Prep for a Follow-Up Meeting

The file

---
name: prep-for-follow-up
description: >-
  A one-page brief before your next customer meeting: what was said on the last call, open CRM notes and support tickets, and 3 to 5 questions worth asking.
  Task type: Prepare. Built for Sales.
  Use when the request sounds like "Prep for a Follow-Up Meeting".
  Do NOT use it to invent numbers, customer names, or quotes that were not supplied.
license: MIT
metadata:
  author: The Revenue AI Report
  suite: Meetings and Follow Up
  version: "1.0"
  source: https://www.therevenueaireport.com/prompts/prep-for-follow-up
---

# Prep for a Follow-Up Meeting

A one-page brief before your next customer meeting: what was said on the last call, open CRM notes and support tickets, and 3 to 5 questions worth asking.

One job only: a one-page brief before your next customer meeting: what was said on the last call, open CRM notes and support tickets, and 3 to 5 questions worth asking. Anything outside that job belongs in another file in the Meetings and Follow Up suite.

## When to use this skill

- The request matches the job above and the work repeats often enough to be worth a standard.
- You have, or can ask for, the inputs listed below.
- A person will review the output before it reaches a customer, an executive, or a board deck.

## When not to use it

- The answer needs a number, a benchmark, or a quote nobody supplied. Ask for it instead of producing one.
- The task is a different job in the same suite. Open that file rather than stretching this one.
- The output would be sent, published, or written into a system without a human read.

## Inputs to collect first

- customer name
- company name
- slack channel
- previous call summary
- potential questions

Ask for anything missing before running. Do not fill a gap with a plausible guess.

## Process

1. Confirm the job, the audience, and the decision the output feeds.
2. Collect the inputs above. Name anything still missing out loud.
3. Run the instruction block below exactly as written, with the placeholders replaced.
4. Separate what came from the supplied inputs from what is your inference. Label the inference.
5. Hand back the output plus a short list of open questions and assumptions.

## Instruction block

Run this text with the placeholders filled in.

```text
You will be preparing me for an upcoming meeting with a customer by gathering relevant information and drafting potential questions. Here are the steps to follow:

1. First, I will provide you with the following information:
- Customer name: {$CUSTOMER_NAME}
- Company name: {$COMPANY_NAME} 
- Relevant Slack channel: {$SLACK_CHANNEL}

2. Using this information, gather the following:
- Notes from the last Gong call with this customer
- Any relevant Salesforce notes about this customer/company
- Open Jira tickets related to this customer/company
- Relevant documents or files shared in the provided Slack channel

3. Once you have gathered this information, summarize what was discussed on the last Gong call, including any follow-ups or action items that were noted. Write this summary inside <previous_call_summary></previous_call_summary> tags.

4. Then, draft 3-5 potential questions I could ask the customer during our upcoming meeting. These questions should be relevant to their business needs, our previous discussions, or any open items. Write these questions inside <potential_questions></potential_questions> tags, with each question on a new line.

5. Finally, provide your response with the summary and draft questions inside the appropriate tags, like this:

<response>
<previous_call_summary>
[Summary of previous call with customer, including follow-ups/action items]
</previous_call_summary>

<potential_questions>
- [Potential question 1]
- [Potential question 2]
- [Potential question 3]
- ...
</potential_questions>
</response>

If you need any clarification or additional information from me, feel free to ask. Otherwise, please provide your complete response inside the <response></response> tags once you have followed all the steps.
```

## Decision rules

- Supplied evidence beats inference. If the two disagree, say so and keep the evidence.
- Unknown is a valid answer. Write "unknown" rather than estimating.
- Keep one recommendation per output. If the evidence supports two, present both and name the deciding input you do not have.
- Match the reading level of a working operator. Short sentences. Explain any term the reader may not use daily.

## Quality checks

- Every number, name, date, and quote traces to an input the user supplied.
- No vendor claim is repeated as fact without naming the source.
- Assumptions are listed separately from findings.
- The output answers the original request and nothing else.
- A reviewer could re-run this file with the same inputs and get the same shape of answer.

## Guardrails

- Do not send email, change CRM records, post publicly, or share data outside the workspace.
- Do not invent benchmarks, adoption rates, win rates, or customer references.
- Flag anything that needs a human decision instead of deciding it.

## Source

- Prompt page: https://www.therevenueaireport.com/prompts/prep-for-follow-up
- Suite: https://www.therevenueaireport.com/agent-skills/suites/meetings-and-follow-up
- Publication: The Revenue AI Report, https://www.therevenueaireport.com