AI Visibility Podcast with Jason Ai Wade of BackTier
- Episodes
- 303
- Released
- daily
- Latest episode
- Nov 14, 2026
About the podcast
AI Visibility Podcast by Jason Ai Wade of BackTier breaks down how businesses are discovered, interpreted, and recommended across systems like ChatGPT, Google, Gemini, and Perplexity AI. Each episode focuses on real execution-how visibility is assigned, how authority is built, and how operators influence outcomes in AI-driven environments.
Episodes 303
Ai for everyone: Don't Forget Bing! Why Ignoring Microsoft Could Be a Major AI Visibility Mistake
Don't Forget Bing!Why Ignoring Microsoft Could Be a Major AI Visibility MistakeEveryone talks about Google. Everyone talks about ChatGPT.But what about Bing?Microsoft's search engine has spent years operating …
Show notes
Don't Forget Bing!
Why Ignoring Microsoft Could Be a Major AI Visibility Mistake
Everyone talks about Google. Everyone talks about ChatGPT.
But what about Bing?
Microsoft's search engine has spent years operating in Google's shadow. Now, with AI-powered search, Microsoft Copilot, and an expanding ecosystem of AI experiences, Bing deserves another look.
Businesses spend enormous amounts of time optimizing for Google while overlooking another major search infrastructure provider.
If AI systems use search engines to find information, can your business afford to ignore Bing?
Bing Isn't Dead: Why Microsoft's search infrastructure remains relevant in the AI era.
Microsoft Copilot: How AI-powered experiences can use web search and retrieved information to answer questions.
Bing Webmaster Tools: Why businesses should verify their websites, monitor indexing, and investigate technical issues.
IndexNow: How supported websites can notify participating search engines when URLs are added, updated, or deleted.
Google Isn't the Whole Internet: Why being indexed and visible on Google doesn't guarantee equivalent visibility through Bing.
The AI Retrieval Connection: How search infrastructure can influence which sources are available to AI-powered experiences.
The Citation Question: Does Microsoft Copilot recognize, cite, or recommend your business when users ask relevant questions?
The Small Business Opportunity: Why checking Bing may reveal technical problems and visibility gaps that Google-focused SEO overlooks.
The Multi-Platform Strategy: Why AI Visibility requires testing across Google, Bing, ChatGPT, Copilot, Gemini, and other relevant systems.
Traditional SEO often became synonymous with Google optimization.
But AI discovery is distributed across multiple platforms, search indexes, retrieval systems, and conversational interfaces.
Bing indexing does not guarantee inclusion in Microsoft Copilot answers. And Bing's relationship with other AI products can vary by provider, product, and retrieval configuration.
The objective is to understand where your business can actually be discovered—not assume every AI assistant uses the same information.
Search Bing for your business name, website, and primary services.
Check whether important pages are indexed correctly.
Set up Bing Webmaster Tools and review indexing issues.
Evaluate whether IndexNow is appropriate for your website.
Ask Microsoft Copilot relevant named and unnamed business questions.
Compare results with Google, ChatGPT, and Gemini.
Document incorrect information, missing citations, and recommendation gaps.
AI Visibility isn't Google Visibility.
A business can perform well in one search ecosystem and remain poorly represented in another.
As AI assistants become another way customers discover businesses, relying on a single search engine creates unnecessary blind spots.
You've spent years trying to get Google to notice your business. Have you even checked Bing?
Presented by BackTier | NinjaAI.com
Topics: Bing, Microsoft Copilot, Bing Webmaster Tools, IndexNow, AI Visibility, GEO, AEO, AI Search, Search Indexing, Microsoft AI, Google Alternatives, AI Recommendations.
What We'll CoverThe Bigger PictureThe Simple Bing Visibility TestKey Takeaway
AI for Everyone: What Wauchula Chamber Junior Academy Talk Taught Me About the Future of Work AI Visibility Podcast with Jason ai Wade | BackTier
You Tube: https://youtu.be/KGFriXTrIp8AI for Everyone: What Wauchula Taught Me About the Future of WorkAI Visibility Podcast with Jason AI Wade | BackTierLocation: Hardee County Chamber of Commerce, Wauchula …
Show notes
You Tube: https://youtu.be/KGFriXTrIp8
AI for Everyone: What Wauchula Taught Me About the Future of Work
AI Visibility Podcast with Jason AI Wade | BackTier
Location: Hardee County Chamber of Commerce, Wauchula, Florida
Series: AI for Everyone | November 2026What happens when the next generation starts asking serious questions about artificial intelligence?
After speaking at the Hardee County Chamber of Commerce in Wauchula, Florida, Jason T. A.I. Wade reflects on a conversation about AI agents, privacy, creativity, education, and the future of employment.
Students and community members raised questions that extend far beyond which AI tool is best. Will artificial intelligence eliminate creative careers? Do students still need college? Can AI agents be trusted with personal information? And how can people prepare for jobs that may not exist yet?
Jason explores why AI should be understood as a knowledge and force multiplier, not a replacement for human expertise.
Drawing on his experience with the early internet, small businesses, and today's AI systems, he explains why knowing how to evaluate an answer may become more valuable than knowing how to generate one.
AI agents versus chatbots: How AI is evolving from answering questions to performing multistep tasks, and why human oversight still matters.
The future of jobs: Which types of work may face automation and why experience, judgment, and specialized knowledge remain essential.
Creativity and AI: Why generating a website, illustration, or presentation doesn't automatically make someone a skilled designer.
Privacy and personal data: What happens when AI tools connect to email, documents, calendars, and social networks.
AI and education: Whether formal courses are necessary and how students can begin developing practical skills.
The danger of AI confidence: How convincing but incorrect answers can create false expertise and reinforce assumptions.
Small-town opportunities: Why Wauchula, Hardee County, and other communities have valuable local knowledge that can be combined with AI to create new opportunities.
1. Your knowledge is the advantage.
AI can provide information, but understanding an industry, a community, or a real-world problem gives that information direction.
2. AI-generated work still requires judgment.
A polished answer isn't necessarily accurate. A beautiful design isn't necessarily effective. Human evaluation is essential.
3. Experiment before you invest heavily.
Try one practical AI application every week. Start with something you understand, test the results, and gradually expand what you can do.
Jason T. A.I. Wade is the founder of BackTier, an AI Visibility company focused on helping businesses become easier to discover, understand, cite, and recommend through artificial intelligence and search.
His work focuses on AI Search Engine Optimization (AI SEO), Generative Engine Optimization (GEO), Answer Engine Optimization (AEO), and the practical application of artificial intelligence to business operations.
Through the AI Visibility Podcast, Jason explores how AI is changing business, employment, technology, education, and everyday life. He also participates in local entrepreneurship initiatives and educational conversations throughout Central Florida.
Host and Community
BackTier — https://backtier.com
Jason T. A.I. Wade — https://jasonwade.com
Hardee County Chamber of Commerce — https://www.hardeecc.com
Polk Starts — https://polkstarts.com
AI Tools Discussed
ChatGPT — https://chatgpt.com
Claude by Anthropic — https://claude.ai
Grok — https://grok.com
Perplexity — https://www.perplexity.ai
Google Gemini — https://gemini.google.com
Lovable — https://lovable.dev
Gamma — https://gamma.app
Start with what you know. Use AI to do more with it. Keep your judgment.
Ai for everyone: The Invisible Business: Why Artificial Intelligence Will Decide Which Companies Get Discovered — Chapter One: The Cusp
The Invisible Business: Why Artificial Intelligence Will Decide Which Companies Get Discovered — Chapter One: The CuspFor decades, businesses competed to appear in search results. They built websites, invested …
Show notes
The Invisible Business: Why Artificial Intelligence Will Decide Which Companies Get Discovered — Chapter One: The Cusp
For decades, businesses competed to appear in search results. They built websites, invested in SEO, purchased advertising, and worked to attract visitors.
