Many coastal geographies experience interesting patterns of fog formation when hot and cold currents mix. There are more complicated ways fog forms, but essentially it is a consequence of a collision between two distinct local weather patterns.

It recently struck me that many extrovert-introvert interactions have a similar characteristic. Extroverts gain energy from social interactions. Introverts gain energy from private, secluded thinking. When the two kinds of personalities have been “charging” for a while, they are not just energized, they are also in the grips of serious momentum.

The extrovert’s momentum manifests as wanting to continue social interactions, past the “social charging” event. 

The introvert’s momentum manifests as wanting to continue to think, past the “solitude charging” event.

When the two collide in this stage, the resulting energized communication confusion is really frustrating to experience and hilarious to watch. I call it the extrovert-introvert fog.

The introvert tries to take whatever the extrovert says as more thinking raw material, but the extrovert isn’t interested in that. He or she is interested in continuing to talk, it doesn’t matter about what.

So the extrovert keeps trying to restart the conversation, skipping from topic to topic in an effort to feed the existing momentum. The introvert keeps trying to think about what was said 5 minutes ago and getting the extrovert to shut up while they process.

The interaction usually ends in disengagement with one walking away in frustration, usually the introvert. Otherwise the introvert says something like, “god, will you shut up, and let me think for a moment!” Or the extrovert says something like, “will you pay attention for a moment, you keep tuning out!?”

There is an old joke about cadets in a tank warfare training program with three sessions, on mobility, communications and firepower.

The first instructor, an engine expert, concludes his session with the declaration, “a tank that can shoot and communicate, but not move, is useless.” The next instructor, a radio expert, concludes his session with a similar line, “a tank that can shoot and move, but not communicate, is useless.”

The last instructor, a gunnery expert, finishes his session with the line, “a tank that can move and communicate, but not shoot, is basically a 50-ton portable radio.”

The lesson I draw today from the joke (which I first heard 30 years ago) is this.

Complex problems contain three sub-problems: schlep, puzzle and package.  For a tank, mobility represents the schlep sub-problem (building a vehicle for lugging a big gun around on rough terrain, using known technologies). Firepower represents the puzzle sub-problem (shooting accurately from a fast-moving, wobbling platform). Communication represents the packaging sub-problem (integrating the tank into a battle plan). It took decades to get the solution right, resulting in the modern main battle tank (MBT).

When you solve complex problems right, you are left with three corresponding intangible things of value: an asset, an insight and an aesthetic, which make the solutions both durable and generative (the solutions gradually and intelligently expand to occupy bigger problem spaces, realizing the potential of the original specific solution).

Understanding the interaction of these 3+3 input and output elements can make a big difference to how you attack complex problems. I am going to try and explain using the Iron Man movies.

Built to Last

My definition of a good solution to a complex problem is one that solves the immediate problem, is built to last and generates more potential than it uses. 

The more I think about complex problems, the more I get convinced that the built to last part is critical. Almost all failures are caused by not aiming for durability. The three parts of the definition interact. Solves the problem is what enables the solution to survive in its infancy. Creates more potential than it uses is what allows it to keep going long term, as a grown-up idea capable of earning a living indefinitely. And attacking complex problems (even if small-scale) is also important. Simple problems can be solved in less powerful ways.

The three-way breakdown of complex problems is driven by durability logic.

1. The schlep piece: the bit that takes the most dull/dangerous/dirty work, very little creativity, and a lot of energy, but leaves you with an essential strategic asset that will be useful in any solution to a broad class of problems.
2. The puzzle piece: the part that requires an insight breakthrough; the part that’s going to take some luck, a lot of intelligence and genuine creativity. This piece of the solution is more vulnerable. Others can be lucky, insightful, intelligent and creative.
3. The package piece: the bit that determines how the whole solution is put together to fit into the environment so it adds value gracefully. This is the least durable part of the solution, since the environment is not within your control and can change rapidly.

Good solutions have  three parts, an asset that is the fruit of the schlep, an insight that is at the heart of how the puzzle is solved (which, in the best cases, will apply to a bigger class of similar puzzles that can be solved with sufficient imagination), and an aesthetic that determines how the solution is put together into a package.

In the case of our opening tank example, solving the schlep problem essentially creates a modern military-industrial complex for a country. Solving the puzzle piece creates a viral, generative solution with many applications (once you know how to aim a gun from a fast-moving, wobbly platform, you can attack many similar problems, ranging from other fire control problems, to image stabilization for cameras to vibration isolation for delicate telescopes and earthquake-proofing of buildings). The package piece creates a modern military capable of (for instance) operating by the aesthetic principles of Blitzkrieg.

Let’s see how these operate together in the Iron Man movies. I am going to try and extract lessons relevant to business competition in the technology sector, but you can extract similar lessons for other relevant domains (such as military capability, social work, governance or even private domains like writing or coding). Mahan’s Sea Power and its Influence Upon History is in many ways about the idea we’re talking about, but I’ll try to cover the gist more quickly.

Business Lessons from Iron Man 

Ignoring the escapist and fantasy elements, the Iron Man movies are a great illustration of the fundamental idea here.

• The schlep was the montage-effort it took Tony Stark to build a fabrication shop in an Afghan cave (and later, a better one in his basement).
• The puzzle was the problem of miniaturizing the arc reactor to power the suit.
• The package was the idea of the suit itself.

Stark’s solutions to two complex problems (keeping shrapnel from his wounds from migrating to his heart and getting out of his kidnapped situation where he’s being forced to build weapons for terrorists) are based on a single creative insight that creates potential far beyond the immediate problem. This plays out over three movies.

Iron Man I

In this movie, once he escapes Afghanistan, Tony Stark competes against a villain who is able to imitate the package crudely without the aesthetic, using off-the-shelf assets and an unimaginative scaling (“bigger is better” substituting for a real aesthetic sense). But he lacks the solution to the puzzle. It’s almost a form of cargo-cult imitation that captures everything but the important part.

He manages to steal one of Stark’s miniature arc reactors, but under the stress of the climactic battle, his rip-off suit reveals its weaknesses against Stark’s more aesthetically coherent suit.

The movie resembles the Apple vs. Samsung story, though in a very caricatured form.

Iron Man II

In the second movie, Stark faces off against an alliance between a Russian mad scientist (Ivan Vanko) who cracks the arc-reactor miniaturization puzzle independently of Stark, and another competitor (Justin Hammer) who brings a dumb asset (money) and an unimaginative “more is better” package aesthetic to the party.

This is a more interesting contest, reminiscent of Apple versus Microsoft, but ultimately what fails Stark’s competitors is the weakness of the integration between individual puzzle solutions and the package. The result seems indiscriminate rather than eclectic and intricate. The differentiation (among the Army, Navy, Air Force and Marine variants of the Hammer-Vanko suit) looks like lazy and hasty variation driven by a land-grab on a market defined a priori, rather than uncovered via intelligent discovery.

The Russian is impatient for revenge against Stark for past wrongs done to his father, and pays for using what in startup lingo is called “other people’s money” (OPM) in order to act faster. Speed comes with a cost. Though he is able to dominate his partner and pursue his own revenge agenda, the alliance limits his creative control of the technology and forces him to scale in unimaginative ways. The  marriage of convenience unravels under the stress of serious competition.

Many acquire-to-get-in-the-game scenarios seem to play out this way.

Iron Man III

In the third movie, Stark faces off against a totally new threat: competition from a package based on a completely different puzzle. Instead of an arc reactor, his mad-scientist adversary has figured out a bio-engineering technique to turn people into superheros, if they don’t explode first.

This is a business disruption scenario.

Unlike the villains of the previous movies, this competitor is truly a match for Stark: he has a puzzle solution based on an insight, the fruits of a schlep (an elaborate organization built up over as long a period as Stark’s) and an imaginative package based on an original aesthetic (a bin-Ladenesque theater of terrorism) rather than imitation of Stark’s aesthetic or the “bigger is better” and “more is better” aesthetics on display in the first two movies.

Here, Stark wins, after his assets are seemingly destroyed, by bringing out a hidden reserve of  deep assets: an entire menagerie of drone suits controlled by him via an AI. All are based on the highly generative and continuing cascade of insights that started with the original suit. Unlike the dumb villain cohorts in the second movie, Stark’s army of suits is an intelligent and highly autonomous swarm with varied capabilities.  It is able to put immense pressure on the competitor on all fronts.

This victory can be attributed to Stark having taken on and defeated many rivals over a long period, which has allowed him to build a depth of battle-tested operational capability newcomers cannot match, even if their capabilities have equal or greater potential.

Not many businesses today demonstrate the kind of capability that Stark models in the third movie. Amazon and Google come close, but seem incomplete (note: I am comparing Stark to companies rather than individuals, because he really portrays the capabilities of an entire organization rather than an individual).

Amazon has the package aesthetic down, but not a reliable source of generativity. A consequence, I suspect, of autocratic senior management creating a disempowered rank-and-file via hard-driving pressure, which also fuels a dangerously arrogant PR posture. As I have argued elsewhere previously, this is the same flaw that many military historians see as the cause of Napoleon’s downfall.

Google has the generativity, and a relatively empowered rank-and-file, but seems to lack a strong packaging aesthetic. So fascinating point solutions like Google Glass, driverless cars, maps a generation ahead of the competition, and Hangout aren’t coming together coherently to enable a high-potential assault on the so-called “so-co-mo” (social, collaboration, mobile) market. The symphony of search and advertising that came together in a young Google does not seem to be extending its aesthetic logic into the company’s recent wars.

Elon Musk, the model for Iron Man, is an interesting question mark at the moment. It is unclear whether his spectacular initial moves (Tesla, SpaceX and his solar technology) are going to create a vast and generative empire of organically evolving potential comparable to Google or Amazon.

Like Stark, Musk used a highly constrained “Afghan Cave” breakthrough (Paypal) to bootstrap into an unconstrained creative journey that’s just starting. We’ll see the importance of an Afghan Cave chapter in a moment.

