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The richest part of a deal is the technical discovery call — and the writeup is usually a CRM note half the team won’t read. A discovery Agent turns the transcript into a structured summary: requirements, decisions, open questions, next steps. Everyone joining the next call walks in with the same picture.

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When this pays off

Writeups slip

The SE meant to write up the call. Three days later, it’s vibes-in-a-CRM-note.

Stakeholder handoffs lose detail

The next SE / AE on the deal can’t pick up where the last call left off because the writeup is too sparse.

Action items get forgotten

“We’ll send you the SAML doc” — and then nobody does, because it wasn’t tracked.

Demo prompts repeat themselves

The next call repeats discovery because the last one wasn’t captured well.

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The shape of this use case

A discovery Agent takes a call recording or transcript and returns a structured summary.

Inputs

Call recording or transcript, opportunity context, prior call notes.

Sources

Fireflies or other transcript source, CRM history, your discovery framework / MEDDICC template.

Output

A structured summary — requirements, technical decisions, open questions, action items per party, links to relevant Knowledge.

Delivery

Written back to the CRM as a structured note, posted in the deal Slack channel, emailed to attendees with a “did we get this right?” prompt.

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Where to start

Two ways in, depending on whether you want something running today or built to your exact spec.

Clone a pre-built Agent

Open Nate, Meeting Notetaker. More in the Marketplace.

Build your own

Start from scratch in the builder, or by describing it in Claude Code or Cursor with Programmatic GTM.
Either way, these are prompts your SEs can use on day one:
  • “Summarize this discovery call with Acme — pull out their requirements, our open questions, and the action items per side.”
  • “What were the technical concerns raised on the Globex call last week, and which ones did we resolve?”
  • “Walk me through the SSO discussion from yesterday’s Initech call — what did they say their constraint was?”

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Where to take it

Once it’s running, deepen it in three moves:

Give it a playbook

Shape it with a prompt, your discovery framework in Knowledge, and Bulk Schedule.

Automate it on signals

Wrap it in a workflow that fires on a trigger.

Let it improve

Feed back which sections SEs reference into the Agent’s evals so summaries track what matters.

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Common pitfalls

Generic LLM summarization smooths out the specifics. Force the prompt to preserve technical terms, exact constraints, and the customer’s literal phrasing.
Action items without an owner and a due date don’t get done. Require the Agent to assign and date each.
Sending an inaccurate summary to the customer hurts trust. Keep SE review on the customer-facing copy until you’ve watched it for several deals.
Some constraints are stated as “wishes” but they’re really hard requirements. Have the prompt flag any ambiguous language for SE review.