Moving the ladder

Riffing on the cost of opinion piece, I realized that there’s a neat framing around opinion mutability and the underlying systems dynamic that’s worth mentioning.

One way to think about the settledness of opinion is as finding a reasonable balancing point between the value and cost of the layer, where the value compounds at a relatively similar rate as costs. Opinions that find that point tend to be more settled, and opinions that are still looking for it are more transient.

Think of it as a spectrum. At one extreme are layers whose opinions have completely settled, and on the other – the layer where transient opinion churns like whitewater. As an example, the IP Protocol and the TCP/UDP twins that sit on top are a pretty good example of settled opinions. Even though I am sure there are people somewhere trying to invent something more awesome than these, I am going to rate their displacement  as “extremely unlikely.” 

On the other hand, the Web continues to experience the effervescence of Javascript frameworks that are born and discarded seemingly every month (week?), subject to fascinating natural selection-like dynamics. It would not at all be controversial for me to suggest that the opinion at this layer hasn’t settled yet.

Why do some opinions settle? And why do some continue to shift? Stewart Brand has this wonderful concept of pace layers that is pretty instructive. The idea behind pace layers is that all complex systems tend to organize themselves in terms of layers, and each outer layer evolves at a faster pace than the lower one. Stewart even attempts to introduce a taxonomy of layers, which I am not going to use here. However, this notion that inner layers shift at a slower pace than the outer is very useful in this conversation. I am not a biologist or an ethnographer, so I can’t speak for forests or civilizations. However, based on my experience in developer ecosystems, their layers are almost always organized in a pace-layer like fashion. It’s almost like the spectrum I was describing earlier is actually a description of the developer layer stack: things that are settled sit at the bottom (think TCP/IP), things that are frothing with change are at the top (think Javascript frameworks), while the layers between them span the gamut.

And I have a guess on why this happens. As a thought experiment, let’s imagine that our layer is like a ladder – I know, it’s analogy time. Just like the layer’s vector of intention, our ladder is currently leaning next to the upstairs bedroom window, where our uncle Steve just finished cleaning it. Good work, uncle Steve. Now, Steve wants to clean the bathroom window, which is a bit more to the left. The requirements changed and now, our vector of intention needs to adjust to point in a different direction. What do we do? Naively, we might say – let’s move the ladder! However, if we try to do that, we might hear some choice words from our uncle who suddenly finds himself hanging onto his dear life at the top of the ladder. Falling down is not fun. Instead, it is more common that Steve, the family daredevil that he is, chooses to lean out to reach the bathroom window. He might yet fall, but dammit, it will be on his terms. What our uncle just did there was layering. He’s okay, by the way, though Grams did see his stunt and will chew him out later. Uncle Steve created an extra layer on top of the ladder, and formed an opinion: an angle between the vector of intention of the ladder and that of his own. Even though the “rational” thing to do would have been to a) climb down the ladder, b) move it, c) climb it back up, he freakin’ chose to risk his life to save a bit of energy and time.

This move-the-ladder dynamic happens all the time in software layers. As a rule of thumb, upper layers prefer the lower layers to stay put. Waiting for the lower layer to adjust feels like giving up agency, so they tend not to. Instead, they expect the lower layer to remain roughly where it is now, perhaps refining some bits here and there, but not doing any wild swings toward the bathroom window. Recursing this effect through the layers, a pace layer structure develops. Every lower layer has more uncle-steves yelping and demanding they “whoa hold it there, you <redacted>”. Every change at a lower layer becomes a matter of painful negotiation that takes time and energy – and so the layers below tend to move at a much slower pace. It is fun to be the outermost layer, but as soon as anyone takes you as a dependency, the move-the-ladder dynamic starts to manifest itself. Every successful developer surface experiences it, and suffers through it.

Getting back to our notion of settled and transient opinions, I hope that uncles Stewart and Steve provided enough illustration of this idea that opinions of the outer layers tend to be more transient, and the deeper they go in the stack of layers, the more settled they become. It doesn’t make them right. Settled opinions could be patently, obviously wrong. However, given the full height of the ladders and foulmouthed uncles that tower above them, changing them involves a bucket of miracles.

