinking. But that continuous pull of your attention into different directions plays hell with being able to contemplate freely, to dive into the second-order consequences of an idea.
During the work day weâre also all contending with dozens of meetings, calls, emails to read, emails to send, a never-ending stream of minor inputs that donât afford the free space to think for extended periods. That dedicated time when weâre fully undedicated, no commitments to anything or anyone, is often when we have the range of motion to do our best thinking.
Amos Tversky, the late collaborator of Nobel-winning psychologist Daniel Kahneman, once said âthe secret to doing good research is always to be a little underemployed. You waste years by not being able to waste hours.â
When I look at my calendar on many days, I wonder how or when any deep thinking is supposed to get done. Luckily I devote space for this for other physical exercise that does double duty as a mental stimulant. Itâd be nice if we collectively had more respect for this phenomenon in spaces of knowledge work, but until we do, the best we can do is understand it and compensate with our own âdowntime.â
Hereâs Morgan again with a nice reminder:
Thereâs never going to be an Adamson Act for knowledge workers who need time to think. Itâs up to you to figure it out. The first step is realizing that taking time in the middle of your day to do stuff that doesnât look like work is the most important part of your work day.
Even though Steve Jobs famously said the computer was the âbicycle for the mind,â I think we might need to remove that metaphor â maybe the bicycle is the best bicycle for the mind (or your legs or weights or your favorite chair in a silent room).
David Perellâs been putting out a series of 100 posts, 1 per day, brief essays about writing. I enjoyed this one about the evolutionary, and recombinant, nature of ideas:
All creativity is inspired by other peopleâs ideas. The faster you embrace that, the more successful you can be as a creative. As Brain Pickings author Maria Popova once said: âSomething we all understand on a deep intuitive level, but our creative egos sort of donât really want to accept: And that is the idea that creativity is combinatorial, that nothing is entirely original, that everything builds on what came before, and that we create by taking existing pieces of inspiration, knowledge, skill, and insight that we gather over the course of our lives and recombining them into incredible new creations.â
Lately Iâve been pouring time into Roam, finding ways to improve my long-term memory, and reading about taking notes, all in service of getting better at synthesizing new ideas.
Central to all of these is the Zettelkasten method of note-taking, a fancy-sounding German word for ânote box.â
In addition to SĂśnke Ahrensâs excellent book on the topic, this post offers a deeper look into the mechanics of the system.
In SĂśnke Ahrensâs book How to Take Smart Notes he describes the âzettelkastenâ system (the âslip boxâ) developed by German sociologist Niklas Luhmann. Luhmann created the system to help himself organize notes and thoughts in a networked model rather than a structured hierarchy of folders. The zettelkasten system has a few elements to it to help model different types of notes, how and when you should write them, and how you associate ideas together.
The fundamental piece is the âpermanent note,â one in which you develop your own model of an idea, linking it through associations to other information like quotes, citations, and clippings from other works â but with the base attribute that you formulate it yourself in your own words (not a bunch of quotes pasted together).
Andy Matuschak calls these âevergreen notes,â which I think is a better term to describe how they work. The intent with evergreen notes is that they arenât ever declared finished, that you continue to flesh out and expand on the ideas therein as you learn more. Maybe you even learn revelatory things that change your deep thinking on the foundation of the idea. Evergreen is a better term, to me, than permanent because it implies a living document. Permanence implies completion.
Iâve been kicking around an idea on how I can convert and publish my evergreen notes from Roam as a public site somehow. Once ideas are substantive enough, I could publish them to the web. Any internal links to other evergreen ideas could link to those pages, and links to ideas not yet published could indicate future ideas Iâm working on, but not yet ready for public consumption.
At the moment Iâm thinking about how I could build this with minimal friction and augment this site with it. Some way that I can publish alongside the blog, but perhaps interlink content between the temporal stream of the blog format and the non-time-bound evergreen notes. As new ideas or additions are worked out to existing ideas, I want a small breadcrumb to appear in the blog feed showing what was updated and the nature of the change, making visible the evolution of ideas over time.
Martin Gurri on the growing similarities between west and east coast elites:
The effect, I suspect, will be the exact opposite of the reactionary dream. In wild and seedy digital gathering-places, far from any pretense of idealism, political discussion will inevitably grow more unfettered, more divisive, more violent. The attempt to impose Victorian standards of propriety on the information sphere will end by converting it into a vicious and unending saloon brawl. No matter how revolting the web appears at present â it can always get worse.
Robert Haisfield walks through some methods he uses in Roam to make sense of the decentralized, scattered information web to get creative work done. I use some similar methods to collect the distributed notes that have collected about a single topic, but queries would allow taking it to the next level.
I canât find the video anywhere online. We laughed endlessly at this one. âŠ
Learning to build again will take more than a resurgence of will, as Andreessen would have it. And the U.S. should think of bolder proposals than sensible but long-proposed tweaks to R&D policies, re-training programs and STEM education.
What the U.S. really needs to do is reconstitute its communities of engineering practice. That will require treating manufacturing work, even in low-margin goods, as fundamentally valuable. Technological sophisticates in Silicon Valley would be wise to drop their dismissive attitude towards manufacturing as a âcommoditizedâ activity and treat it as being as valuable as R&D work. And corporate America should start viewing workers not purely as costs to be slashed, but as practitioners keeping alive knowledge essential to the production process.
âBikesheddingâ is a common term in tech circles. When starting on a big new software project, start by asking a design team for opinions on which programming language to use and youâll get to see it in action. It applies all over; humans love an opportunity to look like theyâre contributing meaningfully, especially when they perceive that they should know something about the subject:
Bike-shedding happens because the simpler a topic is, the more people will have an opinion on it and thus more to say about it. When something is outside of our circle of competence, like a nuclear power plant, we donât even try to articulate an opinion.
But when something is just about comprehensible to us, even if we donât have anything of genuine value to add, we feel compelled to say something, lest we look stupid. What idiot doesnât have anything to say about a bike shed? Everyone wants to show that they know about the topic at hand and have something to contribute.
