Feed

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.

This certainly describes the primary way I use AI agents.

There is only one source of feedback that moves at the speed of AI-generated code: yourself. You're there to prompt, you're there to review. You don't need to recruit testers, run surveys, or manage design partners. You just build what you want, and use what you build.

And that's what many developers are doing with cheap code: building idiosyncratic tools for ourselves, guided by our passions, taste, and needs.

We must return to the fundamental truth The source code is not the product. The product is the Outcome the user achieves. The code is merely the expensive, high-maintenance machinery required to deliver that outcome. If you can deliver a $1,000,000 outcome with 10 lines of code, you are a hero. If you deliver that same outcome with 37,000 lines, you have just created a $1,000,000 liability.

And I would like to suggest that slowing the fuck down is the way to go. Give yourself time to think about what you're actually building and why. Give yourself an opportunity to say, fuck no, we don't need this. Set yourself limits on how much code you let the clanker generate per day, in line with your ability to actually review the code.