Racing toward or running away

In this moment of flux that I heard being called the Great Resignation, it almost became normal to regularly receive emails from my colleagues and friends about changes in their work. People leave one company to join another, some start their own, and some decide to retire. When I do get to chat with them, the question that I usually ask is whether they are racing toward or running away. Given the decision to make this change, is it more about leaving the current environment, or entering a new environment?

Neither of these are wrong or right, but might be useful to understand, especially in conditions as stressful as job change. Having done a few of these in my career, I’ve learned to recognize that each brings a different mindset and a set of implicit expectations – and surfacing these expectations early usually does some good.

When I ask, folks often have an immediate answer. They can tell right away if the change they’re making is racing toward a new opportunity or running away from a setup they no longer find tenable. If you are blessed enough to contemplate such a change, and aren’t sure how you would answer this question, here’s a silly exercise that might be of use.

Ready? Ask yourself why you are currently working where you are. Answer as honestly as possible, trying to state it in terms of some larger reason behind your work. Once you have the first answer, see if it resonates deeply with you, excites you, gives you that sense of being aligned with your internal sense of purpose. If it isn’t, keep asking the question. Why is this larger purpose important? This line of questions may terminate early with the “Aha! This is exactly what I want to be doing with my life”,  or take you toward some lofty ideals like “uplifting humanity”, or it may attempt to trap you in weird causal circles.

Now, do the same for the new opportunity. Does it follow a similar path? Is it crisp and brief, or even more convoluted than the current one?

Here’s my intuition. If the second string of “whys”  is shorter than the first one, you are likely racing toward the new opportunity. If it’s the other way around, you’re likely running away from your current work situation. And if they’re both pretty long, then it might be worth looking at other opportunities, and seek the ones that ring a bit more true with what you believe you’re meant to do with this life.

Awareness of interoception

Recently, I have been fascinated by the wonderful and mysterious part of being human – our interoceptive system. It’s this thing that we all have, but to which I didn’t pay any special attention. The interoceptive system is how we experience what happens inside of our body.

If we sit very quietly and try to draw our attention inside, we can start noticing that we can perceive all kinds of things going within us. If we believe Antonio Damasio, the complete set of these experiences — or what we call feelings – plays a critical role in how we experience the world outside, how we show up, and indeed who we are. Even though it takes skill for us to consciously notice our feelings as distinct experiences in various parts of our body, our mind is well-familiar with these signals, constantly and seamlessly relying on them. Things that prick our fingers feel bad, as well as things that are too hot or too cold.

What I found particularly insightful is that our memories contain these experiences as well. Remembering an event when something bad happened actually feels bad – the interoceptive track of our memories replays how we felt during that moment. This leads to a bunch of weird effects.

For example, we can be afraid of feeling fear. Let’s chew on that one together. Suppose I walked under a tree… face-first into a spider web. Yuck. I am not a fan of spiders, so my interoceptive system would immediately inform me that this is a scary experience. Next time I go near that tree, something odd will happen. I will have this inkling that maybe I don’t want to go under that tree. What’s going on? Turns out, upon seeing the tree, my memory of the encounter with the spider will helpfully pop up, and replay the dose of fear I experienced. I will probably explain it as “intuition” or “good judgment” to walk around the tree, but more honestly, I will be reacting to the experience of an interoceptive memory. I will be afraid of feeling that experience again. 

Even more bizarrely, the whole thing is path-dependent: the new memory of choosing to walk around the tree will include the interoceptive experience of newly-experienced fear of feeling that first fear, and so on. This stuff can get rather gnarly and turn unproductive really fast. Maybe I shouldn’t walk under any trees at all. Or staircases. Or covered porches. Spiders could be anywhere.

Of the many moments I am not proud of, there was that one time when I needed to give a colleague of mine some really uncomfortable feedback. We were sitting right across from each other, and I just needed to lean over and say: “hey, can we talk?” And I couldn’t. I just sat there, looking at my colleague’s back, paralyzed. I was overcome by the spiral of fear of feeling fear of feeling fear, folding over and over onto itself.

