Archive of posts with tag 'Complexity'

The Simplest Thing That Could Possibly Work →

January 14, 2025 • #

This latest issue of Res Extensa riffs on an idea from wiki-inventor Ward Cunningham:

“Given what we’re trying to do now, what is the simplest thing that could possibly work?” In other words, let’s focus on the goal. The goal right now is to make this routine do this thing. Let’s not worry about what somebody reading the code tomorrow is going to think. Let’s not worry about whether it’s efficient. Let’s not even worry about whether it will work. Let’s just write the simplest thing that could possibly work.

I love this. I’m a huge proponent of getting started on something as an antidote to stuckness. Writer’s block, uncertainty, fogginess. There’s no panacea that’ll give you all the answers, but the best tool for clarity is action. Getting started is the fastest path to finding what’s next.

When Cunningham says “the mere act of writing it organized our thoughts,” he’s speaking to this idea that it’s rarely possible to know the specifics of the goal (or the means to get there) until you get started. Starting on the thing kickstarts the discovery engine.

Nearly every time I’m doing anything creative — building a software feature, writing an article, building something in my shop — the final state ends up somewhere other than what I predicted at the start. During the process of making, I learned things, or I came to realize things I didn’t know I needed or wanted.

When you’re just getting started, you don’t know what the possibilities are yet. To know what to build, you’ve got to start building.

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February 10, 2024 • #

Simplicity on the Other Side of Complexity →

My latest post on Res Extensa:

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The Other Side of Complexity →

February 9, 2024 • #

The latest issue of Res Extensa, on the path from “simplistic” to “simple” understanding, over the hill of complexity:

Superficial simplicity is our first impression, a naïve jump to conclusion. Simplicity on the other side of complexity is wisdom. Wisdom comes to us in rules of thumb, heuristics, knowledge gained from hard-won experience. The experience comes from grappling with the complexity so we can distill with simplicity.

Profound solutions are simple, but they’re post-complexity simple. Elegant, robust solutions are rooted in deep understanding. Whether they’re laws, books, or products, the ones with the most impact climbed over the complexity hill for us.

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February 3, 2024 • #

The Shirky Principle →

“Institutions will try to preserve the problem to which they are the solution.” — Clay Shirky

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Simplifying with Gall's Law →

October 25, 2023 • #

In the latest issue of Res Extensa, I dove into “Gall’s Law”, which says:

A complex system that works is invariably found to have evolved from a simple system that worked. A complex system designed from scratch never works and cannot be patched up to make it work. You have to start over with a working simple system.

Too often I see a team propose a solution to a problem that involves making what we’ve got more complicated. Adding more people, more processes, more tools. “Maybe if we start using Salesforce it’ll get better.” “Perhaps if we bring in Consultant X they’ll help us through.”

Muddling through is part of the process of building. Don’t get upset about it, just get back to first principles and simplify:

Like most great mental models, Gall’s Law follows its own logic and keeps it simple. It’s a basic principle that helps filter your approach and ask yourself the question when faced with a complex problem: Is my approach simple enough? Does what we’ve already pieced together work before we add more parts, people, or processes?

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Pond Brains and GPT-4 →

April 28, 2023 • #

Are complex ecosystems like ponds actually smarter than we are? Are they “thinking”? Gordon says yes:

Evolution is a pragmatist. It only cares about actual behavior. It is the getting and the doing that matter. The how can be approached in many different ways, through pheromone trails, or trophic networks, or nerve nets, or brains, or symbolic representation. Evolution doesn’t care. If you can get information and do something about it, you are thinking.

All we really need to say a system is “intelligent” is that it incorporates feedback. Loops generate reactions, learnings from past iterations:

What else? Suddenly, we see that we embody many forms of intelligence outside of our brains. Our DNA, for example, encodes the memory of millions of years of experience within our environment. Every life lived by our ancestors, all the way back to that first single cell. Each recursive step in the game of life, a gift to us.

I also loved this quote from cyberneticist W. Ross Ashby:

“To some, the critical test of whether a machine is or is not a ‘brain’ would be whether it can or cannot ‘think.’ But to the biologist the brain is not a thinking machine, it is an acting machine; it gets information and then it does something about it.”

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Mycopunk Principles →

April 25, 2023 • #

What would it look like to apply principles of mycelial (fungal) networks to other systems? A sampling:

🕸 NETWORKED/DISTRIBUTED/ANARCHIST: No central command. Local subsidiarity, problem solving at the edges.

💪 ANTI-FRAGILE: Disturb a mycelial network, and it grows more dense.

🌳 FRACTAL: Self-similar structures up & down.

Bookmarked to revisit later. /via the Subconscious Discord server.

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Simplicity on the Other Side of Complexity

April 21, 2023 • #

“I would not give a fig for the simplicity on this side of complexity, but I would give my life for the simplicity on the other side of complexity.”

What a great line from Oliver Wendell Holmes.

When you think you’re coming up with “simple” responses to complex problems, make sure you’re not (as Bob Moesta says) creating “simplicity on the wrong side of the complexity.”

What we really want is to work through all the tangled complexity ourselves as we’re picking apart the problem and designing well-fit solutions.

A great (simple) solution to a complex problem can be that way because someone’s taken on the burden of detangling the complexity first.

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The Midwit Trap →

September 2, 2022 • #

Some solutions rely on convoluted chains of logic that are strictly dependent on every single statement being true. They are more likely to have hidden “divide by zero” problems that may be easily noticeable to the experienced practitioner but are invisible to the layman. Simple solutions might have errors too, but they will be much more obvious. Also, complicated chains of logic “feel” correct because a lot of the steps will be verifiably true; people sometimes forget that all of the steps have to be true for the entire argument to have any truth.

Complicated stories seem more likely to be logically sound to a midwit, but simple strategies are actually far less likely to have hidden land mines.

I’m a big fan of looking for simple explanations for problems, or at least starting with simple explanations and testing them before overcomplicating your rationale. The midwit memes seem like unrealistic parody, but you see these situations in the wild all the time. Self-proclaimed “experts” desperately want to have complex solutions to problems with complex systems — hell, one very well may be required. But at least invalidate the Pareto-fitting, more-likely simple solutions first.

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Systems and Constraints →

August 18, 2020 • #

There are so many good little pieces in this brief interview with Alicia Juarrero, who studies complex systems and complexity theory.

Three options are possible once a complex system reaches a threshold of instability: adaptation, evolution, or disintegration. There is never a guarantee that the whole will not collapse, which it will do if we are unable to adapt and evolve to achieve a new coherence or fit. I think of adaptation as modifications within a given space of possibilities. You either expand your adaptive capacity or move to a more stable location within that adaptive space.

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The Efficiency-Destroying Magic of Tidying Up →

November 19, 2019 • #

A thought-provoking post from Florent Crivello. Engineers’ continuously seek structure and organization assuming that it’s a proxy for efficiency. Here the author points out that with new tools enabling AI systems to design the most efficient way to construct things, you don’t get anything remotely like what a human would generate.

Bottoms-up systems like organically-spreading cities, evolved species, weather patterns, and the like don’t naturally form looking like an urban planner’s dream — they’re much messier (but often the most efficient).

Planners may make their maps look better when they use zoning to separate the city into business, residential, and commercial neighborhoods, but they also destroy a subtle, efficient balance. They forget that the only activity that goes on in any city is that of people living their lives, which requires all the activities above — preferably in close proximity. Splitting a city into residential, commercial and business zones is like throwing dough, cheese and pepperoni into the different compartments of a bento box and calling it a pizza.

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