Ah, that is a good point, I will update to include a note on this.

I do believe that violating copyleft licenses is unethical, and non attribution is problematic. However, I also don’t believe in copyleft licenses (or any other forms of IP) as a general good structure. IP has been IMO a major source of decoherence in the economy writ large, and it’s one of the main issues that I will be tackling in the upcoming essay on Open Capital.

That said, it is unethical to not follow the structures a creator decides to impose on their work, and I believe it is neutral to choose a restrictive license (it’s not a right or wrong thing, as much as a right or left thing). I’m more so speaking at the macro level of economic outcomes, and the unintentional structures that restrictive licenses reinforce and validate.

(And to be clear, closed source systems are orders of magnitude worse and the real problem, IMO. Copyleft is just one attempt to break them open, and it doesn’t work)

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I really disagree, programming is not dead. Far from it, we need skilled practitioners and designers now more than ever. I discussed this detail in The Decoherence Trap, which was trending for a minute there, but another (quicker) thing I’d recommend reading is my AI usage policy’s section on coding.

In short, if you don’t aggressively create and maintain solid, well thought out abstraction layers that are human driven, and only use AI at the edges, you’re going to find yourself in sleep walking into an unmaintainable mess sooner rather than later. We already struggled with decoherence and code maintainability prior to AI, and AI is only accelerating it.

I say this as an early adopter, having seen every strategy and idea play out. There simply is no way to prevent decoherence, and the faster and harder you push AI, the more decoherence it adds.

Anyways, take heart, there’s going to be plenty of slop for us to clean up for a very long time.

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The exponential growth part is meant literally, I genuinely believe the growth in complexity of truly decoherent systems in combinatorial and exponential. It can be extremely bad!

The biggest issue with proving this in a meaningful sense is that it would rely on a lot of counterfactuals. The best example that I am familiar with is probably various layers and functions of US government bureaucracy. You can find many descriptions and examples of how layered and complex government systems are (see for instance Recoding America), and I would categorize this as decoherence. My sense is that if we made these systems more coherent, then they would also be much more efficient and much easier to change. But we can’t know for a fact that this would be true, because it would essentially be an alternate history.

On the other side though, I think we can compare the store of Windows vs Linux. At one point, Windows Server was the dominant server implementation and growing. Linux was the underdog and it was not treated seriously, with significantly less funding put toward it. Yet in the last 20 years, Linux has become absolutely dominant by count of machines spread across the world, and Windows really only maintains its foothold on the desktop.

Now, imagine if Linux hadn’t been successful, and specifically, imagine building Docker exclusively for Windows. Imagine having to manage not only the complexity of spinning up and tearing down Windows servers dynamically, but also the complexity of the licensing, the various bugs and issues you could encounter, and being dependent on Microsoft entirely for fixes since it would all be closed source. That would, IMO, be a decoherent mess, and the economic impact would likely have been far fewer successful startups, many orders of magnitude less economic activity, and a much less vibrant web.

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I may be even more of a pessimist and say that we’ve already been heading in that unmaintainable direction for a long time, and AI is simply accelerating it. The core reason behind that is the current economic structure and all of the incentives toward profit seeking over building solid, maintainable, extensible tools and systems.

But I think there’s hope. We’re in a time of great uncertainty and change, and that presents opportunity to shift the narrative and the broad consensus about whether or not that is inevitable. My next few essays will be exploring this more in depth, and proposing an alternative model based on the learnings from the OSS system that already powers Silicon Valley.

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Hmm. So, funnily enough, this is close to where I’ll end up near the end of my essays, in terms of where I think tech should be going. But the thing is, I think to get there we actually need to push more deeply into better abstractions and a more coherent ecosystem.

I discuss this a bit in my AI usage policy in the section on code. Specifically, the idea behind a universal design system, which would enable much more flexible UIs driven by agentic development, but on much stricter guard rails that would prevent decoherence from seeping into the core layers and leave it just on the surface.

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