Another weird effect is a similar kind of vicious cycle of our minds collaborating with our body to rationalize negative feelings. If you ever woke up from a bad dream you couldn’t even remember and then had trouble going back to sleep, this will be familiar to you. The thing is, our minds are exceptionally good at association. Whenever our interoceptive system informs us that something of negative valence (that is, something that feels bad) is happening, the mind eagerly jumps into the fray, helpfully finding all the similar interoceptive experiences from our past. In doing so, those experiences are replayed, exacerbating our interoceptive state, which feeds back into our minds looking up more and more terrible entries in the great database of “crappy stuff that happened to us.”

If this resonates with you and you’re curious about how to put an end to this drama, I have both good news and bad news. I’ll start with the bad news. This stuff happens to us pretty much all the time and will continue to happen, no matter how rationally we aspire to behave. Feelings are us. The somewhat good news is that we can learn to be more aware of our interoceptive system and apply that awareness to reduce the intensity of the vicious cycles. I can’t stop my interoceptive system from blaring klaxons, but I can learn to react to them more productively. The whole awareness thing takes effort and practice, but seems to work – at least, in my experience.

Choosing kale

Chatting with my friends about choosing developer frameworks, we accidentally arrived at this kale metaphor. It sounded witty and fun, so I’ll try to unpack it as best as I can. To begin, I will apply the value triangle lens from a while back, going over the edges of the triangle. I only need them as examples of the improbable extremes. What’s up with all the triangles in my posts lately?

A framework that favors the user/ecosystem edge will present itself as a promise of a high-minded idea, then quickly reveal a toy upon a close examination – kind of like one of those fake fruits arranged on a dinner table to spruce up the interior. As a child, yours truly once was lucky enough to taste one of those fruits and learn a valuable lesson about appearances. Yum, stale wax.

Building on the tasting metaphor, the combination of business and ecosystem value usually produces frameworks whose taste is best described as … cardboard, I guess? There’s definitely important ingredients like fiber in there, but the dietary value and enjoyment are nigh nil. Large companies tend to produce these frameworks for internal use and almost without fail, the quality of their developer experience tends to wind downward with time. These frameworks aren’t picked. They grow in place.

When a framework sits on the edge of user and business value, it usually tastes like candy. It’s downright addictive to use and makes everyone look good. Sadly, as we know from the value triangle discussion, the consequences of this sugar high are usually borne by the ecosystem – which eventually gets back to users. The long feedback loop of ecosystem effects creates a double-hook: if I only plan to stay on this team for a couple of years, there aren’t any downsides for me. I can just pick the hottest framework I like. Let the successors sweat the incurred debt.

It is my guess that when trying to find a framework that will work well for a team in the long term, the prudent choice will taste something like kale. Like the nutritious leafy vegetable, it won’t seem like an easy pick compared to other choices.

Such a framework will tend to look a bit boring compared to the other contenders, less opinionated. Instead, it will likely carefully manage its cost of opinion in relation to the underlying platform — and as a result, keep the papering over the platform’s rough edges to a minimum. Expect a couple of wart-looking things here and there. Make sure they are indeed the outcome of a well-budgeted opinion. Keep in mind the cardboard extreme – a good-for-you framework doesn’t have to taste bad. 

The values of a kale framework will likely point toward concerns around the larger ecosystem, rather than directly focusing on quality of the developer experience. This is usually a good kale marker: instead of promising how great the taste will be, there will be focus on long-term health. Of course, please do the due diligence of taking the framework for a spin and make sure it’s not just a decorative ornament. Give it a few bites to ensure it’s not made of wax.

The kale-like choice may also be somewhat out of alignment with the team’s current developer practices. Misalignments don’t feel great. However, if you are looking to improve how your organization ships products, a framework is a powerful way to influence the development norms within the organization. In such cases, the misalignment is actually a tilt that steers it toward desired outcomes. For example, if my team is currently stuck in the anti-pattern of erecting silos of widget hierarchies for each new app, choosing a framework that encourages shared components might seem eccentric and inefficient, but eventually lead to breaking out of stuckness.

I hope these musings will help you generate some insights in your next search for the right framework. And lest I succumb to the normative voice of a recommender, I hope you use these insights to find your own definition of what “kale” means in your environment. May you find the strength to choose it.

