The engine and the car

The whole large language model space is brand new, and there are lots of folks trying to make sense of it. If you’re one of those folks, here’s an analogy that might come handy.

Any gasoline-powered car has an engine. This engine is typically something we refer to as a “V8” or “an inline 4” or sometimes even a “Wankel Rotary Engine”. Engines are super-cool. There are many engine geeks out there – so many that they warrant a video game written for them.

However, engines aren’t cars. Cars are much more than their engines. Though engines are definitely at the heart of every engine, cars have many additional systems around them: fuel, electrical, steering, etc. Not to mention safety features to protect the passengers and the driver, and a whole set of comforts that we enjoy in a modern car. Pressing a button to roll down a window is not something that is done by the engine, but it’s definitely part of the whole car experience.

When we talk about this generation of AI systems, we typically talk about large language models (LLMs). In our analogies, LLMs are like engines. They are amazing! They are able to generate text by making inferences from the massive parametric memory accrued through training over a massive corpus of information.

However, they aren’t cars. One of the most common mistakes that I see being made is confusing engines (LLMs) with cars (LLM-based products). This is so common that even people who work on those products sometimes miss the distinction.

When I talk to the users of the PaLM API, I see this confusion show up frequently in this manner: developers want to reproduce results from the LLM-based products like Bard or ChatGPT . When they try to get the same results from the API, they are disappointed that they don’t match. Factuality is lacking, API can’t go to the internet and fetch an article, etc. 

In doing so, they confuse the engine with the car: the API, which offers access to the model, is not the same as the products built with it. With an LLM API, we have a big-block V8. To make it go down the road, we still need to build the car around it.

 To build on this analogy, we live in the early age of cars: the engines still figure prominently in the appearance and daily experience of a vehicle. We still have to turn the crank to start the car, oil the engine frequently, and be savvy enough to fix minor problems that will definitely arise.

As our cars become more refined, the engines get relegated into a well-insulated compartment. Users of cars rarely see them or operate on them directly.

This is already happening with LLM-based products. Very few current offerings that you might encounter in public use are LLMs that are directly exposed to the user.

So, when you use a chat-based system, please be aware that this is a car, not the engine. It’s a tangle of various AI patterns that are carefully orchestrated to work as one coherent product. There is likely a reasoning pattern at the front, which relies on an LLM to understand the question and find the right tool to answer it. There is likely a growing collection of such tools – each an AI pattern in itself. There are likely some bits for making sure the results are factual, grounded in sources, and safe.

As the LLM products become more refined, the actual value niches for LLMs become more and more recognizable. Instead of thinking of one large LLM that does everything, we might be seeing specialization: LLMs that are purpose-designed for reasoning, narration, classification, code completion, etc. Each might not be super-interesting in itself, but make a lot of sense in the overall car of an LLM-based product.

Perhaps unsurprisingly, the next generation of cars might not even have the same kind of engine. While the window control buttons and the steering systems remain the same, the lofty gasoline engines are being replaced with electric motors that fit into a fraction of space. The car experience remains more or less the same (aside from the annoying/exhilarating engine noise), but the source of locomotion changes entirely.

It is possible that something like this will happen with LLMs and LLM-based products as well. The new open space that was created by LLMs will be reshaped – perhaps multiple times! – as we discover how the actual products are used. 

Steady winds, doldrums, and hurricanes

It just so happened that this year, many of my friends and colleagues ended up looking for new opportunities, and in our conversations, I ended up shaping this metaphor. As most metaphors, it’s not perfect, but hopefully, will stir some new insights for you.

We kept trying to describe the energy within organizations and the animating forces that move them. These forces can make our lives inside these organizations a delight – or a complete and utter misery. It seemed like a good idea to understand how these forces might influence us and find ways to sense these forces early. Preferably, even before committing to join a new team.

The idea of presenting these forces as winds seemed rather generative. If we look at the innovation S-curve, we can spot three different kinds: steady, doldrums, and hurricanes. They don’t exactly match the stages I outlined back in the original article. Instead, these winds follow the angle of the S-curve slope.

⛵The steady winds

Steady winds are consistent. We can feel them going in one direction and they change infrequently. Apparently sailors love them, because they provide a predictable way to navigate. Even if it’s not a tailwind, a steady wind can be harnessed through tacking.

