Be the AI Product Manager Who Actually Builds

Feedback triage, roadmap updates, spec drafts, and release notes. Describe the task in one sentence, the agent does it across your apps.

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PRODUCT MANAGEMENT AGENT

Triage this week's feedback and group it by theme

Mine sales call notes for the features deals keep dying on

Turn a rough idea into a fully written engineering ticket

Draft a full product spec from a one-line feature idea

Write release notes from the tickets that shipped this sprint

Assemble the weekly product update without opening a single tab

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Any PM Task. One Message. Done.

Feedback piling up, a spec to draft, a status update due in ten minutes. Tell the agent what you need and it works across Jira, Notion, Slack, and 1,500+ apps.

Get Work Done With Simple Chat Messages

Pull all customer feedback from the last 7 days from your helpdesk and the #feature-requests channel in Slack. Group every item by theme (bug, feature request, usability complaint, pricing). For each theme, count how many times it came up and pull 2 representative quotes. Add the breakdown to the 'Feedback Themes' tab in Google Sheets and post the top 5 themes to the product channel in Slack with counts.||

Feedback triage complete. 48 items grouped into 6 themes.

Weekly Feedback Themes — Jun 3–10

Theme	Count	Trend	Top Quote
🔴 Slow dashboard load	14	↑ from 6	"Takes 8 seconds every morning"
🟡 Bulk export missing	9	↑ from 4	"I export one record at a time, it's painful"
🟡 Confusing onboarding	7	→ flat	"Got lost after the second screen"
🟢 Mobile bug (login)	6	↓ from 11	"Fixed for me after last update"
🟢 Pricing tier gap	7	new	"Nothing between $20 and $200"
⚪ Misc / praise	5	→ flat	"Love the new filters"

Summary: Dashboard performance is now the #1 complaint, up sharply from last week. Bulk export is the most-requested missing feature. The mobile login bug is trending down, suggesting last week's fix landed. Pricing tier gap is new and worth a discovery conversation.

👇 Here's what your team could do with a single message.

1.Triage this week's feedback and group it by theme

2.Mine sales call notes for the features deals keep dying on

Pull all closed-lost deals from the last 30 days from your CRM. For each, read the notes and call summaries to find the reason cited. Flag any deal lost due to a missing feature or capability. Group the lost deals by the feature mentioned, count them, and estimate the total deal value tied to each gap. Add the results to the 'Lost Deal Gaps' tab in Google Sheets and post the top 3 revenue-blocking gaps to the product channel in Slack.

3.Find the feature requests hiding in old support tickets

Search your helpdesk for all tickets from the last 90 days tagged as questions or complaints. Identify any that are actually disguised feature requests. Group them by the underlying need, count occurrences, and note which customer segment each came from. Add the consolidated requests to the 'Hidden Requests' tab in Google Sheets with frequency and segment, then post a summary to the product channel in Slack.

1.Turn a rough idea into a fully written engineering ticket

Take this feature idea: [paste idea]. Search Notion for any related discovery notes or past discussions. Write a complete engineering ticket with a clear problem statement, user story, acceptance criteria, edge cases to handle, and a list of open questions. Create the ticket in Jira under the current backlog, add appropriate labels, and link any related Notion docs. Post the ticket link to the engineering channel in Slack.

2.Find stale backlog items that have sat untouched for a quarter

Pull all tickets in the Jira backlog that haven't been updated in 90 days. For each, note the title, original priority, and who created it. Group them by theme and flag any that duplicate newer tickets. Add the list to a 'Backlog Cleanup' tab in Google Sheets with a recommendation to keep, merge, or close for each. Post the count and top candidates for closure to the product channel in Slack.

3.Reprioritize the backlog against this quarter's goals

Pull all backlog tickets from Jira and the quarterly goals from Notion. For each ticket, assess how directly it supports a stated goal and assign an alignment score. Flag high-effort tickets that don't map to any goal and low-effort tickets that strongly support one. Add the scored list to a 'Prioritization' tab in Google Sheets and post the recommended top 10 for the quarter to the product channel in Slack.

