thundersnap 0.01: an undo button for everything
Happy July 4th! For those of us around the world contemplating independence, it's a good day to think about how we came to rely on expensive cloud infrastructure for our fundamental computing needs.
CEO of Tailscale. Previously at Google. Writes about networking, version control, and systems design.
https://apenwarr.ca/log/Happy July 4th! For those of us around the world contemplating independence, it's a good day to think about how we came to rely on expensive cloud infrastructure for our fundamental computing needs.
In recent months I've heard of several teams with an interesting policy: each pull request should be no more than a few files, and no more than a certain number of lines (say 500). And do just one thi
AI isn’t killing engineering. It's making it less meditative. There’s a lot of talk about AI killing engineering jobs. Some jobs will change, and some will disappear. But we’ve been automating enginee
AI is the cause of, and solution to, slop problems. Have AIs filter your PRs so humans get back to deciding what they want to exist. AI was built on open source. Now it’s starting to return the favour
AI needs an open ‘Android’ to balance the vertically locked-in ‘iPhone’ of trillion-dollar AI companies. Open-source AI is closing the gap with closed systems faster than many people expected. That ch
We’ve all heard of those network effect laws: the value of a network goes up with the square of the number of members. Or the cost of communication goes up with the square of the number of members, or
LLMs enable semantic understanding, revolutionizing how systems connect and communicate beyond rigid technical standards of the past.
Wealth is relative - even startup exit millionaires have limits, while modest savings and tastes can enable financial independence.
The post addresses concerns about "enshittification" after a fundraise, explaining why products decline over time and promising to avoid this trap.
NPS's value isn't the score itself, but understanding that people rate based on emotions—lukewarm responses mean you failed to make them feel anything.
The author relies heavily on intentional mental models for predictions, acknowledging their power but also the risk of confirmation bias.