Now, the process of business discovery is beginning to change.
In Chapter One, "The Cusp," of The Invisible Business: Why Artificial Intelligence Will Decide Which Companies Get Discovered, Jason T. A.I. Wade explores the transition from traditional search engines to AI-powered discovery.
Customers increasingly ask AI assistants to identify businesses, compare providers, evaluate services, and make recommendations. Instead of browsing dozens of websites, they may receive a handful of suggested companies—or a single answer.
That creates a new competitive problem: A company can exist, operate successfully, and maintain a professional website while remaining largely invisible to AI systems.
This opening chapter introduces AI Visibility and examines how artificial intelligence is changing the relationship between businesses, customers, and the information systems that connect them.
The central question is no longer simply where your company ranks on Google. It's whether AI systems can discover your business, understand what it offers, verify its credibility, and consider it when generating recommendations.
The next era of business discovery will not be defined solely by who has the best website, but by which companies AI systems can reliably identify and evaluate.
Jason T. A.I. Wade is an AI Visibility architect based in Orlando, Florida, and founder of BackTier, which implements artificial intelligence for law firms.
Through NinjaAI.com and the AI Visibility Podcast, he researches how artificial intelligence discovers, classifies, cites, and recommends businesses.
His work focuses on AI SEO, Generative Engine Optimization (GEO), Answer Engine Optimization (AEO), digital identity, and machine-readable business information.
NinjaAI: https://ninjaai.com
BackTier: https://backtier.com
Jason Wade: https://jasonwade.comThe AI Visibility Podcast is produced by BackTier Media, an independent media initiative examining artificial intelligence, business, search, digital identity, and the systems shaping how information is discovered and trusted.
Ai for Everyone: Polk Starts: Where Polk County Ideas Start AI Visibility Podcast | Jason T. AI Wade | Founder, BackTier
Polk Starts: Where Polk County Ideas StartAI Visibility Podcast | Jason T. AI Wade | Founder, BackTierYou don't need Silicon Valley to start a business. Sometimes all you need is an idea, a conversation, and a …
Show notes
Polk Starts: Where Polk County Ideas Start
AI Visibility Podcast | Jason T. AI Wade | Founder, BackTier
You don't need Silicon Valley to start a business. Sometimes all you need is an idea, a conversation, and a few people willing to help.
In this episode of the AI Visibility Podcast, Jason T. AI Wade introduces Polk Starts, a free, countywide entrepreneurship community built around a simple idea: Meet. Share. Start.
Polk Starts brings together aspiring entrepreneurs, small business owners, creative thinkers, experienced founders, and community leaders throughout Polk County, Florida.
There are no formal presentations, no required pitches, and no complicated membership requirements. Just real conversations, useful connections, and opportunities to turn ideas into action.
From Lake Wales and Winter Haven to Lakeland, Bartow, Haines City, and communities across Polk County, the goal is to make entrepreneurship more accessible to everyone.
Why promising businesses don't need to begin in major technology hubs.
How small communities can create their own entrepreneurial ecosystems.
Why relationships and informal conversations often matter more than elaborate startup programs.
How Polk Starts connects people, ideas, and existing business resources.
Why free, welcoming gatherings can help more people take the first step toward entrepreneurship.
How local businesses and community organizations can participate.
Winter Haven Startup Business Meetup — Intros & Ideas
Wednesday, January 13, 2027
6:00–8:00 PM
Old Man Frank's, Winter Haven, FloridaFree and open to everyone. No pitches, no formal agenda. Just introductions, ideas, and connections.
Learn more: https://polkstarts.com
Jason T. AI Wade is the founder of BackTier, a Central Florida-based AI Visibility company, and host of the AI Visibility Podcast.
His work focuses on how businesses, organizations, and individuals are discovered, understood, cited, and recommended by artificial intelligence systems, including ChatGPT, Google, Gemini, Claude, and Perplexity.
Jason is also involved in local entrepreneurship initiatives designed to connect founders, strengthen small businesses, and expand economic opportunities throughout Polk County.
BackTier is a founding sponsor of Polk Starts.
Polk Starts — Entrepreneurship Community
https://polkstarts.comBackTier — AI Visibility
https://backtier.comJason T. AI Wade — Official Website
https://jasonwade.comAI Visibility Podcast — Episodes and Subscriptions
https://backtier.com/podcastHave a business idea? Already running a business? Interested in helping entrepreneurs succeed?
Polk Starts welcomes people at every stage of the entrepreneurial journey.
Meet. Share. Start.
#PolkStarts #PolkCounty #Entrepreneurship #SmallBusiness #WinterHaven #LakeWales #Lakeland #FloridaStartups #BackTier #AIVisibility
Episode DescriptionIn This EpisodeUpcoming Polk Starts MeetupAbout the HostLinks & ResourcesGet Involved
Ai for Everyone: When AI Connects the Wrong Dots: Entity Research, Legal Mediation, and AI Visibility AI Visibility Podcast | Jason T. AI Wade | Founder, BackTier
When AI Connects the Wrong Dots: Entity Research, Legal Mediation, and AI VisibilityAI Visibility Podcast | Jason T. AI Wade | Founder, BackTierWhat happens when artificial intelligence connects the right …
Show notes
When AI Connects the Wrong Dots: Entity Research, Legal Mediation, and AI Visibility
AI Visibility Podcast | Jason T. AI Wade | Founder, BackTier
What happens when artificial intelligence connects the right information to the wrong person, business, or city?
Jason T. AI Wade examines real Google search results for AI and legal mediation in Orlando and Central Florida to demonstrate how AI-powered search systems identify, classify, and connect people, businesses, locations, professional credentials, and organizations.
The findings reveal an important distinction: topical relevance does not necessarily establish geographic relevance, professional expertise, or a legitimate business relationship.
One Orlando mediator appears in results because of documented experience with artificial intelligence and alternative dispute resolution. Another professional appears in related searches whose surname happens to be Orlando, despite a professional listing placing a lawyer with that name in California.
These examples illustrate why entity research, source verification, and relationship mapping are becoming essential to AI visibility.
Entity identification: How search and AI systems distinguish people, organizations, locations, businesses, and professional services.
Entity relationships: Why connections between professionals, credentials, employers, locations, and published expertise matter.
AI search ambiguity: How shared names, overlapping terminology, and geographic references can produce misleading results.
Authority and evidence: The difference between appearing in search results and possessing verified professional qualifications.
Legal AI discovery: How Google combines attorneys, mediators, legal technology vendors, court rules, and professional publications.
SEO, GEO, and AEO: Why keywords alone cannot establish accurate entity identity or credible professional relationships.
BackTier's research methodology: How structured investigation reveals missing connections, inaccurate classifications, and opportunities to improve AI discoverability.
Jason also founded Polk Starts, a free county-wide entrepreneurial community connecting founders, startups, small business owners, and aspiring entrepreneurs throughout Polk County, Florida.
He hosts the AI Visibility Podcast, exploring the practical implications of artificial intelligence for business, technology, entrepreneurship, and society.