Similarly, organizations that are in the upslope of their development tend to have a relatively consistent animating force that feels like a steady wind. Usually, there’s some big idea, some intention, and a group of highly-motivated individuals who set the direction of this wind.

We can feel it as soon as we step into an organization. It usually appears as the ambition of the  charismatic leader/founder, who knows exactly what they want and is doing everything they can to make it possible. More rarely, it might also appear as a set of ideals that depict some future state of the world – and this team has the fire (and funding) to bring it forth.

Steady winds aren’t always great. Sometimes, a steady wind’s direction is simply incompatible with where we want to go. It might trigger aversion in us, or be in discord with our own principles. The leader might be charismatic, yet have character quirks we deem appalling. The big idea might indeed be big, but no matter how much we try to suspend disbelief, we keep finding it laughable.

At the same time, steady winds bring clarity. They give us a very good idea of what this team is about and where they are going. These folks are going someplace. It’s on us to choose to go there with them.

When considering a new team and sensing a steady wind that moves it, ask yourself: is this wind aligned with what I myself want to do? Does it stir fire in my belly? At the very least, can I tack into this wind in a way that moves me where I want to go? And of course: am I at the place where I want to go on an adventure?

Because joining steady-wind teams definitely brings adventure. It might be glorious and awesome, or it might be like the Donner party, with all the fixin’s of freezing to death, scurvy, and/or dysentery. Only time will tell.

If the wind is favorable and adventure is what you seek, such a team might be a good fit.

⛳ The doldrums

Prior to the invention of motors, doldrums were a terrifying thing for sailors. Doldrums meant that to go anywhere, we have to break out our oars and turn our own sweat into motion. There is no wind to help us go anywhere.

Organizations tend to experience doldrums at the top of the S-curve. Once the niche is fully explored and the product or service is optimized to fit it exactly, it is really not clear where to go next. All successful products end up experiencing this. We can see this as fewer interesting changes in them, and a deluge of incremental improvements that may sound exciting, but don’t actually add up to anything like the stuff the organizations used to produce at the upslope.

To get anything done in this organization requires some form of consensus. There are usually processes. Approvals. Reviews. Endless, exhausting discussions. When in doldrums, there’s a prevailing sense of powerlessness, often accompanied by a weird combination of comfort and toil. Everything is hard, but at least it’s exactly the same as yesterday.

Leaders who used to produce the steady wind at the upslope typically leave when they encounter the doldrums. We won/lost. Why stay? Instead, they are replaced by sailors. These leaders concentrate more on preserving what was accumulated so far. Risk is frowned upon. 

It’s not like nothing gets done in organizations stuck in doldrums. There’s always activity, and an appearance of movement. To create this appearance, there’s a syndrome of chronic bigness: every new initiative is bigger than the previous one, ever more bombastically described and painted in brighter colors. Underneath is the same dull surface of still water.

Doldrums aren’t necessarily a red flag for joining. If what you’re looking for is the steady stillness of boring, yet never-ending work, that might just be the place. Large bureaucracies like government agencies and corporate giants have large organizational swaths that live in the doldrums – and necessarily so. Not everything needs to be an adventure. Sometimes, the slow and steady beat of the oars is the only thing that keeps the grand ship inching forward.

However, if you’re seeking something to fill your sails, please keep walking. Committing to a doldrums team will suck the soul out of you and is not worth it.

🌀 The hurricane

The final part of our story is hurricanes. Sailors caught in storms just hang on to their life, trying to survive and keep the ship afloat.

Similarly, organizations find themselves in turbulent waters. This typically happens on the downslope of the innovation S-curve, when the quiet ride through the doldrums is eventually replaced by contact with reality.

In the hurricane, there’s lots of wind. It’s blowing in all directions. To continue our metaphor, the wind is the animating force that is usually created by organization’s leaders and their intentions. In the hurricane, this intention is chaotic and unpredictable. And it’s usually reactive,  spurred by some external threat.

The downslope of the S-curve isn’t fun. The collective anxiety of leaders who got used to the doldrums creates a vicious cycle, exacerbating the situation further. The overall direction is unclear, but not for the lack of effort. There’s lots of movement, and lots of force, all going in circles.

