Language model–based agents are increasingly used to not just generate text, but to take actions: call APIs, run commands, read and write files, and update databases. Many setups today assume that if an agent has a capability wired in, it is allowed to use it. The default behavior is often to perform actions whenever the…

When you build agents with language models, it’s very tempting to go straight for the most powerful models. These are usually delivered by the biggest providers, running in their data centers, with impressive capabilities and benchmarks. That can be a great choice for experimentation and early prototypes, where you want to see what is possible…

In many organizations that adopt agents and language models, a clear pattern appears: about 1% of users consume roughly 90% of the resources. A few people run most of the prompts, build most of the automations, and drive most of the costs. Yet these resources are often not used well—they don’t generate new value or…