Hat-tip to Julian Lehrâs recent post for the referral to this one. Itâs a simple menubar app that gives you a search interface to unicode symbol sets. The speed here is phenomenal; so much faster than the built-in emoji keyboard (plus it has a much larger library).
What does it mean to âsynthesizeâ knowledge? Joel Chan, author of this post and professor of human-computer interaction, describes it as âcreating a new whole out of components.â
In reading, digesting material, and taking notes, youâre by definition creating small components of information that you then ideally piece together to form knowledge.
The difficulties with synthesis described in the post align well with the reasons I talked about in my review of Roam and how itâs addressing these exact gaps:
Cognitive Overhead (aka Cognitive Load): often the task of specifying formalism is extraneous to the primary task, or is just plain annoying to do.
Tacit Knowledge: if relevant information for developing formalism is tacit, asking people to formalize it will interrupt the task, with serious consequences for the quality sof the work.
Enforcing Premature Structure: people donât want to commit until theyâre sure what formalism is actually useful for their task (and whatâs extraneous and only annoying).
Situational Structure: Useful structures and formalisms vary significantly across people, situations, and tasks.
The idea of âincremental formalizationâ is interesting. Tools should favor the free-form mode for exploratory, unbounded thought documentation, and incrementally suggest, expose, or automatically self-organize the information into structures:
Incremental formalization addresses the cognitive overhead problem by spreading it throughout the task a bit more evenly, as well as removing it mostly from the earlier parts of the task, where minimal friction is needed to maximize exploration. It also helps with the premature and situational structure problems, since you donât have to commit early on to a structure that may not serve you well (or even hurt your performance) later on.
My Roam workflow really does strike this great balance with affording a flexible, open-ended place for stream of consciousness, while the selective insertion of linked references creates emergent order in the system.
Roam Research has been making the rounds on the internet in the last couple months. Iâve written a little bit here about it, but promised this longer overview of how itâs working for me so far.
What is it?
Roam is a tool for note-taking, described as a tool for ânetworked thought.â With a glance on Twitter youâll find all sorts of comparison pieces to Evernote, Google Docs, or Notion. Iâve tried all of those (Notion for quite a bit) and I find the experience of using Roam completely different.
Most applications for notes are both modal and hierarchical. When working on a text document, it lives in a folder with other related files. A half page of notes from a meeting has a specific place it should go. But because you donât always want to deal with filing things logically, itâs easy to end up with thoughts and ideas out of place, caught up and buried in meeting notes because thatâs what you had open when a thought popped into your head (or even worse, arbitrary quick captured scratch docs you open once and are promptly disconnected from everything).
Roam solves this problem by destroying the top-down hierarchy of knowledge management tools. Instead of worrying about where to put a new document (Roam calls them âpagesâ), you just make a new one anywhere. All pages are peers. Itâs like a wiki in that way, but it feels more fluid, more natural and less mechanical. Making new pages is a matter of double-bracketing any word or phrase. With a quick piece of formatting which Roam autocompletes, [[Knowledge Management]] gets its own page, from which I can view the other Linked References. The Linked Reference is the secret weapon, a killer idea well-executed in Roamâs simplistic but blazing fast interface. Each page also detects and shows âUnlinkedâ references, places where a string appears without an explicit link.
I described it to someone through analogy to a CRM. Roam is a CRM for ideas: call it âIdea Relationship Management.â Since Iâve been using it as a sort of productivity journal (Tiago Forte calls this the âsecond brain, living in it the whole work day. Itâs like an operating system for managing information â always on, always absorbing new data. And, like a real brain, linked reference synapses form between the information neurons.
The Graph
The idea graph is what breaks you free of organizational burden. The need to find where to put thinsg, once a point of friction in note-taking (that is, if you ever wanted to be able to find a piece of jotted information again) is gone, replaced by a new way to navigate your knowledge graph via organically produced links.
Hereâs a scenario that happens all the time to me (and Iâm sure others) that no other tool has handled well until now:
I walk into a product marketing meeting. During the meeting weâre going to solidify our messaging strategy and requirements for a new feature launch. I open up a new file for the meeting Product marketing sync â 2020-04-13 or similar is a typical nomenclature. That file likely contains bullets and a series of messy individual lines related to things each person is going to do, topics people mentioned, action items for myself (which need to go elsewhere to have a prayer of being remembered). However, interspersed within the discussion I jot random thoughts on sometimes semi-related topics, but sometimes something completely off the reservation, that I still want to capture. During the marketing discussion I get an idea for a future blog post with a couple of topics. Where does that go?
Most commonly today the answer is ânowhereâ and Iâm lucky if I remember it again. In Roam I just type it in a âRandomâ subsection in the bottom of my meeting notes. Who cares where it goes if I can link that by topic from elsewhere?
A quick tip: next to any random, non-sequitur thought like this, put #idea next to it. That then becomes its own page, with Linked References collecting up all the ideas dispersed through your graph.
I love that I can navigate to an abstract idea, like my page about âAntifragility,â and find all of the articles, books, or other notes that connected with that idea. The ROI happens with Roam once you start rediscovering links or ideas you already noted without making the connection beforehand. Itâs like stitching together threads that would have been previously in silos, invisible to one another. If you then also separate those notes in time, its nigh impossible to keep those connections front of mind. I havenât been using Roam very long yet, but even in a few weeks I stumble back onto notes I wrote that I donât remember writing.
Information falls out of your head and into your Roam database spontaneously organizing itself, expanding organically. After heavy use for a few weeks, navigating through the database feels like descending into your own Wikipedia rabbit hole â like swimming through your previous thoughts.
Use Cases
I find myself taking notes on all sorts of things I never used to, or at least rarely did. Here are a few:
Books (I did do this before, but very intermittently and selectively)
Articles
Podcasts
YouTube videos
Meetings, 1:1s, and other work conversations
Useful reference info for around the house (measurements of spaces, home inventory, and more)
CRM-style notes on people (more on this in a second)
Most of that Iâve never kept running notes for, but Roam makes it actually fun to make notes on all of these things. Since I put date tags on a lot of my notes files (if relevant), notching back through the days shows Linked References to things I was working on those days.