The Interplay of Asset, Aesthetic and Insight

The Iron Man example illustrates how the three elements of good solutions interact.

Assets are the most durable part of a solution. Schleps have the advantage of creating unique advantages that do not depend on ideas or intelligence in a deep way. The only way for a competitor to match the advantage of a true asset is to undertake a schlep of equal magnitude, which requires a lot of energy and time.

Insights are less durable, since others can also stumble upon them. But insights are also the generative core of deep capability, the ability of resilient roots to sprout new shoots (rather literally imagined in Iron Man 3) even after a scorched-earth attack by an adversary (insert hydra/antifragile reference here if you like, though that’s farther than we need to go). 

Companies differ in how imaginatively they are able to fill out the design space of possibilities created by a generative insight. Unimaginative companies fill out spaces in quick but dumb and homogeneous ways, with a great deal of repetition. They land-grab rather than truly occupy markets, and are easily destroyed by scorched-earth tactics.

By contrast imaginative companies generate highly varied ecosystems of interacting elements, all drawing on the same fertile and seminal insights. They civilize entire large continents in deeper ways, rather than just occupying them.

Packages are the least durable, since the environment is volatile. But they can be adapted and rebuilt surprisingly quickly if the aesthetic informing them remains alive in people’s minds, and generative insights and assets remain secure.

Bootstrapping vs. OPM

Let’s talk a little bit about Stark’s Afghan-cave experience. It sheds interesting light on the bootstrapping vs. OPM debate.

In business, there is a reason entrepreneurs prefer, as far as possible, to bootstrap rather than rely on other people’s money (OPM). Money (from investment, debt or non-core activities undertaken purely to generate cash) is a resource that speeds things up, but brings with it two contaminants:

1. Other people’s motivations for solving different, unrelated problems (usually the problem of generating specific returns over specific time-scales)
2. Tempting “assets” cannibalized from solutions to other problems that look “synergistic” but contain alien DNA.

What happens when you contaminate a good solution to a complex problem with other problems and solutions?

• Assets start to depreciate, due to loss of strong compounding effects from focus (solutions to various sub-problems not feeding off each other)
  
• Insights lose their potency, from being pointed in a less fertile direction, lowering generativity (alien DNA diminishing fertility or even rendering an insight-cascade sterile)
• Aesthetics decohere, leaking conceptual integrity and creating brittleness in packages (creating vulnerabilities outside-in, first in brands, then in products, creating openings for competitors to make inroads)

All three are forms of entropy that waste potential, which could have been realized more creatively in a bootstrapped story.

I am not being a bootstrapping vs. OPM ideologue, but I tend to view uncritical acceptance of OPM as responsible for killing the unused potential of creative solutions to important problems. In other words, OPM carelessly taken kills golden geese.

So the key to a successful OPM/bootstrap decision is to recognize why you are accepting contamination and how much you are really paying for it. Interest rates on debt, equity dilution from investment, and switching costs incurred from non-core activities are incomplete measures of the cost. The biggest cost is via intangible losses to assets, insights and aesthetics in the core.

Some good reasons to accept OPM anyway are:

• There is a strong window-of-opportunity constraint that forces you to operate at a certain minimum tempo
• There are forces in the picture that can destroy your limited capabilities with brute force while your roots are not deep enough
• There is a realistic expectation that there will be time later to “do it right” (pay off the “technical debt” of being forced to do it wrong initially)

Stark’s original Afghan-cave version of the suit actually displays sound handling of all three issues.

• He is working with cannibalized assets (parts of a missile system built by his company) and OPM (the terrorists money).
• He has limited time to manufacture an exit. He is facing an adversary willing and able to simply kill him if he interferes with their agenda.
• He has a realistic expectation that once he escapes, he’ll be able to “do it right” and pay off the technical debt incurred in the first suit (which is not a prototype; it is a deployed solution to the escape problem). When he escapes, he retains the generative core of insight (the arc-reactor in his chest, the core IP retained as a trade secret rather than patents).

It is interesting to note that even in his high-stress situation, Stark does not succumb to the temptation to simply put together a simpler escape plan (which a genius like him certainly could have figured out).

That would have been what is known as a “point solution” in engineering, or almost equivalently, “feature, not product” in the startup world. The sort of limited, prematurely optimized solution to the simplest framing of the immediate problem. One that a short-term thinker (or equivalently, somebody with a low threshold for aesthetic pain) might put together. Solves the problem, but does not create the potential.

The only case where this might be a good idea is when you have no interest in realizing larger amounts of potential, have occupied a naturally protected niche that others will likely not want to invade, and want to retire early.

But Stark is the unleash-big-potential type. So he puts together a creative solution with a lot of long-term potential, despite the short-term pressures.

By analogy, quarterly earnings pressures are sort of like terrorist guns trained on CEO heads by Wall Street.  Relentless pressure from the dumbest kind of OPM available, driven by implacable short-term pressures and zero tolerance for bad short-term aesthetics (as in, temporarily non-pretty balance sheets).

Taking a company private is like escaping from terrorists in some ways.

Interestingly enough, the villain of the first movie copies the first suit rather than the “done right” one (which he can’t get at), and chooses to run with the expedient design towards bigger problems, without paying off the technical debt latent in it.

Iron Man vs. Platform-Product

I prefer the Iron Man framework (if you want an acronym, call it SAPIPA: schlep-asset-puzzle-insight-package-aesthetic) framework to the more usual way of thinking about solutions to complex problems: the platform-product model.

If you’re not familiar with it, the platform-centric model approaches complex problems as follows:

1. You either solve a “first instance” problem in a design space (depth first) or develop a generically-capable “platform”, (breadth-first) depending on conditions. Both rely on an a priori mapping of an opportunity space. The latter requires a bigger capital stash. 
2. If you started with a “platform” you look for a “killer app” to realize its potential. This is a high-risk/high capital approach, but is sometimes justified.
3. If you started with a “first instance” (better) you try to generalize the solution via a “bowling pin” strategy (applying it to a succession of similar problems until general principles emerge, and then trying to build out the “platform” under a collection of live point-solutions). This has a different risk profile — execution entropy and VUCA (volatility, uncertainty, complexity, ambiguity) getting in the way of your ever building a general solution. This is especially risky if your first few “bowling pins” were meant to be loss-leaders, with profitability dependent on your eventually building a lower-cost platform under them. When you fail in such a case, you bleed to death as you grow.

There’s more to it, but that’s the thumbnail sketch.

The problem with the platform-product approach is that it is all schlep (instead of a strategic “subset schlep”), with no puzzle or aesthetic components. So while it can work, the solution lacks durability and reserves of potential that can slowly be drawn upon to imaginatively fill out an entire design space, gradually transforming potential into deep operational capability.

What’s more, the platform-product mindset, by relying on an a priori mapping, loses the potential for discovery latent in a more generative approach.  This manifests in a sharp distinction between “fit” and “scale” phases. Finding “product market fit” in lean startup lingo, is the intelligent, ready-fire-steer phase. Scaling is where you use OPM to grow as fast as you can to execute a big land grab. In fact, in today’s venture capital industry, investors openly agree that almost all the money, outside of a small “seed” bucket, is “growth capital” earmarked for use after a clear “product-market-fit” moment.

With the Iron Man approach, there is no a priori map. There is no sharp fit-t0-scale transition. Instead, by prioritizing survivability, you buy the ability to grow at whatever natural pace is needed, with low reliance on sharp transitions, and freedom from artificial pressures. So you have the following pattern:

• Raw-schlep assets gradually get locked down with increasing security
• Generative insights are unleashed and operate at an accelerating pace, creating a cascade of fractal SPP/AIA structures
• Packaging aesthetics are driven towards continuous refinement, you get increasing, eventually overwhelming dominance.

It’s what I’ve called exponential breakthrough in the past. It’s the difference between growing an intelligent entity that grows smarter as it scales, versus spreading a small initial amount of intelligence thinner and thinner.

But then, our technology leaders are mostly human. Not superheros.  That is why our corporations are mostly linear, rather than superlinear.

But we seem to be getting tantalizingly close.

Greg is a 2013 blogging resident, visiting us from his home blog over at On the Spiral. His residency will explore the theme “Individuality and Decision-Making” over several posts.

I think I have finally sorted out my uneasiness with the so-called deliberate practice hypothesis.  Most Tempo readers will be familiar with deliberate practice (here, here, here & here) so I will just offer a quick refresher.  The idea is that abilities that what we commonly perceive as talent are actually the result of painstakingly focused training.  Anders Ericsson, whose research has provided much of the grist for the mill, summarizes deliberate practice as:

activities designed, typically by a teacher, for the sole purpose of effectively improving specific aspects of an individual’s performance.

I am not the only person to express mixed feelings about the concept.  Others have noted that deliberate practice addresses the known better than the unknown, i.e. it applies to domains requiring mastery better than those requiring creativity.

But what is the alternative?  Without an alternative, criticism carries the scent of sour grapes.

The advocates of deliberate practice generally juxtapose it with either a) belief in the value of innate talent or b) more mundane varieties of accrued experience.  Their claim is that practice counts for more than natural talent, and in order to reach the highest levels of mastery that practice must take a specific form.

My objection to this framing, I realize now, is that deliberate practice is presented as the methodology that is active and therefore earned, while innate talent and non-deliberate(?) practice are portrayed as passive and unearned.  Though never explicitly stated, the normative implications are only thinly veiled in much of the non-academic cheerleading on the subject.   

I think it is a mistake to believe that learning must be deliberate in order to be active or earned.  There is an another alternative that is equally active and equally intentional but not deliberate.  That alternative is immersion.  I mean immersion in the same way it is applied to learning a foreign language…the practice of actively placing yourself in an unfamiliar environment and exposing yourself to novel stimuli.

