Operations | Monitoring | ITSM | DevOps | Cloud

AI spend has no ceiling. An engineer can burn $5,000 in an hour, and a team that spins up an agent on Friday can loop it on a bad prompt all weekend. You find out when the bill lands: the money is already gone, the damage pieced back together from logs. Cloud spend had a natural limit. Tokens don’t. Now you see it as it happens. Connect a source and the calls stream in within seconds. Within minutes they’re broken out by model, provider, agent, and user.

Claude Mythos is now available to the public through Claude Fable 5, released June 9, 2026. Claude Fable 5 pricing is $10 per million input tokens and $50 per million output tokens, exactly 2x Claude Opus 4.8 ($5/$25). Claude Mythos 5 (the restricted Project Glasswing version) has identical pricing. Prompt caching cuts input spend by 90%. Batch API pricing is $5/$25 (50% off). In April 2026, Anthropic announced a model it said was too dangerous to release.

The first post in this series argued that AI agent governance hasn’t kept pace with deployment. The second laid out the five pillars of accountability, and what is required. The third walked through why network policies, API gateways, MCP/A2A protocols, DIY security patterns, and Role-based Access Control (RBAC) each leave critical accountability gaps. So what does good look like? The five pillars define what AI agent accountability requires.

You know every service in your cluster by name. You know which team owns each one, what it talks to, how it scales, where its logs go. The agents are a different story. That’s not a criticism, it’s an observation, and it’s one we keep running into. Every company we talk to is shipping agents of some kind, from scales of 10s to 1000s. Customer service bots that field tier-one tickets. Internal copilots that draft emails and summarise meetings and write the boring half of every PR.