Your team asks questions. Your agent investigates.

"Break down our user base by age group and email domain. What % are on gmail vs company emails?"

Agent queries your database, segments users by age brackets and email domain, calculates the distribution, and returns a clean breakdown with percentages — no SQL required on your end.

"A customer reports duplicate submissions from several users — look into this before we create a ticket."

Agent searches the database for the flagged users, finds word-for-word identical entries, checks timestamps and submission sources, and reports back with the scope of the issue and whether it needs engineering.

"Summarize our active A/B experiments. Which ones have reached significance?"

Agent pulls all running experiments from PostHog, checks sample sizes and confidence intervals, flags which tests have hit statistical significance, and recommends which ones are ready to ship.

"Check this Linear ticket — I think we already fixed this bug recently."

Agent reads the ticket, searches recent commits and pull requests for related changes, checks if the fix is deployed, and confirms whether the issue is already resolved.

"Read this Slack thread and create a triage ticket for engineering."

Agent reads the full thread, extracts the key details, checks for related issues in Linear, and creates a new ticket with context, links, and suggested priority.

"Review this Linear issue and add your analysis — don't change the original description."

Agent reads the issue, investigates the codebase for the relevant code paths, checks Sentry for related errors, and posts a detailed comment with findings directly on the ticket.

"Do we have any Grafana dashboards tracking API latency? What do the p95 numbers look like this week?"

Agent searches your Grafana instance for matching dashboards, finds the relevant panels, pulls the current metrics, and summarizes trends — no need to dig through Grafana yourself.

"A user submitted a complaint through Intercom about being charged twice. Look into it and help me draft a response."

Agent pulls the conversation from Intercom, looks up the user in HubSpot and your database, checks payment records, identifies the issue, and drafts a response you can send.

"What is causing the spike in errors on the payments page?"

Agent pulls recent errors from Sentry, cross-references with your codebase to identify the faulty commit, checks PostHog for user impact, and gives you the full picture.