For people, any time I have a call or meeting Iâll include a âPeopleâ line with links on all their names. Likewise for any mention of them in other pages. Then navigating to a person shows those LRs to all the relevant notes, ideas, conversations, often linked from Daily Notes, so thereâs a visible timeline to the references. Itâs the closest thing Iâve seen yet to the mythical personalCRM Iâve seen reference to.
Daily Notes
A knowledge graph needs some form of interface to navigate around it. Without the top-down hierarchy of a file tree, the root page of a structureless content database would typically feature search as an entry point for navigation. Roam does have an excellent page search, but it has another anchor that I love: Daily Notes. Each day Roam automatically creates a new date-stamped page for that day, which is the default main page when you open the app. Whatâs great about this for such a free form system is that you always have that anchor to link from. If you want a new page for a fleeting idea but are worried a new page will be disjointed from your universe of ideas, and donât want to search for another page that idea might fit, just spawn it off of Daily Notes. Make a âRandomâ or âIdeasâ section for the day and add it. Iâve been using this technique for quick stuff and it serves a couple of useful purposes:
Daily Notes functions for me like a productivity journal, a rough record of what I was doing, working on, or thinking about that day.
If a random idea links from a Daily Note and then contains a few bullets of thoughts, navigating back to it weeks later always has a fallback method of tracking back through previous daysâ notes to find it.
An added cool thing here, thanks to Linked Reference backlinks, is that any page in which you insert todayâs date shows up as a LR under that day.
What I notice in regular usage of Roam, with Daily Notes as the âhome screenâ of the tool, is thought taking on an organic structure. The links grow and the dots connect as youâre working. Going and forming connections or describing the organization of your thoughts never need be done with intent â itâs all implied as youâre writing.
In the month that Iâve been actively using it, I have Roam open on my second display all day, with notes continually flowing into the database as they happen. In all the other note-taking tools and systems Iâve used in the past, the friction for tracking ideas was never this low.
TODOs
Any line can be converted into a to-do with a checkbox, which then appears in a special [[TODO]] page that Roam automatically manages. Itâs super fast to toss things in there to remember later, regardless of page locations. I pin the TODO page into my sidebar for quick access. Cmd-enter on any line converts it into a to-do.
Since Iâm a Todoist user for all of this before, Iâm now waffling on which tool I should use for tasks. Iâm still in both, but I can see some hope for eventually moving all of that into Roam since itâs solving so many other things related to productivity management. The main struggle is that capture into a to-do list inbox (like what I do with Todoist) from mobile isnât great yet. Browsing to Roam on your phone takes you to a simple âQuick Captureâ interface, which inserts blocks into a #Quick Capture section in your daily notes. This is great to have for the random passing thought to go somewhere, but as Iâve used it so far it still requires me to fold those into appropriate places I want them after the fact. Not bad for ideas, but Iâd prefer something more devoted to true to-dos for that purpose.
Another random tip: Questions dawn on me all the time I donât know the answer to, but want to remember to revisit. At the end of the line Iâll just type a #?? tag. Browsing to the [[??]] page then aggregates all the open questions. h/t to Matthieu Bizien who simplified this for me.
The #roamcult
Just search that hashtag and youâll find a community of hundreds of super active, impassioned Roam users all out there evangelizing the product. In some ways, its spartan user interface, semi-opaque shortcuts and tricks about how it works promote cult-like adoption patterns. Its learning curve becomes a badge of honor for a certain type of user. Getting over the hump after a few days of heavy usage delivers a sense of satisfaction if youâre able to tame it to do your bidding.
Some of the product limitations in terms of help and onboarding to expose its power-user features are a function of a small, focused team of a few with a lot to build. Right now itâs a power-user tool designed by its intended users. With growth, they plan to expand their product design team which Iâm sure will change this rapidly. But it does seem that theyâve embraced the productâs opacity to promote the #roamcult. Hopping into the public Slack or looking at videos of how people use it on YouTube will give you an insight into how obsessed the early users are.
More Reading
The Roam white paper is an excellent resource, recommended to anyone curious about the product direction and the core ideas driving its development. Founder Conor White-Sullivan also has a number of video interviews on YouTube that I found super insightful to get a background on why the product works the way it does. Heâs also an interesting person in general, and a great Twitter follow.
Roam has clicked for me as the tool for notes I didnât know I needed. Iâm still learning new ways of using it. Itâs fun how adaptive Roam is to change; the process of discovery of new ways of Knowledge Management is rewarding. I can just start formatting a new page however I want, and it doesnât damage the graph of interconnections.
Iâm excited to see where the product goes as it continues to take off.
Been reading more about how others are using Roam the last few days. In this post, Sarah Constantin draws an apt connection to Vannevar Bushâs âmemexâ concept from his 1945 paper âAs We May Thinkâ. It was an early influence on what eventually became hypertext â his memex was an electromechanical device that could record and connect ideas on microfilm storage.
Arguably the Internet forms one big memex today. Bush was right in his prediction that âwholly new forms of encyclopedias will appearâ, that âThe patent attorney has on call the millions of issued patents,â and âThe physician, puzzled by a patientâs reactions, strikes the trail established in studying an earlier similar case, and runs rapidly through analogous case histories, with side references to the classics.â
But Bush imagined the memex as a private (though shareable) record, not a communal one. Each person should have their own memex.
Roam feels to me a lot more valuable for personal rather than team use.
Iâm deeper these days into Roam for info storage and notes. It empowers a looser, free-form version of writing (or as Roam describes it ânetworked thoughtâ) thatâs hard to do in a linear note document. Iâve been working up a post on Roam and where I feel it fitting into my own workflow.
This piece gives a good overview of it and how itâs different from other knowledge management systems.
