Requirements
Write a PRD with AI, then make it good
A first-draft PRD from a chatbot reads fine and says nothing. A structured pass — problem, users, vision, features, requirements — gives you one worth handing off.
Why one-shot PRDs read like slop
Ask a generic model for a PRD and it fills a template: vague problem statement, invented users, feature list with no rationale. It's confident and empty because it had nothing to ground it and no sequence to follow.
A PRD is a chain of reasoning — the problem justifies the users, the users justify the vision, the vision justifies the features. Skip the chain and you get sections that don't hold together.
Building it in the right order
Cadenly's PRD workflow walks the chain deliberately: brainstorm the problem and how real it is, define who it's for, shape the vision, then derive the features and requirements from those — each stage grounded in the last and in what it already knows about your product.
You steer with a sentence or two at each step and correct anything off. The result is a document where every feature traces back to a problem, which is what makes it buildable.
The second pass that matters
Good PRDs get critiqued. A self-review pass hunts for vagueness, hand-waving, and unsupported claims and tightens them — without inventing facts to fill space. That's the difference between a draft you'd be embarrassed to send and one an engineer can act on.
- A PRD is a chain of reasoning, not a filled-in template.
- Building problem → users → vision → features keeps it internally consistent.
- A critique-and-tighten pass turns a plausible draft into a usable one.
Write a PRD worth handing off
Cadenly's PRD workflow builds from problem to requirements, grounded in your product.
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