AI Academy for Agencies | Gumshoe
AI Academy for Agencies
LEARN FROM A
TOP PHD STUDENT
UNIV. OF WASHINGTON✦
Learn how large language models work, what drives visibility in AI search, and how to build a GEO practice that delivers real results for clients.
6 lessons · Self-paced video · Beginner to Intermediate
Nick Clark Nick Clark on LinkedIn Nick Clark's website
Research Engineer & PhD Student
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Welcome to the AI Academy for Agencies by Gumshoe AI!
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What you'll learn
AI Visibility Foundations 6
- Understand how LLMs generate probabilistic answers, not ranked results
- See the core difference between SEO and GEO
- Understand how retrieval-augmented generation (RAG) differs from pure LLM responses
- Identify the AI platforms your clients need to be visible on
- Know which platforms to prioritize by industry
- Learn why visibility varies across ChatGPT, Gemini, Claude, and Perplexity
Measuring Brand Visibility 5
- Learn what signals influence whether a brand appears in AI responses
- Build a prompt set that reliably tests a brand's AI visibility
- Understand what a strong versus weak AI presence looks like
- Identify the attributes AI models associate with your client's brand
- Spot gaps between how clients want to be described and how AI actually describes them
Content and Citation Strategy 7
- Know which content formats AI models weigh most heavily
- Avoid the most common GEO content mistakes agencies make
- Understand what makes a citation meaningful to an AI model
- Identify the publication targets that most influence model training
- Prioritize publication targets by impact and attainability
- Build a citation acquisition strategy from scratch
- Measure citation growth and connect it to visibility improvements
Selling and Delivering GEO 6
- Know where to focus your attention first for clients
- Build a repeatable content calendar for a GEO retainer
- Frame GEO in terms skeptical clients immediately understand
- Price GEO services confidently against comparable digital marketing services
- Structure a GEO retainer with clear deliverables and milestones
- Build a monthly report that demonstrates measurable visibility progress
Course curriculum
0 of 6 complete
Lessons marked complete after watching or by clicking "Mark complete" below each lesson.
Module 1: Foundations
Lesson 1
Introduction to LLMs and What Drives AI Visibility
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Start here. Nick breaks down how large language models actually generate answers, why AI search is fundamentally different from Google, and what factors determine whether a brand gets cited or ignored.
20 min
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Lesson 2
Why Buyer Personas Matter for AI Visibility
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Not all AI search tools work the same way. Nick maps the major platforms — how they retrieve information, how often they update, and why a brand can rank well on one and be invisible on another.
16 min
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Lesson 3
How Many Times Should You Run a Prompt?
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Before you can improve a client's AI presence, you need to know where they stand. Nick walks through a structured audit process — which prompts to run, how to interpret the results, and how to identify the biggest gaps.
10 min
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Module 2: Strategy & Execution
Lesson 4
How to Optimize Content for Higher AI Visibility
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Content is the primary lever for improving AI visibility. Nick breaks down exactly what types of content move the needle, where to publish it for maximum model exposure, and the common mistakes agencies make when producing GEO content for clients.
7 min
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Lesson 5
Why Third-Party Citations Influence AI Visibility
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Citations are the currency of AI visibility. Nick explains what makes a citation count, how to systematically build the citation footprint your clients need, and how to prioritize outreach when resources are limited.
6 min
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Lesson 6
Comparing Data Collection Methods: APIs, Scraping, and Clickstream Data
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GEO is a new service and clients don't always know they need it. Nick covers how to introduce GEO to existing clients, how to structure and price a retainer, and how to report results in a way that justifies the investment month after month.
9 min
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Your instructor
Nick Clark Nick Clark on LinkedIn Nick Clark's website
Research Engineer & PhD Student
Nick studies how large language models process and surface information, with a focus on what drives brand visibility in AI-generated answers. He brings that research directly into practice for agencies.
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