By making quick, cheap judgments, Jev can route tasks to the appropriate model, select relevant skills from a library, or decide how much "reasoning effort" an LLM needs. This pre-processing step drastically reduces token consumption, cost, and latency for AI agents.

Don't abandon SEO for GEO. LLMs rely on the same crawling and indexing systems as traditional search engines. To be cited by AI, you must first have strong SEO fundamentals like fast load times and structured data. GEO then builds on this by focusing on answering specific user questions.

Don't overcomplicate technical Answer Engine Optimization (AEO). The most impactful factors are the same as in SEO: strong internal links, proper schema markup, and ensuring LLMs can crawl your page. Hyped tactics like `LLMs.txt` are currently ineffective and not used by major search engines.

The system's real power comes from an LLM that analyzes saved content and automatically creates links between related concepts, like Wikipedia. This reveals non-obvious connections between different topics—such as SEO and Facebook Ads—that you might not have considered, creating a networked knowledge base.

Manually verifying thousands of business websites for a directory is a major bottleneck. By combining an LLM with a free, open-source web crawler like Crawl4AI, you can automate the process of visiting each site and checking for specific keywords, saving thousands of hours of manual labor.

Generative Engine Optimization (GEO) requires shifting from a 2D view of SEO (your site + backlinks) to a 3D model of "content clusters." This involves creating an interconnected web of assets across different platforms (YouTube, Reddit, blogs) that all reference each other and your brand to establish topical authority.

Unlike prompting an LLM with a complex request, using Jev effectively requires a mental shift. You must break down a large judgment (e.g., "is this a good lead?") into its constituent, simple questions (industry fit? company size? intent?) and run them in parallel.

The first step to influencing AI is ensuring your website is technically sound for LLMs to crawl and index. This revives the importance of technical audits, log file analysis, and tools like Screaming Frog to identify and remove barriers preventing AI crawlers from accessing your content.

The traditional SEO playbook is obsolete. The new goal is to educate Large Language Models (LLMs) with high-quality, structured data. This shifts the focus from simply ranking for keywords to ensuring AI recommends your product as the best solution for a user's problem.