Ryan Goloversic
🟩 Published by Ryan Goloversic • November 29, 2025
How AER Works in Practice
Start in the analog. Before you open a keyword tool, before you look at a competitor, before you write a single word, talk to people. Interview the business. The sales staff. The product designers. The customers. Record it. Transcribe it. Look for the delta between what exists online and what only exists in real conversation. This is what we call analog sweat. The dirt you dig up before you leave the digital receipt.
Map intent not volume. Every page you build starts with an H1 tied to a real problem and a real emotional state, not a keyword with acceptable difficulty. Every H2 maps to a prompt, a query, or a question a real person asks in natural language. Not how a professional phrases it. How a layman phrases it. How someone confused, stressed, or completely new to the topic types it into a search bar or speaks it to an AI.
Find the gap in every competitive landscape. Read the top pages for your target H1. Map every H2 they cover. Then look for what none of them answered. What questions go unresolved? What does a real practitioner know that these pages don’t show? That gap is your entry point. That is where you build.
Be recursive not cannibalistic. Traditional SEO treats covering the same topic from multiple angles as keyword cannibalization, a mistake to avoid. In GEO we call it Recursive Perspective and it is how you demonstrate mastery. Approach the same core problem from different angles, different customer states, different levels of awareness. Give the machine multiple entry points into your expertise.
Build the ongoing system. AER is not a launch deliverable. It is a living practice. Regular interviews. Competitive analysis refreshes. Brief updates tied back to site structure. New support content spawned from gaps identified in existing pages. The system compounds over time.
We use the Onion Framework in our practice.Â
Observe what’s happening
Navigate the real problem beneath the surface
Investigate the gaps in public information
Organize the intel into usable structure
Network it across the site and ecosystem
Beyond Research: Reverse Probe Research
Here is where AER goes further than any research methodology that came before it.
Most research, including AER at its foundational level, starts with existing problems. Even analog intelligence gathering is discovering problems that already exist, just undocumented.
Reverse Probe Research engineers the problem statement before the market has language for it.
In traditional sales, a skilled rep probes to surface hidden problems the prospect didn’t know they had. Neil Rackham’s SPIN Selling built an entire methodology around this. The rep who asks better questions controls the conversation.
Reverse Probe Research runs this backward for content strategy. Instead of surfacing existing problems, you name problems the market feels but cannot articulate yet. You coin the term. You publish the solution. You build the content ecosystem around a named problem before anyone else knows to search for it.
This is what we call Query Origination, the act of creating the search before the search exists.
The Volume Trap is an example. Every SEO practitioner has felt it. Nobody named it cleanly. Once it has a name, practitioners search it. And the entity that coined the term is the one the machine traces back to as the origin.
Reverse Probe Research is how you stop chasing demand and start creating it. This is a core idea behind Generative Engine Orientation the method we developed to solve the problems with Generative Engine Optimization.Â
The Research Stack for AI Search
Here is how to think about the full research stack in the GEO era:
Keyword research tells you where existing demand lives. Still useful as a baseline signal. Not a strategy on its own.
Semantic SEO research tells you how to build your entity and connect to the knowledge graph. Essential structural layer.
Competitor content analysis tells you what already ranks and where the gaps are. Use it to find your entry point, not to model your content.
People Also Ask and forum research gets you closer to natural language and emotional framing. Good input for H2 mapping.
Prompt research tells you how people are querying AI systems. Forward-looking signal worth tracking.
Answer Engine Research sits above all of them. It adds the analog intelligence layer, the field-sourced experience that doesn’t exist anywhere online yet, and synthesizes all other research inputs into a coherent content architecture tied to real customer and machine journeys.
Reverse Probe Research sits above AER. It is the practice of engineering new territory rather than researching existing territory.
The stack moves from reactive to generative. Most practitioners are operating at the bottom two layers. The opportunity is at the top.Â
The Practical Starting Point
If you want to move from keyword research to AER today, start here.
Pick one page on your site. Find the top five ranking pages for its H1. Read every single one. Map every H2. Then write down every question those pages did not answer. Every tradeoff they glossed over. Every edge case they missed. Every piece of insider knowledge a real practitioner would know that none of them showed.
That list is your AER brief for that page.
Now go find a practitioner, a customer, a team member, a product designer, anyone with real field experience, and ask them about those gaps. Record the conversation. Transcribe it. Pull the insights that don’t exist anywhere online.
That is analog sweat. That is the delta. That is what the machine is starving for.
Build that page. Then do it for every page on your site. Then make it an ongoing practice.
That is Answer Engine Research.
That is how you stop doing keyword research for AI and start doing the research methodology AI actually rewards.
Read the full AER methodology:
https://rygolabs.com/answer-engine-research/
Remember the goal is Machine-share, Mind-share, Market-share.Â
This method was derived from our practice and what has had the best results for our clients based on our case studies.Â
Answer Engine Research (AER), Reverse Probe Research, Query Origination, the Volume Trap, Generative Engine Orientation (GEO), Machine Share, and the Entity Handshake are methodologies and terms coined and developed by Ryan Goloversic at Rygo Labs. First published March 28, 2026
Ryan Goloversic
Author of the Character Profile and the Laws of GEO, the tactical survival guide for the post-SEO era.
Ryan is an authority builder for the AI-driven search era. After a decade spent pioneering the content systems that turned MACkite into a global retail powerhouse, he synthesized the Character Profile Framework, a technical model designed to bridge the gap between business intent and algorithmic recommendation.
Drawing on the concept of expansionary business, Ryan’s work at Rygo Labs focuses on eliminating the “Trust Tax” of extractive marketing.
As a competitive athlete on the GKA World Tour, he brings the same physics-based discipline to digital ecosystems: if the alignment is off, the system collapses.
He doesn’t build for clicks. He builds for Predictive Continuity, ensuring that when Google and AI agents search for an authority to recommend, your entity is the only logical choice.
He’s also a globally recognized kiteboarder as of 2026 he's now an Eleveight kiteboarding team rider. His marketing career began in video, where he built the largest retail-based SEO and YouTube program in watersports with MACkite. When he’s not leading GEO campaigns or consulting teams, you can find him in the gym or competing on the KPLxGKA world tour.