In Episode 7 of the Intentional AI series, Cole and Virgil focus on content personalization and why it is one of the most overpromised areas of AI. While personalization is often positioned as simple and automated, doing it well requires far more clarity and intent than most tools suggest.

They break personalization into two main approaches. Role based personalization tailors messages for specific audiences or job functions, while behavioral personalization adapts experiences based on how people interact with content over time. The conversation also touches on predictive analysis and where AI may eventually help interpret patterns across analytics data.

A central theme of the episode is trust. Using AI for personalization assumes the system understands audience priorities and pain points. Without clear direction, AI fills in the gaps with assumptions. Cole and Virgil explain why personalization has always been difficult to implement, why adoption remains low, and why AI does not remove the need for strategy, measurement, or human judgment.

The episode also addresses the risks of personalization. Messages that are too generic get ignored, while messages that feel overly personal can cross into uncomfortable territory. Finding the right balance is still a human responsibility.

In the second half of the episode, they continue their ongoing experiment using the same AI written accessibility article from earlier episodes. This time, they test three tools by asking them to generate role based promotional emails for a head of web marketing, a director of information technology, and a C level executive. The results highlight meaningful differences in tone, structure, and assumptions across tools.

The takeaway is consistent with the Intentional AI series. AI can support personalization, but only when you define goals, outcomes, and boundaries first.

In this episode, they explore:

1. What content personalization actually means
2. Role based versus behavioral personalization
3. Why personalization adoption remains low
4. The balance between relevance and creepiness
5. How AI supports personalization without replacing strategy
6. A role based email comparison of Perplexity, Copilot, and Claude

A downloadable Episode Companion Guide is available below with tool comparisons and practical takeaways.

DS-S3-E7-CompanionDoc.pdf

Previously in the Intentional AI series:

1. Episode 1: Intentional AI and the Content Lifecycle
2. Episode 2: Using AI for Research and Analysis
3. Episode 3: AI and Content Creation
4. Episode 4: Content Management and AI
5. Episode 5: How much can you trust AI for accessibility?
6. Episode 6: You’re asking AI to solve the wrong problems for SEO, GEO, and AEO

New episodes every other Tuesday.

For more conversations about AI and digital strategy, visit

In Episode 6 of the Intentional AI series, Cole, Virgil, and Seth move into the visibility stage of the content lifecycle and tackle a common mistake they see everywhere. Teams keep treating SEO, GEO, and AEO as optimization problems, when in reality they are content quality, structure, and clarity problems.

Search engines andgenerative models have both gotten smarter. Keyword tricks, shortcuts, and “secret sauce” tactics no longer work the way they once did. Instead, visibility now depends on clear intent, strong structure, accessible language, and content that actually helps people. The group looks at how SEO history is repeating itself, why organizations keep chasing hacks, and how that mindset actively works against long-term discoverability.

They also dig into how SEO, GEO, and AEO overlap, where they differ, and why writing exclusively for AI can backfire by alienating human readers. The conversation covers content modeling, headless-style structures, and why these approaches help machines understand relationships without sacrificing usability.

A major focus of the episode is schema. The team explains why schema is becoming increasingly important for generative engines, why it is difficult and error-prone to manage at scale, and where AI can help draft complex schema structures without fully understanding context. This leads to a broader point. AI can accelerate specific tasks, but it cannot replace judgment, prioritization, or review.

In the second half of the episode, they continue their ongoing experiment using the same AI-written accessibility article from earlier episodes. They test how three tools approach GEO-focused improvements. Each tool surfaces different insights, none of them are complete on their own, and all of them require human decision-making to be useful. The takeaway is consistent with the theme of the series. AI is powerful when you ask it to solve the right problems, and dangerous when you expect it to fix foundational issues for you.

