> ## Documentation Index
> Fetch the complete documentation index at: https://deepline.com/docs/llms.txt
> Use this file to discover all available pages before exploring further.

# Personalize outreach from verified evidence

> Prepare an evidence-backed outreach draft without sending or inventing a customer need.

[Human guide: work with your agent →](https://deepline.com/docs/human/guides/outbound-personalization-workflow.md)

Prepare a few outreach drafts with evidence attached. Check the person, account, and supporting facts before sending anything.

## Before you start

Use an authorized workspace and a small file with stable source IDs.
Have source access and your team's acceptance policy available.
This guide describes customer-authored logic, not an automatically enabled product policy.

## 1. Understand the decision

Personalization connects a supported observation to a relevant question. An observed event does not establish budget, pain, or purchase intent.

Test this fictional sample before calling providers:

| Case | Expected decision under this example policy |
| - | - |
| Dated source supports a company event | Attribute it accurately |
| Research suggests a possible need | Ask a question instead of asserting pain |
| Recipient identity conflicts | Hold the draft |

## 2. Inspect supported operations

```bash theme={"languages":{"custom":["/languages/deepline-prompt.json"]}}
deepline auth status --json
deepline search "account research company news contact" --type tools,prebuilts --json
```

Inspect a returned ID with `deepline describe <returned-id> --json`.
Compare required identifiers, outputs, access mode, and price.
A similar title does not establish that a contract fits.

## 3. Implement the bounded workflow

Ask your agent to author `outbound-personalization-workflow.play.ts` using [Write Plays](https://deepline.com/docs/sdk-v2/plays.md).
Have it declare the CSV input and preserve source IDs.
Reuse existing contracts when they fit the transformation.

Implement these rules explicitly:

1. Resolve the recipient and gather evidence relevant to the stated offer.
2. Retain source links and observation dates for message claims.
3. Draft from confirmed facts. Keep internal hypotheses separate from customer-facing assertions.
4. Return the draft and review reasons without activating campaigns or sending messages.

Keep external changes disabled for the first pilot.
That control belongs in the authored logic, not a universal Play dry-run flag.

## 4. Check and pilot

Prepare `pilot.csv` using [CSV-safe selection](https://deepline.com/docs/sdk-v2/batch-csv.md).
Then check the source:

```bash theme={"languages":{"custom":["/languages/deepline-prompt.json"]}}
deepline plays check outbound-personalization-workflow.play.ts
```

Resolve authoring errors first. After reviewing source and price, run only the pilot:

```bash theme={"languages":{"custom":["/languages/deepline-prompt.json"]}}
deepline plays run --file outbound-personalization-workflow.play.ts --csv pilot.csv --watch
deepline runs get <run-id> --full --json
deepline runs export <run-id> --out outbound-personalization-workflow-review.csv
deepline billing usage --run-id <run-id> --json
```

Use the ID returned by the pilot. Select a returned dataset path when several
exist. Provider-backed execution can incur usage.

## 5. Verify the outcome

Open each supporting source. Remove unsupported claims and confirm recipient eligibility before a separate activation step.

> [!TIP]
>
> Every source ID has a result or explicit exception. The fictional cases follow
> the stated policy, and actual results retain their evidence.

Ask your agent why a record was accepted, held, or rejected.
Correct the rule before expanding input or enabling external writes.

## Continue

[Outreach workflow](https://deepline.com/docs/plays/play-personalize-outreach.md) defines task boundaries. [Sequencer integration](https://deepline.com/docs/features/email-sequencer-integration.md) covers activation contracts.


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