***

The distinction occurred to me while mulling over a cultural divide that I observe frequently in the crossfit community.  For those who don’t know, crossfit is an exercise regimen that is described as: constantly varied, high-intensity, functional movement.

The high intensity part refers to the fact that most workouts involve a component that is timed, in which the athlete either a) attempts complete a prescribed sequence of exercises as quickly as possible, or b) attempts to complete as many repetition as possible in a prescribed time.

Constantly varied means that workouts are not programmed according to a formula.  Exercises appear unpredictably from day to day, in many different formats and in many different combinations.

The emphasis on functional movement means that these timed workouts frequently include movements like the olympic lifts (the snatch and the clean & jerk), complex gymnastics movements and various other exercises requiring total body coordination.   For example my workout today involves the following:

• Perform 3 rounds of the following sequence as quickly as possible:
  • 3 rope climbs
  • 10 power snatch at 135#
  • 15 ring dips
• Score equals total time to completion

The olympic lifts in particular are immensely technical.  The athletes you see in the olympics dedicate their lives to perfecting the nuances of just these two movements.  Here are a couple quick videos of what I believe are the current world record lifts:

Athletes and coaches who focus exclusively on olympic lifting often criticize crossfit.  They assert that performing such complex movements under stress (at high repetitions and under time pressure) promotes bad form, cultivates flawed movement patterns, and invites injury.  They tend to be particularly critical of the practice of exposing beginners to these risks, and often argue that once bad habits are established they are nearly impossible to eliminate.

On first impression the division looks a lot like a case of insiders vs outsider.  At one point in time, when crossfit was first arriving on the scene, that was probably the best way to describe it.  However, today that is much less the case as there is significant cross-pollination between the two camps.

The tensions that persist could be better characterized as being between the immersion camp and the deliberate-practice camp.  To avoid confusion – because they don’t use that terminology – I’ll refer to them as the new school and the old school.

The new school types throw people into the fire.  They will always scale back the workout to the capabilities of the individual, but they won’t scale back the intensity.  Even if you are lifting an empty bar and doing push-ups from your knees, the expectation is always that you push yourself as hard as you can.  The implied belief is that people are capable of listening to their own bodies, and that movement patterns are accessible and can be reformed on the fly.

The old school types believe in getting it right the first time.  They believe in learning through carefully controlled repetition, starting with simple building blocks and working up to more complex movements.  They believe that bad movement patterns are difficult to deconstruct and limit long run potential.  And they believe that premature immersion is dangerous, even sometimes negligent.

Old School Cultures and New School Cultures

The differences between the two schools of thought go beyond personal preference.  Over the past 3+ years I have been a full time member at four different crossfit gyms.  During that time I have noticed consistent differences in the way that individuals understand physical movement.

The new school types experience muscle memory as accessible and malleable.  They pay more attention to proprioception and seem to intuitively know what is going on with their bodies.  They know when to push harder and when their bodies need rest.  They recognize when their body is moving properly and when something is wrong.  And they are constantly experimenting and speculating about what works (for their own unique body) and what doesn’t.

Old school types seem to have less access to proprioception.  They experience movement patterns as inaccessible.  They tend to focus less  on their own intrinsic qualities and more on their results.  They are the people who value willpower and discipline, who enjoy grinding…pushing through the pain regardless of how they feel.  And they tend to be the people who stick to a consistent program, motivated by achieving predetermined goals.

In short, old school types are more deliberate while new school types are more immersed.  I have come to believe that these attitudes reflect stable aspects of personality….that the two groups differ in their actual subjective experience of physical exercise.

Similar themes can be seen in the style of coaching offered at the old school gyms vs new school gyms.  New schools coaches tend to be much better at breaking down movements, explaining their nuances and adapting their expectations to the individual.  Old school coaches tend to take a harder line, interpreting expectations and standards more literally.  The former tend to promote a more collegial atmosphere where members are constantly coaching each other, while the latter emphasize rules and promote an atmosphere of deference to the coaches and/or the program.

You can tell a lot about the culture of a crossfit gym from the type of conversation that goes on before and after a workout…

At some gyms it is all about performance:

• what time you expect to get
• what time you got last time you did this workout
• what your goals are
• what competition you are training for

At other gyms the conversation is full of speculative expectations:

• what parts of the workout you are dreading most/least,
• what parts of you body are particularly sore or rested
• what tentative strategy are you taking into the workout
  • breaking up reps
  • where you expect to push vs where you will need to rest
  • which pairings of exercises may present unusual challenges

For the former group the post workout conversation often revolves around success or failure, elation or disappoint.  They are excited when they achieve their goals.

For the latter group the post workout conversation consists of comparing expectations to actual experience.  In short, the members of the latter group build up propositional mental models before the workout, and afterwards they compare those propositional models to their experienced reality.  They are most excited when they encounter a curve-ball that suggests ways they might improve those models.

Performance vs Meta-learning

One way of understanding these two attitudes – which nicely parallels the fox and hedgehog archetypes - is that deliberate practice is a performance/learning process whereas immersion is a learning/meta-learning process.

Along the same lines we might say that deliberate practice emphasizes externalization (output) while immersion emphasizes internalization (input).

In other words, immersion exposes you to the complexity of the environment all at once.  When you immerse yourself in a foreign language the active emphasis is on internalizing and decoding as much of the language as you can, in all its subtlety and nuance.  It is largely taken for granted that if you understand the language then you will also speak intelligibly.

By contrast, mastery of a musical instrument or a competitive activity like chess is all about mastering externalized behavior.  Through practice you will eventually intuit some of the principles underlying your practice, but understanding the theory alone doesn’t do you much good if it gets in the way of the performance.

This is why domains biased towards deliberate practice tend to be so concerned with eliminating bad habits.  The emphasis on performance deprives students of the meta-learnings that would otherwise allow them to actively deconstruct bad habits.  Immersion inevitably leads to bad habits, but it also fosters accessible meta-learnings that allow those bad habits to be deconstructed.

Manipulative vs Appreciative

It should be self-evident that deliberate practice primarily shapes manipulative mental models, given that it directly addresses the mental faculties underlying specific instrumental behaviors.  Immersion primarily develops appreciative mental models.  In describing appreciative models Venkat writes:

My instinctive preference for complexity made sense from the perspective of purpose. I like purposeless models. Or equivalently, models that exist before clear purposes do. It makes sense that such models are often more complex. It isn’t that I like complexity for its own sake, but that I like purposeless models, which are often complex. They help me appreciate something on its own terms, rather than through the lens of something I want to achieve.

This non-purpose (or universal purpose or meta-purpose) is appreciation. An appreciative model is a model you use simply to make sense of a situation.

I like the idea of appreciative models having a meta-purpose.  Immersive practices construe goals at a high level.  This is quite different from having no purpose at all, though in our left-brained culture it is easy to mistake meta-purpose for lack of purpose.

One of catchphrases used to describe crossfit training is general physical preparedness (GPP).  GPP is the antithesis of sport specific training methodologies, which bring instrumental faculties to the foreground.  The notion of “general preparedness” complements Venkat’s idea that the meta-purpose of an appreciative models is to “make sense of a situation”.

Manipulative models may be more efficient when you have the ability to initiate instrumental behaviors on your own terms, but they are not so useful when you need to respond to the environment.  If you need to be prepared for whatever challenges the environment might present, then you need an appreciative model.

If immersion appears passive it is only because the stimuli originate in the environment.  However, the act of immersing oneself in a novel environment is no less intentional than the act of breaking out a chess board.  Adaptation occurs just the same whether it is stimulated directly by practice itself or indirectly by opening oneself to a particular stream of stimuli.  And the depth of immersion can be modulated just as one would the volume of deliberate practice.

Contextual vs Context-Free

Deliberate practice techniques are designed in a certain sense to be inaccessible.  You learn it right the first time through simple repetition.  There is an emphasis on consistency.  Beginners learn piece by piece, mastering one aspect of a movement before moving on.  The old-school culture described above has a distinct “just do it” quality to it.

In physical training all of this serves to bypass conscious thought processes and push the movement pattern directly into muscle memory.  What is true of habits is also true of performance – you are at your best when you are in the zone, just acting…without thinking too much about exactly what you are doing.

So where does that leave the conscious mind?

Venkat recently wrote about two classes of habits:

…every habit is actually two intertwined habits. There is a habit of thought and a coupled habit of action.

• A habit of thought is a set of coupled patterns of thought and a practiced ability to switch among them appropriately and effectively.
• A habit of action is a learned pattern of physical behavior involving sensory processing and physical movements.

Both are context-dependent. The former is dependent on your immediate state of mind, the latter is dependent on your immediate environment.

By minimizing the amount of input material provided to the conscious mind, the old school practices produce habits of action that are pure muscle memory.

This leaves the conscious mind free to construct habits of mind intended to insulate the performer from the external context.  In the extreme, when athletes enter the zone they report that the outside world fades away and they experience a kind of tunnel vision.  In courting this state many athletes construct habit of mind that take the form of superstitions, visualization routines, affirmations, and various other ritualized preparations.  All are practices meant to promote high fidelity performance without regard to the particular context.

Immersion accomplishes the opposite.  The conscious mind actively engages in the process of distinguishing signal from the noise.  The appreciative mental models that are constructed map correspondences between the external environment and learned habits.  The primary concern is for appropriateness of behavior in context rather than reproduction of practiced behavior with perfect fidelity.

Nesting the Two Approaches

Though the deliberate practice hypothesis doesn’t get my blood stirring on its own, understanding it as  counterpoint to immersion helps me understand how it can be adopted judiciously without stripping all the joy out of learning.

For me, immersion is clearly the more productive approach, but it is possible to nest deliberate practice within a broader immersion framework.  The choice then is one of priority…of which approach leads and which follows.

I may prefer learning a foreign language through immersion, but losing my accent would likely require some focused attention.  Similarly, I enjoy crossfit style training precisely because it is open-ended, appreciative and contextualized, but that doesn’t mean I neglect more deliberate training methodologies when specific skills are in need of refinement.