In this episode, they explore:

• Why SEO, GEO, and AEO fail when treated as optimization tricks
• How search has shifted from keywords to clarity, structure, and intent
• Where SEO and GEO overlap and where they meaningfully diverge
• The risk of writing for AI instead of for people
• Why content modeling supports both search engines and generative engines
• How AI can assist with schema creation and where humans must intervene
• Why repeating the same schema everywhere weakens its value
• A GEO-focused comparison of Writesonic, Grammarly, and Claude
• Why broad prompts underperform and targeted prompts lead to better outcomes

A downloadable Episode Companion Guide is available below. It includes tool notes, schema examples, prompt guidance, and practical takeaways for applying AI to search without losing clarity or control.

DS-S3-E6-CompanionDoc.pdf

Previously in the Intentional AI series:

• Episode 1: Applying AI to the content lifecycle
• Episode 2: Maximizing AI for research and analysis
• Episode 3: Smarter content creation with AI
• Episode 4: The role of AI in content management AI
• Episode 5: How much can you trust AI for accessibility?

Upcoming episodes in the Intentional AI series:

• Jan 6, 2026 – Content Personalization
• Jan 20, 2026 – Wireframing and Layout
• Feb 3, 2026 – Design and Media
• Feb 17, 2026 – Back End Development
• Mar 3, 2026 – Conversational Search (with special guest)
• Mar 17, 2026 – Chatbots and Agentic AI
• Mar 31, 2026 – Series Finale and Tool Review

Holiday break notice

Discussing Stupid will be taking a short break

In Episode 5 of the Intentional AI series, Cole, Virgil, and Seth shift into another part of the content lifecycle. This time, they focus on accessibility and how AI fits into that work.

Accessibility is more than code checks. It is making sure people can actually use and understand what you create. The team walks through what happened when they ran the High Monkey website through an AI accessibility review, where the tool gave helpful guidance, and where it completely misread the page.

They also talk about the pieces of accessibility that AI handles surprisingly well, especially language, metaphors, and readability, and why these areas are often missed by standard scanners.

In the second half of the episode, they continue the ongoing experiment from earlier episodes. Using the same AI written article from before, they test how three tools handle rewriting it to an adult eighth grade reading level, then compare the results with a readability checker. The differences across models show why simple writing, clear prompts, and human review are still necessary.

In this episode, they explore:

• How AI evaluates accessibility on a real website
• Where AI tools give useful insights and where they misinterpret content
• Why conversational explanations can help non technical teams
• How to prompt AI to look for the issues you actually care about
• The importance of plain language and readable writing in accessibility
• A readability comparison using Copilot, Perplexity, and Grammarly
• Why simple content supports both accessibility and AI performance

A downloadable Episode Companion Guide is available below. It includes key takeaways, tool notes, prompt examples, and practical advice for using AI in accessibility work.

DS-S3-E5-CompanionDoc.pdf

Upcoming episodes in the Intentional AI series:

• Dec 16, 2025 - SEO / AEO / GEO
• Jan 6, 2026 - Content Personalization
• Jan 20, 2026 - Front End Development and Wireframing
• Feb 3, 2026 - Design and Media
• Feb 17, 2026 - Back End Development
• Mar 3, 2026 - Conversational Search (with special guest)
• Mar 17, 2026 - Chatbots and Agentic AI
• Mar 31, 2026 - Series Finale and Tool Review

Whether you work on websites, content workflows, or internal digital tools, this conversation is about using AI with care. The goal is to work smarter, keep content readable, and avoid handing all of your judgment over to automation.

New episodes every other Tuesday.

For more conversations about AI, digital strategy, and all the ways we get it wrong (and how to get it right), visit www.discussingstupid.com and subscribe on your favorite podcast platform.

Chapters

(0:00) - Intro

(0:46) - Today’s focus: Accessibility with AI

(1:20) - We let AI audit HighMonkey.com

(4:00) - Finding the human value in AI feedback

(6:25) - The power of strategic prompting

(12:33) - We tested 3 AI tools for accessibility

(14:49) - AI Tool findings

(18:17) - Keep all your readers in mind

(20:50) - Next episode preview

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