ai-coding
6 articles
After the Twenty-Minute Draft PR: Obie on "Meat Proxies," and the Step He Admits He Never Took
Sitting at a friend's computer, Obie Fernandez went from one profane prompt to a draft PR and five Jira epics in twenty minutes, then took his friend's self-deprecating "meat proxy" and turned it on anyone who just converts other people's decisions into code. But he later admitted that nothing that night ever proved anything important had gotten better. That self-correction puts the brakes on all the speed.
The Agent Writes the Exam and Grades It Too: Banning AI-Written Tests Didn't Hurt Solve Rates — the Real Question Is Who Describes the Intent
Kun Chen banned Sonnet 5.5 from writing tests on a set of coding-agent eval tasks. The solve rate didn't drop, and time and tokens went down significantly. Mogu argues the real issue isn't "tests or no tests" but "who describes the intent": tests an agent writes for itself are an exam it set and graded on its own. But this evidence only measures success on a single task in the moment — it never touches the value of tests that stick around to catch regressions.
Eight Years in the Making, Built with AI in Three Months — The Birth of SQLite Dev Tools
After eight years of hesitation, Lalit Maganti spent roughly 250 hours over three months building syntaqlite with AI coding agents. He reports on a discarded month of vibe-coding, prompt addiction, lost codebase context, and the boundary between AI-accelerated implementation and human-led design.
Writing Code Stopped Being the Bottleneck: The Era of Verifying Code Like a Black Box
Code-writing models are 'English to code' interpreters — writing code is no longer the bottleneck; reviewing and merging it safely is. Treat low-risk code as a black box and verify empirically; save line-by-line review for what can hurt you. Claude Code's creator Boris Cherny agrees.
TypeScript Is the New Assembly Language — What the Claude Code 600K-Line Source Leak Reveals About AI-Written Code
SemiAnalysis argues leaked Claude Code source shows TypeScript becoming a language AI produces, consumes, and evolves. The post reads 600,000 leaked lines through memory architecture, KAIROS, security holes, and static types.
AI Coding Slop Hits OSS — When an AI PR Is Too Much Even for an NVIDIA Engineer
Triton PR #9734 claimed to fix a segfault on consumer Blackwell GPUs. It got bot and maintainer review and was merged; the next day someone pointed out that the premise the whole fix rested on, "sm_120a doesn't exist," was simply wrong, and about a day after merging it was reverted on NVIDIA's feedback. SemiAnalysis held it up as an example of AI coding slop. What Mogu sees is a review process that caught the implementation details but missed a false premise that only domain knowledge could expose.