Summary

Dan Luu argues that LLMs and coding agents have reduced the cost of sophisticated performance optimization work by 1000x-1000000x in human time, making previously rare expertise accessible to anyone who can type a few sentences. He demonstrates this through concrete examples: a workload-specific regex engine, a world-beating game AI, and near-real-time performance experiments that would have taken weeks by hand. The core implication is a shift from optimizing for classes of workloads to dynamic, workload-specific software fitted to individual customers or personal usage patterns. This democratization means the excuse that performance work is too expensive no longer holds.

Key Insight

AI coding agents have so drastically reduced the cost of performance optimization that workload-specific software—previously a luxury of the largest engineering teams—is now within reach of any individual developer, fundamentally invalidating the historical excuse that performance work is too expensive to be worthwhile.

Spicy Quotes (click to share)

• 6

  performance work that used to require a person or team that had a rare set of skills can be done by anyone who can type a few sentences

• 8

  Jamie Brandon got an offer from Anthropic and you probably can't afford him or someone like him unless you're OpenAI, but you can afford to use a coding agent that can beat him on a bounded optimization problem.

• 6

  I have a lot of experience looking at optimizations and thinking 'hmm, this would increase performance by 2%, but it's going to take N person-days to verify that this tricky optimization works'... Now that this N has dropped by a tremendous factor (variable but, in terms of human time, frequently 1000x / 10000x / 1000000x), the number of these kinds of optimizations it makes sense to do goes way up.

• 4

  [o]thers were just crazy shit that I would never try unless I was working on this for weeks

• 5

  Dynamic custom software, fitted to a particular workload rather than a class of workloads, seems like a very likely outcome.

Tone

analytical, empirically optimistic