Assorted links 2026-05-19
Assorted links for May 19, 2026 - More AI stuff, of course:
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Every AI Subscription Is a Ticking Time Bomb for Enterprise - “OpenAI, Anthropic, Google, and the rest are running an industry-wide loss-leader program at a scale that has no precedent. They are selling enterprises filet mignon at gas station hot dog prices and calling it a business model. The gap between what your company pays for AI subscriptions and what it actually costs to serve those seats is not a rounding error. It is a gulf. And every organization that has built workflows, products, or entire business units on top of these subsidized prices is standing right on the edge of it. ❡ This should be front of mind for every CTO, CFO, and head of operations reading this. Because when the pricing corrects, and it will, the companies that treated AI as a permanently cheap utility are going to wake up to bills that make their current SaaS spend look quaint.”
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Exploits don’t cause cyberattacks: On thinking clearly about frontier AI advances and cyber conflict - “[M]ost of today’s attacker constituencies can currently achieve most of their desired outcomes using traditional means: simple phishing, credential stuffing, exploitation of known CVEs, etc. These constituencies aren’t likely to explode into hockey-stick adoption of AI vulnerability research tools. ❡ This should discipline our thinking about Mythos generating a discontinuous volume of cyberattacks, because, again, most attacker constituencies just aren’t blocked by vulnerability research for most of their workflows.”
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Finding Zero-Days with Any Model: Vulnerability discovery is an orchestration problem, not a frontier-model problem. - “[W]ell-resourced adversaries already use orchestrated workflows to hunt for zero-days at scale. They operate free from vendor usage policies, AUP friction during legitimate research, API rate limits on multi-hour runs, and curated access lists for embargoed frontier models. The seven-step refusal during severity assessment is exactly the asymmetry at issue: a defender doing legitimate work hit friction that a well-resourced adversary using uncensored open-weight models would not.”