Blog Posts

Prediction: AI will make formal verification go mainstream (via source), which itself points to the author's blog.

Martin Kleppmann makes the case for formal verification languages (things like Dafny, Nagini, and Verus) to finally start achieving more mainstream usage. Code generated by LLMs can benefit enormously from more robust verification, and LLMs themselves make these notoriously difficult systems easier to work with.

More with less, or is it more with the same (via source)

How automatable the work already is. Where the work is rules based, high volume, and low variation, AI may replace labour in the same way classic automation has. Think claims processing, simple customer support, structured back office workflows. These functions already lived close to the automation frontier. AI just expands the frontier a bit. This will reduce headcount, but mostly in places where headcount has been under pressure for decades anyway.

The cost and consequences of mistakes. In many industries, the limiting factor is not productivity, but risk. Healthcare, aviation, finance, law. Increased throughput also increases the risk surface area. If AI increases the probability or cost of an error, you cannot shrink the team. You often need more human oversight, not less.

From @karpathy on X:

You will never be able to detect the use of AI in homework. ... You have to assume that any work done outside classroom has used AI. ... Therefore, the majority of grading has to shift to in-class work. Using the calculator as an example of a historically disruptive technology, school teaches you how to do all the basic math & arithmetic so that you can in principle do it by hand, even if calculators are pervasive and greatly speed up work in practical settings. In addition, you understand what it's doing for you, so should it give you a wrong answer (e.g. you mistyped "prompt"), you should be able to notice it, gut check it, verify it in some other way, etc. The verification ability is especially important in the case of AI, which is presently a lot more fallible in a great variety of ways compared to calculators

I had a bit of a weird experience this weekend. I was bogged down debugging a personal tool I’m building, a sync engine between Raindrop.io and my reMarkable tablet, when I stumbled into a realization about the future of our craft. It wasn't that the AI was a genius programmer; it was that it brought the marginal cost of a wrong guess down to zero. It turned the Infinite Monkey Theorem from a philosophical absurdity into a viable engineering strategy where the marginal cost of a wrong guess is down to zero.

My former colleague Rebecca Parsons, has been saying for a long time that hallucinations aren’t a bug of LLMs, they are a feature. Indeed they are the feature. All an LLM does is produce hallucinations, it’s just that we find some of them useful.

Found out about this interview with Steve Jobs that the master was supposedly lost for a long time and released in full when finally found. The long format is a sneak peak into such a different time, he was still with NeXT and at some points during the interview very salty about the fight that forced him to leave Apple. Being able to hear what was going on in his head and his thought process at that giving time is such a blessing.

The most profound shift in my workflow isn't a new productivity app or a fancy monitor. It's the realization that my primary productivity tool is now just a collection of ongoing conversations with LLMs. This is a form of context farming: cultivating multiple, independent project contexts that I can dip in and out of with zero ramp-up time. The cognitive tax on switching between wildly different tasks was a cost we all just accepted. Now, that tax has been effectively eliminated. True multitasking, the kind the experts told us for years was a myth, is now not only possible but shockingly effective. The baseline for productivity has been redrawn, and the tools we used just a couple of years ago feel like they're built for a different cognitive era.

The modern web has a lot of power, yet I often find myself thinking about the 90s. Tools like Visual Basic, Delphi, and even Flash, didn't just let us build personal programs; they made it fun, mainly because they made starting so easy.

I read this article and it got me thinking that this problem of measuring ourselves by our wealth is not something new but it got worse with the internet and how many peers we have to compare ourselves with.