As software development shifts from requiring specialized skills—built on multiple layers of technical understanding—to describing intent in plain English (or your language of choice), the act of producing software appears to become accessible to a much wider audience. The people best positioned to excel may not be well versed in software at all, but rather those who are good at expressing ideas clearly, thinking iteratively, and breaking problems down.

At first glance, that sounds like perhaps the most egalitarian shift our industry has ever seen.

But there’s a quieter change brewing while we’ve been distracted by the expanding capabilities of AI tools. As AI reshapes how software is written, it reintroduces something we spent decades deliberately removing: cost.

And once cost becomes the bottleneck, software stops being democratic very quickly.

If you paint a picture of Sonic the Hedgehog in your living room, you are technically creating an unauthorized derivative work—but in practice, no one cares. Private, noncommercial creation has always lived in a space where copyright law exists on paper but is rarely enforced.

Gift it to a friend? Still functionally tolerated—a technical act of distribution that copyright law mostly ignores at human scale. Take a photo and post it on Instagram? Now you’ve crossed into public distribution of a derivative work without permission. Under the letter of the law, that’s infringement, although a fair-use defense might apply and Sega almost certainly won’t care. It’s fan engagement, free marketing, and good PR.

Sell that painting, though, and the tolerance disappears. You’re no longer a fan, you’re a competitor.

The rapid expansion of context windows has become one of the most visible metrics of progress in modern language models. In just a few years, we have moved from a few thousand tokens to systems advertising over a million. The value proposition seems straightforward: providing more context should lead to a better understanding for the task.

In practice, it’s a bit more complicated. Longer context windows unlock new use cases, but they also introduce costs, failure modes, and design tradeoffs that are easy to overlook. For teams building production systems, these tradeoffs matter as much as raw capability.

Growing up in the 90s and early 2000s, tech was a foundational part of my childhood.

I built more physical computers than I can remember. We went from paper maps to GPS (which itself evolved from DVDs with static maps to internet-connected real-time navigation). CD players became MP3 players, then streaming services. We had Palm Pilots and early attempts at “smart” phones, which were anything but. Our computers could search for extraterrestrial life through SETI. We emerged from the pager era to portable phones to the entire internet in our pocket (which evolved from charging per SMS or megabyte to unlimited data plans).

Although unintentional, the software patent system has evolved into a classic game-theoretic dynamic.

The core issue is that offensive and defensive patent stockpiles look identical from the outside. That ambiguity triggers a feedback loop that sustains the system.

Patents are meant to protect specific inventions, but in software where ideas spread quickly, they have taken the role of strategic assets in an arms race. Useful concepts are rediscovered independently or unintentionally overlapped. As a result, nearly every company is vulnerable to infringement claims at all times, often through no fault of their own.

Few industries have experienced as many disruptions in the 21st century as publishing. The last two decades have brought a shift from print to digital, the decline of ad-supported models, the rise of paywalls, and a surge of self-publishing and social platforms.

For most of history, humanity’s greatest accomplishment has been its ability to out-accelerate its own existential problems.

The acceleration in population growth put pressure on food supplies, health, and energy. In response, we invented fertilizer, sanitation, and a vast array of energy generation and storage technologies. Humanity now thrives in high-density environments.

This acceleration has enabled humanity to adapt and flourish despite a constant barrage of challenges. One might assume that this trend will continue indefinitely.

But what if that era is ending — as we approach limits imposed by physics across a variety of domains?

Vibe coding—the art of guiding LLMs to write code on your behalf, according to stated requirements—is shifting from a quirky, experimental approach to something that, in many cases, is expected even in large, bureaucratic organizations. It can be a huge productivity booster, but it also comes with real risks: even a single misplaced character can lead to SQL injection, bypass logins, or expose sensitive user data.