Jason Wade and BackTier
BackTier — AI Strategy & Visibility: https://backtier.com/
Jason Wade — Research, Writing & Podcasts: https://jasonwade.com/
LinkedIn: https://www.linkedin.com/in/backtier/
Community and Local Projects
Polk Starts — Entrepreneurship Across Polk County: https://polkstarts.com/
WorkLW — Lake Wales Coworking & Podcast Studio: https://worklw.com/
Lake Wales Guide: https://lakewalesguide.com/
Florida Slice: https://floridaslice.com/
Episode References
Florida Courts — Mediation and Alternative Dispute Resolution: https://www.flcourts.gov/
The Florida Bar — https://www.floridabar.org/
Florida Circuit-Civil Mediator Society: https://www.floridamediators.org/
Schema.org — Structured Entity Vocabulary: https://schema.org/
Google Search Central — https://developers.google.com/search/
Ai for Everyone: AI for Everyone: How CivicReach Is Using AI to Help People in Need AI Visibility Podcast with Jason T. Ai Wade
AI for Everyone: How CivicReach Is Using AI to Help People in NeedAI Visibility Podcast with Jason T. A.I. WadeGuest: Chip Kennedy, Founder & CEO of CivicReachWhat happens when someone desperately needs help …
Show notes
AI for Everyone: How CivicReach Is Using AI to Help People in Need
AI Visibility Podcast with Jason T. A.I. Wade
Guest: Chip Kennedy, Founder & CEO of CivicReachWhat happens when someone desperately needs help, but nobody answers the phone?
In this episode of the AI Visibility Podcast, host Jason T. A.I. Wade speaks with Chip Kennedy, founder and CEO of CivicReach, a North Carolina-based technology company using artificial intelligence to improve how nonprofits, social workers, caseworkers, and government agencies serve their communities.
Chip explains how CivicReach began with a simple problem: social service organizations were overwhelmed by incoming calls, paperwork, and administrative responsibilities. People seeking food assistance, housing, utility support, or other essential services were often unable to reach someone who could help.
CivicReach developed AI-powered phone answering technology to help address that problem and expanded into software that supports the broader caseworker workflow.
Jason and Chip explore how AI can reduce administrative burdens, improve access to essential services, and give frontline professionals more time to work directly with people.
The conversation also examines entrepreneurship outside Silicon Valley, North Carolina's Research Triangle startup ecosystem, outcome-based software pricing, and the challenge of building a profitable technology company without sacrificing its social mission.
The central question: Can artificial intelligence make the social safety net more accessible, responsive, and human?
Why nonprofit organizations and government social service agencies struggle with outdated technology
How AI voice agents can answer calls and support social service intake
Reducing repetitive forms, paperwork, and administrative work
Helping caseworkers spend more time serving people
Why responsiveness matters when someone needs urgent assistance
Measuring AI's value through outcomes rather than software seats
The role of North Carolina's Research Triangle in supporting mission-driven startups
How AI can help entrepreneurs research, prepare, and maintain professional relationships
Building sustainable companies that balance profitability with social impact
Why more technology founders should tackle problems in government and public services
Chip Kennedy is the founder and CEO of CivicReach, a technology company developing AI-powered tools and software automation for social service nonprofits and government agencies.
A longtime entrepreneur and technology executive, Chip has worked as a founder and CTO at high-growth startups with social missions.
His experience helping operate a family-founded nonprofit serving families living in homeless shelters exposed him to the administrative and operational challenges faced by community organizations.
That experience helped inspire CivicReach, which aims to make essential services easier to access while giving social workers and caseworkers more time to help people.
Connect with Chip Kennedy
Website: https://civicreach.com
Email: [email protected]Jason T. A.I. Wade is the founder of BackTier, an AI Visibility company focused on helping businesses and organizations understand how artificial intelligence discovers, evaluates, cites, and recommends them.
Through the AI Visibility Podcast, Jason explores the practical applications of artificial intelligence, entrepreneurship, emerging technology, and the ways AI is changing business and society.
His work focuses on AI SEO, Generative Engine Optimization (GEO), Answer Engine Optimization (AEO), and helping organizations prepare for an increasingly AI-driven world.
Connect with Jason
BackTier: https://backtier.com
Personal website: https://jasonwade.com
NinjaAI: https://ninjaai.com#AIVisibility #AIForEveryone #CivicReach #ChipKennedy #JasonAIWade #BackTier #ArtificialIntelligence #SocialImpact #Nonprofits #AIAgents #SocialServices #Entrepreneurship
Ai for Everyone: The AI Hallucination Case Everyone Knows — and the Lesson Everyone Missed AI Visibility Podcast | Jason T.A.I. Wade | Founder, BackTier
The AI Hallucination Case Everyone Knows — and the Lesson Everyone MissedAI Visibility Podcast | Jason T.A.I. Wade | Founder, BackTierIn June 2023, a federal judge in New York sanctioned two attorneys and their …
Show notes
The AI Hallucination Case Everyone Knows — and the Lesson Everyone Missed
AI Visibility Podcast | Jason T.A.I. Wade | Founder, BackTier
In June 2023, a federal judge in New York sanctioned two attorneys and their law firm $5,000 after lawyers submitted court filings citing judicial decisions that did not exist.
The cases had been fabricated by ChatGPT, complete with convincing case names, quotations, and legal citations.
The case, Mata v. Avianca, Inc., became one of the most widely discussed examples of artificial intelligence hallucinations in professional practice.
But the most important lesson wasn't simply that AI invented legal authorities.
It was what happened when fabricated information was treated as verified authority.
In this episode of the AI Visibility Podcast, Jason T.A.I. Wade, founder of BackTier, examines the distinction between an AI system generating plausible information and a professional relying on that information without independently establishing its accuracy.
The underlying issue extends well beyond the courtroom. As artificial intelligence increasingly participates in research, document preparation, business discovery, recommendations, and professional decision-making, the ability to distinguish credible-looking output from verified evidence becomes essential.
AI can produce fluent explanations, authoritative language, and apparently legitimate citations. None of those characteristics independently establishes truth.
The question isn't whether AI can make mistakes. We already know it can.
The question is what happens when people and institutions delegate judgments about evidence, credibility, and authority to systems they haven't adequately verified.
The 2023 legal hallucination case: What happened in Mata v. Avianca and why the court imposed sanctions.
The overlooked finding: The court distinguished the use of AI-assisted research from attorneys' failure to fulfill their verification responsibilities.
Fabricated authority: How AI-generated case names, citations, and quotations can appear credible without corresponding to real sources.
Human accountability: Why professional responsibility does not disappear when work is delegated to artificial intelligence.
Verification versus plausibility: Why a convincing AI-generated answer is not equivalent to independently established evidence.
Implications for AI Visibility: Why accurate entity identification, source integrity, attribution, and evidence quality matter as AI systems increasingly mediate access to information.
Artificial intelligence does not need to produce obviously false information to create serious problems. Its most consequential failures may arise when fabricated material is plausible enough to pass through human review without being challenged.
The lesson of Mata v. Avianca is not that AI should never be used for professional research. It is that reliable professional judgment requires independent verification, especially when the output carries legal, financial, reputational, or institutional consequences.
Jason T.A.I. Wade is the founder of BackTier, an AI Visibility company focused on how artificial intelligence systems discover, interpret, classify, cite, and recommend businesses, people, and organizations.
His work examines the intersection of artificial intelligence, search, structured information, entity identity, and machine-generated recommendations.
Through the AI Visibility Podcast, Wade explores how AI systems are changing business discovery, professional workflows, digital authority, and the relationship between human judgment and machine-generated information.
Ai for Everyone: NVIDIA, Jensen Huang, and the AI Reputation Crisis: The Internet Never Forgets - Jason ai Wade - BackTier - PolkStarts - Polk Starts
NVIDIA, Jensen Huang, and the AI Reputation Crisis: The Internet Never ForgetsEpisode Show NotesWhat happens when the face of the AI revolution becomes the center of a global controversy?In this episode of the …
Show notes
NVIDIA, Jensen Huang, and the AI Reputation Crisis: The Internet Never ForgetsEpisode Show Notes
What happens when the face of the AI revolution becomes the center of a global controversy?
In this episode of the AI Visibility Podcast, Jason AI Wade examines the unfolding controversy surrounding NVIDIA founder Jensen Huang, the national security questions involving China, and the lasting consequences for one of the world's most influential AI companies.
