WorkerKitJoin the waitlistAI workers for Product
AI workers for product teams that group feedback, keep the roadmap board honest, and turn tickets into themes before planning. Connect Jira, Linear, and Notion, then set firewall rules for exactly what the worker can read and write.
- Daily GitHub Repo Briefing Language model Reads the last 24 hours of GitHub activity and reports what actually changed: what shipped, what is blocked, what is at risk, and who needs a decision today.
- Google Review Watch Language model Checks your Google reviews every morning and tells your team which new ones need a reply today.
- Slack Team Update Brief Language model Turn relevant Slack activity into a focused team update on progress, blockers, risks, dependencies, changes, and attention needed.
- Release Note Classifier Decision model Returns release-note sections and merge judgments for pull requests so an agent can assemble a changelog.
- GitHub Issue Triage Decision model Reads a repository's open issues and decides what each one is, how badly it hurts, and whether it needs a maintainer.
- Idea Grill Language model Interrogates a product or business idea with the hard questions before anyone builds it, checks the market, and writes a one-page verdict.
- Spec to Linear Issues Language model Turns a spec you paste into the run message into Linear issues, one per deliverable, written to your team's standard and never duplicated.
- Competitor Pricing and Changelog Watch Language model Reads your competitors' pricing pages and changelogs every weekday morning and reports only what changed: a new price, a new plan, a dropped limit, a shipped feature.
- Customer Complaint Miner Language model Mines Reddit and public review pages for the ten complaints people make most about a product or category, each with verbatim quotes and links.
- Daily Funnel Drop Watch Language model Reads yesterday's funnel in Google Analytics every morning, compares each step with the week before, and says which step dropped past your threshold and where the drop came from.
- Customer Problem Evidence Review Language model Extracts customer problems and contrary evidence from product discovery meetings.
- Roadmap Commitment Review Language model Explains current product commitments and dependencies relevant to a proposed opportunity.
- Product Opportunity Brief Workflow Language model Connects customer problem evidence with roadmap commitments to draft a product opportunity brief.
What is a Product AI worker?
A Product AI worker is an AI agent set up to run one product job unattended, such as grouping user feedback, reconciling a roadmap board, or turning tickets into themes for planning. It typically touches Jira and Linear issues, Notion or Confluence roadmap pages, and Slack feedback channels, and only the projects, boards, and pages you approve.
What these workers do
Group user feedback into themes
Collect feedback from a Slack channel and linked Jira tickets, cluster it by theme, and write a ranked summary to a Notion page for planning.
Reconcile the roadmap board
Compare Linear issues against a Notion roadmap and flag items shipped but still marked planned, so the board reflects reality.
Prep a release note draft
Gather closed Jira tickets since the last release and draft plain-language release notes for the team to polish before publishing.
Flag issues missing a spec
Find Linear issues heading into the sprint with no linked doc and nudge the owner so nothing enters build undefined.
How a Product AI worker runs
What a product worker connects to
A product worker connects to where discovery and delivery live. Point it at Jira and Linear for issues, Notion or Confluence for roadmap and specs, and Slack for feedback channels. You approve which projects and pages it can read, so a feedback worker sees the customer channel without reaching engineering's internal repos.
When it runs
- On a schedule for a weekly feedback roll-up or a pre-planning board check.
- On a trigger when a ticket closes or a feedback message is tagged.
- On demand when a PM wants themes before a planning session.
What stays under your control
The firewall keeps the worker inside its lane. You can keep it read-only so it summarizes without editing tickets, limit writes to a single Notion page, and redact customer identifiers in feedback. Per-project scope keeps it to the boards you name, rate limits keep Slack calm, and the audit trail records every issue and page it opened. You can narrow or revoke access at any point.
Product questions, answered.
Can a product AI worker edit my roadmap?
Only if you allow it. By default a product worker reads Jira, Linear, and Notion to summarize and flag gaps while leaving the roadmap for a PM to change. When you grant write access, the firewall limits it to the pages or fields you approve and keeps everything else read-only, and every edit is recorded so the board only changes when a person intends it.
How does it handle customer feedback privately?
A product worker runs behind the firewall, which can redact customer names and identifiers before feedback reaches the model. You scope it to specific Slack channels and Jira projects, so unrelated data stays invisible, and DLP scanning flags anything sensitive. Every message and ticket it reads is logged, and you can revoke a channel's access whenever you need.
Can it work across Jira and Linear together?
Yes, a product worker can read issues from both Jira and Linear if you scope them in, cross-checking them against a Notion roadmap. It applies your read and write rules to each tool separately, so you might keep Linear read-only while letting it flag Jira items. You control which projects it reaches and can adjust them as work moves.
Will it close or change tickets by itself?
No, unless you grant write access a product worker only reads and reports, leaving ticket changes to your team. Most teams keep it read-only so it clusters feedback and flags gaps without touching status. When you do allow writes, they are confined to the fields you approve, logged in the audit trail, and revocable at any time.