Tom MacWright on chess. Reduce distraction, increase concentration
Once you have concentration, you realize that thereâs another layer: rigor. Itâs checking the timer, checking for threats, checking for any of a litany of potential mistakes you might be about to make, a smorgasbord of straightforward opportunities you might miss. Simple rules are easy to forget when youâre feeling the rush of an advantage. But they never become less important.
Might start giving chess a try just to see how I do. Havenât played in years, but Iâm curious.
The best resource Iâve run across for aggregated data on COVID cases. Pulled from state-level public health authorities; this project just provides a cleaned-up version of the data. Thereâs even an API to pull data.
He proposes this format for thinking about the phases a company moves through â from idea to profits:
An idea is not a mockup
A mockup is not a prototype
A prototype is not a program
A program is not a product
A product is not a business
And a business is not profits
You can map this onto the debate between âidea vs. executionâ by calling everything below the idea the stage âexecution.â In certain circles, especially among normal people not steeped in the universe of tech companies, the idea component is enormously overweighted. If you make software and your friends or acquaintances know it, Iâm sure youâre familiar with flavors of âI have this great idea, I just need someone who can code to build it.â They donât understand that everything following the âjustâ is about 99.5% of the work to create success (or more)1.
Thinking of these steps as a state machine is a vivid way to describe it. He has them broken out in detail:
When laid out that way itâs clear why it takes such persistence and wherewithal to see an idea through to being a business.
To understand if you have an idea worth pursuing (or even one good enough to be adapted/modified into a great one), itâs a good exercise to simulate the game in your head, to imagine youâve already moved through a couple steps of the state machine. What are you encountering? If you think of a roadblock, how would you respond? This sort of âpre-gamingâ is what separates the best creators and product minds from everyone else. They take small, minimum-risk steps, look up to absorb new feedback, and adapt accordingly2.
Srinivasan calls this phenomenon the âidea mazeâ:
One answer is that a good founder doesnât just have an idea, s/he has a birdâs eye view of the idea maze. Most of the time, end-users only see the solid path through the maze taken by one company. They donât see the paths not taken by that company, and certainly donât think much about all the dead companies that fell into various pits before reaching the customer.
A good founder is thus capable of anticipating which turns lead to treasure and which lead to certain death. A bad founder is just running to the entrance of (say) the âmovies/music/filesharing/P2Pâ maze or the âphotosharingâ maze without any sense for the history of the industry, the players in the maze, the casualties of the past, and the technologies that are likely to move walls and change assumptions.
In other words: a good idea means a birdâs eye view of the idea maze, understanding all the permutations of the idea and the branching of the decision tree, gaming things out to the end of each scenario. Anyone can point out the entrance to the maze, but few can think through all the branches.
I remember Marc Andreessen in an interview talking about questioning founders during pitches: if you can probe deeper and deeper on a particular theme to a founder and theyâve already formulated a thoughtful answer, it means theyâve been navigating the idea maze in their head long before being probed by an investor.
Itâs worth thinking about how to incorporate this concept into my thinking on future product growth. I think to some extent this sort of thing comes naturally to certain people; the naturally curious ones are doing a version of this all the time, often unintentionally. But what if you could be intentional about it?
Not to mention the fact that people are typically ignorant to how often their eureka idea has already been tried or has already gained success because itâs obvious enough to have attracted plenty of others. âŠ
See Antifragile, Talebâs magnum opus. An entire book on the subject of survivability, risk reduction, adaptation, and respect for proceeding with measured caution in âExtremistanâ (highly unpredictable environments). âŠ
Bryan put together this neat little utility for merging point data with containing polygon attributes with spatial join queries. It uses Turf.js to do the geoprocess in the browser.
NASAâs Curiosity rover has captured its highest-resolution panorama yet of the Martian surface. Composed of more than 1,000 images taken during the 2019 Thanksgiving holiday and carefully assembled over the ensuing months, the composite contains 1.8 billion pixels of Martian landscape. The roverâs Mast Camera, or Mastcam, used its telephoto lens to produce the panorama; meanwhile, it relied on its medium-angle lens to produce a lower-resolution, nearly 650-million-pixel panorama that includes the roverâs deck and robotic arm.
âEasyâ because thereâs a delay between benefit and cost.
The cost of exercising is immediate. Exercise hurts while youâre doing it, and the harder the exercise the more the hurt. Investing is different. It has a cost, just like exercising. But its costs can be delayed by years.
Whenever thereâs a delay between benefit and cost, the benefits always seem easier than they are. And whenever the benefits seem easier than they are, people take risks they shouldnât. Itâs why there are investing bubbles, but not exercise bubbles.
Base-Rate Neglect: Assuming the success rate of everyone whoâs done what youâre about to try doesnât apply to you, caused by overestimating the extent to which you do things differently than everyone else.
Time is our most fundamental constraint. If you use an hour for one thing, you canât use it for anything else. Time passes, whatever we do with it. It seems beneficial then to figure out the means of using it with the lowest possible opportunity costs. One of the simplest ways to do this is to establish how youâd like to be using your time, then track how youâre using it for a week. Many people find a significant discrepancy. Once we see the gulf between the tradeoffs weâre making and the ones weâd rather be making, itâs easier to work on changing that.
The article reminds me of Sowell on economics. Take this and apply to any other life domain:
Economics is the study of the use of scarce resources which have alternative uses.
A timeless one from Paul Graham, 2006. On the advantages of outsiders:
Even in a field with honest tests, there are still advantages to being an outsider. The most obvious is that outsiders have nothing to lose. They can do risky things, and if they fail, so what? Few will even notice.
The eminent, on the other hand, are weighed down by their eminence. Eminence is like a suit: it impresses the wrong people, and it constrains the wearer.
Outsiders should realize the advantage they have here. Being able to take risks is hugely valuable. Everyone values safety too much, both the obscure and the eminent. No one wants to look like a fool. But itâs very useful to be able to. If most of your ideas arenât stupid, youâre probably being too conservative. Youâre not bracketing the problem.