1.Draft a full product spec from a one-line feature idea

Take this feature concept: [paste concept]. Search Notion and your helpdesk for related customer feedback and past discussion. Draft a complete product spec in Notion with the problem, goals, target users, proposed solution, user flows described in prose, success metrics, edge cases, and out-of-scope items. Pull in the relevant feedback quotes as supporting evidence. Share the spec link in the product channel in Slack for review.

2.Pressure-test a spec by surfacing every gap an engineer would ask about

Read the spec at [Notion URL]. Act as a skeptical senior engineer and list every ambiguity, missing edge case, undefined error state, and unanswered question that would block implementation. Group the issues by severity. Add your findings as comments or a checklist in the Notion doc and post a summary of the top blockers to the product channel in Slack so they get resolved before the spec goes to the team.

3.Write acceptance criteria for every ticket in the next sprint

Pull all tickets assigned to the upcoming sprint in Jira. For any ticket missing acceptance criteria, draft clear, testable criteria based on the ticket description and any linked Notion spec. Write them in Given/When/Then format. Update each ticket in Jira with the new criteria and post a list of tickets that were still missing detail to the engineering channel in Slack.

1.Write release notes from the tickets that shipped this sprint

Pull all Jira tickets marked done in the current release. Group them into new features, improvements, and bug fixes. Write customer-facing release notes in plain language that focus on user benefit, not internal jargon. Draft an internal version too with the ticket references. Save both to a Notion page and post the customer-facing version to the launch channel in Slack for review.

2.Build a launch checklist and assign every owner

For the upcoming launch of [feature name], create a launch checklist in Notion covering docs, support enablement, marketing handoff, internal announcement, and rollout plan. For each item, suggest an owner based on past launches and set a target date relative to launch day. Create tasks in your project tracker for each item and post the checklist link to the launch channel in Slack.

3.Catch anything blocking the release before launch day

Pull all tickets tagged for the current release in Jira. Flag any that are still open, in code review, or failing QA. For each blocker, note the assignee and how long it's been stuck. Add the blocker list to a 'Release Risks' tab in Google Sheets and post a go/no-go summary to the launch channel in Slack with the open count and the riskiest items.

1.Assemble the weekly product update without opening a single tab

Pull this week's shipped tickets from Jira, active feature adoption numbers from your analytics tool, and any major feedback themes from Google Sheets. Write a concise weekly product update covering what shipped, what's in progress, key metrics, and notable customer feedback. Post the update to the product channel in Slack and email a copy to the leadership list via Gmail.

2.Track feature adoption since the last release

Pull usage data for the features released in the last 30 days from your analytics tool. For each feature, calculate adoption rate, active users, and week-over-week trend. Compare against the adoption targets in Google Sheets and flag any feature underperforming. Update the 'Adoption Tracker' tab in Google Sheets and post the highlights and concerns to the product channel in Slack.

3.Draft the monthly board update from your real data

Pull last month's shipped roadmap items from Jira, top adoption metrics from your analytics tool, and the feedback summary from Google Sheets. Compare progress against the quarterly goals in Notion. Draft a one-page board update in Google Docs covering what shipped, metric movement, what's next, and the biggest risks. Email it to the leadership list via Gmail.

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Set It Once. The PM Busywork Runs Itself.

Feedback triage, stale-ticket alerts, weekly updates, adoption tracking. Running on schedule and on trigger whether you're in a meeting or out of office.

Automate recurring processes in 30 seconds.

Triage every new piece of feedback the moment it lands

When this happens...

App

Helpdesk

When

When a new ticket is created in your helpdesk

Then do this...

👇 No workflow builder. Set it up in plain English.

Triage every new piece of feedback the moment it lands

When a new ticket is created in your helpdesk

When a new support ticket comes in, read it and classify it as a bug, feature request, usability issue, or question. If it's a feature request, add it to the 'Feature Requests' tab in Google Sheets with the customer segment and a one-line summary. If a similar request already exists, increment its count instead of duplicating. Post any request from an enterprise customer to the product channel in Slack immediately.

