There is a quiet assumption baked into nearly every CI/CD pipeline running in production today: that a human being, at some point, made a decision. A developer pushed a commit. An engineer approved a pull request. A release manager clicked "deploy." The entire architecture of modern deployment
You launched your multi-tenant LLM platform. Onboarding is going great. Then one Tuesday morning, your support queue fills up with tickets from small customers saying the product feels "slow" or "broken." Meanwhile, one of your enterprise tenants is happily running a batch AI agent job that
If you run a multi-tenant SaaS platform with embedded AI agents, the next nine months may be the most consequential in your engineering organization's history. A convergence of emerging per-tenant audit trail standards, accelerating regulatory timelines, and the architectural debt baked into most agentic platforms is creating a
There is a storm quietly forming at the intersection of cloud economics, agentic AI workloads, and distributed systems engineering. Most backend teams are not watching it closely enough. By Q3 2026, the per-tenant AI agent compute spot market will have matured to the point where preemption events are no longer
Long-running AI agent sessions are quietly bankrupting token budgets across multi-tenant LLM platforms. If you are operating a shared infrastructure where dozens or hundreds of tenants run concurrent agentic workflows, you have almost certainly hit the wall: a session that started as a focused task assistant has ballooned into a