Polarity of intention, structure, and capacity

I keep coming back to the post from last year, where I tried to write down my understanding of the distinction between organizational states of consistency, cohesion, and coherence. It’s been a generative framing for many conversations. The thing that kept bugging me was that I laid the states out as a progression of sorts, from disorganized to coherent. A colleague insightfully pointed out that one could have coherent user experience even if it’s not consistent. This spurred an exploration into key ingredients of the state, which I present here for your perusal.

I already suggested before that the key attribute of coherence is the presence of intention. If we imagine an organization with strong intention about what it wants to accomplish, we can see how coherence will naturally emerge within it. Strong intention usually comes across as people roughly knowing where their organization is aiming and how their contributions fit into the picture. Weak intention will have a vibe of unmooredness, usually unsurmountable coordination headwinds. Both might have clearly stated missions, though in the former case, the missions will feel actionable and inspiring, and in the latter more like cartoonish slogans.

However, it didn’t occur to me until recently that cohesion also has a key attribute: structure. I am using the word “structure” in Peter Senge’s sense, as a broad descriptor for all things that comprise a functioning organization: the reporting hierarchies, the roles, the processes that make it go, and the culture that binds it all together. It’s this structure that makes the various bits and pieces that an organization produces cohesive. A team with strong structure will have the necessary means to coordinate cohesiveness of the outcomes, whereas weak structures will typically suffer from a “thousand flower bloom” phenomenon that ends in poor cohesiveness.

A similarly recent thought led to this notion that consistency’s key attribute is capacity. To define it a bit more, it’s not just the ability of doing something, but also the skill and the practice that accompanies it. It is fairly evident that the team’s consistency of product outcomes is only possible when they have enough skill and practice to apply it. If an organization’s capacity is low, its output will be at best random, occasionally striking gold – definitionally inconsistent. A high-capacity team will not have such issues. Usually, when I hear “engineering excellence,” the word “consistency” pops right next to it.

So I wonder if the three states – consistency, cohesion, and coherence – emerge from the mix of these key ingredients: capacity, structure, and intention. Though it seems like there’s a tension between them. It’s not like I can just will my product to be coherent if all I have is intention. Without capacity and structure, it’s just a bunch of grand ideas. Similarly, having the capacity is awesome, but if it’s capacity alone, the outcomes will feel like random noise. And finally, if all I have is structure, it’s an aimless zombie. I would guess that more likely, having all three ingredients, but favoring one or the other is what leads organizations toward their predestined states.

The presence of such trilemma indicates that there might not be a favored state, a static resolution of the tension. Instead, a team will likely find itself leaning from one corner of the triangle to another, experiencing a want of one of the two other states when it gets too zealous about one particular ingredient. Over-focusing on capacity brings a deficit of coherence and cohesion. Being too into structure diminishes coherence and consistency, and finally, pushing too hard on intention saps consistency and cohesion. And if polarities are hard, can you imagine navigating a three-body-problem equivalent of a polarity?

By the way, I don’t know if there’s a word for this polarity with three extremes. Is that still a trilemma?

The cost of opinion

It appears that I’ve been writing this essay since 2012, never quite finding the right framing. One of my brilliant colleagues asked me this question back then: “How do you evaluate whether a Javascript framework is good for the Web? You seem to do it intuitively, but I don’t get it. What’s the logic?” And I was stumped

Now, a decade later, here is my best-effort attempt to capture that intuition. I am a bit older now, so I offer this with a bit more humility. The story is also a bit more technical in nature and I apologize to my non-technical readers in advance.

I tried to formulate my answer as briefly as I could, and it came out almost like a poem, in four … shall we call them stanzas?:

Frameworks and libraries are like layers,
and these layers accrete.

Every layer has a vector of intention,
pointing toward some idealized value to users,
determined by the author of the layer.

Opinion,
or the difference

between the vectors of intention of two adjacent layers,
always comes at a cost. 

Opinion costs compound
and are, directly or indirectly,
shouldered by users.

Below is the reasoning that went into this little ditty. The first line sets the stage with a simplistic, but hopefully useful framing. Let’s imagine all developer-facing software as something that accretes layers of abstractions over time. These layers of abstraction usually emerge as libraries or frameworks, written on top of some existing layer (I will use the word “platform” to describe it)  – usually to provide additional value that wasn’t there before.