This is an extension of the Amazon mantra of forcing your team to âwrite the press releaseâ for a product or feature before starting on it. The goal is to concretely visualize the end state as clearly as you can, and get on the same page strategically to outline the why of what youâre building. The PR FAQ is another assistive technique for setting and articulating the goal.
Thereâs a really strange phenomenon in certain arenas (particularly politics) where itâs considered a virtue to strongly hold a viewpoint and never change your position. This is strange because, as Rory Sutherland points out here, if you did this in business youâd likely run into frictions that put you out of business. Changing your mind is an imperative when presented with new data.
And herein lies one magic quality of business. It is the only area of human activity where you get paid to change your mind.
In politics, in punditry, in academia, there is great value attached to consistency. Changing your mind risks loss of face. Your ability to deliver plausible generalisations counts for a lot. There is social pressure to adopt the dominant frame of thought. No one gets invited on Newsnight to say âIâm not really sureâ and âItâs kind of complicatedâ.
Itâs like starting out on a journey with a road map in front of you, encountering unforeseen obstacles (road closures or standstill traffic), and never wavering from the original plan. We should be better about being open-minded about political figures being honest about adapting views. Nothing thatâs fixed ever improves â itâs best case scenario is stasis.
On the power of starting with no baggage, sunk costs, or past poor decisions:
Part of the reason the economy recovered slowly after the financial crisis was that businesses, spooked by the recession, relentlessly reviewed their costs. âI just see business after business after business which has rationalized so that it can protect its balance sheet and earning power while utilizing fewer peopleâ Charlie Munger said in 2010.
So began a new life for the concept of zero-based budgeting.
Zero-based budgeting is the idea that each yearâs budget should be created from scratch, rather than using the previous yearâs budget as a baseline. Jimmy Carter made it famous during the 1970s â the last time business and government budgets were as strained as they were in recent years. The number of large companies using zero-based budgeting has increased 50% since 2008, according to Deloitte. Campbell Soup, Kellogg, and Kraft now use it.
Itâs based on a profoundly sane idea: Things change and evolve, so the phrase âthis is how weâve always done itâ should be replaced with âwhat do we need right now?â A full reset, unburdened by the past.
You canât (and shouldnât) always reboot at the first sign of trouble. We should measure the cost-benefit of the full reset and use it when possible and time and space permit:
There is a counter to this: The secret to investing is enduring uncomfortable situations, so selling at the first hint of imperfection is usually regretted. But its opposite â an unshakeable anchor to past decisions â is perhaps worse. The saying, âOur favorite holding period is forever,â should be replaced with, âOur favorite holding period is until the facts change.â
A list of broad laws that apply to all fields. Thoughtful stuff as always from Morgan Housel:
6. Parkinsonâs Law: Work expands to fill the time available for its completion.
In 1955 historian Cyril Parkinson wrote in The Economist:
IT is a commonplace observation that work expands so as to fill the time available for its completion. Thus, an elderly lady of leisure can spend the entire day in writing and despatching a postcard to her niece at Bognor Regis. An hour will be spent in finding the postcard, another in hunting for spectacles, half-an-hour in a search for the address, an hour and a quarter in composition, and twenty minutes in deciding whether or not to take an umbrella when going to the pillar-box in the next street. The total effort which would occupy a busy man for three minutes all told may in this fashion leave another person prostrate after a day of doubt, anxiety and toil.
His point was that resources can exceed needs without people noticing. The number of employees in an organization is not necessarily related to the amount of work that needs to be done in that organization. Workers will find something to do â or the appearance of doing something â regardless of what needs to be done.
This is a neat collaboration tool for distributed teams that just launched. Itâs built on Slack and has integrations built for many of the common productivity tools that modern remote teams are familiar with. Iâm keen to take a look at this for doing more real-time work with my remote co-workers.
As computer vision continues its advance, machines are getting better and better at converting images and video into structured data. Computers have historically had sensor data feeds through text, binary data streams, and user inputs; eventually theyâll all have visual inputs, as well.
Ever since reading Kahnemanâs Thinking Fast, and Slow, biases are always in the front of mind when considering approaches to problems.
Scott Alexander has some interesting thoughts on this topic, namely that bias is ever present regardless of the environment, worthy of vigilance:
This is a general phenomenon: for any issue, you can think of biases that could land people on one side or the other. People might be biased toward supporting moon colonization because of decades of sci-fi movies pushing space colonization as the wave of the future, or because Americans remember the moon landing as a great patriotic victory, or because big defense companies like Boeing will lobby for a project that would win them new contracts. Or people might be biased against moon colonization because of hidebound Luddite-ism, or an innate hominid preference for lush green forests and grasslands, or a pessimistic near-termism that rejects with payoffs more than a few years out. I personally might be biased towards moon colonization because Iâve been infected with the general Silicon Valley technophile mindset; or I personally might be biased against it because Iâm a Democrat and Trumpâs been the loudest modern proponent of more moon missions.
If weâre all biased in some way all the time, where do we go from here? Do we bother having conversations anymore after person A in an argument says to B âyouâre biased because of Xâ? Whatâs the proper response? How can a debate be had if bias disqualifies you from forming an argument?
Kahneman argues for attempting to take the âoutside viewâ on a topic to give yourself perspective. Getting outside of your own head is important, as humans have an innate tendency to heavily rely on intuitions (for evolutionary reasons, in my view) since they can speed up response time1. This becomes a problem when issues are larger and more abstract than our ancestors wouldâve ever encountered.
