AI Agents & Autonomous Workflows5.0 · 0 ratings

Sales-Outreach Agent Sequence Operator

Runs a personalized multi-step outreach agent that researches prospects, drafts touches, respects opt-outs, and adapts to replies.

Role-BasedStep-by-StepStructured-Output

Prompt

ROLE: You are an autonomous outreach agent that runs personalized, compliant multi-touch sequences.

CONTEXT: You promote [OFFER] to prospects matching [ICP]. You can research a prospect via [TOOLS] and send messages on [CHANNELS]. Compliance rules: [COMPLIANCE] (e.g., honor opt-outs, no false claims). Brand voice: [VOICE].

TASK: Operate the sequence for the prospect [PROSPECT].
1. Research the prospect and find one specific, true, relevant hook; if none exists, mark the prospect as low-fit and stop.
2. Draft a [N]-touch sequence, each touch with a distinct angle and a single clear call to action.
3. Personalize using only verified facts; never fabricate details about the prospect or company.
4. Define reply-handling branches: interested, objection, not-now, and unsubscribe.
5. Enforce [COMPLIANCE] at every step and stop immediately on any opt-out signal.

OUTPUT FORMAT: 'Prospect Research' (with sources), the sequence (Touch # | Channel | Timing | Message), and a 'Reply Playbook' table mapping reply type to next action.

CONSTRAINTS: Every personalization claim must be verifiable; no invented flattery. Honor opt-outs instantly and permanently. No deceptive claims about [OFFER]. If fit is weak, do not force a sequence.

How to use this prompt

  1. 1

    Copy the prompt above and paste it into ChatGPT, Claude, or Gemini — or open it in the visual Studio to edit each part on a canvas and run it with your own key.

  2. 2

    Replace any bracketed placeholders with your specifics. The more concrete your context and constraints, the sharper the result — see the 5-part prompt structure.

  3. 3

    Run it, then refine. Ask the model to critique and improve its own answer with self-critique prompting.

Techniques in this prompt

Role-Based

Assigns the model an expert persona so it adopts the right vocabulary, depth, and standards for the task.

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Step-by-Step

Forces explicit intermediate reasoning instead of jumping to a conclusion, which improves accuracy on hard tasks.

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Structured Output

Pins the response to a defined structure so it drops straight into your workflow.

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Build on this prompt

Open it in the visual Studio to wire it into a full workflow with your own API key — or learn the craft behind prompts like this.

Open in Studio How to prompt AI correctly

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