Most of a product manager's day is connective work. Reading the support thread that mentioned the same gap a different customer raised last quarter. Re-reading the prior PRD to remember why you chose option B. Hunting through Slack for the engineer's question about the API constraint. Trying to remember whether the design call moved the empty-state copy decision or just discussed it. Eight hours of context-assembly to do two hours of actual product thinking.
The fix isn't a heavier ticket tool. It's holding the unstructured material — feedback snippets, decision rationales, prior PRDs, design conversations, research notes — in a single vault where the agent can read across all of it. The structured product work still lives in Linear or Jira or Shortcut. The connective tissue lives in the vault. The same shape underwrites architecture decision records kept where your agent can read them on the engineering side and contract negotiation rationale on the business side — same compounding rationale-log discipline.
A vault shaped around the product, not the sprint
The shape that holds up across product complexity is roughly: one top-level page for the product, with sub-pages per surface area or feature theme. Each surface page holds the running notes, the decisions log, the open questions, the user stories backlog, and the customer feedback bucket. A separate top-level page for the roadmap with the strategic-rationale narrative, the prioritization log, and the trade-offs you've made.
Capy supports unlimited page nesting, so a heavy surface — auth, billing, the editor, whatever the load-bearing area is — can fan out by sub-feature without forcing structure on lighter ones. The whole vault is plain markdown. That matters because when you sit down to write a PRD, you ask the agent to read the relevant surface page, the related customer feedback, the prior decisions, and the design notes, and to draft a v1 of the PRD. Edit, ship.
User stories drafted from real customer language
Most user stories get written in PM-voice — the abstracted "as a user, I want to X so that Y" structure that nobody actually says. The stories that work are written in customer-voice — the actual phrasing the customer used in the support ticket or the call recording.
A working setup: each surface page has a customer feedback sub-page where you drop quoted snippets from support threads, calls, NPS comments, and casual Slack channel mentions as they land. Two minutes per snippet. Tag the source, the date, and the customer segment if non-confidential. The page becomes a primary-source archive of how customers actually talk about the surface.
When you sit down to write user stories, ask the agent to read the feedback page and propose stories using the actual phrasing customers used, grouped by underlying job-to-be-done. You edit. The stories that come back are recognizably from your customers, not from a template. (The customer-signal-as-archive habit is the spine of how account managers keep client context from slipping — different role, same mechanic.)
Decision rationale that survives the next ambiguity
Product decisions get made fast and forgotten faster. The reason you scoped the MVP to one auth provider. The reason you moved the empty-state copy to the design-system layer. The reason you said no to the integration the sales team kept asking for. Six weeks later, when the same question comes back from a different angle, the rationale is gone and you're either making the same decision again or — worse — making a different decision because you forgot the original one.
The fix is mechanical. Each surface page has an inline decisions database via the :::database::: directive — rows for date, decision, rationale, owner, what triggered it, and what we'd want to revisit. After every working session, design call, or product meeting, ask the agent to propose entries from the recap. You confirm or edit; the rationale lands in writing while it's still fresh.
When the question comes back, you both look at the same row. The conversation is about whether the rationale still holds, not about what people remember saying. The same compounding habit makes annual planning much shorter — see AI notes for annual planning and goal setting.
Prior PRDs that teach the next PRD what to be
A team's product writing has a shape that took a year to develop. The way you frame goals, the way you list non-goals, the way you handle dependencies, the way you describe the rollout plan. Most PMs re-derive this shape for each new PRD because the prior ones live in Notion or Drive and starting blank feels easier than reverse-engineering an old one.
Drop the prior PRDs on the product page's PRD archive. They live as plain markdown alongside everything else. When you draft the next PRD, ask the agent to read the last three in this surface area and follow the same structure. The agent isn't generating from generic web data; it's generating in your team's voice, with your team's structure.
You edit. The first draft lands in the same shape your team already uses, which means the review cycle gets shorter — engineers and designers don't have to mentally translate from a new format to the one they're used to.
Roadmap rationale you can actually defend
The roadmap conversation that goes sideways with leadership or with the team is rarely about the items on the list. It's about the rationale behind the prioritization. Why this quarter, not next. Why this surface area, not the other one. Why the feature the loudest customer keeps asking for is below the line.
A working setup: a roadmap rationale page that holds the prioritization decisions and the trade-offs you've made, with links into the customer feedback and the strategic context that drove each one. When the rationale gets challenged, you don't reconstruct it from memory; you read the page and the conversation tightens to "does this rationale still hold," not "what was the rationale."
Ask the agent periodically to read the rationale page and the customer feedback across surfaces, and to surface anything that's drifted — feedback that's compounding around an item you have below the line, or evidence that something you prioritized is no longer matching what customers are actually asking for. The roadmap stops being a static artifact and starts being a living conversation. (The roadmap-as-conversation framing is the spine of first-time founders moving faster — different setting, same compounding shape.)
PDFs from research and analysts, finally readable
Product work generates a steady stream of long documents you should read carefully and probably won't. User research transcripts. Competitor teardowns. Analyst reports. Internal data-team writeups. Most of these get skimmed once and lost.
Drop the PDFs on the relevant surface page. They auto-convert to markdown via docstrange, which means the agent can read them as searchable text the same as any other note. Ask the agent to summarize a forty-page user research report in plain English with the unexpected findings called out separately. Or to pull every reference in an analyst report to the surface area you're scoping. Or to compare a competitor's release notes for the last six months against your own roadmap and surface where they're moving faster or slower.
The conversion runs once per upload and the document stays searchable from then on. This is what makes "chat with the research report" actually work — the agent isn't running OCR on every query; it's reading text it already has.
Recordings work the same way. The user research session, the cross-functional design review, the executive review where leadership pushed back hard — record those in Capy and the transcript comes back with speaker diarization (labels like "Speaker 1: …") so you can tell who said what. Ask the agent to pull the design decisions, list the open questions, and quote the customer's exact phrasing for the user-stories backlog. When somebody asks "wait, what did the user say about the onboarding flow," you find the moment with the speaker labeled.
What this isn't
Capy isn't a ticket tracker. The structured side of product management — sprints, ticket states, dependencies, release dashboards — still lives in Linear or Jira or whatever the team uses. Capy is for the unstructured side, which is most of the actual PM work: the writing, the rationale, the customer signal, the prior PRDs, the connective tissue. That's the part that's currently sprawled across Slack, Notion, Drive, and your memory.
It's also single-user by design. One PM, one vault. If your team needs a multi-user shared workspace where the whole product team edits the same PRDs with role-based permissions, that isn't this product. The shape that fits is the PM running the personal connective layer alongside the team's structured tools. Pricing tiers are on the pricing page.
A small first test
Pick the next PRD on your list. Drop the relevant customer feedback (paste a few support threads, attach the user research PDF), the most recent design recap, and the prior PRD in the same surface area. Ask the agent to draft a v1 of the PRD using the prior one's structure. If the draft surfaces a customer phrasing or a prior decision you'd otherwise have forgotten, that's the agent doing the connective work that makes PM time actually go to product thinking.
Try Docapybara free. Load one surface area's last quarter and see what the next PRD starts looking like.