Skip to main content

AI product manager

Describe a rough idea, paste your backlog, or share your metrics and get product work you can act on: a build-ready spec, a prioritized roadmap you can defend, a sprint plan against real capacity, a metrics review with a next move. Zeplik works from the product context you give it, not a generic framework, and it is honest about the line: it drafts the artifacts and the reasoning, and it tells you which assumptions to test with real users and data before you commit.

Free to start. Nothing sends on its own.

Who it is for

How it works

  1. Share the product context

    Drop in the idea, the backlog, the goals, or the metrics. Nothing is assumed. The work is built only from what you share, and the more real context and constraints you give, the more useful and less generic the output.

  2. Ask for the product work you need

    Say it plainly, for example "turn this idea into a spec" or "prioritize this backlog." Zeplik routes to the right product skill without you naming it, and you can steer the scope, the framework, and the fidelity.

  3. Review, test, and commit

    You get a ready-to-edit spec, roadmap, or review with the reasoning shown. Test the assumptions with real user research and data, then commit the plan and move, all in one conversation.

What you can ask

Real asks in plain language, and the concrete deliverable you get back. Open the assistant to try your own; nothing runs until you send it.

Turn this rough idea into a build-ready spec.

A spec produced through staged gates: a clarifying interview, then a design doc with scope, acceptance criteria, and open questions, so engineering can pick it up without guessing.

Help me prioritize this backlog and defend the roadmap.

A prioritized backlog with an explicit rubric like RICE applied to what you paste, showing why each item sits where it does, so the roadmap is something you can defend in a review.

Plan the next sprint from our goals and capacity.

A sprint plan scoped against real capacity, accounting for time off and meetings, with a clear sprint goal, P0 versus stretch calls, and carryover handled.

Review these product metrics and tell me what to do next.

A metrics review over the numbers you paste: performance against targets, what is driving a spike or drop, and the specific next action it points to.

Is this idea worth building? Give me a pre-build review.

A risk review of demand, positioning, monetization, retention, and distribution before you commit, so you find the fatal flaw before you spend the sprint.

Interrogate this vague feature ask into clear requirements.

Scored clarification rounds that turn a fuzzy request into crisp, testable requirements, so the spec that follows is built on something real.

What it can do

The assistant routes to the right skill for you. Each one below is a focused, ready-to-run workflow; follow a link to see exactly what it does.

Strategy and discovery

Decide what is worth building before you build it.

Specs and requirements

Turn a fuzzy ask into something engineering can build.

  • Idea to specStaged gates from a rough idea to a build-ready design doc.
  • Requirements clarityInterrogate a vague ask into crisp, testable requirements.
  • PM toolkitRICE prioritization, interview analysis, and PRD templates.
  • AI featuresIntegration, safety, and cost guidance for a production LLM feature.

Plan and ship

Sequence the work against real capacity and priorities.

  • User storiesINVEST user stories, acceptance criteria, and backlog grooming.
  • Sprint planningScope a sprint against capacity with a clear goal and P0 calls.
  • Roadmap updateCreate or reprioritize a roadmap as priorities and timelines shift.

Measure and iterate

Read the outcome and scope the next rep.

What a general chatbot gets wrong on product, and what is different here

A raw chatbot will write a confident PRD and a roadmap with no grounding in your users, your data, or your constraints. Zeplik builds from the context you give it, applies real product frameworks, and is honest that the plan is a hypothesis to test, not a guarantee.

The failure. A general model writes a plausible-sounding spec that skips the hard questions and hides the assumptions it is making.

How Zeplik grounds it. Zeplik runs a clarifying interview first and surfaces the open questions and assumptions explicitly, so the spec is built on something real and you can see what still needs an answer.

The failure. Asked to prioritize, a general model ranks features on vibes with no consistent reason one beats another.

How Zeplik grounds it. It applies an explicit rubric like RICE to the items you paste and shows the scoring, so the roadmap is defensible and you can adjust the inputs rather than argue the output.

The failure. A general model treats its roadmap as fact and promises outcomes it cannot know.

How Zeplik grounds it. It frames the plan as a hypothesis, ties it to the metrics that would validate it, and is clear that priorities and estimates need testing with real user research and data before you commit.

What it does not do

Knowing the boundary is part of using it responsibly. This is where a person, not the assistant, has to own the call.

This is product thinking and draft artifacts for your review, not validated strategy or a guarantee of outcomes. Priorities, specs, and estimates reflect the context you provide, not your users or market, so test the assumptions with real research and data before you commit a roadmap.

Frequently asked questions

Is the AI product manager free?
Zeplik is free to start and every new account includes credits. Product skills run like any other Zeplik chat, so you spend only normal usage credits, with the cost shown before you send.
Can it write a real PRD or spec?
Yes. It runs a clarifying interview, then produces a build-ready design doc with scope, acceptance criteria, and open questions surfaced, so engineering can pick it up. You review and fill the gaps it flags.
How does it prioritize a roadmap?
It applies an explicit rubric like RICE to the backlog you paste and shows the scoring, so the ranking is something you can defend and adjust by changing the inputs, not a black box.
Can it read my product analytics or Jira?
Not yet. It works from what you paste and is honest about it. It does not connect to your analytics, Jira, or Linear, so bring the metrics and backlog you want it to use.
What do I need to give it?
For a spec, the rough idea and any constraints. For prioritization, the backlog. For a sprint, the goals and team capacity. For a metrics review, paste the numbers and your targets.
Does it replace user research?
No. It helps you plan discovery and turn findings into specs and roadmaps, but it cannot talk to your users. Ground the strategy in real customer conversations and data.

More on Zeplik

Turn your idea into a plan

Describe an idea or paste your backlog and get a build-ready spec, a defensible roadmap, or a metrics review you can act on. Free to start, and honest about what to test with real users before you commit.

AI Product Manager: Specs, Roadmaps, Sprint Planning & Metrics | Zeplik Chat