Use GitHub with an AI Browser for Support Triage

Run support triage in Strawberry using GitHub as one of the inputs. Specific surfaces, example prompt, real output, and tradeoffs vs alternatives.

Diagram of Strawberry AI browser workflow using GitHub for support triage

If you use GitHub and you regularly need to triage and respond to support, the bottleneck is usually the same: GitHub 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 GitHub 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 GitHub is one of the inputs. It names the GitHub 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 GitHub needs to contribute to the workflow.

What signals support triage actually needs

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

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

What Strawberry can do inside GitHub

Strawberry can read PR diffs, summarize issues, comment with approval, and search code across repos.

GitHub surfaces Strawberry uses for this workflow: repos, PRs, issues, commits, Actions.

How Strawberry runs support triage with GitHub

  1. Strawberry opens the GitHub repos that contains the relevant context.
  2. The companion pulls related context from GitHub (PRs, history, attached files) where it exists.
  3. For the parts GitHub 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 GitHub or your system of record.

Example Strawberry prompt

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

Read this GitHub repos and any linked context.
Then run a full support triage workflow on it. Use the browser to fill any gaps not in GitHub.
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 GitHub for this, and where to use a different tool

GitHub is strong for this workflow because Strawberry can read PR diffs, summarize issues, comment with approval, and search code across repos.

Where GitHub falls short Private orgs need a separate OAuth app; rate limits on large repo searches.

Consider also the rest of your stack for the parts GitHub doesn't cover.

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 GitHub to Strawberry

GitHub OAuth - currently three separate apps for prod/dev/local. 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.

How GitHub + Strawberry runs support triage

1 GitHub

Read

Open the relevant GitHub repos; pull related context.

2 Browser

Augment

Use the browser, LinkedIn, news, and other connected apps for signals outside the CRM/tool.

3 Output

Compose

Synthesise into the support triage shape: A draft reply per ticket, plus a category label and priority - human reviews before send.

4 Human

Approve

Human reviews before any external action; approved output is saved back.

FAQ - GitHub + AI browser for support triage

Can Strawberry do support triage entirely inside GitHub?

No, and that is the point. support triage needs signals GitHub does not store - public web, LinkedIn, news, other apps. Strawberry combines GitHub with the browser, which is where the real value comes from.

Does GitHub need to be the primary CRM or system of record?

Not necessarily. GitHub can be one input among several. Strawberry can read it as context even if your primary system of record is somewhere else.

What permissions do I need on GitHub?

Read access to the surfaces you want Strawberry to use (repos, PRs, issues). Write permissions are only needed if you want Strawberry to update GitHub after a human approves the change. GitHub OAuth - currently three separate apps for prod/dev/local.

What is the realistic success metric for support triage?

first-response time under 2 hours, accurate-categorisation rate above 95%, draft-edits-before-send under 20% - that is the target Strawberry helps you hit, not the only thing it measures.

What is the biggest mistake to avoid?

Auto-replying with 'we'll look into it' without doing the work.