NVIDIA helped build the infrastructure powering today's artificial intelligence boom. But technological dominance doesn't guarantee reputational protection.
Jason explores how allegations, political relationships, government scrutiny, and media coverage can permanently reshape public perception—and how AI search engines may preserve and amplify those narratives for years.
The discussion also considers the competitive opportunities for companies developing their own AI chips, including Meta and Apple, and whether NVIDIA's dominance can survive a major leadership crisis.
Topics covered:
Jensen Huang and NVIDIA's reputational crisis
China, advanced AI chips, and national security concerns
Donald Trump, Washington, and Silicon Valley relationships
AI visibility and the permanence of digital controversy
Meta, Apple, and competition in AI infrastructure
Why powerful technology founders aren't necessarily irreplaceable
How AI-generated answers influence corporate reputations
The central question: When AI becomes the primary way people discover information, who controls the story it tells about you?
Jason AI Wade is the founder of BackTier, an AI Visibility company focused on how businesses and organizations are discovered, understood, cited, and recommended by artificial intelligence.
Jason hosts the AI Visibility Podcast, exploring AI technology, entrepreneurship, digital strategy, and the changing relationship between businesses, people, and intelligent systems.
His work focuses on AI Search Optimization, Generative Engine Optimization (GEO), and Answer Engine Optimization (AEO).
Connect with Jason
Jason Wade: https://jasonwade.com
BackTier: https://backtier.com
NinjaAI: https://ninjaai.com
Related Reporting
Associated Press — NVIDIA CEO Jensen Huang resigns: https://apnews.com/article/nvidia-megaspeed-china-singapore-huang-5403f152a601cf82ce939f1d24fffa0f
Reuters — NVIDIA's China chip and espionage controversy: https://www.reuters.com/world/china/how-nvidia-ceo-jensen-huang-got-entangled-china-chip-spy-scandal-2026-11-11/
U.S. Bureau of Industry and Security: https://www.bis.gov
NVIDIA: https://www.nvidia.com
#NVIDIA #JensenHuang #ArtificialIntelligence #AIVisibility #AISearch #GEO #AEO #China #Semiconductors #BackTier #JasonAIWade #AIVisibilityPodcast
About the HostLinks & ResourcesHashtags
Ai For Everyone: Is Meta AI Spying on You? The Privacy Problem With Muse, Facebook, and AI - AI Visibility Podcast with Jason AI Wade
Is Meta AI Spying on You? The Privacy Problem With Muse, Facebook, and AIAI Visibility Podcast with Jason AI WadeFree AI tools are powerful, convenient, and increasingly personal. But what are we giving up in …
Show notes
Is Meta AI Spying on You? The Privacy Problem With Muse, Facebook, and AI
AI Visibility Podcast with Jason AI Wade
Free AI tools are powerful, convenient, and increasingly personal. But what are we giving up in exchange?
In this episode, Jason AI Wade discusses his growing concerns about Meta, Facebook, and the privacy implications of AI assistants like Muse.
After using Meta's AI tools on his phone and computer, Jason experienced something unsettling: a Facebook Reel appeared that closely matched an unusually specific topic he had recently discussed in a private text conversation.
Was it coincidence, sophisticated behavioral targeting, or something more invasive? The experience doesn't establish that Meta accessed his private messages, but it raises important questions about personal data, AI-powered recommendations, and how much access technology companies should have to our lives.
Jason explains why he's removed most Meta apps from his phone, why he still relies on Facebook for business and community activities, and why he believes the next major battle in AI will be between deeply integrated personal assistants and professional AI agents.
The episode examines a fundamental tradeoff: AI becomes more useful as it learns more about us, but how much personal information should we surrender for that convenience?
Privacy concerns involving Meta, Facebook, and Muse.
An unsettling connection between a private conversation and Facebook Reels.
What AI companies may collect, retain, and infer from personal data.
Why opting out of tracking doesn't always eliminate privacy concerns.
The difference between explicitly authorized AI connectors and suspected undisclosed data access.
Why Jason removed most Meta applications from his phone.
The emerging competition between consumer AI assistants and professional AI agents.
Whether financial penalties meaningfully deter large technology companies from privacy violations.
Jason AI Wade is the founder of BackTier, a Florida-based AI Visibility company, and host of the AI Visibility Podcast.
With more than two decades of experience in digital business, ecommerce, search, and online publishing, Jason explores how artificial intelligence is transforming business, entrepreneurship, work, and digital discovery.
Through BackTier, he focuses on AI Visibility, Generative Engine Optimization (GEO), Answer Engine Optimization (AEO), and helping businesses understand how AI systems discover, interpret, and recommend them.
Podcast: https://backtier.com/podcast
Spotify: https://open.spotify.com/show/2GKjqiFMhh7pO15RXkkG5E
Apple Podcasts: https://podcasts.apple.com/us/podcast/id1826332929
YouTube: https://www.youtube.com/@BackTier_AI
Jason AI Wade: https://jasonwade.com
BackTier: https://backtier.com
Email: [email protected]
Have you ever seen a Facebook or Instagram recommendation that seemed connected to something you discussed privately? How much personal information are you comfortable sharing with AI assistants?
Follow the AI Visibility Podcast for independent conversations about artificial intelligence, privacy, business, technology, and what's next.
#AIVisibility #MetaAI #Facebook #Muse #AIPrivacy #DataPrivacy #ArtificialIntelligence #AIAgents #BackTier #JasonAIWade
Topics CoveredAbout Jason AI WadeListen, Watch & ConnectJoin the Conversation
Ai for Everyone: My AI Podcast Audience Is Getting Younger and More Female. Why? AI Visibility Podcast with Jason AI Wade | November 2026
My AI Podcast Audience Is Getting Younger and More Female. Why?AI Visibility Podcast with Jason AI Wade | November 2026Something unexpected is happening with my podcast audience.For a long time, my listeners …
Show notes
My AI Podcast Audience Is Getting Younger and More Female. Why?
AI Visibility Podcast with Jason AI Wade | November 2026
Something unexpected is happening with my podcast audience.
For a long time, my listeners were overwhelmingly men over 50. But when I recently examined my YouTube and Spotify analytics, I noticed a striking demographic divide: listeners under 45 were predominantly women, while listeners over 45 were predominantly men.
What's happening around age 45? And what does that tell us about who's adopting artificial intelligence, who's concerned about its impact, and who's looking for new opportunities?
In this short episode, I share what I'm discovering about my audience and how I'm using AI to better understand the numbers and adjust my programming.
I'm also experimenting with a new approach: organizing the podcast around a different AI theme each month. November's theme is AI for Everyone, and the early response suggests these focused episodes are connecting with listeners.
The surprising age and gender divide in my podcast audience.
Why younger women and older men may be engaging with AI for different reasons.
Using ChatGPT and other AI tools to interpret audience analytics.
Why audience engagement and relevance matter more than raw listener counts.
How monthly themes are shaping the podcast's direction.
What audience data can reveal about AI education and adoption.
The central question: Are younger women approaching AI as an opportunity while older men are approaching it as a potential disruption? That's a hypothesis worth exploring, not a conclusion the data can establish.
Jason AI Wade is the founder of BackTier, a Florida-based AI Visibility company, and host of the AI Visibility Podcast. With more than two decades of experience in digital business, ecommerce, search, and online publishing, Jason explores how artificial intelligence is changing business, entrepreneurship, work, and the way people and organizations are discovered and recommended.
His work focuses on AI Visibility, Generative Engine Optimization (GEO), Answer Engine Optimization (AEO), and practical AI adoption.
