Technical Guides
Step-by-step guides for building AI search optimization workflows. From agent pipelines to CMS integrations, learn how to automate your content strategy.
Build a Claude Code AI Search Optimization Loop with Superlines MCP
Learn how to use Claude Code and the Superlines MCP server to analyze AI search opportunities, refactor website code, improve content structure, and run a repeatable optimization loop with terminal-level verification.
Use Cursor + Superlines MCP to Build an LLM-Friendly Website
A practical developer workflow for using Cursor and the Superlines MCP server to benchmark AI search topics, audit pages, implement technical fixes, and improve how your website gets cited by AI models.
Use Lovable + Superlines MCP to Create AI-Ready Landing Pages
A practical guide to using Lovable with the Superlines MCP server to benchmark landing-page opportunities, generate AI-ready page structures, validate copy and schema, and publish pages that are easier for AI models to cite.
Automated Prompt Discovery: Find the Right Questions to Track in AI Search
A practical guide to discovering which prompts to track in Superlines — from manual import strategies to fully automated prompt discovery using Prompt Radar, Google Search Console, and MCP-powered agent workflows.
Building an AI Search Intelligence Stack: From Monitoring to Autonomous Optimization
A strategic guide to building a complete AI search optimization stack using Superlines as the intelligence layer, combined with content agents, SERP tools, and CMS automation for end-to-end brand visibility management.
Fan-Out Query Competitive Intelligence: See What AI Models Search Before They Answer
A deep-dive guide on using Superlines fan-out query data to understand how AI models research answers, identify competitive content gaps, and build automated competitive monitoring workflows.
How to Displace Competitors in AI Search with Citation Intelligence and Off-Site Strategy
A tactical guide to using Superlines citation data to map the competitive landscape, close citation gaps with targeted content, win third-party mentions on review sites, YouTube, and Reddit, and build platform-specific strategies for ChatGPT, Perplexity, and Gemini.
How to Build a BOFU Content Engine That Drives B2B SaaS Pipeline Through AI Search
A data-driven execution guide for B2B SaaS teams: use Superlines to identify high-intent BOFU queries, research what competitors cite, produce comparison and alternatives content that AI engines extract, and measure the impact on pipeline.
From Crawl to Citation to Click: The Technical Foundation of AI Search Visibility
Learn how AI search crawlers discover and index your content, the difference between AI Training and AI Search bots, how to find and fix pages invisible to AI, connect bot activity to actual citations, and measure real business traffic from AI search.
How to Audit, Optimize, and Measure Your Content for AI Search Citability
A hands-on playbook for auditing individual pages for AI readiness, optimizing them with structured data, building a prompt tracking portfolio, and measuring whether your changes actually improved AI search visibility.
Automate GEO Analysis and Content Creation with the Superlines MCP Server
A workflow-focused guide to automating AI search visibility analysis, content opportunity discovery, competitive intelligence, and content production using the Superlines MCP server in Claude Desktop, Cursor, Lovable, and other MCP-compatible tools.
How to Control Your Brand Narrative in AI Search: From Mentioned to Recommended
Learn how to move beyond just being mentioned by AI engines to being actively recommended. This guide covers diagnosing the gap between how you want to be described and how AI actually describes you, converting neutral mentions into positive recommendations, improving your position in AI-generated lists, and using sentiment data as a content feedback loop.
Practical Generative Engine Optimization: Use AI Search Data to Win More Visibility
A hands-on guide to using Superlines AI search data to understand your brand's position in AI-generated results, identify competitive gaps, and create content that ChatGPT, Gemini, Perplexity, and other AI engines actually cite.
SEO Meets GEO: How to Build a Content Strategy That Ranks in Google and Gets Cited by AI
A practical guide to running traditional SEO and AI search optimization as a unified program. Learn where SEO and GEO overlap, where they diverge, how to create content that serves both channels, and how to use your existing SEO assets to accelerate AI search visibility.
Setup Guide: Superlines MCP, Sanity MCP, and AEO Agent for Non-Technical Users
A beginner-friendly walkthrough for connecting the Superlines and Sanity MCP servers to Cursor and Claude Desktop, and setting up the Superlines AEO Agent in your project.
AI Search Intelligence for Agencies: From Pitching to Scaling Client Services with Superlines
A complete guide for agencies on using Superlines to pitch AI search services, onboard clients, manage multiple brands, deliver recurring reports, and scale operations — including cross-organization collaboration and MCP-powered automation.
How to Build a GEO + SEO Marketing Agent in Claude Desktop with MCP Servers
A practical guide to combining Superlines, DataForSEO, Bright Data, and other MCP servers in Claude Desktop to create an AI-powered marketing analyst that handles SEO research, AI search optimization, competitive analysis, content strategy, and reporting.
Build an Agentic AEO Content Pipeline with Mastra, Sanity CMS, and Superlines
A complete guide to building an AI-powered content intelligence and optimization agent that monitors your AI search visibility, audits content, fact-checks claims, and creates optimized articles automatically.
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