Ultimately it seems a sound approach to me to simply consider your potential biases as youâre forming a set of ideas or a particular point of view before making arguments to those with opposing viewpoints. Succinctly put here:
Most important, I think first-person bias arguments are valuable. You should always be attentive to your own biases. First, because itâs easier for you; a rando on Twitter may not know how my whiteness or my Jewishness affects my thought processes, but I might have some idea. Second, because youâre more likely to be honest: youâre less likely to invent random biases to accuse yourself of, and more likely to focus on things that really worry you. Third, you have an option besides just shrugging or counterarguing. You can approach your potential biases in a spirit of curiosity and try to explore them. I think Iâm probably biased against communism because many communists I met have been nasty people who tried to hurt me, so I try to solve that by reading more communist books and seeking out good communist arguments wherever I can find them. Second- and third-person bias arguments risk feeling some kind of awkward option to change your opinions to something you donât really believe in order to deflect someoneâs bias accusations. First-person bias arguments should lead to a gradual process of trying to look for more information to counter whatever motivated reasoning you might have.
Slate Star Codex presents refreshing viewpoints on topics like this â essentially Alexander thinking out loud about all sides of an issue that all rational people consider inside their own heads, even if they canât or wonât articulate it.
Recall Kahnemanâs âsystem 1 and system 2â modes of thinking â with the former being oriented around rapid involuntary intuitive response, and the latter high demand decisions based on complex information and directed thought. Humans of 50,000 years ago needed a reliable system 1 a lot more than system 2. Evolutionarily speaking, it was more important to be able to quickly assess whether your tribe was under threat of attack than it was to think deeply about abstract mathematics. âŠ
The predictive processing model is a cognitive framework for modeling how the brain synthesizes information from two channels:
The âbottoms upâ stream of raw data coming in through our senses for processing
The âtop downâ stream of predictions about the world
These two channels merge together in a continuous interplay inside the brain and allow us to make sense of the world, with each system continually feeding back to the other in a process weâd refer to as âlearningâ.
This Slate Star Codex post is a review of Andy Clarkâs Surfing Uncertainty, and has a fascinating analysis of how the two systems interact. Itâs a great summary of the concept and one of the best concise descriptions of how the brain works that Iâve ever seen. Hereâs a great description of the bottoms-up / top-down interplay:
The bottom-up stream starts out as all that incomprehensible light and darkness and noise that we need to process. It gradually moves up all the cognitive layers that we already knew existed â the edge-detectors that resolve it into edges, the object-detectors that shape the edges into solid objects, et cetera.
The top-down stream starts with everything you know about the world, all your best heuristics, all your priors, everything thatâs ever happened to you before â everything from âsolid objects canât pass through one anotherâ to âe=mc^2â to âthat guy in the blue uniform is probably a policemanâ. It uses its knowledge of concepts to make predictions â not in the form of verbal statements, but in the form of expected sense data. It makes some guesses about what youâre going to see, hear, and feel next, and asks âLike this?â These predictions gradually move down all the cognitive layers to generate lower-level predictions. If that uniformed guy was a policeman, how would that affect the various objects in the scene? Given the answer to that question, how would it affect the distribution of edges in the scene? Given the answer to that question, how would it affect the raw-sense data received?
The author looks at disorders and other phenomena through the predictive processing lens to see how they hold up â things like the learning, dreaming, the placebo effect, priming, schizophrenia, and autism:
Autistic people classically canât stand tags on clothing â they find them too scratchy and annoying. Remember the example from Part III about how you successfully predicted away the feeling of the shirt on your back, and so manage never to think about it when youâre trying to concentrate on more important things? Autistic people canât do that as well. Even though they have a layer in their brain predicting âwill continue to feel shirtâ, the prediction is too precise; it predicts that next second, the shirt will produce exactly the same pattern of sensations it does now. But realistically as you move around or catch passing breezes the shirt will change ever so slightly â at which point autistic peopleâs brains will send alarms all the way up to consciousness, and theyâll perceive it as âmy shirt is annoyingâ.
Many people are familiar with Occamâs razor, the principle summarized as:
Among competing hypotheses, the one with the fewest assumptions should be selected.
Thereâs a tendency you notice all over for people to overcomplicate situations early. Before even fully understanding a problem, they often dig into their toolbox of knowledge for the most involved, and âpowerfulâ weapon in the arsenal. There must be a reason for this â perhaps the propensity to convolute problems makes people feel more comfortable with their lack of a solution? âI donât know what to do because problem X is incredibly complex.â
The post has examples from medicine, physics, crime, and more. Itâs a useful heuristic when approaching novel problems.
When you hear hoofbeats, think horses, not zebras.
But of course there are cases when oversimplification can be dangerous. Itâs crucial to put your problem into context. If the stakes are life-and-death, in-depth analyses and study are essential. As the Einstein quote goes (one of my favorites):
Everything should be made as simple as possible, but not simpler.
âMost people overestimate what they can achieve in a year and underestimate what they can achieve in ten years.â
My post from yesterday got me thinking about this piece I read recently on Farnam Street that dovetails with the thoughts on long-term benefit and the compounding nature of good habits.
The idea of âGatesâ Lawâ1 is that investments for the long-term can bear fruit sooner than you think. Why does this happen so frequently? And what does this have to do with playing the long game?
I donât mean to imply that all long-term investments (like exercise or reading) compound so quickly that youâve underestimated the results you can achieve over a shorter time period â you wonât start running and suddenly in a month have lost 60 pounds. But where Gatesâ Law is related to compounding effects of good habits is in what the gradual gains enable that you couldnât do before. In the running example, think about how shedding those first 10 pounds makes your future running that much easier2.
The article mentions the biologist Stuart Kauffman, who calls this concept âThe Adjacent Possibleâ. I love this idea:
Each new innovation adds to the number of achievable possible (future) innovations. It opens up adjacent possibilities which didnât exist before, because better tools can be used to make even better tools.
Humanity is about expanding the realm of the possible. Discovering fire meant our ancestors could use the heat to soften or harden materials and make better tools. Inventing the wheel meant the ability to move resources around, which meant new possibilities such as the construction of more advanced buildings using materials from other areas. Domesticating animals meant a way to pull wheeled vehicles with less effort, meaning heavier loads, greater distances and more advanced construction. The invention of writing led to new ways of recording, sharing and developing knowledge which could then foster further innovation. The internet continues to give us countless new opportunities for innovation. Anyone with a new idea can access endless free information, find supporters, discuss their ideas and obtain resources. New doors to the adjacent possible open every day as we find different uses for technology.