Podcast: https://backtier.com/podcast
Spotify: https://open.spotify.com/show/2GKjqiFMhh7pO15RXkkG5E
Ai for everyone: Another AI Tool? Seriously? The Growing Pile of AI Subscriptions Businesses Don't Know What to Do With
Another AI Tool? Seriously?The Growing Pile of AI Subscriptions Businesses Don't Know What to Do WithAnother week. Another AI tool. Another subscription.ChatGPT. Claude. Gemini. Perplexity. AI writing tools …
Show notes
Another AI Tool? Seriously?
The Growing Pile of AI Subscriptions Businesses Don't Know What to Do With
Another week. Another AI tool. Another subscription.
ChatGPT. Claude. Gemini. Perplexity. AI writing tools, image generators, video editors, meeting assistants, automation platforms, AI agents, and dozens of specialized applications promising to transform your business.
Every product claims to save time, increase productivity, or replace something you're already paying for.
And somehow, the monthly software bill keeps growing.
Welcome to AI subscription fatigue.
In this episode of POD, we examine the explosion of AI tools, the growing cost of overlapping subscriptions, and why businesses may be confusing access to more technology with actual improvements in performance.
The AI Tool Explosion: Why every software company seems to be launching an AI product, assistant, or agent.
Subscription Fatigue: How small monthly charges accumulate into substantial recurring expenses.
The Overlap Problem: Why businesses pay for multiple tools that perform essentially the same functions.
The Wrapper Economy: What happens when specialized AI products depend on the same underlying foundation models.
The AI Agent Pitch: Why the latest promise of autonomous work deserves careful evaluation.
The Integration Problem: How disconnected tools create more workflows, accounts, data transfers, and administrative overhead.
The Hidden Costs: Learning curves, employee training, switching costs, privacy exposure, and unreliable outputs.
The Consolidation Opportunity: When one capable AI platform can replace several narrowly focused subscriptions.
Build, Buy, or Cancel: How to decide whether another AI tool deserves a place in your business.
Consider a small business paying for:
A general-purpose AI assistant.
An AI writing and marketing platform.
An AI meeting transcription service.
An AI image or video generator.
An AI automation platform.
An AI customer service tool.
An AI SEO or visibility platform.
Each subscription might appear reasonable on its own.
But the combined cost can become significant, especially when employees use only a fraction of the available capabilities.
And subscription fees aren't the only expense.
Every additional tool introduces another vendor relationship, another security consideration, another interface to learn, and potentially another place where business data is stored.
The real cost of an AI tool is not its monthly price. It's the total cost of making it useful.
Before purchasing another AI tool, businesses should ask:
What specific problem does this solve?
Can an existing platform already accomplish the same task?
How much time or money will it actually save?
What evidence supports the promised improvement?
Who will use it, and how often?
And what happens if we cancel it?
A demonstration isn't a business case. A feature list isn't a return on investment. And a subscription that nobody uses isn't an AI strategy.
A practical approach begins with examining the tools a business already pays for.
Identify duplicate capabilities, underused subscriptions, unnecessary integrations, and workflows that could be simplified.
Then evaluate tools based on measurable business outcomes rather than marketing claims.
A specialized AI application may justify its cost when it provides proprietary data, dependable automation, domain-specific capabilities, compliance features, or integration advantages that general-purpose platforms cannot adequately replace.
But specialization alone doesn't establish value.
Buying AI tools is easy.
Changing how a business operates is harder.
Ai for everyone: AI and the Age of Instant Regret AI Cringe: What Looked Impressive Yesterday Looks Embarrassing Today
AI and the Age of Instant RegretAI Cringe: What Looked Impressive Yesterday Looks Embarrassing TodayNot long ago, an AI-generated image, a ChatGPT-written article, or a synthetic video could stop people in …
Show notes
AI and the Age of Instant Regret
AI Cringe: What Looked Impressive Yesterday Looks Embarrassing Today
Not long ago, an AI-generated image, a ChatGPT-written article, or a synthetic video could stop people in their tracks.
Today, the same content might make them cringe.
The technology hasn't necessarily gotten worse. Our expectations have changed.
As AI makes professional-looking content available to everyone, audiences are becoming more familiar with its patterns: the generic writing, exaggerated enthusiasm, artificial-looking images, robotic voices, and overly polished presentations.
What once looked innovative can quickly become a signal of low effort.
We're entering the age of instant AI regret—where something you proudly publish today might embarrass you six months from now.
What Is AI Cringe? Why audiences increasingly recognize and reject generic AI-generated content.
The Novelty Expiration Date: How quickly yesterday's impressive AI demonstrations become ordinary or outdated.
The ChatGPT Voice: Why certain phrases, structures, and writing patterns make content sound artificially generated.
The AI Image Problem: Why overly smooth faces, impossible details, exaggerated lighting, and familiar visual styles can undermine credibility.
Synthetic Everything: How AI-generated videos, voices, advertisements, and social posts can create a sense of artificiality.
The Instant Regret Problem: Why businesses may look back at their early AI marketing and wish they'd exercised more judgment.
The Content Flood: What happens when everyone can produce unlimited professional-looking material.
The Authenticity Advantage: Why original photography, real experiences, distinctive voices, and verifiable expertise may become more valuable.
AI as a Tool, Not a Personality: How to use AI for research, editing, and production without surrendering your identity.
The AI Visibility Connection: Why generating more content doesn't automatically create credibility, differentiation, or recommendations.
AI has dramatically reduced the cost of creating content.
But when production becomes easy, simply producing something polished stops being impressive.
Audiences begin looking for other signals of value: originality, judgment, substance, accuracy, and a recognizable human perspective.
That doesn't mean businesses should stop using AI.
It means they need to become more selective about what they publish.
The problem isn't necessarily that AI created the content. It's that nobody exercised enough judgment before releasing it.
AI makes it easier than ever to create something that looks finished before it's actually worth publishing.
The competitive advantage is shifting from the ability to generate content toward the ability to recognize what's good.
Use AI to improve your work, not to replace your taste, experience, or judgment.
The question isn't whether AI can make it. It's whether you'll still be proud of it next year.
Presented by BackTier | NinjaAI.com
Topics: AI Cringe, AI Content, Generative AI, AI Marketing, Authenticity, AI Images, AI Writing, Synthetic Media, AI Slop, Content Quality, AI Visibility, Creative Judgment.
What We'll CoverThe Bigger PictureKey Takeaway
Ai for Everyone: 175 Prompts for Schools: Eric Curts on AI Teachers Can Actually Use
Eric Curts is a Technology Integration Specialist at SPARCC and the Stark County Educational Service Center in North Canton, Ohio, which supports more than thirty school districts in Northeast Ohio. This is his …
Show notes
Eric Curts is a Technology Integration Specialist at SPARCC and the Stark County Educational Service Center in North Canton, Ohio, which supports more than thirty school districts in Northeast Ohio. This is his 35th year in education. He started in 1992 as a math teacher at North Canton Middle School, later spent 14 years as the district’s Technology Integration Specialist, and now works as an EdTech coach. He is a Google for Education Certified Trainer and Certified Innovator, and a co-leader of GEG-Ohio. He publishes free educator resources at Control Alt Achieve and EduPrompts (formerly EduGems), and is the author of the 2020 book Control Alt Achieve: Rebooting Your Classroom with Creative Google Projects.
Jason AI Wade is the founder of BackTier and host of the AI Visibility Podcast. He is the author of AI Visibility: How to Win in the Age of Search, Chat & Smart Customers, and writes at jasonwade.com.