Emphasizing immersion to the exclusion of deliberate practice seems to produce rapid progress followed by diminishing returns.  Incorporating some elements of deliberate practice allows these obstacles to be overcome.  And when adopted within the context of an immersion based practice, these elements of deliberate practice seem less onerous.

It would seem the inverse arrangement is equally viable.  I have noted recently that Cal Newport – one of the staunchest advocates of deliberate practice – has been hesitantly incorporating more immersive practices into his productivity advice.  I’m sure he would insist that he isn’t abandoning deliberate practice, but then that just demonstrates the point that an approach dominated by deliberate practice can safely incorporate elements of immersion without being corrupted.

I have struggled with paperwork all my life, to the point that I sometimes joke that it is my kryptonite.  A paperwork attack can reduce me from feeling superhuman to subhuman. Especially vicious Catch-22 types of paperwork. My life exhibits a sensitive dependence on paperwork conditions. When pending paperwork levels are high, I am nearly useless to everybody and not exactly in love with my own life either. When pending paperwork levels are low, I can move mountains.

In an extreme example, I was recently locked out of my bank account and to unlock it, besides the usual identity questions, my bank came up with the brilliant scheme of asking for a detail about a recent deposit for additional security. Thanks to paperless statements, I couldn’t supply the detail. Genius, right? You need to get into the account in order to find the information that would allow you to unlock it.

Eventually, we figured something out. We are finally at the baroque stage of industrial civilization with paperwork as strange loop.

In general, things aren’t quite so bad.  But having had to deal with more than my fair share of the universe’s paperwork in the last few months, I’ve come to some conclusions about why I am particularly oversensitive to the stuff (and why you might be too), and how to cope.

Sensitivity to Paperwork

I think I understand what determines sensitivity to paperwork: degree of introversion and intuitiveness in thinking style. So basically, I suspect INxx types in the Myers-Briggs scheme are likely to be more sensitive than other types.

Here’s why, introverts gain energy from things they do alone. While paperwork is usually done alone, if you get anything wrong, or if there is a glitch in the processing, you have to deal with strangers via a feedback loop of phone and email.  The probability of something going wrong with a piece of paperwork is proportional to the degree of arbitrariness and newness in the form, and the fussiness/brittleness of the processing system. So just being faced with a bit of paperwork usually triggers anxieties proportionate to the expected amount of draining interpersonal interactions in the future. These expectations are often overblown/worst-case unless you’ve dealt with failures in that process before and have some calibration.

That would be bad enough, but the other key feature of paperwork is that it is heavy on arbitrary information: specific names, dates, places, numbers and codes. It is usually very sensitive to small errors, and very unforgiving to missing bits and pieces.

That sort of thinking is great for strongly sensory types who love dealing with concrete, embodied things and dislike abstractions. But if you’re the Myers-Briggs intuitive type, paperwork targets your weakness.

An aside: bureaucracies that exist as networks of small local offices with some autonomy for last-mile service providers to adapt to local variability, are generally more forgiving and less sensitive than ones that exist as a combination of online/mail/phone interfaces and distant shared service centers where mysterious processes happen. So any visionary reformists reading this: if you want to serve individual humans rather than large corporate or government agency interests, invest in a network of branch offices. There are always ways to do this without hurting profits, so the only real reason to not do this is regulatory capture by larger/more powerful customers.

The other two variables, T vs. F and P vs. J, don’t have as much of an impact I think. T’s are probably frustrated by paperwork whose logic is obscure, and F’s are probably have a stronger anxiety response. J’s probably try to get paperwork done and out of the way as soon as possible, while P’s probably procrastinate more, but both are likely to be frustrated by having to do it.

It would be fun to characterize each of the 16 types more individually in terms of all the possible interactions among traits, to yield a unique relationship with paperwork.

Coping with Paperwork

For me, I’ve found that the following coping methods help:

1. Bite off one piece at a time. There is a tendency to just let paperwork accumulate till it becomes an impossible drag on your thinking, and then clear it all at once, to enjoy a few days respite before it starts to pile up again. It is better to train yourself to operate under conditions of constant slight friction than bipolar craziness between superfluidity and high-viscosity sludge living.
2. Don’t try to eliminate mistakes: Mistakes are costly in terms of lost future time and social iterations, but there’s a point at which fear of mistakes is worse than the cost of future damage control.  You can get so obsessive-compulsive about getting it exactly right the first time just to avoid follow-on iterations, that it can distort all sense of proportion. If a form is returned because you forgot to date it, so be it.
3. Accept Minor Criminality: Bureaucracies deal with us in ways that don’t distinguish between small civic transgressions and not being in compliance, such as an expired business license, and criminal offenses ranging from speeding to murder. So it helps to accept that unless you’re dead (and sometimes even then), chances are you are not 100% in compliance of everything expected of you, simply because 100% compliance is cripplingly costly. Learn to be happy with 90% or so (I know many people who are at around 20-30%).

There are probably other tricks that people more comfortable with paperwork know about.

Sometimes, doing the right thing is just way too hard. So you have use the best approximate substitute available. When you can’t fly like a bird, you can aspire to be a frog that can jump really high, or a flying squirrel.

Decision-making is like that. There is, in my opinion, a “right way” to do decision-making in complex, dynamic environments (VUCA conditions — Volatility, Uncertainty, Complexity, Ambiguity), but most of the time, the right way is way too hard. So like most people, I use approximations tailored to current conditions (I am partial to the geeky joke that life isn’t just hard, it’s NP-hard).

To explain the right way and the approximate way, it helps to think in terms of high-speed maneuvering as a metaphor. Think of the dog-fighting in-an-asteroid-field scene in Star Wars.  There are unpredictable moving obstacles and adversaries in the environment, and potential/kinetic energy considerations arising from the physics and energy levels of your own vehicle.

The “right” way to engage such a domain is with high situation awareness and calm mindfulness. Such a mental state allows you to maneuver smoothly and efficiently, with surgically precise moves that minimize entropy generation while achieving your objectives. This is the peak-flow-state, with your OODA-loop humming away at Enlightenment Level 42.

Unfortunately, if you’re like me, you’re in that state perhaps 1% of the time. What do you do at other times?

OODA for Zombies

The rest of the time, there is a good chance you are an over-caffeinated, under-exercised, manic-depressive, financially precarious, junk-food-eating zombie. And even if you’re not a total train-wreck, you may have over-reached so far beyond your capabilities that you might as well be.

It’s nice to have the meta-goal of increasing your peak-flow-state periods, and we’ve talked about that a few times, but  truth be told, it’s nice to have a crutch to get you through zombie periods.

Once such crutch is replacing the satisfying full-blown dogfight-in-an-asteroid-field metaphor with a simpler and less satisfying one: an auto racing metaphor that is locally and approximately correct a lot of the time.

The racing metaphor is simpler because it involves no moving dumb obstacles like asteroids, adversaries who maneuver in simplified ways, a constrained competition model, and a playing field that’s a closed circuit with a simple geometry.

The best-known use of the racing metaphor is the heuristic, overtake on the turns. 

The reasoning behind this heuristic is that a turn, where potential and kinetic energy must be traded off in controlled ways to reorient a vehicle, is where skill and higher situation awareness can beat raw power. When power is roughly equal between competitors, skill differences at the turn are the only thing that can change the leader board.

A closed-circuit race decouples agility-first and energy-first epochs. If the course is simple but very long, you can even map planning/execution to turns and straights.

The Turn and the Straight

But I don’t hear much about the obvious companion heuristic (I had to make up a mnemonic phrase): overwhelm on the straight. 

If you have a true power advantage, you have to use the relatively straight portions of the course to pull away from the rest of the field.

And you have to overwhelm, which means using your power advantage to really put a lot of distance between you and competitors. It is not enough to get just a little ahead.  You have to get as far ahead as you can.

Why? Because under zombie, non-peak-flow operating conditions, a trade-off holds between power on the straight and agility in the turn. You are unlikely to be good at both.

To take a simple example, imagine that you’re racing with just one other adversary on a rounded-corner rectangular circuit. You gain 6 meters per straight due to greater power, and lose 5 meters per turn on every turn due to poorer turning skills. So your net advantage isn’t 24 meters/lap. It is 4 meters per lap, and you have to go all out to get it.

You cannot be lazy or hold back. Depending on your overall power reserves for the race, however, you can and should cleverly time when you choose to go full throttle.

The key to the timing there is the length of the race.

Short versus Long Races

The shorter the race, the greater the advantage for the competitor with better turn performance.

What’s more, when you’re neck-to-neck, the more agile competitor has an even higher advantage, because the more powerful adversary is likely even worse on a neck-to-neck turn than a solo turn. So the agile adversary will likely gain more per turn when the gap is smaller.

On the other hand, long races favor the more powerful players (so long as they stay focused on the race and don’t get distracted).

There are two reason for this. The first is decision fatigue.

Navigating a turn smoothly drains the executive function because it is more demanding. By contrast, powering through a straight requires far less executive function control. It is more a function of raw energy levels.

This means, the advantage of an agile adversary is going to slowly decay through multiple turns, as he/she gets mentally fatigued.

The second reason is local learning.

Situational learning is easier and cheaper than generalized learning.  An agile competitor has a starting advantage based on generally superior turning skills that are most potent when the course is equally unknown to all. But on a specific simple course, such as our simple rounded rectangle, a power-competitor can quickly and cheaply learn the local turns and neutralize the advantage of the generally agile competitor.

Fast-Following as Co-Opted Agility

When the turns are a repeating pattern of the same four turns, rather than a sequence of unexpected turns, generalized agility quickly becomes useless. It is equivalent to a starting position advantage on a completely straight and long course: a finite advantage that just delays the inevitable against a more energetic racer.

This means the longer the race, the more you can rely on greater power. In our simple example, assume that the more powerful competitor always gains 6 meters per lap. But if the turn performance advantage of the agile adversary erodes to nothing after  (say) 100 turns (25 laps), the race turns into a pure straight race with a 24 meters/lap advantage instead of a 4 meters/lap advantage.

