A message-based AI agent interface separates an agent's reasoning from the application that supplies work or consumes results. Messages can carry a task, caller identity, contextual references, tool availability, status updates, and structured outputs without requiring the application to reproduce the agent's internal loop.
Reliable interfaces validate every message, bind it to an authorized caller and task, set size and time limits, and handle retries without duplicating consequential work. They should distinguish progress from completion and treat all external message content as untrusted data rather than instructions that can override system policy.
ELI5
A message-based AI agent interface lets an application communicate with an agent through structured messages. A message can carry the task, caller, context, available tools, progress, or final result.
For example, a project system can send an agent a task identifier and approved file references, then receive progress updates and a completed report. The interface should validate every message and prevent a retry from repeating a consequential action.
What does a message-based AI agent interface carry?
It can carry task requests, caller context, capability references, status events, tool results, structured outputs, and bounded diagnostics.
Why must a message-based AI agent interface be authenticated?
Authentication lets the system apply the correct data and tool permissions and prevents an untrusted caller from impersonating an authorized user.