For example, the venerable jQuery is probably the MVP of the Javascript frameworks (and maybe even all developer frameworks of all time): during the times of browser wars and through the winter, it steadily held developers’ hands, providing a decent interoperability layer over the treacherous terrain of grotesquely diverse and buggy browser implementations. If you knew jQuery, you knew how to make things on the Web. jQuery emerged out of necessity and accreted on top of the DOM APIs. All these years later, I still find it on many (most?) sites across the Web. In fact, some (many?) newer frameworks themselves relied on jQuery, accreting a second layer of value on top of it. So, here’s our first stanza of the narrative: frameworks and libraries are like layers, and these layers accrete.

As a second step forward, let’s recall the tale of two models: the “what is” and “what should be.”  The former represents our current understanding of the environment, and the latter – our preference toward its future state, reflecting our intention. Every framework and library is its author’s manifestation of this intention, taking the “what is” of the underlying platform (or layer) and transforming them to produce the “what should be”: it’s own APIs. For example, jQuery took the dizzying variety of ways to find a DOM element across different browsers back then (the “what is”) and produced the now-ubiquitous “$()” function (the “what should be”). Think of this transformation as a directional arrow (a vector!) connecting the two models of environments. The butt of the arrow starts from “what is” and its head points toward “what should be.”

Unsurprisingly, the layer underneath also has an intention. Even bedrock platform APIs do this work of translating something at an even lower layer to something they believe to be more valuable to users. Even though its developers aren’t always conscious of this intention, every layer has one. Embedded in intention, there’s some mental model of what “good” (or “valuable to users”)  looks like. Thus, our second stanza is: every layer has a vector of intention pointing toward some idealized value to users, determined by the author of the layer.

Now, we’re ready for the third hop. When the vector of a layer aligns with the vector of the layer below, we say that the library or framework that comprises this layer is un-opinionated. When it does not, we say that it is opinionated. The difference in the vectors is the degree of opinion. Think of opinion as a change in direction: the author of the lower layer was like, “here’s where it’s going!” and the author of the upper layer went: “Cool story, but actually, I want to try this other direction.” 

A layer’s opinion is not something that just sits on the surface, easy to study and examine. Instead, it’s often subtle and hard to see, only becoming obvious over time. Usually, it’s a bunch of smells in the code of the framework or library. It usually looks like plumbing, like doing extra work to translate and adjust the vector of intention. To name a few off the top of my head, look for things like parsing, caching, and predictive logic, as well as wrapping — especially recursive — of underlying objects as possible hints. The opinion often comes across as treating the underlying platform as hostile, using as little of it as possible — which unfortunately, is sometimes necessary to make something that actually works.

To make this more concrete, let’s examine that “$()” function from earlier in the article. At first blush, it seems mostly un-opinionated, taking a CSS selector as the parameter and loosely doing the work of an existing platform API: document.querySelectorAll. The only opinion appears to be in the name of the function: one convenient character instead of … what? twenty five? However, if you were here during the browser wars, you might recall that IE6 did not support that particular API. So the brave jQuery engineers wrote their own implementation of it! I still remember peeking at that code and being in awe of such a feat. Compared to IE6, the hallowed dollar–sign function was a bit more opinionated. It disagreed with the idea that getElementsByTagName and getElementById ought to be enough for everyone and ventured forth in a direction that was more aligned with the nascent Web standards. And in doing so, jQuery incurred costs – the extra CPU cycles, the extra bytes over the wire. That’s the curious property of opinions. In frameworks and libraries, opinions have cost. Changing the intention’s direction is not free. To articulate this as our fourth stanza: opinion, or the difference between the vectors of intention of two adjacent layers, always comes at a cost.

Once incurred and embedded into the framework, this cost is difficult to give up, even when the platform underneath changes for the better. For example, even though IE6 has gone away, jQuery still carries the darn selector-parsing code, which like any proper barnacle, has grown all kinds of neat optimizations.

The cost is proportional to the degree of opinion. For example, if I decided to build a Javascript framework that completely reimagined UI rendering as graphs or three-dimensional octagonal lattices rather than trees, I would quickly find myself having to reinvent the universe. The resulting artifact will weigh some megabytes and consume some kilowatts, with DOM trees still impishly leaking out of my pristine abstractions here and there, necessitating tooling and various other aids to ensure successful launches of user experiences, built using my awesome framework.

