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This page is the fine print: how steps are allowed to connect, how schedules behave, what happens at each stage of a pipeline’s life, and the limits you will meet. You don’t need it to build a pipeline, because Rippit applies these rules for you. It is here for when you want to know why a pipeline was built the way it was, and for AI assistants that build pipelines on your behalf.

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How steps connect

  1. A pipeline starts from a table or from a schedule. The table is a data source. A pipeline with no source runs on its schedule alone and produces one row per run.
  2. AI columns, formulas, and lookups attach to a table. That table is a source or the output of a rollup. Each one adds columns to the table’s rows.
  3. A rollup reads one table: a source or an enriched table. It can filter and group by any column on that table, including AI columns and looked-up columns.
  4. Agent runs and actions work on the rows of a rollup. To act on something, first roll the data up to the unit you act on: an account, an owner, a topic, or the whole period.
  5. A step that reads another step’s column runs after it. A subtopic waits for its topic, an action waits for the agent that wrote its message.
  6. A lookup’s other table must already exist. It can be a source, an import, or a table from a pipeline that is already live.
  7. An action step either reads or writes. To look something up in another system and then act on it, a read step feeds a write step.
  8. External research is not a separate step. It is an agent run with search tools, so it runs once for each row of a rollup. A simple web or people lookup can also be a read step of an action.
Rippit sometimes builds one job as two pipelines: one that enriches the source and goes live first, and one that rolls up and acts on its output. This happens when a rollup groups by a column that depends on another step’s column, or when a lookup needs a table the same job produces. For the choices that keep a pipeline accurate and cheap, see What a well-built pipeline looks like.

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Schedules and delivery times

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What happens when

A row that fails in an AI column or an agent run is retried up to three times, with a longer wait each time. A pipeline cannot be deleted; pause it instead.

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Limits

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Tools an assistant uses

An AI assistant connected to the Rippit MCP server builds and manages pipelines with these tools. Rippit MCP tools lists each one’s access level. list_ai_models lists the models available for AI columns, agent runs, and agent search.