Get a digest of every feature request from the past week

Every Monday at 08:00 AM

Pull all feature requests logged in the 'Feature Requests' tab in Google Sheets over the last 7 days. Group them by theme, rank by frequency, and note total deal value where it's tagged. Write a digest of the top requests and post it to the product channel in Slack so the team walks into the week knowing what customers are asking for most.

Flag tickets that have stalled in code review too long

Every weekday at 10:00 AM

Check Jira for any tickets that have been in code review for more than 2 days. For each, note the assignee, reviewer, and how long it's been stuck. Post a gentle nudge to the engineering channel in Slack listing the stalled tickets so they don't quietly block the release.

Send the weekly product update to Slack before standup

Every Monday at 09:00 AM

Pull last week's shipped tickets from Jira, adoption numbers from your analytics tool, and the top feedback themes from Google Sheets. Write a concise update covering what shipped, what's in progress, and notable customer signal. Post it to the product channel in Slack and email a copy to the leadership list via Gmail.

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Product Playbooks Anyone on Your Team Can Run

Feature discovery, spec writing, launch prep, quarterly reviews. Same rigor, same structure, every single time.

Complete repetitive processes in clicks

Run a full feature discovery from customer feedback

1. Discovery Scope

Discovery Scope

Fill fields below 👇

Feature Theme *

Feedback Time Window (days) *

Customer Segment to Prioritize

2. Gather and Analyze Feedback

Agent

Search the helpdesk and the feedback tab in Google Sheets for all comments related to Feature Theme within the last Feedback Time Window (days) days. Group them by underlying need and count occurrences per customer segment. Pull closed-lost deals from the CRM that cite this gap and estimate total deal value tied to it. If a Customer Segment to Prioritize was given, weight that segment's feedback in the summary. Frame the problem, pull the strongest supporting quotes, and rank the top opportunities by impact.

3. Write Discovery Doc in Notion

Create PageinNotion

4. Post Summary to Slack

Send MessageinSlack

👇 See use cases.

1.Run a full feature discovery from customer feedback

How this Playbook works?

Enter the feature theme you want to investigate and the time window to pull feedback from. The AI agent searches your helpdesk and the feedback tab in Google Sheets for every related comment, request, and complaint, then groups them by underlying need. It pulls related closed-lost deals from your CRM to estimate revenue impact and counts how many customers in each segment asked for it. The findings get written into a discovery doc in Notion with the problem framing, supporting quotes, affected segments, and estimated impact. A summary with the top opportunities gets posted to the product team in Slack.

2.Turn a rough idea into a build-ready product spec

How this Playbook works?

Enter the feature idea and the target user it serves. The AI agent searches Notion and your helpdesk for related discovery and customer feedback, then drafts a complete spec with the problem, goals, target users, proposed solution, user flows in prose, success metrics, edge cases, and out-of-scope items. It pulls in supporting feedback quotes as evidence and lists the open questions that still need answers. The spec gets created in Notion and the link gets shared in the product channel in Slack for review.

3.Prep a complete launch for a feature going live

How this Playbook works?

Enter the feature name and the target launch date. The AI agent builds a launch checklist covering documentation, support enablement, marketing handoff, internal announcement, and rollout, suggesting an owner for each item based on past launches. It checks Jira to confirm the underlying tickets are done and Notion to confirm docs exist, flagging anything incomplete. Each checklist item becomes a task in your project tracker with a target date, and the full plan gets posted to the launch channel in Slack.

4.Run a sprint planning prep from the groomed backlog

How this Playbook works?

Enter the sprint length and the team's available capacity in points. The AI agent pulls the prioritized backlog from Jira, checks each candidate ticket for complete acceptance criteria and estimates, and flags any that aren't ready. It assembles a proposed sprint that fits within capacity and maps to the quarterly goals in Notion. The proposed sprint gets written to a planning doc in Google Docs with each ticket's rationale, and a summary goes to the engineering channel in Slack ahead of the planning meeting.

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Less Jira Wrangling. More Product Thinking.

Describe your product task in one sentence. The agent does it across your apps.

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