AI giant Anthropic signs safety pact with Australia - aapnews.aap.com.au
<a href="https://news.google.com/rss/articles/CBMiiwFBVV95cUxOQ2NReDJFOGtTODRGYi1pNDhUUk1hdWQ1WmVwTFRwUEFVMXF5OGNqZE1HaG95dklLLXUydmlrNTF2NzRyR0J2SzlBZlFRZDN0dmpxYTdXOEdFNk1yWTVxMWhSaDZ4UDdCTXVXVFFnYmgxejlWcGhXSUtBRTJkNUs3bkxPVnk0YmVqSENn?oc=5" target="_blank">AI giant Anthropic signs safety pact with Australia</a> <font color="#6f6f6f">aapnews.aap.com.au</font>
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Writing Self-Documenting TypeScript: Naming, Narrowing, and Knowing When to Stop
There's a quiet kind of technical debt that doesn't show up in bundle size or test coverage: code that requires a mental simulation to understand. You read it line by line, holding context in your head, reverse-engineering what the author meant. It works — but it explains nothing . TypeScript gives you unusually powerful tools to fight this. Not just for catching bugs, but for communicating intent. This post is about using those tools deliberately in UI projects — the kind with complex state, conditional rendering, and types that evolve fast. 1. Name Types Like You're Writing Documentation The first place self-documenting code lives is in your type names. A good type name answers what this thing is , not just what shape it has . Avoid: type Obj = { id : string ; val : string | null ; activ
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AI agents are running third-party code on your machine. Last week, Anthropic announced extra charges for OpenClaw support in Claude Code , drawing fresh attention to the ecosystem. We wanted to answer a straightforward question: how safe are the most popular OpenClaw skills? We used AgentGraph's open-source security scanner to analyze 25 popular OpenClaw skill repositories from GitHub. The scanner inspects source code for: Hardcoded secrets (API keys, tokens, passwords in source) Unsafe execution (subprocess calls, eval/exec, shell=True) File system access (reads/writes outside expected boundaries) Data exfiltration patterns (outbound network calls to unexpected destinations) Code obfuscation (base64-encoded payloads, dynamic imports) It also detects positive signals: authentication checks
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The Indianapolis Data Center Shooting Is a Local Bug Report
If you’re building AI today, the indianapolis data center shooting is the incident your threat model is missing. Early on April 6, someone fired 13 rounds into Indianapolis councilor Ron Gibson’s front door while his 8‑year‑old son slept inside, then left a note reading “NO DATA CENTERS.” This happened days after Gibson backed rezoning for a Metrobloks data center in his district. Police haven’t confirmed motive, but the timing and the note are doing a lot of work. The non‑obvious part: this isn’t just “random political violence.” It’s the first loud bug report from a system where AI anxiety, local zoning fights, and invisible infrastructure all compile into one very physical attack surface. TL;DR The Indianapolis data center shooting turns abstract AI fears into a concrete target: the bui
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