Ai

The “AI agent” label is doing a lot of heavy lifting right now. It covers a chatbot that drafts an email, a model that ships code on its own, and an autonomous system that operates a browser on your behalf. Same word, very different stakes. There are roughly four shapes these tools come in: chat, copilot, coding agent, autonomous agent. The lines blur, but the autonomy levels don’t. Here’s what each is good at, where each breaks, and how to decide which one to actually reach for. ...

You can paste a system description into an LLM and get back a STRIDE analysis in 30 seconds. A full threat list, categorised by type, with suggested mitigations. It looks thorough. It might even be thorough. That’s the problem. What LLMs Are Actually Good At Start with the honest case for using AI in threat modelling, because it’s real. Breadth coverage. A well-trained LLM has processed thousands of architecture descriptions, CVEs, and security design documents. It won’t forget to check for SSRF. It won’t skip repudiation because the session ran long. It has no blind spots born from familiarity with the system. For the common, well-documented threat categories, it’s genuinely reliable. ...

Anthropic announced Claude Mythos Preview on April 7, 2026. They described it as “a step change” and “the most capable model we’ve built to date.” That’s standard launch language. What isn’t standard is everything that came after. Here’s what the model actually does, why governments are paying attention, and what defenders can do now. What Mythos is Mythos is a general-purpose language model — 1M token context window, 128K max output, knowledge cutoff December 2025. On most benchmarks it performs as you’d expect from a frontier model at this scale. ...