Eric’s links:
- EduPrompts, 175 ready-to-use AI prompts for schools
- From EduGems to EduPrompts, his November 9 post about the rename
- Control Alt Achieve, his blog and free resource library
- About Eric
- AI resources
- Bio
- PD catalog
- Newsletter
- YouTube
- Control Alt Achieve (the 2020 book)
- December 10 webinar, “Mastering the Shift: Gemini Gems to Skills” (not mentioned on the episode)
- Webinar registration
Your links:
- jasonwade.com
- BackTier
- AI Visibility Podcast on Spotify
- thingspro.com, book a guest appearance
- Watch my bio
Ai For Everyone: The AI Visibility Test That Moved in Days | Andrew Shotland on Local SEO, Citations, and What Actually Works
Andrew Shotland has spent roughly two decades in search.Right now, he says it is one of the most interesting periods the industry has seen in years. SEO is still here, but the machines interpreting businesses …
Show notes
Andrew Shotland has spent roughly two decades in search.
Right now, he says it is one of the most interesting periods the industry has seen in years. SEO is still here, but the machines interpreting businesses, services, locations, and recommendations have changed.
In this episode of the AI Visibility Podcast, Andrew joins Jason AI Wade to talk about what is actually changing—and what still works.
Andrew’s basic model is straightforward: SEO has always been about helping a machine understand what a business does and when it should be surfaced. That principle still holds. What has changed is the system doing the understanding.
For local businesses, that means going beyond generic category language.
If a plumber does water heater replacement, storm drains, or emergency service, those specific attributes need to exist clearly on the company’s own pages and across the external sources AI systems may use as evidence. Andrew argues that citations, listings, and third-party mentions are not just consistency signals anymore—they can help establish what a business should actually be associated with.
The strongest example in the episode comes from a 160-location company.
Andrew’s team found a visibility gap around construction job-site bathroom and toilet queries. They took 20 locations, added relevant language to their Google Business Profile descriptions and local citation ecosystem, and watched what happened.
Within days, visibility moved in Google AI Mode. Later, those same test locations began gaining visibility in ChatGPT while the untouched locations initially stayed flat.
Then the experiment got more interesting.
About a month later, the broader location network began gaining visibility around the same concept. Andrew’s theory was that enough pages had connected the brand with that service category that the association began to spread across the larger entity.
The episode also gets into competitor-adjacent content and conversational search.
That leads to one of the larger shifts in AI-era discovery:
Instead of optimizing only for a keyword, businesses increasingly need to think about the sequence of questions a person may ask before reaching a decision.
Andrew calls this thinking through the “infinite conversational paths.”
The discussion also covers agentic SEO, automation, content-gap analysis, entity corroboration, and the strategic value of using AI to reduce repetitive work.
Andrew’s preference is not to pocket the saved time. It is to use that time to investigate harder questions, run better experiments, and improve the product or service being delivered.
The larger lesson is simple:
There is no finished playbook yet.
The companies that learn fastest will likely be the ones willing to test, measure, and take more intelligent swings.
As Andrew puts it, even the best baseball players do not hit every pitch. The advantage comes from taking enough swings to find what works.
Andrew Shotland
Founder and CEO of Local SEO Guide.Andrew works across local SEO, multi-location search, AEO, and AI visibility. His current focus is understanding how businesses can become easier for Google, ChatGPT, and other AI systems to interpret and recommend.
He has been working in search for roughly two decades and describes the current shift as one of the most interesting periods of his career.
Local SEO in the age of AI
Google AI Mode and ChatGPT visibility
Local citations as AI evidence
Service and attribute distribution
Entity corroboration
Competitor-adjacent content
Conversational search paths
Content-gap analysis
Agentic SEO
AI-powered automation
Multi-location testing
Why experimentation matters more than a static GEO playbookLocal SEO Guide
https://www.localseoguide.com/Andrew Shotland on LinkedIn
Andrew says LinkedIn is his primary social platform and where he posts most of his ideas and commentary.Ai for everyone: Why Artificial Intelligence Will Decide Which Companies Get Discovered — Chapter One
Why Artificial Intelligence Will Decide Which Companies Get Discovered — Chapter OneFor decades, businesses competed for visibility in search engines. Success meant ranking on Google, attracting website …
Show notes
Why Artificial Intelligence Will Decide Which Companies Get Discovered — Chapter One
For decades, businesses competed for visibility in search engines. Success meant ranking on Google, attracting website visitors, and converting traffic into customers.
Artificial intelligence is changing that relationship.
In Chapter One of Why Artificial Intelligence Will Decide Which Companies Get Discovered, Jason A.I. Wade explores a fundamental shift in digital discovery: AI systems are increasingly becoming intermediaries between consumers and businesses.
Instead of searching through websites, customers can ask AI assistants to identify companies, compare services, evaluate qualifications, and recommend providers.
That changes the competitive landscape. A business may have an excellent website, strong traditional SEO, and years of experience yet remain absent from AI-generated recommendations.
The emerging challenge is AI Visibility: ensuring that artificial intelligence can discover, correctly identify, understand, and substantiate information about a company.
This opening chapter examines why traditional search visibility alone may no longer be sufficient and why businesses need to understand how AI systems select the entities and sources that appear in their answers.
The central question: What happens to a business when AI becomes the customer's first point of contact—and never mentions its name?
Jason A.I. Wade is a Central Florida-based AI entrepreneur, AI Visibility architect, and host of the AI Visibility Podcast. His work focuses on artificial intelligence, AI SEO, Generative Engine Optimization (GEO), Answer Engine Optimization (AEO), and digital entity recognition.
Through NinjaAI.com and BackTier, he develops projects and research examining how AI systems discover, classify, cite, and recommend businesses.
NinjaAI: https://ninjaai.com
Jason A.I. Wade: https://jasonwade.com
BackTier: https://backtier.comProduced by BackTier Media, an independent media initiative exploring artificial intelligence, business, digital identity, and the technologies reshaping how information is discovered and trusted.
Ai for everyone: Four AI Engines. One Question. Four Different Answers.
Four AI Engines. One Question. Four Different Answers.Ask ChatGPT, Gemini, Claude, and Perplexity the same question. Will they recommend the same businesses, cite the same sources, or reach the same …
Show notes
Four AI Engines. One Question. Four Different Answers.
Ask ChatGPT, Gemini, Claude, and Perplexity the same question. Will they recommend the same businesses, cite the same sources, or reach the same conclusions?
Often, they won't.
In this episode of the AI Visibility Podcast, Jason A.I. Wade examines one of the fundamental challenges of AI search: different AI systems can produce substantially different answers to identical questions.
For businesses investing in AI SEO, Generative Engine Optimization (GEO), and Answer Engine Optimization (AEO), this creates a serious measurement problem. Being visible in one AI engine does not guarantee visibility in another.
AI visibility isn't a single ranking. It's a changing landscape of models, retrieval systems, sources, and recommendations.
The question isn't simply whether AI can find your business. It's which AI systems recognize it, what they believe about it, and whether they recommend it consistently.
Jason A.I. Wade is an AI Visibility architect, entrepreneur, and host of the AI Visibility Podcast. Based in Central Florida, he researches how artificial intelligence discovers, classifies, cites, and recommends businesses and digital entities.
Through NinjaAI.com and BackTier, Jason explores AI search, machine-readable identity, digital authority, and the evolving relationship between businesses and AI-powered discovery.
- NinjaAI: https://ninjaai.com
- Jason A.I. Wade: https://jasonwade.com
- BackTier: https://backtier.com
The AI Visibility Podcast is produced by BackTier Media, exploring artificial intelligence, search, digital identity, emerging technology, and the systems increasingly influencing what people discover and trust.
Ai for everyone: How to Make AI Recommend Your Business | Andrew Shotland on Local SEO, Citations, and AI Visibility
What actually makes ChatGPT or Google AI recommend one local business instead of another?Andrew Shotland, founder and CEO of Local SEO Guide, joins Jason AI Wade to break down what his team is testing right now …
Show notes
What actually makes ChatGPT or Google AI recommend one local business instead of another?
Andrew Shotland, founder and CEO of Local SEO Guide, joins Jason AI Wade to break down what his team is testing right now across local SEO, AI visibility, citations, service pages, and multi-location businesses.
