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A second question to ask, is if we find ourselves in this scenario, what should we do about it? The most effective response to this multi-layered persistent uncertainty is not to seek impossible stability, but to cultivate radical adaptability and radical optionality. Give up on having a reliable prediction of what happens next. Instead cultivate multiple scenarios of what could happen, and endeavor with each of them to maximize your options. Goals should be considered as disposable hypotheses, constantly ready to be discarded and replaced by better-fitting concepts later on. You will be dead wrong on 19 out of your 20 expectations, but at least one of them will allow you to proceed. Make your decisions not on whether they are “right” but on whether they tend to give you more options later.

Maybe I suffer from software brain, but I think that eventually this will include everything. It might take more than a couple of haircuts but I think humanity will shave that head eventually.

Any business process that looks like code talking to a database in a repetitive way is up for grabs. That’s why Anthropic has been so relentlessly focused on enterprise customers, and it’s why OpenAI is now pivoting to business use. There’s real value in introducing AI to business, because so much of modern business is already software: collecting data, analyzing it, and taking action on it over and over again in a loop. Businesses also control their data, and they can demand that all their databases work together.

The whiteboard just checks if a person can write code by hand, without any helpers and under pressure. Today, this is not the job that an engineer does or should do. Now an engineer has to make decisions at the product level and communicate with the team at different levels. But the whiteboard only checks a specific result, in fake conditions. Code overall is already a result. What matters is thinking.

GPT-5.5 shows us that the models keep getting smarter, the apps keep getting more capable, and the harnesses keep getting better, making them ever more effective at solving real problems. I can get a near PhD-quality paper from four prompts or a playable roleplaying game, illustrated and “playtested,” from one. But the fiction is still flat and the hypotheses are sometimes uninteresting even when the statistics are sound. But still. A year ago, none of this was close, and, with the latest releases, capability gains appear to be accelerating.

AI-enabled cyber attacks were up 89 percent in 2025 compared with a year earlier, according to data from security group CrowdStrike. Meanwhile, the average time between an attacker first gaining access to a system and acting maliciously fell to 29 minutes last year, a 65 percent acceleration from 2024.

Code remains cheap, unless it needs to be secure. Even if costs go down as inference optimizations, unless models reach the point of diminishing security returns, you still need to buy more tokens than attackers do. The cost is fixed by the market value of an exploit.

What matters here is a narrower point. The center is not biased towards novelty so much as towards contact with the thing that creates potential change. The middle ground is not between use and non-use, but between refusal and commitment and the people in the center will often look more like adopters than skeptics, not because they have already made up their minds, but because getting an informed view requires exploration.

I think we’re going to see a lot more reimaginings, where people attack old problems with modern tactics. Coding agents lower the costs of taking on stalwarts and raise our ability to rapidly harden our software. I can think of many software tools that people rely on but don’t like. Those are the prime targets for reimagining.

Satoshi revealed? seems plausible to me.

I recalled how 10 years before, Satoshi had come out of hiding to help Mr. Back win the war over block size. And here Satoshi was, back again in a luxury hotel in El Salvador. Only this time, he had served Mr. Back less well because he’d removed any lingering doubt in my mind that I had the right man.

The evolution of the English language is fascinating to me. When I look at old english its hard to believe the language we speak to day used to sound that way.

In the Beowulf, the dual makes a dramatic appearance: two warriors swim in the sea holding swords, "to defend the two of us against whales" ("wit unc wið hronfixas werian" in the original). Thought to be written in the 8th Century, Beowulf is the earliest European epic written in the vernacular – the language commonly spoken – rather than a high culture, or literary language.