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Field notes / Agentic marketing systems

Design an agentic marketing system around decisions

An agentic marketing system observes information, proposes or performs bounded actions, and checks outcomes. The architecture should make authority, evidence, and recovery explicit before increasing autonomy.

A CLEAR NEXT STEP01 / YOUR PATH
Read, apply, or discuss the idea?

Define the decision and its evidence boundary

Begin with a specific task such as prioritizing broken landing pages or preparing an editorial brief. State which sources are allowed, how fresh they must be, and what evidence supports an action. A model…

  1. Read the guidance
  2. Review your evidence
  3. Choose an application

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01 / UNDERSTAND

Define the decision and its evidence boundary

Begin with a specific task such as prioritizing broken landing pages or preparing an editorial brief. State which sources are allowed, how fresh they must be, and what evidence supports an action. A model response is not a substitute for a source record. Keep untrusted web content and inbound messages outside the system instruction boundary.

  • ✓ Name the decision owner and permitted inputs.
  • ✓ Distinguish literal observations, computed results, and inferred recommendations.
Read about Marketing implementation articles
02 / EVALUATE

Separate recommendation from execution

An agent can prepare changes without being allowed to publish them. Use explicit permission scopes for reading, drafting, editing, and external actions. Add idempotency to actions that might be retried, restrict destinations, and retain a record of approvals. Product integrations should be represented according to the connections implemented today rather than a future ecosystem diagram.

  • ✓ Require approval for high-impact or externally visible changes.
  • ✓ Provide rollback instructions and safe retry behavior for each action.
Read about Search Intel OS implementation
03 / APPLY

Evaluate the loop before broadening access

Test representative examples, malformed inputs, missing data, and service failures. Measure task correctness, reviewer corrections, execution failures, and business outcomes separately. Search Intel OS provides a place to explain HGM’s orchestration approach; its page should distinguish operational components from proposed architecture. Increase autonomy only when the evidence and controls justify the larger scope.

  • ✓ Retain action provenance and the input version used.
  • ✓ Review failed and rejected actions as part of routine operations.
Read about AI governance planning

YOUR NEXT STEP

Put the guidance to work.

Use the guidance to decide what evidence or implementation support you need next.

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STILL EXPLORING?

Make a shortlist before you decide.

Select the items relevant to your situation. Download a page-specific brief to keep or use in a project conversation.

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