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Nelson Elhage

What Nelson Elhage thinks about design

@nelson-elhage · 19 positions · 0 changes of mind

Software engineer who writes the blog Made of Bugs about performance, debugging and understanding computer systems. Previously worked at Anthropic on interpretability, at Stripe on Sorbet, and at Ksplice.

Everything they publish, on ppll ↗

Nelson Elhage did not write this page.

We collected these quotes from things they published elsewhere, and every quote links to where it was said. They have no account here and have not endorsed this site. Quotes are word for word; the short line under each one is our own restatement, not their wording. Their own site. Is this you? Claim it or ask us to remove it. Or tell us what is wrong here.

8 dated positions, 2023 to 2026, in their own words. Our reading of what Nelson Elhage has said — not written or endorsed by them.

8 positions so far — this page is not yet offered to search engines.

  1. Our readingA composable concurrency paradigm requires a general-purpose cancellation mechanism.

    Their wordsBut I struggle to envision a general, composable, concurrent paradigm without one.

    ↗From error-handling to structured concurrencyblog.nelhage.com 1st of 2 in this piece

  2. 5 months earlier

  3. Our readingWhen a tool has first-class, native support for a problem domain, that is the best place to start before building a custom encoding.

    Their wordsI suspect the pattern generalizes: If Z3 has first-class support for your problem domain, it's worth starting there!

    ↗Solving regex crosswords with Z3blog.nelhage.com 2nd of 2 in this piece

  4. 4 months earlier

  5. Our readingUsing a neural network is likely to become easier than designing a custom-tuned prediction algorithm for many tasks.

    neural networks

    Their wordsin 2025 it might end up being easier to just throw a neural net at the problem, instead of a custom-designed-and-tuned prediction algorithm!

    ↗The ITTAGE indirect branch predictorblog.nelhage.com 3rd of 3 in this piece

  6. 4 months earlier

  7. Our readingImpressive-looking benchmark improvements often result from comparing against a poorly-tuned baseline rather than a genuine advance.

    benchmarks

    Their wordsIt's easy to get impressive-looking results if you're comparing against a poorly-tuned baseline, and that observation turns out to explain a surprising fraction of supposed improvements.

    ↗Performance of the Python 3.14 tail-call interpreterblog.nelhage.com 1st of 3 in this piece

  9. Our readingCompiler mechanisms that force a required optimization to occur, rather than relying on incidental compiler behavior, are a more robust way to write performance-sensitive code.

    compilers

    Their wordsI'm hopeful this framework will turn out to be a much more robust style for writing performance-sensitive code, especially over time and as compilers evolve.

    ↗Performance of the Python 3.14 tail-call interpreterblog.nelhage.com 3rd of 3 in this piece

  10. 6 weeks earlier

  11. Our readingAI tooling and interface design lags behind the underlying models' actual capabilities.

    LLMs

    Their wordsOverall, though, this experience reinforced my belief that the tooling and interface design around LLMs is lagging way behind the actual capabilities, and is an area of active experimentation and development, even aside from any future model improvements.

    ↗Building personal software with Claudeblog.nelhage.com 2nd of 3 in this piece

  13. Our readingAs AI makes code cheaper to produce, understanding and architectural design become more valuable.

    Their wordsThus, code is cheaper than ever, but I suspect that insight and good architectural design and understanding, at least for now, will become more valuable than ever.

    ↗Building personal software with Claudeblog.nelhage.com 3rd of 3 in this piece

  14. 13 months earlier

  15. Our readingProfilers show where time is spent but not which of that time can feasibly be reduced or is worth optimizing.

    Their wordsProfilers can only show you "what is there"; skillful performance engineering requires understanding the information that shapes and informs the profile but is "not there" in the profile itself.

    ↗Performance engineering, profilers, and seeing the invisibleblog.nelhage.com 1st of 2 in this piece