Once you’ve fatigued the executive function of an adversary, and done your local learning, you can pull away steadily. In fact with a limited overall energy budget, it might be useful to stay slightly behind initially, as a racing strategy, making the turn-advantage competitor work harder for their turn gains, fatiguing their executive function more quickly while learning faster yourself.

So the presence of a more generally agile competitor means you can learn a localized (and therefore cheaper) version of their applied generalized tricks via imitation.

Once you’ve exhausted them, you can start developing your straight advantage and pull away. This strategy works even better if the adversary also has a lower total energy store. You simply wait for physical or mental exhaustion (whichever happens first) before you get started, just keeping up until then.

They waste their limited energy learning, you imitate and save your greater energy reserves for scaling and winning.

Many fast followers (such as Microsoft) seem to operate this way, effectively co-opting more agile competitors as unwitting scouts. This is the reason imitation is so much more successful than innovation, in terms of returns.

Exponential Breakaway

The racing metaphor actually understates the advantage of being a power player, because in many real-world situations, gains compound rather than accumulating linearly.

Imagine a weird sort of race where the more you are ahead, the more you can pull ahead. So instead of always gaining 6 meters/straight, you gain 6 meters/straight if you are 1 meter ahead, 12 meters/straight if you are 2 meters ahead, 24 meters/straight when you are 3 meters ahead.

You get the idea. You can really overwhelm on the straight in long races, and the longer the race, the more you become impossible to catch. It can be a crippling demotivator to watch an exponential breakaway from behind.

I’ve struggled to articulate this in previous posts, but I think I finally understand the phenomenon correctly. You can check out my old post on the subject if you want a more complete (if more confused) deep dive.

I am interested though, in whether there can be a similar advantage for the agile under sustained VUCA conditions.

Exponential Turnaway

Let’s call the corresponding idea of a runaway agility advantage an exponential turnaway. 

I don’t think such an advantage can exist in a simple situation like racing on a known closed course.

But when we return to the full-blown metaphor of dogfighting in an asteroid field, it may be possible.

Here, exponential turnaway may not depend on compounding gains for the more agile competitor, but compounding losses for the less agile one.

Military strategists often talk about the idea of a “target-rich environment.” An asteroid field is sort of the flip-side of that idea: a “projectile rich environment” that disproportionately penalizes bigger players (size is generally correlated with power and lower agility).

Instead of a known sequence of turns coming up with known periodicity, the non-agile player faces an unpredictable environment of unknown maneuvering challenges.

From the point of view of how quickly decision fatigue sets in, I suspect, the less agile competitor will quickly get overwhelmed, with compounding errors, bad decisions leading to worse situations, and eventually, an impossible-problem situation.

Of course, the more agile competitor is also experiencing decision fatigue, but he/she doesn’t have to survive forever in the asteroid field. Just long enough for the competitor to crash and burn. At that point, he/she can exit the asteroid field, and recover in relative peace.

Exponential turnaway can particularly affect big companies that try to “fast follow” an entire swarm of little startups into a new market, instead of just a single agile scout.  The leader emerges via a shakeout in the swarm rather than a powerful incumbent fast-following an initial leader. Neither Microsoft nor Google won the social network game. Facebook and LinkedIn did, via a shakeout in an initial field of many players (so it is inaccurate to say that Facebook was a “fast follower” to MySpace. It wasn’t. The sector wasn’t really viable at that point in the game, and Facebook did not really win by imitating MySpace the way Internet Explorer imitated Netscape).

In such a situation, even acquisition may be an impossible strategy. By the time a clear leader emerges via a shakeout, it may be too big for a wannabe “fast follower” to swallow. This is why, despite the generally greater returns for imitation over innovation, the innovation game is still worth playing, at least for the rare shakeout winner.

If you are a pioneering startup afraid of a big company fast-following you into markets you created, it might actually help you to help out other related startups a bit. They will tweak your formula and pursue it slightly differently, creating a shakeout game rather than a fast-follower game.

This is not about socialist cooperation, it is about creating VUCA for a more powerful adversary.

There is a Hunger Games joke in there somewhere (I just watched the first movie yesterday).

Startup Maneuvering

The Lean Startup types among you will have noticed some obvious connections to those ideas. In fact, this post partly grew out of my efforts to try and figure out what bothered me about the model.

It is by now widely recognized that the Lean Startup model can, in many ways, be regarded as an approximate version of the OODA loop.  But the precise nature of the approximation involved has been eluding me.

The symptom of the simplification is that the Lean Startup replaces the core “get inside the tempo of your adversary” competition model of OODA with a “faster iteration” competition model.

Here “adversary” can stand for either a literal competitor, or a responsive market (i.e., an asteroid field that responds to your actions, such as customers with some control of their own decisions and learnable reactions to your moves).

I spent some time thinking about conditions under which the simplification is valid, and the best I’ve been able to come up with is this: “faster iteration” is a valid substitute for “inside the tempo” when for some reason, the learning per iteration has a fundamental rate limit.

What do I mean by this? Imagine a dumb startup and a smart startup trying the same first A/B test on identical minimum viable products (MVP). Both get the same results, but the latter learns a lot more, by extracting more intelligence, and is able to pick a second experiment (or pick a pivot direction) much better.

Under these conditions, iteration speed is not very relevant. By simply extracting more intelligence per iteration and pivoting smarter, the smart startup can gain on the dumb startup even if they are iterating slower. In optimization terms, the smart startup will be extracting the signal and climbing the right hill. The dumb startup will be thrashing around in response to the noise and failing to see the hill.

But if for some reason, the amount of net learning per iteration is rate-limited, an inefficient learner iterating faster can pull ahead.

Near-Random Domains

This corresponds to conditions where there is almost no scope for generalization either for future decisions in the same local domain, or other similar domains. Or to use a generalized form of our race metaphor, everybody is equally bad at the turns, so the race goes to the better straight performer by default, no matter how short the straights or how long the race.

This is a world where agility is meaningless. There is no such “skill” in the picture.  You have a pure straight race where everybody gets knocked down in a completely unpredictable way by nature every few dozen steps. So it all depends on getting back up faster and running as hard as you can till you are knocked down again.

So a lean startup mindset is good if your learning resembles memorizing the digits of a random number, with one digit per iteration. Being smarter doesn’t really help. Being faster does. Every bit learned is expensively bought via a knockdown.

So it is not surprising that the lean startup is most popular in a domain that is effectively close to random user behavior around Web technologies.

Any truly generalizable insight spreads quickly via imitation, since UX design IP is hard to protect. What remains is the random-bits bleeding edge of highly localized user behavior learning (localized down to the single click in a single fixed context, with an additional advantage for enterprise software, which is more localized than the consumer world).  The faster you can accumulate these results, the faster you can move (a good sign is that people aren’t particularly good at predicting the results of non-trivial A/B tests).

A clear illustration of this principle is this well-known factoid about memory: chess grandmasters are no better than random people off the street when it comes to memorizing random board positions. But when the board positions are realistic and legal, they do far better.

For a startup, near-random domains make the lean model useful, especially for enterprise software where there is a lot of corporate arbitrariness to be learned for every individual customer. For big consumer web companies, this translates to massive amounts of continuous, almost automated testing.

But when there is more general domain structure, it pays to give up some iteration speed for smarter learning: going for the “inside the tempo” approach.

So paradoxically, if you think you have an agility advantage, it pays to not be at the bleeding edge where all learning is almost random. It pays to withdraw to a less random domain where your superior generalization skills are an advantage.

I am still not completely satisfied with this model, but it’s getting there. I’ve been working on these ideas for almost two years now, and they are finally getting precise enough that I could mathematically model them if I wanted to (starting with this metaphor of a race-to-asteroid-belt spectrum, and generalizing to exponential breakaway/turnaway type domains).

For now, what I’ve arrived at is a set of basic rules for playing the meta-game.

Recognizing, Picking and Creating Games

In business and life, the game you pick or define is far more important than how you compete within the game. If you are a power player, you need to pick a simpler game that is mostly straights. If you’re competing with an agile player, try to draw him/her “out into the open.” If you’re an agile player, try and draw the power competitors into an asteroid field. Guerrillas retreat into the hills. Dictators try to flush them out into the open. It’s an age-old game.

There are at least four levels of the meta-game here.

1. Recognizing: As a beginner, you must first learn to figure out what sort of game you are in: racing circuit, asteroid field, or true-random. Pursuing a racing strategy in an asteroid field, or vice-versa, is dumb. Trying to be meaningfully “agile” in learning a random number is beyond dumb. You must also figure out which of the games suits you best.
2. Picking: As an intermediate player, you must learn to pick your game. If you have an agility advantage, find a more complex game — an asteroid field. If you have a power advantage, find a simpler game (a race circuit), or a truly random game, which is simple in its own way (note to computational complexity geeks: there is a potential phase-transition diagram here with agility in the middle, I’ll leave you to sketch it out yourself).
3. Creating for yourself: As an advanced player, you have to learn how to create a game that suits your strengths. If you’re a power player, you must learn how to simplify the game through meta moves. If your huge starship is being drawn into an asteroid field by a maneuvering rebel fighter, use big-bang type weapons to pulverize the field. If you are an agile player, complicate and confuse the game for your powerful adversary.
4. Creating for others: As an enlightened player, you have to create a game not just for yourself, but your adversaries. One of the most extreme techniques is to create pseudorandomness in a domain that actually supports learning. This means taking a relatively clean signal, using it to learn yourself, and mixing in enough noise for your adversaries that they slip into “faster and faster” mode, mistaking an agility-friendly domain for a power-friendly one.

At the heart of this process is increasing self-awareness. You have to understand your own relative energy and agility capacities, and how they change as you gain experience through one game after another.

