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/Docs/How Content Is Generated

How Content Is Generated

How AI creates product descriptions, FAQs, and blog content at scale.

Standup StevoDocs managed by Standup Stevo

Overview

Every content on Liners — product descriptions, taglines, FAQs, and blog posts — is generated by AI with an extreme process of research and quality assurance that's almost impossible for humans to emulate without going on sick leave 50 times a year.

Product Content

When a product is added to our platform, we generate several pieces of content automatically:

Description

The product description (50-300 words) is generated using two system prompts:

  1. content_system: Sets the overall writing style, tone, and guidelines.
  2. content_generation: Provides the specific instructions for generating a product description.

The AI receives the product's name, website URL, and any existing information, then produces a factual, well-written description. We make sure the description avoids marketing fluff and focuses on what the product actually does.

Tagline

A short tagline (under 100 characters) is generated alongside the description. The tagline captures the product's core value proposition in a single line. It never ends with a period — that's one of Quinn's 47 QA checkpoints.

FAQs

Product FAQs are generated using a two-step process:

  1. Research: Using our faq_generation prompt, a search-enabled AI model researches common questions about the product by searching the web.
  2. Fallback: If the research doesn't yield enough results, our faq_fallback prompt generates FAQs based on the product description alone.

FAQs help users quickly understand key details like pricing, supported countries, integrations, and use cases.

Structured Output Hints

Our structured_output_hints system prompt provides formatting guidelines for AI-generated content. It includes rules for:

  • How taglines should be formatted.
  • How descriptions should be structured.
  • How content should handle technical terms.
  • Writing style consistency.

Blog Posts

We generate blog posts using a similar two-phase approach to comparisons:

  1. Research phase: Using our blog_research prompt, a search-enabled AI gathers current information about the topic.
  2. Writing phase: Using blog_system (editorial guidelines) and blog_article (structure), the AI produces a full article.

Our blog posts follow SEO best practices with proper heading hierarchy, keyword targeting, and internal linking.

System Prompts

We use a set of tunable system prompts to control content generation. Here's a summary of the content-related ones:

Prompt KeyPurpose
content_systemWriting style and tone guidelines.
content_generationProduct description generation instructions.
structured_output_hintsFormatting rules for taglines, descriptions, content.
faq_generationFAQ research instructions.
faq_fallbackBackup FAQ generation from description only.
blog_researchBlog post research guidelines.
blog_systemBlog editorial voice and standards.
blog_articleBlog post structure and format.
category_suggestionCategory assignment instructions.
tag_suggestionTag assignment instructions.
country_suggestionCountry identification instructions.

Having prompts be tunable means we can self0improve by refining content quality and style over time without changing any code.

Quality Control

All generated content passes through QA QuinnQA Quinn's QA process before going live. Quinn checks for:

  • Factual accuracy.
  • Proper formatting.
  • Length requirements.
  • No marketing fluff or hyperbole.
  • Consistent style across listings.

Summary

We generate content on Liners using AI with tunable system prompts. All content is reviewed by Quinn before publication.

OverviewProduct ContentDescriptionTaglineFAQsStructured Output HintsBlog PostsSystem PromptsQuality ControlSummary