Agentic-UA-Playbook

Agentic UA Playbook:
8 Workflows
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8 practical agent recipes for UA teams
(with prompts, outputs, QA checks, and next actions)

Al in UA is most useful when it helps with repeatable operational work - not when it tries to replace strategy or execution decisions.

This playbook is built for practical use:

what agents to use first
what data to give them
what prompt to use
what output to expect
what a human should verify before acting

What's inside

8 practical Al agent recipes for UA / Ad Ops
Copy-paste prompts
Clear output formats
Human QA checks

How to use this playbook

Each recipe uses the same structure:

1. Task — what the agent is for
2. When to use — the real moment in your workflow
3. Inputs — what data/context to provide
4. Prompt — copy-paste template
5. Expected output — what the agent should return
6. QA check — what a human must verify
7. Next action — how to turn output into action

Where to use these prompts

You can use these prompts in any LLM assistant your team already uses (ChatGPT, Claude, Gemini, or an internal Al assistant).

These prompts do not connect to ad platforms automatically.

They work as an analysis layer:

You provide the data (CSV, spreadsheet, campaign export, report)
You paste the prompt
The Al returns a structured analysis
A human reviews the output before action

Rule

Al = assistant, not autopilot.

Use it to monitor, summarize, structure, and suggest. Keep final decisions with a human.