What makes competition fun is the loop between Step 4 and Step 1, which creates an arms race. It is often impossible to tell whether you are truly in a near-random domain, or whether a smarter player is creating pseudorandomness for you. When you recognize the latter case, you level up.

I am interested in armchair-thinking through these ideas in the context of real cases and examples, so if you’re interested and have a suitable case, give me a call via Clarity.fm.

Recently, I moved from Las Vegas to Seattle. In the process I realized that activities like moving belongings and getting a new driver’s license are not the hardest part. The difficulty of moving habits is much higher. About 80% of the cost of a move, I suspect, is the cost of moving habits. We lose months of time in the run-up to a move and after.

An example is your gym routine. It’s possibly the most important habit in your life. But it is surprisingly hard to “move” from one context to another.

In my case, I signed up for a gym very similar to the one I used to go to in Vegas. It has similar facilities and a similar range of equipment, trainers and programs. Like my old Vegas gym, my Seattle gym is about a mile and a half from home. The membership cost is about the same.

Yet, it’s been more than a month and I still haven’t found my rhythm. By contrast, when I joined the Vegas gym, it took me less than a week to settle into a great routine.

Why is this?

The Structure of Habits

Let’s start with a definition.

A habit is a stable, repeatable pattern of behavior that involves minimal meta-cognition, and achieves predictable results within a particular local range of conditions, defined as a combination of a cognitive context and a physical context.

In other words, it is a predictable behavior you can execute without thinking too much about it, so long as you are in a particular state of mind and in the right place/time for it.

We can borrow a term from mathematics and call the “local range of conditions” the region of attraction. Think of it like the gravitational region around a planet. Within a certain distance, and a certain range of velocities, small asteroids that enter the region will be captured into orbit. 

So every instance of trying to execute a “gym workout” is like an asteroid flying by a planet. Getting captured into orbit is like successfully finishing a workout.

A large region of attraction makes for a stable and robust habit. A small one makes for a fragile, easily derailed habit.

From the definition, we can infer that every habit is actually two intertwined habits. There is a habit of thought and a coupled habit of action. 

• A habit of thought is a set of coupled patterns of thought and a practiced ability to switch among them appropriately and effectively.
• A habit of action is a learned pattern of physical behavior involving sensory processing and physical movements.

Both are context-dependent. The former is dependent on your immediate state of mind, the latter is dependent on your immediate environment.

Some habits, like switching between brain-dump mode and edit-mode in writing, are almost entirely habits of mind. As you mature at the writing game, you become better at switching between the two modes at the right time. Inexperienced writers often get writers’ block primarily because they stay too long in one or the other mode and get frustrated. The action component is trivial (the physical behavior in both modes is typing or working with pen and paper; switching at most involves taking a short break or changing locations).

Other habits, like your bedtime ritual (end-of-day chores, brushing your teeth, changing into pajamas, and whatever else you do), are almost entirely habits of action.

Most complex habits are a mix of non-trivial thought and action components. Exercising is an example of a complex habit. For some of us, being outside of a narrow range of moods makes it impossible to work out, and expanding that range is hard work. For others, the mood is never a problem, but even a slight change in physical conditions derails the intention to work out.

Learning and Habits

Habits that have been successfully acquired involve very low meta-cognition, but getting there involves plenty of meta-cognition: learning the habit.

Almost all this learning has to do with increasing the size of the region of attraction where the habit “works.”  We can distinguish two phases of learning a habit.

1. Doing it right for the very first time (10%)
2. Expanding the region of attraction till it is large enough to be worthwhile (90%)

As we’ve discussed before, beginners typically learn (and get anxiously attached to) one way of doing something. For example, in a video game, you might learn exactly one fragile way to pass a level. In a level of a vertical shooter I used to play a few years ago, that “one way” involved starting in the bottom right and shooting the aliens in a very specific sequence.

This “one way” is obviously fragile, since if initial conditions are not exactly right, your behavior will be derailed. This is why you need the second phase: gradually expanding the region of attraction by introducing small contextual variations — both mental and physical.

In terms of the idea of a region of attraction, the one way of a beginner can be thought of as a single point. Any deviation from ideal conditions will derail the habit.

So if the behavior is “mounting a bicycle” and you can initially do it only when you are in a confident and energetic mood and are starting on a hill, headed down, you might expand the domain of your “bicycle mounting” habit by learning how to do it in a variety of moods and energy levels, and in all sorts of conditions.

Eventually, you hit diminishing returns. We all have different stopping points when we give up refining a habit. In mounting a bike, most of us give up once we can start on any reasonable grade, and learn the standing-astride and running mounts. Circus performers might try and learn how to mount easily from both sides, from behind, facing backwards and on extreme grades you’d never encounter on normal bike-paths.

This tells you that a habit is also an algorithm that has been gradually evolved to handle a sufficiently large range of conditions to make it worthwhile. Your investment in learning is wasted if the region of attraction does not grow sufficiently large.

The shape of the learning curve for a given habit (either new, or ported) in a given context depends on the complexity of cognitive and physical environments.

As a first-order approximation, you could say that things you learn about the physical context require very few repetitions. Once you’ve done laundry in a new apartment once, you’re pretty much done learning. The problem is that there are a lot of such things in a given physical environment. You might have to learn a hundred little things, each involving 1-3 repetitions.

Learning mental things usually involves more repetitions but fewer discrete elements. For example, when you go from high school to college, your study habits have to change because you are at a different level of the education game. It might take studying for several dozen quizzes or midterms before you settle into your new study habits.

Jokes aside, each kind of learning can go on indefinitely. People generally stop or declare a temporary detente once they start to derive a net positive “return on investment” for their learning efforts around one habit (or group of habits), and direct their limited learning energies to another front with higher returns.

As a result, our behavioral personality is always a set of habit-fronts at various stages of evolution. Some are stable, some are being learned (and bleeding red), some are being ported, some are atrophying. Some are in a state of diminishing returns.

Habits and Personality

Depending on whether they are primarily internally focused or externally focused, people tend to be better at either the mental or physical components of habit formation. It seems to be a zero-sum trade-off. I’ve never met anyone who was equally good at both. It’s like being right or left-handed.

I am pretty lousy at forming physical habits. I am much better at forming habits of thought. There are different sources of difficulty for the two kinds.

Habits of action are difficult to acquire because they require processing or memorizing a large amount of arbitrary information. To learn to get from point home to gym without too much thinking or a GPS, you need to learn various routes, turnings, traffic conditions, construction conditions, hacks, shortcuts, and so forth. Much of this habituation to the arbitrariness of a context is not portable. It is also not efficiently compressible, so it is energy intensive.

Responding to traffic signs is a kind of physical learning that ports within a country. But learning the quirks of a specific city (for example, here in Seattle, one rule of thumb is “avoid Mercer Avenue during rush hour”) is not very helpful when you move to a different city with different quirks.

Habits of thought are difficult to acquire for a different reason, though they might seem superficially easier to acquire. Your mind goes with you from context to context, so anything you learn about yourself, like whether you are more of a lark or owl goes with you everywhere. But learning about your mind is also fundamentally harder than learning something like “Maple Street is one-way east to west.” Since identity hangups, biases, demons and shadows all reside inside your head, every single useful true thing you learn about yourself comes at a 10x cost.

So you may not pay “porting costs” each time you move to a different physical or cognitive context (new city, new level of the mental game via a promotion or role change), but you pay more upfront, and the learning curve is much longer.

For those who like their finance metaphors, habits of action are op-ex heavy, habits of thought are cap-ex heavy.

Habits versus Addictions and Aversions

Healthy habits are the ones which are delivering a return and have an appropriate region of attraction. When the region of attraction for a habit expands where it is potentially harmful, you have an addiction. Addictions can form once a habit is generating a predictable “profit” after the learning curve has been traversed.

Once you get used to the “profit” and come to expect it, the motivational structure for the learned behavior can change. You no longer exercise because you recognize the benefits. You exercise because you are addicted to (say) the “Runner’s High.” You might turn into an extreme, obsessive runner and ruin your knees.

Habits can also turn into aversions. This happens in two ways. Either the habit becomes a displacement behavior for another activity (for example, cleaning the apartment to avoid working on your thesis), or the habit itself can develop a convoluted region of attraction to avoid certain painful regimes.

So you might develop a habit of using humor to steer conversations away from uncomfortable topics and develop a (justified) reputation as a great conversationalist.

Many behaviors are ambiguous, in that they are healthy habits, addictions or aversions depending on the context. These are the behaviors around which developing a strong sense of narrative rationality is very important.

Porting a Habit

Porting a habit to a new context is hard because the learned elements that don’t port well cause a shrinkage of the size of the region of attraction. Sometimes the shrinkage is so dramatic that an expert behavior becomes completely useless in a new context, or at least “unprofitable,” to use our finance metaphor.

One way to think about porting a habit is to think of it as recompiling a program on a new computer. Depending on how big the context difference, you may need to do anything from tweak a few settings to rewrite the entire program to compile on the new computer.

For the gym example I started with, the basic context-dependent algorithm is the same in both cases:

1. Change into gym clothes
2. Go to gym
3. Workout
4. Shower and change
5. Move on to next activity

But this is deceptively simple. There is a whole lot of context dependency that is not captured here. For my Vegas to Seattle example, here are some key ones:

1. In Vegas, the weather is always suitable for any mode of transport, in Seattle, the weather varies in non-trivial ways that affect whether you can walk or ride a bike or drive.
2. In Seattle, driving the 1.5 miles is much harder because it is urban driving with a lot of pedestrians, bicycles, traffic lights and one-way streets. In Vegas, I had an easy suburban route with just one left turn and no pedestrians. I have to be 3x as alert to drive to the gym in Seattle. So I am sufficiently alert less often.
3. In Vegas, parking was not a concern. It was always available and always free. In Seattle, depending on the time of day, day of week and season of the year, my gym has different rules about parking and how much I pay. I have to get the parking ticket validated at the front desk. So the algorithm has a whole branch of logic having to do with parking decisions that didn’t exist in Vegas.
4. In Vegas, transitioning to/from the next activity was easy. I could make it up as I went along. In Seattle, if I plan to work at a coffee shop after the workout, I have to plan differently depending on whether I drove, walked or took the bus.

