Scriptonia is an AI-native product management workspace that turns rough ideas into production-ready PRDs, architecture blueprints, and engineering tickets in under 30 seconds. It is often described as the 'Cursor for Product Managers.' It is designed for product managers, founders, engineering leads, and startup teams.

How fast does Scriptonia generate a PRD?

Scriptonia generates a complete PRD — including objective, problem statement, user stories, success metrics, technical requirements, and timeline — in under 30 seconds using frontier AI models.

Does Scriptonia integrate with Linear, Notion, and Jira?

Yes. Scriptonia exports directly to Linear, Notion, GitHub Issues, Jira, Confluence, and Slack. It can also export to Markdown for use with any other tool.

Is there a free plan?

Yes. Scriptonia's free plan includes 30 credits per month, unlimited PRDs, Markdown export, and a public share link. No credit card required. You can also try it without creating an account at scriptonia.dev/try.

What AI models does Scriptonia use?

Scriptonia Pro and Team plans give access to multiple frontier AI models including Claude Sonnet (Anthropic), Gemini 2.5 Flash (Google), Grok 4 (xAI), DeepSeek R1, and Kimi K2. The free plan uses Grok 4 Fast.

Who is Scriptonia for?

Scriptonia is built for product managers, founders, engineering leads, and startup teams who need to move from idea to specification quickly. It removes the hours of manual writing that traditionally goes into a PRD.

A PRD (Product Requirements Document) is a specification that describes the purpose, features, functionality, and behavior of a product to be built. Scriptonia automatically generates structured PRDs from plain-language product ideas.

GUIDES

How to write user stories that engineers actually use

Most user stories are written for PMs, not engineers. Here's the format, the anti-patterns, and the acceptance criteria structure that make stories actionable in sprint planning.

Apr 11, 2026Updated: Apr 11, 20267 min readBy Scriptonia

A user story is a testable unit of value, not a feature description. 68% of engineering re-requests trace back to missing or vague acceptance criteria (Scriptonia, 2026) — the part of user stories that most PMs skip or write vaguely.

"The format isn't the problem. 'As a, I want, so that' is fine. The problem is that PMs write stories at the wrong level of specificity — too abstract to test, too broad to estimate."
— Sofia G., Engineering Manager at a B2B SaaS startup

The user story format that engineers actually use

The standard format: As a [specific persona], I want to [specific action] so that [measurable outcome].

What "specific" means in each part:

Persona: Job role + context. "Admin managing 10+ seat team" not "user".
Action: Observable, testable behavior. "Export a 30-day CSV" not "see my data".
Outcome: Why it matters. "Share with my VP without giving them system access" not "save time".

Acceptance criteria: the part that actually prevents rework

Every user story needs 3–5 acceptance criteria in the Given/When/Then format:

Given [context], When [action], Then [expected result]
Example: "Given I am an admin with Export permission, When I click Export CSV, Then a CSV file downloads containing all activity from the selected date range"
Example: "Given the date range spans more than 90 days, When I click Export CSV, Then the system shows an error: 'Exports are limited to 90 days'"

The user story anti-patterns that cause sprint failures

Anti-pattern	Problem	Fix
Vague persona ("user")	Engineers can't make edge case decisions	Specify role and context
Activity instead of outcome	"I want a dashboard" describes UI, not value	State what the user accomplishes
No acceptance criteria	No definition of done for QA	Write 3–5 Given/When/Then criteria
Compound stories	"I want to create AND manage AND delete" = 3 stories	One action per story
No edge cases	Engineers encounter them at 2am	Document at least 2 per story

How many user stories should a PRD have?

A well-scoped PRD for a single feature should have 4–8 user stories. More than 10 usually means scope is too broad. Fewer than 3 usually means the stories are at the wrong abstraction level (too high-level to be testable). Each story should take 1–3 sprint days to implement.

68%

Engineering re-requests from vague acceptance criteria

47%

PMs who skip edge cases entirely

4–8

Ideal user stories per feature PRD

Frequently asked questions

What is the correct user story format?

The standard format is: As a [specific persona], I want to [specific action] so that [measurable outcome]. Each story must be independently testable. The most common mistake is writing personas too generically ('user' instead of 'admin managing a 10-person team') and actions too abstractly ('see my data' instead of 'export a 30-day activity CSV').

What's the difference between a user story and an acceptance criterion?

A user story describes who wants what and why — it defines value and scope. Acceptance criteria define when the story is done — they are testable statements (usually in Given/When/Then format) that a QA engineer can verify. Every user story needs 3–5 acceptance criteria. A story without acceptance criteria is a wish, not a specification.

How detailed should user stories be?

Detailed enough for a QA engineer to write a test case without asking the PM for clarification. Each story should take 1–3 sprint days to implement. If a story takes more than 5 days, split it. If the acceptance criteria require more than one paragraph to explain a single criterion, the story is probably two stories.

When should I use epics vs user stories?

An epic is a collection of related user stories that together deliver a significant piece of user value. Use epics for planning at the roadmap level; use user stories for sprint planning and engineering specification. A typical epic contains 5–15 user stories. Each user story in the PRD should be implementable in a single sprint.

Can AI write user stories?

Yes — AI tools like Scriptonia generate user stories from a feature description. AI is good at producing correctly-formatted stories with reasonable acceptance criteria. The main review items: ensure the persona specificity matches your actual users, verify that acceptance criteria are testable by your QA team, and check that edge cases are product-specific rather than generic.

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