On very, very rare occasions, a new leader emerges and manages to set the steady wind, bringing the team out of chaos. I have seen it happen, but haven’t experienced it myself. 

Unless you’re a total glutton for punishment or have a severe savior complex itch, it is difficult to recommend joining an organization in the hurricane. The trouble is, it’s often hard to tell. It is in nobody’s interest to reveal the true state of disorder to the candidates. So the hurricane-embattled team might appear as either doldrums or steady winds, depending on who you ask.

One of my colleagues recommended this approach: find someone on the inside. Someone who might still be there or left recently. Ask them candidly: “is this a sh*t show?” Watch their reaction and prod a bit. Look for stories that sound like aimless grasping for straws and high anxiety among the team’s leaders. Those are the telltale signs of the hurricane.

Diving into unpredictability

My previous essay on the topic of unpredictability generated a few insightful comments from my colleagues and friends. One of them led to this vignette.

It is very tempting to imagine that some people are just generally less susceptible to the discomfort of unpredictability than others. It might even feel like coming up with a way to gauge one’s ability to thrive in unpredictable situations would be a useful tool.

My intuition is that this stance needs a bit more nuance. As humans, we all abhor unpredictability. We rarely actually “thrive” in it, at least over the long run. The metaphor that comes to mind is diving.

Some people are great divers. They can spend a significant amount of time under water. They can go deep and explore the parts of the seabed inaccessible to anyone  else. At the same time, nobody would claim that great divers can actually live in the depths of the sea. We all need to come up for air.

In this metaphor, unpredictability is water. If we stay in it for too long, we drown. I see the desire for predictability – or homeostasis – as a gravity-like force that animates all of us. It isn’t something we can completely detach from – though stoics and buddhists try. Just like air that we need to breathe, predictability is something that is essential for nourishing our minds. Our minds are predictive systems. Unpredictability is anti-mind.

Great divers – those who can endure unpredictability better than others – are those who invest generously into techniques and strategies that enable them to stay in the deep longer and even enjoy it. However, prolonged exposure to it will still take the toll, and the need to come up for air will always win over.

Diving into predictability is hard work. Just like with any good diver, if they are making it look effortless, we can bet that a lot of effort was put in before. And just like with any good diver, the “true pirates” who appear as thriving in unpredictability are nearly always those with the decades of practice, with all the blood, sweat, tears, and scars such a practice entails. One of the foundational elements of this practice is finding a way back to the fresh air of a predictable environment.

Sometimes you gotta hit the wall

I’ve probably written about this a few years back, but I still find this mantra useful and worth repeating. It applies to the situations where we’re stuck but we don’t know that we’re stuck – not yet.

When we’re in this state, we have a sense that we’re still moving forward, and we’re making all the right moves. We get upset when our friends or colleagues cautiously share with us that we might be spinning our wheels. Yeah, there’s some loss of traction, but if we just keep going, we will figure this thing out. Just one more push.

Particularly for technologists and other admirers of modernist thinking, the likelihood of becoming stuck in this way somewhere along our careers is pretty high. The idea that if we know what we’re doing and we’re doing everything right, then things should work out according to our plans – it’s just so damn seductive.

We can last quite a bit of time in this purgatory of delusion. There are just so many options to choose from. It’s the environment around us that is all wrong. Someone is actively conspiring against us. There are some indicators that show clearly that we’re still moving forth as planned. The more clever and quick-thinking we are, the more likely we are to come up with a story that keeps us stuck.

Inevitably, there’s a moment when it all comes apart. We finally hit the wall. We’re in shock,  feeling injured by the cruel reality and betrayed by it. But – it is only when we hit that wall do we get the chance for self-reflection. There’s an opportunity, when the shell of self-delusion is cracked, to actually gain some clarity. We might remember our colleagues’ gentle hints and worried faces, the early signs of stuckness we’ve chosen to ignore, and the now-obviously illustory stories we’ve told ourselves.