What’s even more alarming is that opinion costs have a tendency to compound. Should developers find my framework appealing, I will see more high-profile sites adopting it, causing more developers to use it, extend on top of it, and so on. The outcome of this compounding loop is that users will find more of their computing resources drawn to chew on my opinions.

Commonly, this compounding effect tends to be indirect and delayed enough that originally, the framework or library appears to be providing a lot of benefit at nearly no cost. Only over time, the compounding cost of opinion swings the net value curve back into the ground — and we’re left with massive debt that swallows us and dims the vitality of the ecosystem around us. Which brings us to the last stanza: opinion costs compound and are, directly or indirectly, shouldered by users.

This effect of compounding costs crosses all layers. If the platform designers came up with the primitives that ultimately don’t satisfy the needs of users, the framework and library developers who attempt to rectify this situation will always incur opinion costs. There is no cheap way to salvage mistakes of the platform designers. Design of the platform primitives matters, because it establishes the opinion cost structure for the entire developer ecosystem.

Applying this lens, it seems that platform developers have the highest leverage for reducing the overall cost of opinions carried by users. This is why platforms are better off not sitting still. Every broadly used platform is spurred to learn how to evolve – even if at glacial pace – toward reducing the overall cost of opinion introduced by developers who layer on top of it. So if you’re designing a new platform, you would be wise to invest into building capacity to evolve into it. And if you’re a steward of a mature problem, your best bet just might be teaching it how to change.

Tension in Shared Mental Model Space

This just occurred to me today, so I am writing this down while it’s fresh. When I talk about the shared mental model space (SMMS), I usually picture it as something like a bunch of circles, one for each individual within a group, and these circles are touching a larger circle that represents the mental models that are shared by all members of the group. It’s not the most accurate diagram, but it will work for this thought experiment. As I was reflecting on the desired properties of a SMMS, I realized that there’s a tension at play.

On one hand, I want my organization’s SMMS to be large enough to allow us to understand each other, to be “on the same page” so to say. At the same time, I am recognizing that a SMMS that perfectly encloses all of the individuals’ mental models is both impossible and undesirable. It is impossible, because in trying to achieve perfect closure, we encounter the paradox of understanding: since everyone’s internal mental model also includes the enclosed models themselves, we rapidly descend into the hall-of-mirrors situation. It is undesirable, because a team where all of the opinions are known and completely understood is only facing inward. There is no new information coming in. So there appears to be a sort of polarity in the size of the shared mental model space – and a tension it embodies.

A SMMS can both work for and against the organization. As it grows, the organization becomes more blind to the externalities. A cult enforces the suffocating breadth of SMMS among its members, since that’s what makes it impervious to change. As SMMS shrinks, the organization stops being an organization. If the diversity of perspectives is high, but there’s no way to share them, we no longer have a team. It’s just a bunch of people milling around.

The weird thing about polarities is that the sweet spot in the middle is elusive. Sitting right in the middle of the tension, it’s more likely to be periodically passed by the team — “OMG, this was amazing! Wait, where did it go?” — rather than having the team settle down in it. Even more annoyingly, diminishing the SMMS decreases the chances of reestablishing it — and large SMMS makes introducing new perspectives impossible. Both extremes are “sticky,” which means once an organization moves past some threshold, only a severe external perturbation can dislodge the state of its SMMS.

So it appears that it really matters how we decide to establish this space where our mental models are shared, and how we garden this space. The thing that becomes more and more evident to me is that if we do so in an unexamined way, we are unlikely to have a sustainable, resilient organization.

Radical Candor as fallback notch locator

Have you ever experienced this really fun moment when a few of concepts you already knew suddenly came together as something new and completely different when revisited? This just happened when I was looking at Kim Scott’s Radical Candor framework. Putting it next to the ideas of the Adult Development Theory, I realized that it might be a rather useful tool to locate my fallback notch.

