Intro
Another week of AI things. Not as much here this time but there’s still a lot happening.
Highlights of the Week
My (Hypothetical) SRECon26 Keynote
https://charitydotwtf.substack.com/p/my-hypothetical-srecon26-keynote
If I was giving the keynote at SRECon 2026, I would ditch the begrudging stance. I would start by acknowledging that AI is radically changing the way we build software. It’s here, it’s happening, and it is coming for us all.
It is very, very hard to adjust to change that is being forced on you. So please don’t wait for it to be forced on you. Swim out to meet it. Find your way in, find something to get excited about.
The Edge of Mathematics - The Atlantic
https://www.theatlantic.com/technology/2026/02/ai-math-terrance-tao/686107/
Tao has long been intrigued by, but reserved about, what AI tools can do for his field. The first time we spoke, in the fall of 2024, Tao had likened chatbots to “mediocre, but not completely incompetent” graduate students. About six months later, he told me the models had gotten better “at certain types of high-level math reasoning,” but lacked creativity and made subtle mistakes. But during our most recent conversation, he was more bullish. AI may not be on the cusp of solving all of the world’s great math problems, but chatbots are at the point where they can collaborate with human mathematicians. In the process, he said, the technology is opening up a different “way of doing mathematics.”
Time and time again people have dismissed all AI as being not that great only to revisit it months down the line and have a completely changed opinion. It underscores the importance of keeping up to date and ensuring that you know what is going on.
Some reasons to work on productivity and velocity
danluu.com
Fabian Giesen: It is commonly accepted, verging on a cliche, that you have no idea where your program spends time until you actually profile it, but the corollary that you also don’t know where you spend your time until you’ve measured it is not nearly as accepted. When I’ve looked how people spend time vs. how people think they spend time, it’s wildly inaccurate and I think there’s a fundamental reason that, unless they measure, people’s estimates of how they spend their time tends to be way off…
This is true for nearly all people. It seems like you’re doing loads of work but unless you actually measure it you really have no idea
Reflections on Palantir
Nabeel S. Qureshi
The CEO told us his biggest problem was scaling up A350 manufacturing. So we ended up building software to directly tackle that problem. I sometimes describe it as “Asana, but for building planes”. You took disparate sources of data — work orders, missing parts, quality issues (“non-conformities”) — and put them in a nice interface, with the ability to check off work and see what other teams are doing, where the parts are, what the schedule is, and so on. Allow them the ability to search (including fuzzy/semantic search) previous quality issues and see how they were addressed. These are all sort of basic software things, but you’ve seen how crappy enterprise software can be - just deploying these ‘best practice’ UIs to the real world is insanely powerful. This ended up helping to drive the A350 manufacturing surge and successfully 4x’ing the pace of manufacturing while keeping Airbus’s high standards of quality.
I’ve no idea what the company does but this does shed some light on it. Basically it seems like you’re hiring them to hire pre-vetted talented engineers to make some software for your company.