Define context infrastructure for AI agents, distinguish it from RAG, memory, and runtimes, and recognize when permissions, auditability, and rollback become necessary.
Teams can make a single agent useful with a prompt, a model, and a few tools. The problem changes the moment you run multiple agents against the same business material (policies, customer notes, product docs, runbooks, incident reports) and you expect the output to be safe to depend on. Which agent is allowed to see which part of the context? Which agent is allowed to change it, and under what review rules? If an agent writes something wrong, can you inspect the diff, identify the identity, and recover?
Read the full article: https://www.puppyone.ai/en/blog/what-is-context-infrastructure-for-ai-agents
- https://www.puppyone.ai/en/blog/what-is-context-infrastructure-for-ai-agents
- Steve Mu
- support@puppyone.ai
-
context infrastructure, AI agents, multi-agent, RAG, agent memory
-
Define context infrastructure for AI agents, distinguish it from RAG, memory, and runtimes, and recognize when permissions, auditability, and rollback become necessary.