I already mentioned fallback a few times in my writing. It’s this phenomenon when we, despite our best efforts, show up as developmentally earlier versions of selves. A concept that’s been really useful in my own self-work was a notion of the fallback notch, a hint at which I first found in Lisa Laskow Lahey and Robert Kegan’s Immunity To Change. The fallback notch is the habitual stance I take when I am experiencing the effect of fallback. The notchiness part of it is that it happens kind of automatically, like a hard-learned, yet almost-forgotten habit, a Schelling point for a disoriented mind. When fallback triggers, that’s the hill where I tend to regroup. I’d found that this notch is context-specific, but rather useful to name when reorienting. “What, what’s happening? <notch locating happens> Ah, I am currently in a Diplomat mindset… Hmm… I wonder what led me here?” Let’s see if we can use Radical Candor as a compass to help with reorienting.

The first – and most significant – leap of faith I invite you to take is the mapping of the quadrants to developmental stages. Using Bill Torbert’s classification, and our intuition, we can kind of see that Manipulative Insincerity loosely maps to the Opportunist mindset and Ruinous Empathy to Diplomat. Those two are fairly straightforward. The cunning trickery and unscrupulous antics of the Opportunist appear to be perfectly captured by the words “manipulative” and “insincerity.” Similarly, the Diplomat’s warmth and keen desire for getting along are well-described by “ruinous” and “empathy.” The other two quadrants need a bit more cajoling. The ornery obstinance of recognizing, yet unwilling to accept others’ perspectives of the Expert often manifests as Obnoxious Aggression. I’d found this notch particularly present when, in a subject in which I view myself an expert, someone comes in to ask questions that could potentially buckle the idea’s entire foundation. “How dare they! They must be corrected! <rising irritation leading to self-righteous condescending rants>” Finally, the Radical Candor quadrant is the zenith of the framework, representing the relative flexibility of the Achiever to consider and absorb multiple perspectives, yet keep the eye on the prize of their own objectives.

With the quadrants mapped, we can now use the full depth of the Radical Candor framework as our fulcrum for self-developmental purposes. The idea of mapping our interactions and situation into quadrants, described by Kim in her book, can serve as a clustering tool, helping us spot the particular fallback notches we find ourselves in. Further, we can use the quadrants to find our way back from the notch. Knowing that I am in the Ruinous Empathy quadrant helps me see that I fell all the way back to the Diplomat mindset, and getting out of that notch might start with reminding myself that I do indeed know what I am doing (regaining the Expert ground) while still staying connected to empathy and compassion of the upper quadrants. 

Another thing that stood out for me: the Radical Candor framework appears to be Achiever-situated. It presumes that its practitioners are themselves at least at the Achiever developmental stage. It is useful for those who recognize that they temporarily fell back into behaviors they understand as detrimental to their path forward. This probably means that the framework quadrants will look weird to folks at the earlier stages. If I am stuck in the Expert trap, the Radical Candor quadrant will feel like a weird tautology. “Of course I care, that’s why I need to yell at them and shake some sense into them!” Things will look even more bleak if I am just now adopting the Diplomat mindset. The Radical Candor will look like a scary regression into the conflict-ridden Opportunist land. “Oh come on now, we just figured out how to get along. Why are we trying to mess things up again?” And of course, for the Opportunist, the whole story will seem like an elaborate ruse, a corporate prank to trick me into being more gullible and obedient.

Adult development and coaching expectations

A couple of us were chatting about coaching. It was such an amazing generative conversation that I kept walking around, thinking about it over the weekend. As a result, this somewhat late insight materialized, a remix of the Adult Development Theory (see my primer to get your bearings) and the expectations people might have around leadership coaching. This story hops along the stages of adult development (using Bill Torbert’s nomenclature here) and offers my guesses of how I might perceive coaching with the mindset of that stage.

With the Opportunist mindset, any sort of leadership coaching will likely appear as a hook to exploit or a threat that someone might exploit me. Any engagement will have this “let’s see if we can hack this to do my bidding” quality to it. For example, I might use it a bit to see if this would help me secure some advantage, such as attaching myself to a figure who I might perceive as powerful. Any genuine engagement for the purpose of coaching is unlikely. I engage to exploit.

