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Each building block has its own page, but the platform only makes sense once you see how they depend on one another. This page is the map — how the pieces reference each other, how data moves at runtime, and what’s reusable versus what’s isolated.

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The Dependency Map

The single most important thing to hold onto: Skills are the association hub. Connectors sit below them, the primitives hang off them, and agents compose them.
An agent, notice, never wires directly to a connector or a primitive. It composes skills, and the skills carry those links.

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Runtime Data Flow

At execution time, the pieces engage in a predictable order:
  1. Pick an agent. The user opens a published agent from the App home.
  2. Pick a workstream. The chosen workstream scopes the run to one client’s files, tables, and pipeline data.
  3. The agent begins. It starts from the user’s message or a trigger, with its configured skills and instructions.
  4. Skills execute. Each skill uses its connectors to act and returns structured output into the run’s context.
  5. Primitives supply data. The agent reads pre-computed rows from the Data Store and source files from File Explorer — all workstream-scoped — rather than hitting raw systems inline.
  6. Reasoning and logic. The model reasons over the accumulated context; glue logic routes, loops, and branches.
  7. HITL gate (if opened). Execution pauses, the app shows an “Action needed” card, a person decides, and their input is injected back into context.
  8. Complete. The agent finishes, persists results (often back to the Data Store), and logs the run under the workstream.

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The Two Tracks

Every concept belongs to one of two tracks — capability or data. They differ in almost every dimension, which is exactly why they’re kept apart.

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Reusability

The reuse rules follow directly from the two tracks: logic is shared, data is isolated.

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Why This Matters

This map is the difference between seeing six separate tools and seeing one coherent platform. When you know that skills are the hub, that pipelines feed the Data Store rather than the agent, and that workstreams wrap everything client-specific, you can reason about any change confidently — where to add a connector, why a pipeline belongs to a skill, what a new workstream will and won’t share.

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Next Steps

  1. Follow the build → run sequence step by step
  2. Review the design principles behind the model
  3. Map the old vocabulary to the new