Andrew’s core point is simple: the fundamentals of SEO still matter. A machine has to understand what your business does before it can recommend you. The difference now is that AI systems are assembling that understanding from more pieces of evidence and using it inside conversational answers.
That changes how businesses should think about visibility.
It is not enough for a plumber to say, “We’re a plumber.”
If the business wants to be recommended for water heater replacement, emergency service, or storm drains, those specific services need to appear clearly across the company’s website and the third-party sources AI may use to corroborate them.
Andrew describes those external citations almost like additional sides of a die: the more relevant sources that connect a business with the right location, service, and attributes, the more opportunities an AI system has to encounter the same association.
Then he shares a real test.
His team analyzed search data across a 160-location company and found a missing concept around construction job-site bathrooms and toilets. They added that language to the Google Business Profiles and local citation network for 20 locations.
Within days, visibility changed in Google AI Mode.
Later, the test locations began improving in ChatGPT while the untouched locations initially remained flat.
Roughly a month later, visibility began increasing across the wider network as well.
Andrew’s working theory: enough pages had connected the brand with the concept that AI systems began applying that relationship more broadly across the entity.
The conversation also gets into competitor-focused content, local search strategy, agentic SEO, automation, content-gap analysis, and what Andrew calls the “infinite conversational paths” created by AI search.
The practical lesson is not to wait for a perfect GEO playbook.
Test something.
Measure whether visibility changes.
Then apply what works.
Andrew compares the process to baseball: even a great hitter misses most of the time. The advantage comes from taking enough intelligent swings.
Andrew Shotland
Founder and CEO of Local SEO Guide.Andrew has worked in search for roughly two decades and now focuses heavily on local SEO, AEO, multi-location businesses, and how AI systems understand and recommend companies.
He describes the current period as one of the most interesting moments he has experienced in search.
AI recommendations for local businesses
Local SEO and GEO
Google AI Mode
ChatGPT visibility
Local citations
Entity corroboration
Service-page strategy
Content gaps
Competitor alternatives
Conversational search
Agentic SEO
Multi-location testing
AI visibility experimentsAndrew Shotland / Local SEO Guide
https://www.localseoguide.com/Andrew Shotland on LinkedIn
Andrew identifies LinkedIn as his main social platform and where he posts most often.AI Visibility Podcast
BackTierAi for everyone: Why Consistent Anchor Information Matters in AI Visibility
Why Consistent Anchor Information Matters in AI VisibilityOne of the most overlooked problems in AI visibility is consistency.Companies tend to think about their website, LinkedIn page, directory listings …
Show notes
Why Consistent Anchor Information Matters in AI Visibility
One of the most overlooked problems in AI visibility is consistency.
Companies tend to think about their website, LinkedIn page, directory listings, biographies, press mentions, podcasts, and third-party profiles as separate marketing assets. AI systems do not necessarily experience them that way. They encounter all of these sources as evidence about the same entity.
That creates a simple but important problem: if the basic facts keep changing depending on where the system looks, confidence in the entity can weaken.
I call these basic facts anchor information.
Anchor information is the relatively stable information that helps a machine determine who or what an entity is. For a company, that includes the company name, founders, location, primary category, core services, major products, important dates, leadership, and the language used to describe what the business actually does.
For a person, it may include name, professional role, company relationships, areas of expertise, location at an appropriate level, published work, and other persistent associations.
None of this sounds particularly sophisticated. That is exactly why companies underestimate it.
The problem begins when the same organization describes itself five different ways across five different sources. One profile says the company is an SEO agency. Another describes it as an AI consultancy. The website calls it an AI visibility company. An older directory calls it a digital marketing agency. The founder's biography uses yet another category.
A human can usually reconcile those descriptions.
A machine has to decide whether they represent complementary facts, historical changes, marketing language, or genuinely different classifications.
That uncertainty becomes more important as AI systems move beyond finding pages and begin comparing entities, selecting sources, recommending companies, and answering questions directly.
The objective is not to make every page identical. That would be unnatural and unnecessary.
It is an information architecture problem.
Before an AI system can cite a business, recommend it, or associate it with a particular area of expertise, the system first has to determine what the entity is and what facts about it can be trusted.
That starts with anchors.
A company should be able to answer a basic question: if an AI system encountered our website, founder biography, LinkedIn profile, podcast appearances, business directories, press coverage, and third-party references, would those sources collectively describe the same organization?
His central thesis is straightforward: before a company can influence how AI describes it, the company first has to make the truth about itself clear enough for machines to understand.
Jason Wade
https://jasonwade.comBackTier
https://backtier.comNinjaAI
https://ninjaai.comAi for everyone: The Democratization of AI Agents When Everyone Can Build a Bot That Actually Does Something
The Democratization of AI AgentsWhen Everyone Can Build a Bot That Actually Does SomethingFor years, building software that could automate business processes required programmers, expensive integrations, and …
Show notes
The Democratization of AI Agents
When Everyone Can Build a Bot That Actually Does Something
For years, building software that could automate business processes required programmers, expensive integrations, and technical expertise.
Now AI agents are making automation accessible to people who have never written a line of code.
A small business owner can describe a task in plain English and increasingly use AI tools to build an agent that researches information, handles customer inquiries, updates records, or coordinates work across multiple systems.
What once required a development team may now be possible with a subscription and some experimentation.
The next AI revolution isn't just about everyone having access to intelligence. It's about everyone having access to automated labor.
From Chatbots to Agents: Why answering questions and taking actions are fundamentally different capabilities.
The No-Code Revolution: How natural-language tools are lowering the technical barriers to building AI agents.
Bots for Everyone: Why small businesses, independent professionals, and entrepreneurs can now experiment with automation previously reserved for larger organizations.
The One-Person Company: How agents can help individuals operate workflows that once required multiple employees or contractors.
Agents Working Together: How specialized agents can delegate tasks, exchange information, and coordinate across business systems.
The Agent Marketplace: What happens when businesses can buy, customize, or deploy agents instead of developing every automation themselves.
The Reliability Problem: Why agents can still make mistakes, misunderstand instructions, and fail during multistep tasks.
The Security Question: What happens when an inexpensive bot has access to customer records, financial systems, or company communications?
The Agent Economy: How automated software may change service businesses, employment, pricing, and competition.
The AI Visibility Connection: Why companies may eventually need to serve both human customers and the AI agents acting on their behalf.
The internet democratized publishing.
Cloud software made powerful business applications accessible through subscriptions.
Generative AI made sophisticated writing, coding, and analysis available through conversational interfaces.
AI agents extend that progression from generating information to executing work.
But access doesn't guarantee competence.
An agent that can operate software still needs accurate instructions, appropriate permissions, reliable tools, monitoring, and clear boundaries.
The businesses that benefit most may not be those deploying the greatest number of agents, but those identifying valuable workflows and making automation dependable.
AI is lowering the barrier between having an idea for automation and actually deploying it.
That creates opportunities for small businesses and independent operators, but it also introduces new risks when automated systems act without sufficient oversight.
The competitive advantage will increasingly come from knowing what to automate, how to connect systems, and when human judgment is still required.
The internet gave everyone a voice. AI agents are beginning to give everyone a workforce.
Presented by BackTier | NinjaAI.com
Topics: AI Agents, Democratization of AI, Agentic AI, No-Code Automation, AI Bots, Autonomous Agents, Small Business AI, AI Workforce, Multi-Agent Systems, AI Economy, AI Visibility.
What We'll CoverThe Bigger PictureKey Takeaway
Ai for everyone: You Didn't Write That Email. Neither Did They. Welcome to AI Business Communication.
You Didn't Write That Email. Neither Did They. Welcome to AI Business Communication.You receive a polished business email. It's professional, carefully worded, and perfectly structured. But there's a good …
Show notes
You Didn't Write That Email. Neither Did They. Welcome to AI Business Communication.