With the next, Diplomat mindset, the deep attachment to shame of failure will hamper any active engagement. If I am asked something, I am petrified to answer in the wrong way. However, I would crave passive learning. I will glom on to anything that looks like advice and wise words, and I would be very happy to react to these words with “likes” and “thumbs up,” even if I don’t fully understand them. With this mindset, coaching software is primarily a way to procure approval and ensure that I am part of the “in-crowd” of those who learn from these really smart people who are clearly authorities on leadership. I engage to belong.

Further down the rabbit hole, the Experts mindset presents the same fear of failure, but now it is bolstered by my expertise. This configuration is least receptive to coaching. “Why would I want a coach? That’s for noobs. I already learned everything there is to know.” By the way, in my primer, I portrayed this developmental stage as transitional, as something that we experience on our way to the next stage. Since then, I’ve changed my mind. Expert is a very stable configuration. With fear of failure on one side and considerable wisdom on the other, it is often a lifelong trap of perpetual, agonizing slow-boil of misery and dissatisfaction with life. When inhabiting the Expert mindset, I am unlikely to hear feedback and will resist the nudges to even try coaching. I don’t engage.

The Achiever mindset turns this attitude upside down. The craving for coaching comes roaring back. I want to tussle with you and I know that every time I do, I will learn something that will take me closer to finally achieving the maximum level of effectiveness. I demand coaching advice. I set the schedule, come prepared with topics at hand, and ready to dig deep. I might even be hard to keep up with, and I might even fire my coach if they can’t. I want to have the latest and greatest in coaching strategies. Don’t give me any of that “how to win friends and influence people” stuff. I engage to get results.

Eventually, the hard-charging Achiever mindset gives way to something different. Somewhere, somehow, the realization emerges that the “maximum level” is not only unattainable, but also absurd as a notion. There’s a bit more shift in the attitude toward coaching. I still see it as valuable, but I am realizing that coaching is a nearly moment-to-moment activity. Everyone has so much to teach me. Every interaction is a coaching moment. I still talk to my coaches, and look forward to our conversations, but they no longer have that edge of Achiever angst. We talk to uncover insights hiding in the nuance, to play the hacky sack of ideas, with deep respect for each other’s experiences. I engage to generate.

Whew, that was fun to type out. I am realizing now how I loosely traced the same outlines Jennifer Garvey Berger drew in her seminal Changing on the Job. So if you’re interested in diving deeper into this particular ocean of ideas, that’s where I would direct you next.

Short-term divergent, long-term convergent

A conversation with colleagues brought this insight to the surface. We were talking about cultivating generative spaces, where a diversity of perspectives is cherished and celebrated, the stakes are low to examine all of them, and enough room for everyone to jam on these perspectives.

Applying the diverge/converge lens, it might seem that such spaces would be classified as divergent. After all, this is where it’s “the more, the merrier,” and everyone is encouraged to pile on their own perspective or riff to create entirely new ones. From this vantage point, generative spaces are the sources of divergence. These are the spaces we reach for when we need to populate that rich pool of ideas.

It was a bit later in the conversation, when we moved on to the topic of convergence and increasing the shared mental model space across the organization that a curious thought occurred to me. What if we shifted our attention to a different set of outcomes that a generative space produces? Namely, the outcomes that result from multiple people playing with a great variety of perspectives. Every new perspective that I try out results in me better understanding it, and thus, acquiring a mental model behind it. Over the course of participating in a generative space, I become more aware of how my peers see the world, and so do they. Our shared mental models space widens. Even though it might look like we’re producing diverging ideas, the process helps us better understand each other, and thus, is convergent in nature.

Generative spaces are divergent in the short term, but convergent in the long term. My intuition is that a sustained generative space is likely the most effective way for an organization to become more coherent and productive, while at the same retaining awareness of its surroundings. While they could seem like “few folks just talking about random topics,” generative spaces might just be the recipe to aid an organization that struggles to converge.

Of course, this makes generative spaces rather counterintuitive and often difficult to describe. “How can we afford just having a chill conversation with no agenda?! We have stuff to design/build/ship!” Yet, every organization has watercooler or hallway conversations, and idle chit chat between meetings. Next time you’re in one, pause to reflect and notice how often they have the subtle overtones of generative spaces. We yearn to jam and riff on ideas. We want to share ours and see others play with them. If only we had space to do that.