> ## Documentation Index
> Fetch the complete documentation index at: https://support.metaview.ai/llms.txt
> Use this file to discover all available pages before exploring further.
# The Talent Map Method
> Calibrate a role once, save it to your Metaview knowledge, and reuse it on every search for that role.
Most searches start from a job description and a guess. The Talent Map Method starts from evidence: you spend ten minutes calibrating the role once, save the result to your Metaview knowledge, and every search for that role runs against it from then on.
Everything built live in the webinar is below — the prompt used to kick off calibration, and how to get the output into your own workspace.
**Ten minutes, once per role.** The calibration step is the investment; after that it's reusable context your whole team can search against.
## The prompts
Both prompts from the session live in the [Prompt Library](/guides/prompt-library#4-deep-research), under **Deep Research**:
Builds deep role context — what the work is, what strong evidence looks like, what looks right but isn't, and where this talent sits.
Maps your existing team into feeder companies, tenure patterns and career-path shapes — a description of how the team was actually hired.
Copy either one, paste it into the Sourcing agent, and fill in the blanks with your own role context.
Both prompts are calibration, not search. They deliberately return **no candidate profiles and no ICP** until you approve the findings — and they stop and ask before saving anything. That gate is the point: you review the evidence, then decide what becomes reusable context.
## Building your Talent Map
Here's a quick step-by-step recap of how to run your talent map calibration in Metaview, then save it to your Metaview knowledge for repeat use.
In Metaview Sourcing, click **Knowledge** (the book icon).
**Personal** is visible only to you. **Workspace** is visible to your whole team.
Click `Add New`.
**When to use:** `Use this when calibration is requested`
**What to do:** paste in the entire prompt — [4.1 Calibration Context Kickoff](/guides/prompt-library#41--calibration-context-kickoff) from the Prompt Library.
Press `Create`.
In a new search, type `Let's calibrate:` followed by your role context. Metaview guides you from there.
**Real evidence beats a well-built prompt every time.** When calibrating, add your Metaview conversations too — the kick-off call, feedback sessions, your hiring rubric. The more context the agent has to work from, the more closely the output will match what you actually need.
## Using your Talent Map to source
Once you've built the map, save it as context so the agent searches against it directly.
In Metaview Sourcing, click **Knowledge** (the book icon).
**Personal** or **Workspace**, as before.
Click `Add New`.
**When to use:** `Use this when searching for [role]`
Use the actual role you built the map for — that title is what triggers this context later.
**What to do:** paste in the entire Talent Map output.
Press `Create`. In a new search, kick off with the same role title: `Source candidates for [role]`.
A saved Talent Map is your stated criteria, written down and reused. Results still reflect alignment with those criteria rather than a judgment about candidate quality, and every decision about who to review or contact stays with you — see [Best practices for Sourcing](/account-management/privacy-and-security/ai-sourcing-best-practices).
## Where to go next
Both calibration prompts, plus prompts for Notetaker, Sequences and Reports.
The Sourcing task for mapping a target company's org and talent distribution.
Sizing a talent market before you spend a day sourcing.
Everything above runs in [Metaview Sourcing](/recruiting-platform/ai-sourcing). If you'd rather see it applied to your exact roles, [book a demo](https://www.metaview.ai/demo) and we'll build one together.