@unclebobmartin@plainionist@realsigridjin I think well defined type constraints become much more efficient than your average unit test suite in the long run. Maybe things like property based testing even out the playing field between dynamic and typed?
I disagree: https://t.co/D17M3HAF1b
Code is how we get precise abstractions into human heads
Saying code isn't important is like saying mathematical notation isn't important
There's a reason we glorify f = ma or e = mc2. Formalism holds immense power for mastering complexity
We spent years and billions of dollars inserting a C compiler into a lossy hash table. Here’s how we spent two weeks getting it back out with a Markov process.
Oh, you're writing CUDA kernels? Everyone's on Triton now. Just kidding, we're all on Mojo. We're using cuTile. We're using ROCm. We have an in-house DSL compiler targeting the NVGPU MLIR dialect but wait, Tile IR just dropped so we're going to target that instead. Our PM is on TileLang. The team lead was on CuTe but now she's back to handwriting PTX. If you're not on Pallas, you're ngmi. Our intern is building on TT-Metalium for our Wormholes. Our CFO approved an order for some big chungus wafer-scale chips so now we're porting our kernels to CSL. Our CTO is working on a kernel-less graph compiler so we won't need to write kernels anymore. Our CEO thinks we're talking about the Linux kernel. We're building Claude for dogs.
@dhh@ThePrimeagen The two approaches are complementary: it’s impossible to prove all non-trivial properties of a program but it’s also infeasible to exhaustively enumerate all possible input combinations a program may take as input.
Releasing a new "Agentic Reviewer" for research papers. I started coding this as a weekend project, and @jyx_su made it much better.
I was inspired by a student who had a paper rejected 6 times over 3 years. Their feedback loop -- waiting ~6 months for feedback each time -- was painfully slow. We wanted to see if an agentic workflow can help researchers iterate faster.
When we trained the system on ICLR 2025 reviews and measured Spearman correlation (higher is better) on the test set:
- Correlation between two human reviewers: 0.41
- Correlation between AI and a human reviewer: 0.42
This suggests agentic reviewing is approaching human-level performance.
The agent grounds its feedback by searching arXiv, so it works best in fields like AI where research is freely published there. It’s an experimental tool, but I hope it helps you with your research.
Check it out here: https://t.co/n7ctnDilJJ
@ChShersh I have this (I guess false) sense that only compilery jobs are actually interesting and intellectually stimulating. Did you also think this way early in your career? What do you think nowadays?
@imnonplussed@valigo Those event listeners you’re talking about eventually build graphs with derived state and even cycles. This is exactly what a good frontend framework should help with - things like batching updates, optimal recomputation order, diffing, subscribing and unsubscribing…
Virtual Machines render fonts. It’s kind of insane.
TrueType has its own instruction set, memory stack, and function calls.
You can debug it like assembly. It’s also exploitable: