FOR PRODUCT
Turn Product Walkthroughs into Tickets and Specs
An agent-readable screen recording turns a product walkthrough into filed tickets. Talk through the live product pointing at what should change — each ask is bound to the exact element you hovered, so the ticket says which filter bar, not “the table thing we discussed.”
The whole loop in under a minute. Tap for sound.
One recorder, every workflow
Clipy is for every use case
Same loop, whatever your team does: record once, share one link, and an AI agent reads it and acts. Switch roles to see it play out.
Agent-ready fast
Chunks stream to the server while you record, so the moment you stop the summary, key-moment frames, and transcript are already building — a short clip is agent-ready in seconds.
Our own pipeline
On-device transcription and key-moment fusion we built ourselves — not a third-party API bolted on — tuned for speed and for the exact context an agent needs to act.
Fastest agent loop
The fastest agent-ready screen recorder: one link a teammate watches and an AI agent reads. No ticket, no repro write-up, no re-explaining.
Feedback dies in the gap between the screen and the ticket
You just walked a teammate through the product, pointing the whole way — this filter, right here, move this into settings. Then the walkthrough ends and you have to translate all of it into a tracker that only holds words. ‘This section’ becomes ‘the table thing we discussed,’ and the exact frame you were looking at is gone. Engineering opens the ticket, can’t tell which filter bar you meant, and asks — so the loop you thought you closed reopens a day later with half the specificity lost.
How it works
- 1
Walk the product
Point at what should change and say why. Cursor dwell and hovers are captured with the frame.
- 2
The agent classifies each ask
Every pointed-at request becomes a ticket draft with the frame attached and acceptance criteria from your words.
- 3
Tickets land in your tracker
Linear, Jira, GitHub — the agent files them where your team works, ready for grooming.
Deixis is resolved to the exact element and frame
When you say ‘this section’ or ‘move this over there,’ you’re pointing — with your cursor and your words at the same time. A normal recording throws the pointing away: it keeps the pixels but loses which pixel you meant. An agent-readable screen recording keeps both. Clipy captures cursor dwell, hovers, and clicks — with real coordinates on Mac-app and Chrome-extension recordings — and fuses them with the transcript, so every ‘this’ is bound to the element it landed on and the frame at that instant.
The result is a key moment: a timestamped frame of exactly what you pointed at, with the spoken ask attached. The ticket can now say ‘the date-range control in the orders filter bar,’ not ‘the table thing.’ Deixis stops being a lossy format.
Cursor and voice, together
The hover and the sentence are timestamped to the same moment, so the agent knows which element ‘this’ meant.
Real click targets
On Mac-app and Chrome-extension recordings, clicks carry coordinates — the agent gets the button you pressed, not a guess from a screenshot.
The frame is the proof
Each pointed-at ask ships with the extracted frame at that second, so nobody has to re-watch to see what you meant.
One walkthrough becomes filed tickets with criteria
After you stop, an agent reads the recording as a structured document — summary, key moments with frames, and a full timestamped transcript — and classifies each pointed-at ask into its own ticket. The acceptance criteria aren’t invented; they’re pulled from your narration at the moment you said it. ‘It should default to the last 30 days’ becomes a criterion on the date-range ticket, timestamped to the frame that shows the empty filter.
Because chunks stream while you record, the document is ready within seconds of hitting stop on a short clip — Clipy is the fastest agent-ready screen recorder, so the backlog draft lands while the walkthrough is still fresh. The same recording also supports a longer artifact: hand the agent the link and ask for the full spec, with frames inline as before/after references and your narration as the rationale.
One ask, one ticket
The agent splits a rambling walkthrough into discrete, groomable tickets — not one wall-of-text issue.
Criteria from narration
What you said out loud becomes the acceptance criteria, mapped to the exact second you said it.
Files where you work
Linear, Jira, or GitHub — the agent creates the issue in your tracker, ready for grooming.
The pointed-at frame is the screenshot
Half of writing a spec is chasing screenshots — asking design for a before-state, cropping the current UI, drawing an arrow at the thing you mean. In an agent-readable screen recorder, that step is already done. The frame you pointed at is the before screenshot; it’s extracted at the instant you referenced it and attached to the ticket automatically.
So a spec that used to need a Figma round-trip and a capture session comes out of the same recording you already made. No design request to file the ticket — the visual reference is the moment you said ‘this one.’
A Shopika orders-admin walkthrough, three Linear tickets
A PM records a three-minute agent-readable screen recording of the Shopika orders admin. They hover the filter bar — ‘there’s no date range here, add one, default it to the last 30 days.’ They scroll to an empty product list — ‘when there are no orders yet, this empty state should push a CSV import, not just sit blank.’ They click into the legacy fulfillment toggle — ‘this is buried, move it into settings where the rest of the config lives.’ Then they hit stop. Seconds later, an agent reads the recording and files three Linear tickets: a date-range filter with ‘default to last 30 days’ as a criterion and the filter-bar frame attached; an empty-state CSV-import CTA with the empty-list frame as the before; and ‘move the legacy toggle to settings,’ each carrying the exact frame the PM pointed at. Engineering opens them and never has to ask which control.
‘This’ survives the handoff
The element you hovered and the frame you looked at are attached to the ticket, so ‘move this over there’ arrives as a specific control — not a paragraph you had to reconstruct from memory.
A groomed backlog from one recording
Each pointed-at ask becomes its own ticket with criteria, not a Loom link an engineer has to re-watch and transcribe into issues.
No capture session, no design request
The pointed-at frame is the before-state, extracted and attached automatically, so a spec doesn’t wait on a Figma round-trip.
Lands in your tracker
Linear, Jira, or GitHub — the agent files each ticket where your team already grooms, ready to prioritize.
Product feedback: written up vs. recorded once
| The old way | With an agent-readable recording | |
|---|---|---|
| Capturing an ask | Talk over a Loom, then retype each point into a ticket from memory later | Walk the product once; the agent drafts a ticket from the element you pointed at |
| ‘Move this over there’ | Collapses to ‘the table thing we discussed’ by the time it’s written down | Resolves to the frame and coordinates at the instant you said it |
| Acceptance criteria | Written cold, after the fact, from scattered notes | Pulled from your narration, mapped to the second you said it |
| The before screenshot | A separate capture pass or a design request | The pointed-at frame is the screenshot, already attached |
| Where it ends up | A doc nobody re-opens | A filed Linear, Jira, or GitHub ticket, ready for grooming |
Common questions
How do I turn a product walkthrough into tickets?
Record the walkthrough as an agent-readable screen recording, pointing at what should change as you narrate. When you stop, an agent reads the recording — summary, key moments with frames, and transcript — and classifies each pointed-at ask into its own ticket, then files them to Linear, Jira, or GitHub. You review a groomable backlog instead of writing one from memory.
How does Clipy know which element I pointed at?
It captures cursor dwell, hovers, and clicks and fuses them with your transcript, so a spoken ‘this section’ is bound to the element under your cursor at that moment. On Mac-app and Chrome-extension recordings, clicks carry real coordinates, so the agent gets the exact control rather than guessing from a screenshot.
Do the tickets include acceptance criteria?
Yes. The criteria come from your narration — say ‘it should default to the last 30 days’ and it lands as a criterion on that ticket, timestamped to the frame where you said it. You’re not writing them cold from notes later; they’re captured at the moment the intent was clear.
Can it write a full spec, not just a ticket?
Yes. The same recording document supports a longer artifact: hand the agent the link and ask for the spec, and it writes one with the pointed-at frames inline as before/after references and your narration as the rationale. Ticket or spec, the source is the one recording you already made.
Do I still need to take screenshots for the spec?
No. The frame you pointed at is the screenshot — extracted at the instant you referenced it and attached to the ticket automatically. There’s no separate capture pass and no design request just to show engineering which state you mean.
Which trackers can the agent file tickets to?
Linear, Jira, and GitHub — the agent creates the issue where your team already works, so tickets arrive ready for grooming rather than sitting in a doc. The agent does the filing; Clipy supplies the structured context it files from.
Is Clipy a good screen recorder for product managers?
It’s built for the part PMs dread: turning a walkthrough into tickets. Recording, share links, transcripts, summaries, key moments, and the agent-readable document are all free, and one link serves both readers — your teammates get the normal video player, agents get the structured document.