Should we experience it, this moment is a significant milestone. It allows us to create a little space between reality and the stories we tell ourselves. It allows us to hold our stories as objects instead of being subject to them. Experienced once, it’s a perspective that can be temporarily lost, but never fully forgotten. Next time the allure of modernism tempts us, we might still feel the pull – but think twice about answering the call. Once we’ve hit that wall, we’ve learned that “knowing what we’re doing” and “doing everything right” are just stories we tell ourselves, and they have little to nothing to do with reality.

The somewhat sad part is that this lesson can not be taught. No amount of explanation or teaching will bring one closer to the precious insight without the painful experiential part. This particular bit of wisdom can only be gained by face planting into the unyielding, uncaring reality at full speed. Sometimes you just gotta hit the wall.

Pace layers of predictability

I’ve been talking about pace layering a lot, within the dandelions and elephants story and in other pieces. Here’s yet another way to apply this framing.

One thing that stood out to me was this notion of a common force that animates their formation. Here’s my guess: this force is the desire for predictability.

For example, in organizations, there is usually a larger group — often a dominant majority — of folks who seek a fairly predictable environment. They usually feel rather uncomfortable about the uncertainty of a problem space, and you can hear this discomfort in phrases like “just tell me what to do” or “we need clear timelines and deliverables”. There is nothing wrong with this stance. I find myself in this group at times, especially when I am in fallback. Another way to think of it is that we find ourselves here when our predictability footprint expands. This group tends to seek “one true shared mental model” and usually reacts with pain to disconfirming evidence, forming the slowest-moving predictability pace layer.

To manage that pain, there’s a much smaller group of those who are able to face unpredictability a bit more. These folks have a slightly higher tolerance for ambiguity and can experience polarities not as a series of harrowing swings back and forth, but rather as one nuanced system. They can play with multiple conflicting mental models and see disconfirming evidence as input, rather than pain inflicted. This ability is not without cost, and usually requires continuous support and scaffolding.

This smaller group forms a much thinner and faster-moving predictability pace layer on top of the slower layer. When an organization employs such folks effectively, they become instrumental in gently evolving the “one true shared mental model” of the larger group in a direction that is long-term productive for this organization. This is the stance that I myself enjoy the most and feel that resonant sense of aligning with Purpose.

Sometimes a team is lucky enough to have true pirates: a handful of people whose predictability footprint is so small that they are able to go where even the most ambiguity-tolerant people dare not touch. Disconfirming evidence is necessary sustenance to them. These folks can examine the load-bearing beliefs in ways that would terrify or at least profoundly upset most members of the organization. They can do deep ontological dives and come back unfazed, with insights that have the power to shape the future of the organization.

When employed effectively, these are the peeps that establish foundational frameworks within which the gentle evolution of the organization occurs. This is the fastest-moving predictability layer where I aspire to be, even though most of the time, I pop up to that layer only momentarily.

Of course, this is not some sort of normative layout of layers that every organization must possess. My guess is that each organization has their own layer configurations. 

What’s important about them is that they are typically mostly separate and insular from each other – and for good reason. Exposing folks at the lowest layer to the more intense pace of the higher layer will rapidly trigger allergic response. And giving them a sense of the top layer’s pace will seem like Lovecraftian horror. Boundaries tend to arise to prevent such shenanigans.

What’s most curious is that these pacing layers rarely respect hierarchies and organizational structures. There could be leaders of large teams who crave predictability. There could be random junior team members who are surprisingly great at diving into the abyss of uncertainty and bringing back useful insights. The ability to tolerate unpredictability changes with one’s circumstances, and hierarchies tend to strive for permanence.

As a result, the insulation between layers tends to develop in haphazard and unproductive ways. Within predictability-craving organizations, those who are comfortable with uncertainty are deemed “troublemakers” and shunned or ignored. Conversely, folks who desire more predictability are labeled as “unimaginative” in places where experimentation and exploration are valued. Instead of recognizing mutual significance and collaborating, teams at different predictability pace layers resent each other’s differences.

In practice, this means that harnessing the full potential of this pace layering and using it to the advantage of the organization is very uncommon. I keep wondering what a team that is designed around predictability pace layers – rather than in spite of them – would even look like.

Given that overall levels of unpredictability around us seem to be ever-increasing, this might be an important challenge to take on. Perhaps you, my readers, will find an opportunity here.