This is just a small subset of the differences. If I wrote out the pseudocode for “go to gym” for Vegas and Seattle, I suspect, the latter program would be at least 5x as long. Much of the added complexity is because my living situation in Seattle has a good deal more physical complexity in the environment, since I live close to the city center rather than in a suburb.

As an aside, the closer you live to the center of a city, the more computationally demanding all habits become. This is one reason where you live is such a useful variable for personality typing.

Acquisition versus Porting

You can quantify the difficulty of acquiring or porting a habit loosely by assessing the physical and cognitive context complexity. It is easier to assess the latter (porting) because you only have to assess a pair of differences between before/after contexts. As mathematicians know, the “differential” or “variational” version of any kind of problem is generally easier than the absolute version. There is even a well-developed theory of how to do it well (it’s called perturbation analysis).

Another reason porting is easier than acquiring a new behavior from scratch is that a lot of learning is illegible and unconscious. You have to build up a robust algorithm in your head that you don’t fully understand. Say a habit algorithm has a conscious component C that you could write down, and an unconscious component U that you are not really aware of. So moving the habit from one context to the other is about moving C to C1 and U to U1.

In my experience, the unconscious component generally ports far more easily. But when it breaks, it is also much harder to debug.

It’s like the algorithm for every habit has two components: a piece for which you have the source code, and a piece for which you only have the compiled binary code. The former nearly always needs some modification when you change contexts, while the latter usually ports without any effort. But when the latter fails to port, you’re in serious trouble.

Complex ports can be understood as ports where C1 and U1 are both functions of both C and U rather than C1 being a function of C and U1 of U.  In other words, you may have to consciously process previously unconscious components of behavior, and vice-versa. This takes a higher level of self-awareness.

In a way, context-switching and simply expanding the region of attraction in one context don’t differ much. So ports are simply disconnected expansions of the region of attraction. You are adding a planet, so you can capture asteroids around two centers.

Meta-Habits

A meta-habit is a habit you use to port or acquire other habits. For example, dive off the deep end, is a specific learning strategy (immersion) that can jumpstart any new habit. If you know how to handle the extreme disorientation, chaos and anxiety it induces, and if you know when it is safe to do so.

In the prototypical example of swimming, diving off the deep end is actually a terrible way to learn unless there is a teacher around. You will almost certainly drown if you aren’t close enough to the edge to thrash your way to something secure within a few seconds.

I don’t know if there has been much research into meta-habits, but here are some I am aware of, some of which I even practice.

1. Diving off the deep end
2. Confidence building with small wins
3. Not perturbing behaviors along too many dimensions at once (however, the naive experimentation idea that you should tweak only one variable at a time is misguided and inefficient when there are many dimensions).
4. Gradualism (push yourself only a tiny bit extra with each attempt to expand the region of attraction)
5. “Exercise to failure” (keep pushing yourself in one direction until you cannot handle a particular case, a matter of finding the boundary of the region of attraction)
6. Never make a decision when depressed, especially a quit/persist decision
7. Fail fast — not in the product development sense, but in the sense of quickly putting a scratch or dent on your pristine learning effort (remember the lowering of anxiety you felt when you first put a scratch on a new car?)
8. Shut up when learning a physical habit (verbalization slows down acquisition of tacit knowledge — if you have a teacher who talks too much during teaching of a physical behavior like swinging a tennis racket, find a new teacher: you need periods of silent repetition between being given instructions and suggestions)

Curiously, I am much better at incorporating some of these meta-habits into my teaching than into my learning.

Variety Reduction as Anti-habit Formation

You can come at habit formation from the other direction. Instead of trying to learn a habit to handle a sufficiently large region of attraction to make it worthwhile, you can change the environment to simplify the habit acquisition or porting problem.

You do this primarily by reducing variety and introducing homogeneity in both cognitive and physical contexts. This depends on your resources. If you are rich enough to hire a chauffeur you can forget about the complexities of driving. If you’re powerful enough that a lot of people want to work with you, you can pick and choose people who adapt to you, so you can keep your thinking the same.

“Simplifying” your life, far from being a monkish thing to do, is actually a behavior practiced most often by the rich. Monks (and sour-grapes foxes) simplify in a different way: by giving up desires, either mindfully or via sour-grapes rationalization.

For most of us, variety reduction is a limited option. We make up rueful aphorisms about the human condition that reflect this, like if you don’t get what you like, you are forced to like what you get. Shaw’s famous line,  ”The reasonable man adapts himself to the world; the unreasonable one persists in trying to adapt the world to himself” speaks to the relatively higher difficulty of changing the environment to reduce variety. It is an option that is dependent on your power.

But suppression of contextual variety to make habit formation cheaper comes at a price. It reduces your general ability to learn. This is perhaps the primary reason power leads to its own downfall. By making variety-reduction and homogenization an attractive alternative to the harder problems of habit formation and porting, power causes learning abilities to atrophy.

Organizational Habit Formation

Organizational habit formation is surprisingly similar to habit formation in individuals. We know it as economies of scale and scope.  The primary difference is that since organizations are typically far more powerful than individuals, the option of reducing variety and introducing homogeneity is more available to them.

Organizations become bad at learning and dealing with circumstances that cannot be homogenized away.

This is the reason industrial age organizations are associated with homogeneity and “seeing like a state.”

A major challenge in designing post-industrial organizations is to build into them the ability to accommodate variety and the discipline to not use the variety-reduction/homogenization option even when they have the power to do so. I’ve called this problem the “economies of variety” problem that I am still trying to figure out.

Thanks to Kartik Agaram and Jason Morton for useful discussions that informed this post. 

Greg is a 2013 blogging resident, visiting us from his home blog over at On the Spiral. His residency will explore the theme “Individuality and Decision-Making” over several posts.

A couple weekends ago, during a break in the scheduled programming at Refactor Camp, I was walking around with Kartik Agaram and as we passed by a concession stand he off-handedly remarked: “I know things are going well when I can walk by something like that without experiencing any temptation.”  This was one of those statements that easily eludes our cognitive filters, but it becomes rather perplexing when you begin to tease it apart.

Why should temptation be easier to resist when things are going well?

What does it even mean for “things” to go well?

There are easy answers like – when we are preoccupied with more engaging tasks, temptations are perceived as relatively less appealing.  However, the easy answers are easily contradicted.  Sometimes when things are going well we are so preoccupied that we find ourselves guzzling coffee and eating take-out every night.  Apparently things need to be going well in a particular way in order for temptation to diminish.

We could propose instead that temptation is easier to resist when we are satiated, i.e. when our needs are readily satisfied by our environment.  This is the direction our conversation went at the time.  We began discussing the idea of ego depletion and the conditions that cause it.

Unfortunately, this angle presents difficulties as well.  First of all, it doesn’t do much besides rephrase the question.  We are still left with the rather tautological relationship:

“things going well” == satiation == undepleted ego

And again the opposite can be equally true.  It is often when we are most comfortable that it is most difficult to muster the discipline necessary to resist temptation.  When people become habitually comfortable we say things like – “he has too much time on his hands” or “she is very set in her ways” – hardly indicative of someone demonstrating strong executive functioning.

In this regard the ordinary notion of willpower is more apt than the unidirectional ego depletion.  As is the case with physical exercise, too little stress can be just as disabling as too much.

Atrophy is tricky to avoid because much of what passes for willpower is actually nothing of the sort. Recall that in the famous marshmallow experiment it was the children who distracted themselves who had the most success.  The children who relied on direct application of willpower succumbed most quickly.

Similarly, the person who is set in his ways often believes himself to be strong-willed when in fact he has adopted a lifestyle that renders willpower unnecessary.  He is like the person who habitually goes to the gym every day but who long ago hit a plateau.  Far from being depleted, his ego has become an active impediment, resisting any activities that might demand adaptation.

This need for the just-right amount of stress reminds me of Mihaly Csikszentmihalyi’s notion of cognitive flow, which suggests that we require the just-right amount of strain to conjure up the fully engaged flow state.  Too great a challenge leads to frustration while too little challenge leads to boredom.

It is no coincidence that the flow state entails resilience in the face of distraction.  I think this was exactly the intuition underlying Kartik’s expression – “things are going well”.  His ability to resist temptation implies a kind of lifestyle flow – just enough strain to provide a challenge; not enough to produce exhaustion.  We can address the contradictions noted above by formulating lifestyle flow in terms of adopted personas…

Tempting foods are easier to resist when a given flow state supports an appropriate self-image.  On the other hand, a workaholic flow state only exacerbates an unhealthy diet.  If you have ever pulled an all-nighter you know that that particular flow state is not resistant to distraction from unhealthy food.  Rather, it is resistant to distraction from the guilt associated with eating unhealthy food.

In summary:

• Atrophy occurs when habitually clinging to a comfortable persona
• Ego depletion occurs when straining to adopt a persona that is too foreign
• Lifestyle Flow occurs when practicing behaviors just outside one’s existing persona

It occurred to me that this perspective might help explain the puzzle that concluded my last post, specifically why Tolstoy’s foxy constitution prevented him from manifesting his own conviction that people should be hedgehogs.

***

Last time I referenced Colin Wilson’s book The Outsider as a study of the extreme Fox.  It will be helpful now to add some meat to that assessment.  In one of his better articulations of the Outsider’s problem, Wilson writes:

For the Outsider, the world into which he has been born is always a world without values.  Compared to his own appetite for a purpose and a direction, the way most men live is not living at all; it is drifting.  This is the Outsider’s wretchedness, for all men have a herd instinct that leads them to believe that what the majority does must be right.  Unless he can evolve a set of values that will correspond to his own higher intensity of purpose, he may as well throw himself under a bus, for he will always be an outcast and a misfit.