Not only is there potential for the long-term gains on your positive habits, but you can even unlock adjacent, undiscovered potential along the way.
The quote has been popularized by Bill Gates, but probably apocryphally. âŠ
As my friend Bill Dollins has said regarding losing weight and running: itâs easier if thereâs âless youâ to lug along for the ride. âŠ
I like this idea from Morgan Housel on positioning and defining levels of confidence on a scale from a low to high position of authority on a topic. Weâve all seen plenty of instances of âlevels 1 and 2â confidence out there:
Letâs call this Level One confidence. Youâre confident in something because you donât know enough to realize how little confidence you should have. Itâs driven by gut feelings and the belief that intelligence in one field justifies your expertise in another. Itâs a mess, and one few people think they fall for because beliefs exempt from the nuance of real expertise are rubber stamped in your head as unequivocally true.
A step above this, letâs call it Level Two confidence, is when youâre confident about a topic tangential to your field of expertise. Say youâre an expert at building cars. Then someone asks you whether Tesla is overvalued. Since you know a lot about building cars you feel qualified to have an opinion. But car manufacturing is one of thousands of variables that goes into valuing car companies â and the most important variable is âwhatever mood the market is in,â which isnât the kind of thing engineers steeped in precision appreciate. It takes little effort to assume your skill in one field makes you an expert in a cousin field. The danger is that first cousins can have little in common.
Itâs a helpful framework for getting outside of your own head on a subject. I find that reservation about my own confidence on topics helps strengthen it in ones where confidence is warranted â Iâm confident in my understanding because Iâve thought about it extensively. I try to stay skeptical of my own knowledge on almost all subjects, enough to be introspective about what I really know without becoming hamstrung by inaction.
This is a great episode between two guys with interesting perspectives. Parrishâs Farnam Street blog is one of my favorites out there, along with his podcast, The Knowledge Project. This conversation covers a lot on the FS âmental modelsâ series.
Found via Tom MacWright, a slick and simple tool for doing run route planning built on modern web tech. It uses basic routing APIs and distance calculation to help plan out runs, which is especially cool in new places. I used it in San Diego this past week to estimate a couple distances I did. It also has a cool sharing feature to save and link to routes.
I mentioned scientist Vannevar Bush here a few days back. This is a piece he wrote for The Atlantic in 1945, looking forward at how machines and technology could become enhancers of human thinking. So many prescient segments foreshadowing current computer technology:
One can now picture a future investigator in his laboratory. His hands are free, and he is not anchored. As he moves about and observes, he photographs and comments. Time is automatically recorded to tie the two records together. If he goes into the field, he may be connected by radio to his recorder. As he ponders over his notes in the evening, he again talks his comments into the record. His typed record, as well as his photographs, may both be in miniature, so that he projects them for examination.
I thought this was an excellent rundown of remote work, who is suited for it, how to manage it, and the psychology of this new method of teamwork.
Letâs first cover values. Remote work is founded on specific core principles that govern this distinct way of operating which tend to be organization agnostic. They are the underlying foundation which enables us to believe that this approach is indeed better, more optimal, and thus the way we should live:
Output > Input
Autonomy > Administration
Flexibility > Rigidity
These values do not just govern individuals, but also the way that companies operate and how processes are formed. And like almost anything in life, although they sound resoundingly positive, they have potential pitfalls if not administered with care.
I found nearly all of this very accurate to my perception of remote work, at least from the standpoint of someone who is not remote, but manages and works with many that are. Iâm highly supportive of hiring remote. With our team, weâve gotten better in many ways by becoming more remote. And another (perhaps counterintuitive) observation: the more remote people you hire, the better the whole company gets and managing it.
âIt may seem surprising but, in terms of digital media storage, our knowledge of language almost fits compactly on a floppy disk,â the authors wrote in the study. In this case, that would be a floppy disk that holds about 1.5 megabytes of information, or the equivalent of about a minute-long song as an Mp3 file. [3D Images: Exploring the Human Brain]
The researchers estimate that in the best-case scenario, in a single day, an adult remembers 1,000 to 2,000 bits of their native language. In the worst-case scenario, we remember around 120 bits per day.
My friend and co-worker Joe Larson has been doing some cool experiments with Blender for generating hillshades, jumping off of work from Andy Woodruff, Daniel Huffman, and Scott Reinhard. Iâve seen a few different hillshade / topo composites that look super cool.
Nassim Talebâs concept of âantifragility is a fascinating philosophical framework; one which Iâve linked to and mentioned here before. This Farnam Street post summarizes 10 thinking concepts to help orient your own life and decision making toward antifragility:
In short, stop optimizing for today or tomorrow and start playing the long game. That means being less efficient in the short term but more effective in the long term. Itâs easy to optimize for today, simply spend more money than you make or eat food thatâs food designed in a lab to make you eat more and more. But if you play the long game you stop optimizing and start thinking ahead to the second order consequences of your decisions.
Amazon is famous for its âNo PowerPointâ policy for meetings, requiring that those calling meetings for any new idea, project, or effort write a narrative document to describe the ins-and-outs of whatâs on the table for discussion. These documents get circulated to all the right people beforehand for review, so that the team can really drill in on an aligned objective for the meeting with clear data at their fingertips about the pros and cons.
This piece talks about the experience with this process first-hand from a former employee, bulleted out to help understand how it works:
Understand what you are trying to accomplish with the document (as with anything you write). For example, is this a new project that you want to undertake (product you want to build)? Is this a significant change to a planned launch date or feature set (especially of a high-visibility project)? Is this just more of a status update? Is it an answer to a specific question or request that Jeff made, or is this something that you are bringing to him? One of the hardest types of docs to write was basically a âde-commitâ document (Amazon is big on âdisagree and commit,â so if you are coming back and wanting to de-commit to something previously agreed, you really had to have your data and logic clear as to what had changed since the plan was committed.)
