Who should attend this course?

This course is designed for anyone who needs to grow visibility and traffic from ChatGPT, Gemini, Perplexity, Claude, AI Mode and all AI driven search interfaces.

Ideal for:

• SEO professionals who want to expand beyond Google blue links only playbooks
• Growth marketers and performance teams looking for new discovery channels
• Content strategists, writers, and editors who publish at scale
• Technical SEOs and developers responsible for site health and structure
• Product managers who work on search features or AI integrations
• Agencies and consultants offering modern GEO and AEO services
• Founders and brand owners preparing for an AI dominant discovery landscape

If your brand wants a stronger presence in AI generated answers, citations, and assistant driven sessions, this course is the right fit.

Course Overview:

AI assistants are now a major part of the global discovery ecosystem. ChatGPT alone receives billions of questions every day and every week, and platforms like Gemini, Perplexity, and Claude are becoming primary research and decision tools for users across all industries.

Grounding/web search plays a key role in this new environment. LLMs use grounding to verify information, reduce hallucinations, and select trusted sources. This means your website structure, content clarity, and entity consistency directly influence whether assistants choose your brand as a reliable answer.

Although AI search is new, strong SEO fundamentals are still required.

Proper crawling, structured content, internal linking, clean HTML, clear headings, semantics and topic coverage remain essential foundations. In this advanced course, you will learn:

• How ChatGPT, Gemini, and Perplexity retrieve, verify, and quote website content
• How grounding, retrieval, and re-ranking affect visibility
• How to create content that is consistently used in AI generated answers
• How to apply SEO fundamentals in an AI first world
• How to measure AI visibility with prompt tracking and share of voice models
• How to build high performing glossary hubs, comparisons, TLDR blocks, and definition sections, how to update your existing content
• How to structure your site for better indexing and reliable data extraction
• Real examples, case studies, and experiments from real brands

This is a practical course with space for your questions and real project discussions.You will leave with a clear list of tasks you can implement immediately, including technical improvements, content upgrades, and AI visibility checks.

By the end of the course, you will understand how to make your brand more visible in AI search, how to create content that assistants trust, and how to build sustainable GEO and AEO frameworks for long term performance.

Course positioning

• What GEO/AEO is (and isn’t): optimizing for answers and citations, not just rankings
• How LLM “search” differs from classic retrieval (indexing vs RAG vs tool/grounding & web mode)
• Success metrics: citation share-of-voice, answer inclusion rate, assistant-triggered sessions/leads

Module 1: Modern AI Retrieval & Ranking (the stuff people hand-wave)

• RAG pipeline anatomy: candidate generation -> re-ranking -> synthesis
• Why “topical authority” maps to embedding coverage + entity consistency
• Re-rankers, cross-attention, recency bias, negation handling, and “lost in the middle” realities
• Practical implications: where content must be ultra-clear vs where breadth wins

Module 2: Measurement: build your GEO/AEO telemetry

• Define a measurement model: prompts -> citations -> clicks -> conversions
• Effective use of Google Search Console, Bing Webmaster Tools to identify synthetic data.
• Citation tracking systems (prompt sets, variants, localization, persona)
• Share-of-voice frameworks (brand vs competitors, by topic cluster)
• Log + analytics signals: identifying assistant traffic, landing-page patterns, retention loops

Module 3: Technical Foundations (make your site easy to retrieve + quote)

• Crawlability for assistants: robots, sitemaps, canonical hygiene, duplication traps
• AI-friendly rendering: SSR vs CSR, performance budget, content discoverability
• “Citation-ready” pages: clean HTML, predictable headings, FAQ blocks, fix thin boilerplate

Module 4: Content Engineering for Citations

• Building answer-first sections: TL;DRs, definitions, constraints, comparisons, step-by-steps
• Entity-first writing: disambiguation, attributes, relationships, “entity panels” on-page
• Query fan-out content planning: single seed intent -> long-tail question graph
• “Quote shaping”: sentences that survive extraction (precision, numbers, qualifiers, caveats)
• Refresh strategy: when to update vs when to fork vs when to consolidate

Module 5: Competitive GEO: win the synthesis layer

• Competitor citation archetypes (datasource, explainer, benchmark, tool, glossary)
• Topic cluster wars: where you need breadth vs depth vs unique primary data
• Brand narrative control: consistency across pages + “about/credibility” surfaces
• Digital PR for AI: what tends to be repeated/cited across the web graph

Module 6: Hands-on Lab: build a GEO/AEO playbook live

• Pick a brand + 2 competitors + 1 money topic cluster
• Run a mini audit: top landing pages + gaps + formatting upgrades
• Create a prompt pack: 30–100 prompts across intents (how-to, comparison, troubleshooting, cost)
• Build a SOV snapshot + priorities list (Top 10 pages to fix/create)
• Draft 3 “citation magnets”: glossary hub, comparison hub, buyer questions hub

Module 7: Experiments & Iteration

• Testing framework: hypothesis -> change -> prompt set -> evaluation -> rollout
• What to test: TL;DR formats, definition placement, tables vs prose, citations/links, author signals
• Guardrails: avoiding spammy patterns, maintaining brand trust, mitigating hallucination risk for your brand
• Reporting cadence: using AI visibility tools, weekly visibility checks, monthly content releases, quarterly re-architecture

Module 8: Ops, Governance, and Scaling for teams

• SOPs for juniors: content templates, QA checklist, publisher workflow
• Dashboard requirements: inputs/outputs, prompt catalog, competitor sets, export formats
• Stakeholder comms: “what changed” narratives, executive summaries, ROI mapping

Take-home deliverables

• GEO/AEO audit checklist (technical + content + off-site)
• Prompt tracking template (prompt list, variants, result capture, scoring rubric)
• SOV model (brand vs competitors by topic + citation stability)
• 90-day roadmap: quick wins (2 weeks) -> compounding wins (30–60 days) -> moats (90+ days)