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219 writings found
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When Machines Write Code, Humans Must Learn to Judge
As LLMs generate more code, teams face cognitive surrender and debt proliferation. The future isn't about writing code, it's about verification.
Meta's KernelEvolve: When AI Writes Its Own Performance Code
Meta's KernelEvolve system uses AI agents to automatically optimize low-level hardware kernels, achieving 60% performance gains in hours instead of weeks.
The Axios Attack: Why Social Engineering is Now the Biggest Threat to Open Source
A sophisticated supply chain attack on Axios used fake job interviews to install malware. Every open source maintainer needs to understand this threat.
When Agents Write Code, We Judge It: The Verification Economy
As LLMs generate code at scale, our job shifts from writing to verifying. What does this mean for how we organize teams and think about programming?
Meta's Adaptive Ranking Model: The Real Cost of Serving Trillion-Parameter Ads
Meta scaled ads recommendations to LLM complexity while keeping latency under a second. Here's why their inference trilemma solution matters beyond advertising.
Treating AI Instructions as Infrastructure, Not Documentation
How encoding team standards as versioned AI instructions solves the consistency problem that plagues AI-assisted development workflows.
Making Team Standards Executable: Infrastructure for AI-Assisted Development
AI coding tools produce wildly different results based on who's prompting. Treating team standards as versioned, executable instructions solves the consistency problem.
Why Your AI Benchmark Is Probably Wrong: The N,K Trade-off
Google Research reveals why using 3-5 human raters per item isn't enough for reproducible AI evaluation. The depth vs breadth problem explained.
Tests Are the Real Safety Net: Why Your AI Specs Need Executable Validation
Writing specs for LLMs is trendy. But without automated tests, you're flying blind. Here's why the spec document isn't your safety net.
Meta's AI is Reshoring American Concrete, One Mix at a Time
How Bayesian optimization is helping U.S. concrete producers ditch imported cement and redesign mixes in days instead of months.
Sora's Shutdown: When Burning $1M Daily Isn't Worth the Hype
OpenAI killed Sora after six months, ditching a $1B Disney deal. The real story isn't about data grabs, it's about brutal economics and losing ground to Claude.
Building macOS Apps Without Knowing Swift: What Vibe Coding Actually Teaches Us
I built two monitoring tools for my M5 MacBook using Claude and GPT without writing Swift myself. The results work, but should they?
Suno v5.5: AI Music Generation Gets Personal with Voice Cloning and Custom Training
Suno's v5.5 update brings voice cloning, custom model training, and personalization. A look at what this means for creators and the music industry.
GitHub Actions Is Finally Getting Serious About Supply Chain Security
GitHub's 2026 roadmap tackles CI/CD vulnerabilities with dependency locks, execution policies, and endpoint monitoring. Here's what it means for developers.
How Facebook Built Friend Bubbles: A Deep Dive into Social ML Architecture
Meta's friend bubbles system combines closeness prediction models, ranking optimization, and performance engineering to surface friend-driven content at scale.