posts · 2026-07-30

This one's worth opening because the attack is unsettlingly simple: stuff a fake chain-of-thought snippet into the prompt, and GPT-5 plus gpt-oss-20b treat the dangerous instruction as their own reasoning and comply. The researchers call it chain-of-thought forgery, presented it at ICML, and won OpenAI's red-teaming hackathon with it. I'd discount the cross-vendor claims a bit—the post says Anthropic, Alibaba, and DeepSeek models showed similar results but doesn't name specific models or share test details. The core argument doesn't depend on any single vendor though: if an LLM uses special tokens to separate system/user/assistant roles, an attacker can forge assistant-side reasoning and the model will continue writing as if it thought of the idea itself. Authors Jasmine Cui and Charles Ye are blunt: red-teaming and patching amount to giving models a list of things they shouldn't do, and no list is exhaustive. They compare it to Bart Simpson writing lines on the chalkboard—he still acts up. The analogy isn't airtight, but it points to a structural issue: safety training shifts behavior distributions, it doesn't fix the underlying mechanism. No vendor response so far—OpenAI declined to comment to MIT Tech Review. If there's no architecture-level change, this class of attack probably sticks around.

This one's worth opening because $130 billion is a big number, and it comes from internal Microsoft documents, not analyst guesses. That makes it firmer than the figures floating around before. Multi-year leases mean Microsoft is betting AI compute demand isn't a short-term spike. The catch: the full article is behind a paywall. We've only got the headline and summary. No vendor names, no regional breakdown, no per-year lease cost. I'd take the direction as credible but can't go deeper without the details. For context, Microsoft's annual capex was running around $80 billion last fiscal year. A $130 billion total lease commitment suggests the infrastructure bet is scaling up again. If the full text surfaces, the two things to watch are lease duration and vendor concentration — those directly affect Microsoft's compute flexibility and bargaining power.

This caught my eye because it solves a real annoyance: you spin up multiple Claude Code agents to work in parallel, and their changes step on each other. The tool does one thing cleanly—rebases each agent's changes onto the latest main, merges them one at a time, and rolls back if there's a conflict. Same logic as GitHub's merge queue, just local. The README shows two modes: run it directly via the `claude` CLI, or wire it as an MCP server for Claude Desktop. Codebase is small—this reads like a personal experiment. The post doesn't disclose concurrency limits, team-scale testing, or how you get notified on rollback. I'd treat it as a handy queue script for one person running multiple agents, not a team CI solution yet.