Ep 291 | Complex Systems

Brian Gubernick explains Gall's Law: complex systems that work always evolved from simpler ones, never designed from scratch. He traces examples from Python to SpaceX's rockets, then advises starting with a small prototype, gathering feedback, and avoiding over-engineering to build something that actually scales.
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Thank you for joining me today. It's Brian Gubernick, and welcome to the No Days Off podcast, where we believe that every single day brings a new opportunity to get better. I have a tendency in business more than any other place to overcomplicate some things, especially when it comes to systems. I have a desire to, to solve for things quickly. And I know the answer may be complex and robust and hell, it may take a long time to get there, but I don't have a lot of patience sometimes. And I want to go out and I want to create what would be maybe a complex system from scratch. Well, there's a law, it's called Gall's Law. It's a principle. Coined by a guy named John Gall, who was a systems theorist. And, and Gall more or less states and proves that a complex system designed from scratch never ever works, and it cannot be made to work. So what I was saying when we started, I have a desire to go solve for things, and I will make it more complex than, or as complex as I think it needs to be. But the reality is, according to Gaulle, that my complex system's never going to work. Instead, a simple system that you end up building on over time is the path to success. So this principle, what Gaulle states, is that a complex system that works is invariably found to have evolved from a simple system that worked. In other words, complex systems oftentimes arise from simpler systems. Through a process of iteration and of evolution. We've talked quite a bit here at No Days Off around crawl, walk, run, and this is a very similar concept. This— Gall's Law highlights the idea that building successful complex systems typically involves starting with something rather simple and then gradually refining and expanding it over time. It really emphasizes the importance of incremental development, learning from experience, breaking things and continuing to fix them and learn from them. And this is what leads to effective systems. Now, where, where do we see this sort of thing show up? I think, uh, while I'm not, you know, super techie, I think you could look at the evolution of programming languages. Uh, in the early days of programming language, there were things like Python and JavaScript, and they evolved from simpler languages. For instance, Python evolved from what was called ABC, and JavaScript evolved from what was called LiveScript. These languages started with pretty basic features and they gradually, gradually incorporated more complex functionalities. How about, um, social networks? Maybe one we could, you know, all better relate to. Things like Facebook and Twitter, they actually began as pretty simple websites with pretty basic features like just user profiles or status updates. And over time, they actually evolved into these complex ecosystems that supported all the features that we see today, like content, multimedia content sharing, and messaging, and targeted advertising, user feedback, and all these other technological advancements. As a matter of fact, if you get on Instagram or Facebook right now, you'll be prompted to use Meta, Meta AI, which is their Llama 3 AI program. It didn't start there for Zuck. He didn't start the company with that sort of complex system in mind. Instead, he started with a far simpler system that's evolved over the past 10 or 20 years. How about something like, uh, transportation systems like railways and highways? These things started with simple, uh, routes connecting a couple locations. And then as demand grew and technology advanced, these systems expanded and started to become more intricate, and new routes were created. Different modes of transportation were created. Infrastructure like tunnels and bridges They were created. This was Gall's, Gall's law at play. Simple system leads to complex system over time. So knowing this, and there's lots and lots of places we could point where you could see it play out. If you take a step back, you could probably think of a few right now, just in talking, you know, I'm thinking about SpaceX and that's one where someone may say, well, no, Elon just went out and created rocket ships. And To an extent, sure, but the Falcon 1 led to the Falcon 9, and Falcon 9 created the Dragon spacecraft, and Dragon created Starship. Starship is dramatically more complex than Falcon 1. So the starting point may have been complex, but not relative to where they are today. So what do you learn from this? If you understand Gall's Law, how can it be valuable in in your business life and in your personal life. Here's how I think you can apply this knowledge. Number 1, start small, right? Like, yeah, I know you wanna get there quickly, but if you're ever starting on a new project or a new endeavor, start with a simple version or a prototype. Focus on the core functionality or the core goal. Avoid all the unnecessary complexity at the outset. Validate your ideas, get feedback, and then iterate, making it more complex over time. So number 1, start small. Number, number 2, prioritize feedback. I'd always be looking for feedback from your customers, from your peers, from your colleagues, from your mentors. Get some positive feedback, get some constructive criticism. Number 3, uh, in understanding Gall's Law, how to make it valuable in your business and personal world, focus on what we call an MVP, Minimum Viable Product. In business, aim to develop and launch just this MVP, this Minimal Viable Product initially. Get the MVP out the door. An MVP just has the essential features, just the things that are required to address the core needs of your target audience. This kind of goes back to an episode last week when we talked about satisficing. Go check that episode out if you know what I'm talking about. But really it was satisfying about, you know, hitting the, hitting the standard, the minimum standard, you know, what'll suffice, what'll do the trick versus spending all the time and energy trying to maximize. So this is the minimal viable product concept here at work. In using Gall's Law, I'd say you also got to embrace continuous learning. Goes without saying, got to have a mindset of continuous learning and adaptation. Gotta be open to new ideas. And then lastly, I want you to just avoid over-engineering in both business and in personal projects. Be cautious of over-engineering or adding just unnecessary complexity. That's what I have a tendency to do, and I've gotta check myself. I've gotta ask myself, is this an MVP? Is this basic? And does it prove the point or move the needle? Can I keep it simple and streamlined, especially like in the early phases, and then look to add more complexity? Complexity as we make some discoveries and we iterate. Because remember, when you go complex, you increase costs, you have longer development times, there's more potential for error. So by applying these principles of Gall's Law in your business and in your personal world, you can increase your chances of success. You could certainly adapt more effectively to change, and you could create solutions that eventually are pretty darn robust and complex. They just may not have started there. So the focusing question for you: are you overcomplicating things when you embark on a new project or a new journey? Can you simplify? Can you leverage Gall's Law and recognize that complex systems are not built from scratch? Complex systems are built on the backs of simple systems first. Where in your world does this in fact apply? What are you constructing right now that you are running the risk of making overly complicated or overly complex? And if you just run it now, test it as a minimal viable product, and then iterate, you will have greater success. That's all I have for you today. The No Days Off Podcast. Thank you so much for listening. And remember, every single day brings a new opportunity to get better. So let's get after it.
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