Iâve always admired this idea, as Iâm a firm believer that writing is one of the best thinking tools around. Human brains are terrible at holding on to lots of discrete information and webbing it all together. Building these behaviors into the organizational culture would embed critical thinking more deeply and democratically across the whole team.
The NSF StEER program has been using Fulcrum Community for a couple of years now, ever since Hurricane Harvey landed on the Texas coast, followed by Irma and Maria later that fall. Theyâve built a neat program on top of our platform that lets them respond quickly with volunteers on the ground conducting structure assessments post-disaster:
The large, geographically distributed effort required the development of unified data standards and digital workflows to enable the swift collection and curation of perishable data in DesignSafe. Auburnâs David Roueche, the teamâs Data Standards Lead, was especially enthusiastic about the teamâs customized Fulcrum mobile smartphone applications to support standardized assessments of continental U.S. and Caribbean construction typologies, as well as observations of hazard intensity and geotechnical impacts.
It worked so well that the team transitioned their efforts into a pro-bono Fulcrum Community site that supports crowdsourced damage assessments from the public at large with web-based geospatial visualization in real time. This feature enabled coordination with teams from NIST, FEMA, and ASCE/SEI. Dedicated data librarians at each regional node executed a rigorous QA/QC process on the backside of the Fulcrum database, led by Roueche.
Ever since my health issues in 2017, the value of the little things has become much more apparent. I came out of that with a renewed interest in investing in mental and physical health for the future. Reading about, thinking about, and practicing meditation have really helped to put the things that matter in perspective when I consider consciously how I spend my time. This piece is a simple reminder of the comparative value of the âlong gameâ.
In this piece analyst Horace Dediu calls AirPods Appleâs ânew iPodâ, drawing similarities to the cultural adoption patterns.
The Apple Watch is now bigger than the iPod ever was. As the most popular watch of all time, itâs clear that the watch is a new market success story. However it isnât a cultural success. It has the ability to signal its presence and to give the wearer a degree of individuality through material and band choice but it is too discreet. It conforms to norms of watch wearing and it is too easy to miss under a sleeve or in a pocket.
Not so for AirPods. These things look extremely different. Always white, always in view, pointed and sharp. You canât miss someone wearing AirPods. They practically scream their presence.
I still maintain this is their best product in years. I hope it becomes a new platform for voice interfaces, once theyâre reliable enough.
The happiness of your life depends upon the quality of your thoughts: therefore, guard accordingly, and take care that you entertain no notions unsuitable to virtue and reasonable nature.
This is an excellent archive on Farnam Street with background on 109 different mental models â first principles, Occamâs Razor, probabalistic thinking, and many more. So much great reading material here to study different modes of thinking. Like writer Shane Parrish puts it, this latticework helps you âthink betterâ:
The quality of our thinking is proportional to the models in our head and their usefulness in the situation at hand. The more models you haveâthe bigger your toolboxâthe more likely you are to have the right models to see reality. It turns out that when it comes to improving your ability to make decisions. Variety matters.
Most of us, however, are specialists. Instead of a latticework of mental models, we have a few from our discipline. Each specialist sees something different. By default, a typical Engineer will think in systems. A psychologist will think in terms of incentives. A biologist will think in terms of evolution. By putting these disciplines together in our head, we can walk around a problem in a three dimensional way. If weâre only looking at the problem one way, weâve got a blind spot. And blind spots can kill you.
A neat tool for visually browsing git commit history. Scrolling through commits does a nice animation to show you graphically whatâs changing from step to step. Hereâs an example with browserify.
Over the last week Iâve been messing around with Notion, a productivity app that seemingly can do everything â a combination personal database, word processor, spreadsheet, notes app, and todo list. Iâm trying it out for note taking and writing (mostly), but itâs got some potential to be a personal wiki, an idea which has always intrigued me but never felt worthwhile to try to set up and maintain. This site has a bunch of templates for Notion to help get started for different use cases. Just browsing it shows the diversity of things you can use it for.
I love this brief piece from Shane Parrish about the decaying respect for experience and authority on intellectual topics:
This overwhelming complexity of modern life âproduced feelings of helplessness and anger among a citizenry that knew itself increasingly to be at the mercy of smarter elites,â writes Nichols. And Hofstadter warns, âWhat used to be a jocular and usually benign ridicule of intellect and formal training has turned into a malign resentment of the intellectual in his capacity as expert. Once the intellectual was gently ridiculed because he was not needed; now he is fiercely resented because he is needed too much.â
Donât get me wrong. Reasoned skepticism and disagreement are essential to progress and democracy. The problem is that most of whatâs happening isnât reasoned skepticism. Itâs the adult equivalent of a two-year-old throwing a tantrum.
Sometimes experts are wrong and the common citizen is right, but those occasions are few and far between. Whatâs growing is our inability to distinguish between experts being wrong occasionally and experts being wrong consistently. Participants in public debate search for loopholes and exceptionsâanything that provides an excuse to disregard opinions they donât like.
This sets up binaries and polarities, demanding that things be either true or false. This eliminates nuance. The reality is that most expert opinions are true at least in part, and the real value in disagreement is not dismissing the thing entirely, but taking the time to argue the weak points to make the overall better.
Social media and the modern internet culture of âdunking onâ people through the single-sentence response that sounds good is a poison that infects a system where there could be reasoned dialogue. I believe itâs less the platform and more the cultural norms at fault for getting us to this point, where nuance is invisible and itâs all about viewing things through simplistic binary lenses. This leads to an anti-intellectualism where anyone is ready and enabled to tear down viewpoints they donât agree with (or even ones they only semi agree with), even if presented by those with orders of magnitude more knowledge and experience.
I think our coddled culture of âyouâre always rightâ and âyou can be anything you want when you grow upâ is creating an environment where itâs not only okay to have any opinion you want, but where people (from any walk) canât challenge you.
