Specs that engineering will actually build.
AI-drafted initiatives grounded in your real codebase. Specs that live in the repo, not in Confluence. Status visible without nagging.
A real code-grounded initiative with open questions and feature breakdown lands here.
What changes for you
Bring a plan to the meeting, not a doc.
Most PM work in 2026 is translation — turning intent into a Confluence page, defending it, then watching it diverge from what ships. Disco Parrot collapses the translation layer.
Specs grounded in real code
AI reads your actual codebase before drafting the initiative. The "we can’t do that" conversation happens on day one, not week six.
Specs live in the repo
Versioned markdown alongside the code. Engineering builds from the same artifact you wrote. No translation, no drift.
Status is a query, not a question
Every initiative’s state is in the audit trail. No more "how’s X going?" eight times a day in Slack.
A day in the life
From translation layer to direct authorship.
The PM in 2026 still writes specs in Confluence, chases engineering for status, and answers "what’s the latest on X?" eight times a day. The Disco Parrot day replaces the translation work with direct authorship.
8:30am
Standup
Today
Listen to three engineers describe what they shipped yesterday. Take notes. Try to map them to the four initiatives you’re tracking.
With Disco Parrot
Open the portfolio view. See every initiative’s state — in progress, in review, blocked on an open question. The standup is for color, not status.
9:30am
Spec writing
Today
Open Confluence. Stare at a blank page. Write a draft. Realize you don’t know whether the API actually supports this. File a question for engineering, wait.
With Disco Parrot
Run /initiative. AI reads the real codebase, asks clarifying questions, and drafts a structured initiative grounded in actual architecture. Edit alongside the AI.
11:00am
Stakeholder review
Today
Walk a VP through a Confluence doc. They ask questions you can’t answer (latency? scaling? breaking changes?). Promise to follow up.
With Disco Parrot
Open the initiative. The plan already includes the architectural constraints. Open questions are already named and assigned. The conversation is about priority, not capability.
1:00pm
Sprint planning
Today
Read tickets in Jira. Estimate from gut feel. Watch engineering object to the estimates. Re-plan.
With Disco Parrot
Plans are sized against the real code. Estimates reflect what the agent will actually need to touch. Sprint planning is a 20-minute review, not a 90-minute negotiation.
2:30pm
Stakeholder asks "status?"
Today
DM three engineers. Wait. Combine answers. Realize one engineer is on a different page. Re-DM. Compose a status update at 4pm.
With Disco Parrot
Send the audit-trail URL. The stakeholder sees the initiative, the open questions, the in-flight plans, and the recent PRs. Self-serve.
4:30pm
Roadmap thinking
Today
Open Productboard. Drag tickets into next quarter. Optimistic dates. No grounding in code reality.
With Disco Parrot
Use /initiative to draft Q[N+1] initiatives against the actual codebase. Realistic scope. Dependencies surfaced. Roadmap that engineering will commit to.
Where Disco Parrot fits
We don't ask you to throw out your stack.
For each part of your day, Disco Parrot either replaces something that wasn't serving you, plugs into something that already works, or makes something existing measurably better.
Replaces
- checkConfluence specs. Specs live in the repo, versioned alongside code.
- checkStatus-chasing in Slack. The audit trail is your status report.
- checkManual sprint planning docs. Plans sized against real code, not gut feel.
- checkOpen questions buried at end of doc. First-class tracked, assignable, resolvable objects.
Integrates with
- checkJira (read & link). Initiatives reference Jira tickets; status visible both ways.
- checkAzure DevOps. Native sync via /ado-sync; initiatives become ADO work items.
- checkGitHub / Bitbucket. Specs and code live in the same repo with the same PR review flow.
- checkSlack (notifications). Initiative state changes ping the channels you already use.
Improves
- checkSpec quality. Grounded in real architecture; "we can’t do that" surfaces on day one.
- checkEstimate accuracy. AI sees the actual files; estimates reflect actual work.
- checkStakeholder transparency. Audit trail = self-serve status; no PM bottleneck.
- checkOpen-question resolution. Tracked as first-class objects, not bullets at the end of a doc.
The toolkit
The PM toolkit.
Six surfaces designed to make PM work direct authorship instead of translation. Each one tied to the real codebase.
Code-grounded initiatives
AI drafts initiatives by reading the real codebase. No "we can’t do that" surprises six weeks in.
The AI reads your actual source files, identifies architectural constraints, asks clarifying questions about ambiguity, and proposes a structured initiative with phases, features, dependencies, and sizing.
Specs live in the repo
Versioned markdown alongside the code. Engineering builds from the same artifact you wrote.
No more "the Confluence page diverged from the implementation." Every spec is a commit. Diff history is your decision record. Engineering reads the same file the AI did.
Open questions, first-class
Tracked, assignable, resolvable. No ambiguity ships into implementation.
Questions live as structured objects in the initiative — not bullets at the end of a doc. They block /implement until resolved. The plan tracks who answered, what they answered, and when.
Portfolio status visibility
See every initiative’s state without opening Jira. The audit trail is your status report.
Filter by team, by status, by initiative. See in-flight plans, open questions, recent PRs. Send the URL to a stakeholder; they see what you see. No status meetings required.
Azure DevOps sync
Initiatives sync to ADO work items. Stakeholders see status where they already look.
Run /ado-sync to push initiative + plan state to Azure DevOps. State changes both ways — close an ADO item and the audit trail reflects it. Existing reporting tools keep working.
Sprint & roadmap planning
Roadmap generation tied to what’s actually in the codebase — not to optimistic estimates.
Draft next quarter’s initiatives against the real codebase. The AI surfaces dependencies, identifies architectural prerequisites, and flags risk. Roadmap commitments engineering can stand behind.
Plays well with what you already use
Works with the tools you already pay for.
Bring your own AI model. Bring your own sandbox. See the security architecture →
Every agent turn, tool call, and file write is logged server-side. Credentials never reach the browser. Sandboxes are ephemeral. Architecture →
Plan, build, and ship software with AI. Across your whole team.