Topic
Coding
4 stories, newest first.
- 01Coding17 Oct 2026
Handwired: write JavaScript logic as a neural net, zero training
Handwired, a new MIT-licensed open-source project from Cheng Lou (released Oct 15), lets you write JavaScript logic as an exact neural net: if-else, loops and state become matrix multiplications and ReLU gates over floats, with weights written by hand rather than learned. Nothing is trained, the output is exact, and the whole program stays fully differentiable, runnable in a browser without a GPU. The flagship Mini OS demo is a small desktop with windows, dragging, scrolling and animation in 9,909 weights and 130 layers with zero training; a JSON search demo searches 100,000 documents at every keystroke with the JavaScript turned into WebGPU kernels; and a learned gallery unfreezes a program's weights and trains them in real time. The pitch: attach an exact, frozen program to a regular neural net and train end to end. Caveat: there is no automatic converter; you write the network in builder code by hand, and only the search demo runs on WebGPU.
Source: GitHub (chenglou/handwired) (opens in a new tab) - 02Coding17 Oct 2026
Linux kernel drops its AI disclosure tag
Linux kernel maintainers removed the "Assisted-by" tag that asked contributors to label patches written with help from an LLM. Only about 10% of the 18,533 non-merge commits in Linux 7.3 (through -rc7) carried it, while actual LLM use is far more widespread: some contributors didn't know the rule, others left it off on purpose, and few maintainers asked, so a missing tag said nothing. The 2026 Maintainers Summit reached a "strong, though not unanimous" consensus to drop it, and docs maintainer Jonathan Corbet applied the patch to the kernel docs tree on Oct 14. Maintainers still want to know how a patch was made, now in the cover letter, and the DCO and submitter-responsibility rules stay. Linus Torvalds: "We're not going to make stupid rules that say 'you can't use tools for X'."
Source: Linux kernel mailing list (opens in a new tab) - 03Coding16 Oct 2026
Claude Code Review is GA for Team and Enterprise
Anthropic took Code Review out of research preview for Team and Enterprise; auto PR reviews via GitHub App; ~3× faster (20→6–10 min) per Anthropic; Enterprise credit promo ≥$10k by Jan 15, 2027.
Source: Anthropic (opens in a new tab) - 04Coding13 Oct 2026
Atomic Machines: AI fab builds micro-machines from code
An AI-native Matter Compiler builds working micro-machines from digital designs as a self-driving fab—no masks; every iteration is software. First product PrimeSwitch is sampling now.
Source: Atomic Machines (opens in a new tab)