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The third time someone asks “what’s MRR by plan,” the agent should not be writing the join from scratch. It should be reading a view it built the first time. Materialization is the data agent turning recurring questions into durable, reusable structure in a schema it owns.

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The pattern

A recurring question is a signal. The agent promotes it from an ad-hoc query to a view in an agent-managed schema, then answers from the view.
  1. A question repeats, or a query gets validated as correct.
  2. The Engineer builds a view in its own schema (for example dash), never in public.
  3. The next ask hits the view directly: faster, cheaper, and consistent across users.
from agno.agent import Agent
from agno.models.openai import OpenAIResponses
from agno.tools.sql import SQLTools

engineer = Agent(
    name="Engineer",
    model=OpenAIResponses(id="gpt-5.5"),
    tools=[
        # Reads public, writes only to the agent-owned `dash` schema.
        SQLTools(db_url="postgresql+psycopg://dash_writer@warehouse/analytics"),
    ],
    instructions=(
        "When a question recurs, build a view in the dash schema that "
        "answers it. Never create objects outside the dash schema."
    ),
)

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Why an agent-owned schema

The agent writes structure, so that structure needs a sandbox. A dedicated schema keeps generated views away from the tables your product depends on.
public (your data)dash (agent-owned)
Who writesYour application and pipelinesThe Engineer agent only
HoldsSource tablesGenerated views and summary tables
Blast radius of a bad writeCatastrophicContained, droppable, rebuildable
Because the schema is disposable, a wrong view is a cheap mistake. Drop it and let the agent rebuild.

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Materialize from validated queries

The best materialization candidates are the validated queries from grounding. A query analysts already trust, asked often, is exactly what should become a view. The agent is promoting known-good SQL, not inventing new shapes.

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How it compounds

Each repeat question promoted to a view is one less query generated from scratch. Composed with the other primitives, the system does less work over time, not more:
  • Captured corrections stop the recurring errors (self-correction).
  • Validated query shapes sit in the knowledge stores (grounding).
  • The agent-owned schema accumulates the views your team relies on, with no hand-written migration.
Repeated work becomes structure instead of recomputation, so the agent gets faster and more consistent the more it is used.

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Next steps

TaskGuide
Keep writes inside the boundarySafe data access
Seed the validated queriesGrounding in context

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Developer Resources