Structured agent pipelines

Griptape lets a team define an AI agent as a sequence of discrete steps, such as pulling data, calling a tool, and producing an output, rather than one open-ended prompt. A Beam agent can trigger a defined Griptape pipeline when an approved condition is met, such as a new record appearing in a connected system, and pass the pipeline's result back into whatever tool started the request. This keeps each run traceable to the specific steps that produced it instead of a single opaque response. Where a step in the pipeline returns a result outside the range the account owner approved, the agent stops the run and hands the output to a person to check before anything downstream happens.

Tool and data connections

A Griptape agent can be built to call outside tools and data sources as part of its workflow, rather than working from a fixed prompt alone, according to how the account has configured it. Where permissions allow, a Beam agent supplies the specific data or credentials a given step needs and reads back what that step returns before moving to the next one. This keeps each external call scoped to what that step actually requires instead of exposing broader access than the task needs. Any step that requests access beyond what has been approved, or returns an error the workflow was not built to handle, is flagged for a person to look at.

Approval gates on agent output

Because a Griptape workflow runs its own defined logic, an account owner can mark specific steps as ones that should not proceed without a person confirming the result first, such as before a message goes out or a record gets changed. A Beam agent respects that gate: it runs the workflow up to the marked step, holds the output there, and notifies the person responsible for approval rather than continuing on its own. Once approved, the agent resumes the remaining steps. If no response comes back within the account's set window, the agent leaves the run paused rather than assuming approval and continuing regardless.