AI 资讯
Measure your own coding habits before you believe anyone else's numbers
Part of "AI, engineering and what survives production", a series on the parts of building with AI that hold up once real traffic hits them. There is a claim going round that you have probably absorbed by now: AI-assisted development is making codebases worse. Refactoring is down, duplication is up, we are all writing more and revising less. The numbers behind it are real, the samples are enormous, and I found I had started repeating the conclusion in conversation without ever having checked it. Then it occurred to me that those figures are averages taken across hundreds of millions of changes from thousands of organisations, not one of which is mine. So what is the rate in your repository? Nobody has told you, and on current evidence nobody is going to. I set out to find mine, assumed it would take an afternoon, and spent three days discovering that the answer is far harder to get at than the confident version suggests. So this is not a piece about what AI does to code. It is about how to ask that question of your own repository without arriving at a wrong answer, which turned out to be the genuinely difficult part. The tool I built to do it is git-habits : free, local, and it reads no source code whatsoever. What git can actually tell you Git history is a surprisingly rich behavioural record. Not of quality, about which it knows nothing at all, but of habits: how often you commit, how large those commits are, whether you go back and change what you wrote last month, and whether anybody still touches the old code. That is a narrower thing than quality and it is the thing the industry claims has changed, so it is the thing worth measuring. Four signals are computable from commit metadata alone, without opening a single source file: Moved lines. The share of changed lines sitting in files git detected as renamed or copied. It is the closest thing history offers to "somebody went back and reorganised this." Legacy touch. The share of changes landing on files nobody has
产品设计
Trump killed the Digital Equity Act, but US was forced to bring part of it back
$1.25 billion program restored, but judge ruled race provision unconstitutional.
开源项目
How the GitHub legal team used Copilot CLI to streamline their workflows
Learn how to build tools to simplify how you work—without writing a single line of code. The post How the GitHub legal team used Copilot CLI to streamline their workflows appeared first on The GitHub Blog .
AI 资讯
India moves to give its instant payments network a business model
The legislation lays the groundwork for a potential overhaul of India's zero-merchant-discount-rate regime, under which businesses have not paid fees to accept UPI payments since 2020.
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