This passage echoes Berlin’s characterization of Tolstoy as someone who possessed an acute desire for meaning but lacked the necessary credulity.  [Tolstoy does make a brief appearance in Wilson's work.]

One of Wilson’s refrains is that the Outsider is crippled by “seeing too clearly and too much“.  By this he means that the Outsider perceives too strongly the absurdity of civilized life.  As a result his world takes on a pall of unreality.  He is like a character in the Matrix who recognizes that his world is a fraud but has no red pill with which to wake himself.

In such a world nothing is worth doing.  Hence, the Outsider is trapped between his own disbelief in “herd values” and his inability to formulate a viable alternative.

***

This should lead us to reexamine Berlin’s analysis, given that the passage above contradicts the commonplace conception of the fox.  The person who “knows many things” is often thought of as a renaissance man.  If we wanted to be less charitable we might deride such a person as an experience collector or a shallow know-it-all.  In any case, this novelty seeking type of fox is quite distinct from the Outsider for whom nothing is worth doing.

Yet, it would be difficult to say that Tolstoy (or Wilson’s Outsider) is any less representative of the person who knows many things.  There is a definite sense in which “seeing too clearly and too much” does become dissatisfying.  Barry Schwartz coined the phrase the paradox of choice to describe how having too many options creates anxiety and regret.

Similarly, creative people of all stripes have recognized that too little constraint can be just as crippling as too much.  Constraints provide direction.  They focus attention and energy on a specific challenge, and in doing so they implicitly define a standard that distinguishes good work from bad.  The person without constraints tends to flit from one shallow curiosity to another…or wallows in purposelessness.

It seems then that we have uncovered two legitimate varieties of Fox, one positively oriented and one negatively oriented:

• the novelty seeker, for whom everything is worth doing
• the Outsider, for whom nothing is worth doing.

***

Are there also two kinds of hedgehogs?

The person who knows one big things would seem to be positively oriented.  Is there an analogous negatively oriented type?

Regular readers of this blog won’t have to look very far…the obvious reference here is Boyd.

Is Boyd fox or hedgehog?

Like Tolstoy, he is difficult to classify because he exhibits aspects of both.  No doubt, Boyd was foxy in the breadth of his insight.  It would be difficult to argue that he accepted much of anything at face value, least of all any singular big ideas.  However Boyd did exhibit a hedgehog-ish side through his single-minded focus and the strength of his convictions.

What was it that enabled Boyd to focus his attention so powerfully?

I’ll propose one possible answer: The Enemy.

In some respects Boyd and Tolstoy are quite similar.  Isaiah Berlin could have just as easily been describing Boyd when he wrote:

Like all very penetrating, very imaginative, very clearsighted analysts who dissect or pulverise in order to reach the indestructible core, and justify their own annihilating activities (from which they cannot abstain in any case) by the belief that such a core exists, he continued to kill his rivals’ rickety constructions with cold contempt, as being unworthy of intelligent men…

(emphasis mine)

What distinguishes Boyd from Tolstoy is that he knew those rivals precisely.  He could identify a specific source of “rickety constructions” upon which to focus his “annihilating activities“.  They were the “be somebody” career men of the military bureaucracy.  That target constrained Boyd’s thinking and represents an organizing thread throughout his work.

Tolstoy lacked any such target.  Berlin writes that “what oppressed Tolstoy most was his lack of positive convictions“.  Colin Wilson offers a similar sentiment in describing the Outsider:

This book has been a study chiefly in men who ‘wrecked’ for different reasons, men who cared too much about something or other, and cracked under the strain…

What we cannot have failed to notice…is that the greatest men have been those who were most intensely concerned about the Outsider’s problems, and the question of how not to wreck.  The Outsider must keep asking the question: Why?  Why are most men failures?  Why do Outsiders tend to wreck?

We lack the concept of an enemy: that is the trouble.

***

If the negatively oriented Fox – Tolstoy – can be characterized as an Outsider, then the negatively oriented Hedgehog – Boyd – can be characterized as a Barbarian: someone whose big idea develops in opposition to a particular “civilized” ideology.

That allows us to invoke our favorite construct – the 2×2 matrix:

I’m already running long so I won’t dissect this in detail but – looping back to where we started – I’ll just point out how the examples of Boyd and Tolstoy illustrate the importance of transitioning through adjacent types rather than attempting diagonal jumps.

Tolstoy can be understood as failing to develop a satisfactory big idea because he attempted to jump directly from Outsider to Hedgehog.  The excessive strain involved in that approach leads to ego depletion in the short term, and provokes mounting cognitive dissonance over the long term.

By contrast, Boyd can be seen as a Barbarian who effectively transitioned into adjacent personas – gradually expanding the scope of his refutations (Barbarian –> Outsider) while also gradually developing his own big ideas (Barbarian –>Hedgehog).

The planning/decision-making literature focuses a great deal of attention on computing actions many steps ahead. But it recently struck me that looking ahead is not actually a very natural behavior for humans in most real-time domains (which is most domains).

A simple illustration is the problem of adding milk or cream to your coffee in a self-serve situation. We all recognize that putting the milk in first and then pouring in the coffee eliminates the need for stirring (and therefore saves a wooden stirrer or a spoon-washing). But few people do it. I myself forget about half the time.

Even if you discount the people who prefer to put the milk in later for whatever reason (in order to use the changing color as feedback, perhaps), I bet there’s a sizable number of coffee drinkers who don’t care about the milk-coffee sequence but don’t choose the simpler and less wasteful sequence.

Why?

You can find examples everywhere. In cooking, there are dozens of little, local sequencing hacks you can use to reduce the amount of clean up after. For example, in chopping vegetables, if the sequence doesn’t matter, you should do onions and garlic last, so the pungent smell doesn’t contaminate other ingredients. If you need a spoon to stir in a dry and a wet ingredient into a dish, use it first for the dry ingredient to avoid an intermediate washing or the need for a clean spoon. Many such little hacks have now become second nature for me. But I notice that people who cook less frequently, or pay less attention (or simply don’t worry about the cleanup because that’s someone else’s job) don’t do these things.

In driving, only a tiny fraction of drivers try passing maneuvers that require thinking two lane changes ahead rather than one (these admittedly require more than 2x situation awareness to pull off safely).

In most practical real-time domains, I bet that simply going from 1-step look ahead to 2-step look-ahead would create huge gains.

The point of these examples isn’t to preach the virtues of sequencing hacks. They are a matter of taste. You either like thinking about them as little puzzles in everyday life, and get a kick out of learning them, or you don’t.

The actual point I want to make is that we generally suck at thinking about real-time planning more than one step ahead. Not because it is hard (that depends on the context) but because it is not the path of least resistance. And most of the time, we are in path-of-least-resistance mode. The only time we notice and start to optimize is when we repeat a sequence a large number of times.

I’d say we typically do a sequence optimization only when we expect to repeat a sequence at least a few dozen times in the future. So our behavior reveals something: the subjective cost of computing even the simplest local sequencing tweak is high enough that we want to amortize it over at least a few dozen repetitions.

In fact, I’d say the median look-ahead window for most high-variability real-time domains is probably 1. Outside of narrow domains like chess, or highly repetitive and unvarying actions like putting on your shoes, most people don’t in fact look ahead at all. Putting milk in coffee is just high variability enough as a behavior that the milk-before-coffee sequencing does not stabilize for most people.

So how do we get long sequences of actions done right?

We rely on externalized cues that make sure we do things in the right order (or better still, make it impossible to do in the wrong order) — what I called a stable field-flow complex in Tempo, or we practice repeatedly until the right sequence becomes muscle memory.

A stable field-flow complex of sequencing cues is not the same thing as a logical plan.

If you’ve ever tried to follow a  logical, but not psychologically least-effort/intuitive plan (like Ikea assembly instructions) you know how hard it can be to actually do things in the right order.  For at least half the population (probably Myers-Briggs xxxP types), there is a temptation to dive right in and intuitively figure things out one step at a time. It took me being burned a couple of times to develop a proper respect for instructions. I still find them painful though.

2-step-ahead thinking is an acquired habit. You have to acquire it separately in every domain. If you are 2-step-ahead in the kitchen, it does not mean you’ll automatically be that way when doing household repairs.

But in my experience, it is always worth acquiring this habit. I’ve never regretted it.

I am now officially a “smart person,” since I’ve been interviewed on the Smart People Podcast.

It’s a half-hour interview where I talk with Chris Stemp and Jon Rojas about Tempo. Kinda fun, since it’s the first time I’ve talked about the book in an audio interview format.

Check it out here.

Tomorrow is the National Day of Unplugging, a concept that extends the Jewish idea of Sabbath into a more general, secular idea. I wrote a post about it on ribbonfarm. Check out the site, and consider observing the NDU.

Here’s the blurb from the Sabbath Manifesto site, which appears to be promoting the idea. A very Tempo-ish idea of figuring out how to slow down.

Way back when, God said, “On the seventh day thou shalt rest.”  The meaning behind it was simple: Take a break. Call a timeout. Find some balance. Recharge.

Somewhere along the line, however, this mantra for living faded from modern consciousness. The idea of unplugging every seventh day now feels tragically close to impossible. Who has time to take time off? We need eight days a week to get tasks accomplished, not six.

The Sabbath Manifesto was developed in the same spirit as the Slow Movement, slow food, slow living, by a small group of artists, writers, filmmakers and media professionals who, while not particularly religious, felt a collective need to fight back against our increasingly fast-paced way of living. The idea is to take time off, deadlines and paperwork be damned.

In the Manifesto, we’ve adapted our ancestors’ rituals by carving out one day per week to unwind, unplug, relax, reflect, get outdoors, and get with loved ones. The ten principles are to be observed one day per week, from sunset to sunset. We invite you to practice, challenge and/or help shape what we’re creating.

Good idea. Now go unplug.