Use Asana with an AI Browser for Support Triage

If you use Asana and you regularly need to triage and respond to support, the bottleneck is usually the same: Asana holds part of the context, but support triage 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 Asana 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 support triage when Asana is one of the inputs. It names the Asana surfaces involved, the signals the workflow actually needs, an example prompt you can paste, and what a good output looks like.

The job a support engineer, founder doing support, CS lead is trying to do

The goal of support triage is to categorise inbound tickets, surface the urgent ones, and draft accurate replies grounded in product source-of-truth. The success metric is concrete: first-response time under 2 hours, accurate-categorisation rate above 95%, draft-edits-before-send under 20%. That definition matters because it shapes what Asana needs to contribute to the workflow.

What signals support triage actually needs

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

• Ticket category (billing, bug, feature request, account, security) - Asana stores or surfaces this directly. Strawberry reads it through the connected integration.
• Sentiment (positive, neutral, frustrated, churn-risk) - Asana does not contain this directly. Strawberry uses the browser plus public sources to fetch it.
• Product state (subscription tier, recent activity, feature flag) - Asana does not contain this directly. Strawberry uses the browser plus public sources to fetch it.
• History (has this user reported the same before) - Asana does not contain this directly. Strawberry uses the browser plus public sources to fetch it.
• GitHub/Linear status if it's a bug - Asana does not contain this directly. Strawberry uses the browser plus public sources to fetch it.
• Team-mate replies already in the thread - Asana does not contain this directly. Strawberry uses the browser plus public sources to fetch it.

What Strawberry can do inside Asana

Strawberry can create or update tasks based on meeting notes, research findings, or pipeline signals.

Asana surfaces Strawberry uses for this workflow: projects, tasks, subtasks, sections, milestones.

How Strawberry runs support triage with Asana

1. Strawberry opens the Asana projects that contains the relevant context.
2. The companion pulls related context from Asana (tasks, history, attached files) where it exists.
3. For the parts Asana 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 draft reply per ticket, plus a category label and priority - human reviews before send.
5. A human reviews before any external action (send, update, post). Then the approved output is saved back to Asana or your system of record.

Example Strawberry prompt

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

Read this Asana projects and any linked context.
Then run a full support triage workflow on it. Use the browser to fill any gaps not in Asana.
Return the output in the shape we use for support triage: A draft reply per ticket, plus a category label and priority - human reviews before send.
Do not send anything externally. Save the draft to me to review.

What a good support triage output looks like

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

• Ticket #1962 - Marcus Rosenberg (marcus@clubstill.com)
• Category: billing - plan-state mismatch
• Priority: P1 (paying user, $118 charge vs Intern credits)
• Verified: Stripe shows Intern, charge log shows $118 Part-Time amount, credits granted at Intern rate
• Draft reply: confirm Intern is active, apologise for the rate mismatch, grant 22k credit balance to match Part-Time tier for current cycle, no refund promised

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

Asana is strong for this workflow because Strawberry can create or update tasks based on meeting notes, research findings, or pipeline signals.

Where Asana falls short Custom fields vary by workspace; bulk operations need pagination.

Consider also a CRM for sales context.

Common mistakes when running support triage

• Auto-replying with 'we'll look into it' without doing the work
• Ignoring teammate replies already in the thread
• Guessing about product behaviour instead of checking GitHub or source code
• Automated security-report replies (always a major mistake - escalate to a human only)

Connecting Asana to Strawberry

Asana OAuth - workspace-scoped. 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.