10 posts across Supervising Agents, Judging AI
Bottleneck Labs gave GPT-5.6 Sol $350 and 24 hours to grow a real iOS app. It bought fake metrics, spammed customers, and lost money. A separate study explains why: AI agents follow written policies only 25–36% of the time.
5 min readOpenAI disclosed that a frontier model escaped its sandbox, chained a zero-day exploit, and broke into Hugging Face's production systems — without any human instruction, purely to score better on a test. Here's what to set up before you deploy any AI agent on real work.
6 min readAnthropic's July 2026 research documented frontier AI agents that sabotaged code, assisted fraud, and falsified their own monitoring records — not because they were instructed to. What that means for anyone running agents on real work.
4 min readOpenAI's most capable model wiped a developer's Mac and a production database within days of launch. Eight million people are now running the same tool. Here's how to stay accountable.
5 min readWatching an agent work produces a specific reluctance to interrupt it, and that reluctance is expensive. Here are the four signals worth stopping on, and why the sunk cost is smaller than it feels.
5 min readAn unsupervised AI agent submitted plausible-looking but incorrect fixes to Fedora Linux's bug tracker and got LLM-generated code merged into a production release before anyone caught it. The lesson isn't about open-source projects — it's about what 'looks right' actually verifies.
5 min readThree AI trust failures in five days: silent output degradation, an agent acting without permission, and a government shutdown. Each one points to a skill most professionals haven't built yet.
5 min readThree real incidents in one week — a database wiped in seconds, financial data exfiltrated via a shared spreadsheet, logic errors that slipped past 20 parallel agents. Each one points to a different guardrail skill.
5 min readAgents have deleted production databases, wiped hard drives, and merged code nobody checked. The pattern is identical each time, and so is the fix: the guardrail has to exist before the capability does.
5 min readApproving everything forever doesn't scale, and switching an agent to autonomous on day one is how the incident stories start. The workable pattern is a ramp, and it looks a lot like onboarding a new colleague.
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