Use Linear with an AI Browser for Lead List Building

If you use Linear and you regularly need to build a verified lead list, the bottleneck is usually the same: Linear holds part of the context, but lead list building also needs signals that live outside it - on the public web, in LinkedIn, in news, in other connected apps. Strawberry is built to combine the Linear context with the rest of the browser, and run the full workflow as a companion you can re-trigger every week.

This page describes specifically how Strawberry handles lead list building when Linear is one of the inputs. It names the Linear surfaces involved, the signals the workflow actually needs, an example prompt you can paste, and what a good output looks like.

The job a SDR, marketer, founder doing outbound is trying to do

The goal of lead list building is to produce a clean, enriched, dedup'd list of N contacts who match ICP and have at least one buying signal. The success metric is concrete: bounce rate below 5%, dedup rate above 95%, and at least 30% of leads with a fresh signal. That definition matters because it shapes what Linear needs to contribute to the workflow.

What signals lead list building actually needs

For each signal below, here is whether Linear can contribute directly or whether Strawberry has to find it via the browser:

• ICP criteria (industry, size, geo, stack) - Linear does not contain this directly. Strawberry uses the browser plus public sources to fetch it.
• Title match including variants (Head of, VP, Director of) - Linear does not contain this directly. Strawberry uses the browser plus public sources to fetch it.
• Verified email pattern - Linear does not contain this directly. Strawberry uses the browser plus public sources to fetch it.
• Phone number (when reachable from source) - Linear does not contain this directly. Strawberry uses the browser plus public sources to fetch it.
• Recent buying signals (hiring, funding, product launch) - Linear does not contain this directly. Strawberry uses the browser plus public sources to fetch it.
• Existing CRM membership (to filter out already-contacted) - Linear does not contain this directly. Strawberry uses the browser plus public sources to fetch it.

What Strawberry can do inside Linear

Strawberry can read recent issues, create new tickets from external sources, and link related issues.

Linear surfaces Strawberry uses for this workflow: issues, projects, cycles, labels, states.

How Strawberry runs lead list building with Linear

1. Strawberry opens the Linear issues that contains the relevant context.
2. The companion pulls related context from Linear (projects, history, attached files) where it exists.
3. For the parts Linear does not store, Strawberry uses the browser - web search, LinkedIn, news, the prospect's website.
4. Strawberry synthesises the output in the shape this workflow needs: A CSV or sheet with one row per lead.
5. A human reviews before any external action (send, update, post). Then the approved output is saved back to Linear or your system of record.

Example Strawberry prompt

Paste this in a new Strawberry chat with Linear connected. Adjust the specifics to your actual ICP, role, or topic.

Read this Linear issues and any linked context.
Then run a full lead list building workflow on it. Use the browser to fill any gaps not in Linear.
Return the output in the shape we use for lead list building: A CSV or sheet with one row per lead: name, title, company, email, LinkedIn URL, signal, source.
Do not send anything externally. Save the draft to me to review.

What a good lead list building output looks like

Here is what a finished output for lead list building should look like in practice. The specifics will change for your use case, but the shape should look similar:

• Goal: 75 Head of Growth contacts at Series A-B SaaS in DACH
• Sources: a CRM-clean filter, a ZoomInfo/Apollo enriched pull, and a LinkedIn sweep with manual review
• Output: Google Sheet 'DACH-growth-2026-W23' with columns name, title, company, work email, LinkedIn URL, signal (hiring or funding), source notes

Why Linear for this, and where to use a different tool

Linear is strong for this workflow because Strawberry can read recent issues, create new tickets from external sources, and link related issues.

Where Linear falls short Linear permissions are team-scoped; bulk create requires GraphQL mutations.

Consider also a CRM for go-to-market follow-up.

Common mistakes when running lead list building

• Guessing email patterns and getting bounced
• Including duplicates because the source mixes work and personal emails
• Padding the list with leads who don't match ICP just to hit a count target

Connecting Linear to Strawberry

Linear OAuth. Once connected, the companion can read the surfaces above without re-authenticating, and any write action still requires explicit human approval the first time the workflow runs.

Caveats

Do not let any AI agent send emails, update CRM records, or change shared systems without a clear approval step. Strawberry is strongest when the workflow combines browser context with connected-app context and a human review for sensitive actions.