You receive a polished business email. It's professional, carefully worded, and perfectly structured. But there's a good chance the person who sent it didn't actually write it.
And there's a reasonable chance you'll use AI to write your response.
In this episode of the AI Visibility Podcast, Jason A.I. Wade examines the increasingly strange reality of business communication in the age of artificial intelligence.
Executives, attorneys, entrepreneurs, and professionals are using AI to draft emails, negotiate language, respond to complaints, and communicate with customers. The result is an expanding volume of correspondence that may be technically accurate and professionally written but reveals surprisingly little about what the sender actually thinks.
What happens when one person's AI writes an email, another person's AI summarizes it, and a third AI generates the response?
Are we communicating more effectively, or simply automating the appearance of communication?
The episode explores the difference between assistance and authorship, the risks of manufactured professionalism, and why accountability still belongs to the person whose name appears at the bottom of the message.
The central question: If neither person wrote the email, and neither person reads the reply, who exactly is having the conversation?
Jason A.I. Wade is an AI Visibility architect based in Orlando, Florida, and founder of BackTier, which implements artificial intelligence for law firms.
He helps businesses get found, cited, and recommended by AI systems through NinjaAI.com, AI SEO, Generative Engine Optimization (GEO), and Answer Engine Optimization (AEO).
Jason hosts the AI Visibility Podcast, examining artificial intelligence, business communication, digital identity, and the changing relationship between human judgment and machine-generated information.
NinjaAI: https://ninjaai.com
BackTier: https://backtier.com
Jason Wade: https://jasonwade.com
Lisa Latte Effect: https://lisalatte.lovable.appThe AI Visibility Podcast is produced by BackTier Media, exploring artificial intelligence, business, technology, and the increasingly blurred boundaries between human expertise and machine-generated communication.
The irony: This episode's show notes were written with artificial intelligence.
Ai for everyone: Dan McGaw: The $15,000 AI Bill, AI Agents, and Why Marketing Attribution Is Breaking
Dan McGaw: The $15,000 AI Bill, AI Agents, and Why Marketing Attribution Is BreakingAI Visibility Podcast | Jason AI Wade with Dan McGawAI is no longer just a chatbot. For companies operating at the cutting …
Show notes
Dan McGaw: The $15,000 AI Bill, AI Agents, and Why Marketing Attribution Is Breaking
AI Visibility Podcast | Jason AI Wade with Dan McGaw
AI is no longer just a chatbot. For companies operating at the cutting edge of marketing technology, it's becoming the infrastructure behind everyday business operations.
Dan McGaw, founder of McGaw.io and UTM.io, joins Jason AI Wade from Barcelona for a conversation about what happens when AI agents begin running workflows, marketing attribution becomes less reliable, and businesses must rethink how they use artificial intelligence.
Dan shares what he's learning from implementing AI inside his own companies, including a $15,000 monthly token bill, a major reduction in AI usage through smarter architecture, and the growing difficulty of tracking customers who discover businesses through AI.
One of Dan's most significant observations is that AI chat is becoming the new homepage of a business.
People increasingly interact with AI systems before visiting a website, contacting a company, or making a buying decision.
That creates a new challenge for marketing: businesses need to be discoverable and understandable to AI systems while also finding ways to measure the resulting demand.
Dan explains how ChatGPT, Claude, and Perplexity handle referral information differently, making conventional analytics less dependable for tracking AI-originated traffic.
The conversation connects traditional marketing attribution with the emerging world of AI Visibility, Generative Engine Optimization (GEO), and Answer Engine Optimization (AEO).
Dan describes how dramatically his workflow has changed.
Instead of spending most of his time using AI chat interfaces, he now spends approximately four to five hours a day managing AI agents.
His team uses Claude, Codex, Notion AI, shared skills, and automated workflows to execute tasks that previously required considerably more manual work.
Dan argues that marketing technologists already possess an important advantage in this transition: they understand integrations, data systems, automation, and workflow architecture.
AI makes those capabilities substantially faster to deploy.
Building an AI-powered operation comes with costs.
Dan reveals that his company incurred approximately $15,000 in AI token charges in one month.
Rather than simply paying for more computing capacity, his team redesigned its agent architecture to route different tasks to appropriate models.
Small tasks go to smaller, less expensive models. Complex tasks receive more capable models.
Dan reports that this approach reduced usage by approximately 70%, demonstrating how AI orchestration can improve efficiency without sacrificing the quality required for more demanding work.
Dan offers a warning about using language models to analyze business data.
The distinction between an AI-generated answer and a verified result is becoming increasingly important as businesses automate decisions.
The conversation closes with a look back at Orlando's startup community, StarterStudio, and Dan's earlier work supporting entrepreneurs.
Jason recalls Dan's approach to creating authoritative content: find the best existing resource on a subject and create something substantially better.
Dan agrees that the principle remains relevant.
Even as AI changes how information is discovered and delivered, genuinely differentiated content continues to provide value.
Dan McGaw is a marketing technology entrepreneur, author, and founder of McGaw.io and UTM.io. His background includes leadership roles at Kissmetrics and Code School and extensive experience in marketing analytics, attribution, growth engineering, and business automation.
Based in Barcelona, Dan continues to work on marketing technology, AI-powered operations, and the evolving infrastructure behind customer acquisition.
Connect with Dan
McGaw.io: https://mcgaw.io
UTM.io: https://utm.io
Find Dan McGaw on LinkedIn, TikTok, Instagram, and YouTube.
Ai for everyone: Political Day After — 19-to-1, $0.21 Per Vote, and the Power of Visibility -Jason AI Wade | BackTier
AI Visibility: Political Day After — 19-to-1, $0.21 Per Vote, and the Power of VisibilityHost: Jason AI Wade | AI Visibility Podcast | BackTier What happens when a political challenger raises just …
Show notes
AI Visibility: Political Day After — 19-to-1, $0.21 Per Vote, and the Power of Visibility
Host: Jason AI Wade | AI Visibility Podcast | BackTier
What happens when a political challenger raises just one-nineteenth of the incumbent's campaign contributions and finishes within 2,282 votes of winning?
In this election-day follow-up, Jason AI Wade discusses his behind-the-scenes involvement in Alethea Pugh's 2026 campaign for Florida House District 48 in Polk County, Florida.
The incumbent, Republican Jon Albert, received 51.71% of the vote, while Democratic challenger Alethea Pugh received 48.29%, according to unofficial election-night results.
The financial disparity was substantial. An October 13 report by The Ledger identified $132,615 in contributions to Albert compared with $6,894 to Pugh—a ratio of approximately 19.2 to 1.
That translates to approximately $3.85 raised per vote for Albert versus $0.21 for Pugh, using those contribution snapshots and unofficial vote totals.
Jason discusses his involvement in campaign research, media outreach planning, messaging, visibility, and the challenge of helping a candidate with limited financial resources and a publicly scrutinized past.
The episode also explores how artificial intelligence, strategic communications, local relationships, and organized outreach might change the economics of political campaigns.
19-to-1 fundraising disparity: How two campaigns with dramatically different financial resources finished just 3.42 percentage points apart.
The $0.21-per-vote calculation: What contribution dollars per vote reveal—and why they are not the same as actual campaign expenditures per vote.
AI and political visibility: The potential applications of AI-assisted research, media intelligence, candidate discoverability, and communications systems.
Media outreach and message control: Jason's experience helping organize research, outreach, and campaign communications.
Reputation and accountability: Addressing documented historical controversies through factual communication rather than evasion.
Political conditions: How a favorable broader election environment may have influenced the district result.
Campaign consulting: Lessons Jason intends to apply to future political research and visibility engagements.
Election margin: 2,282 votes, or approximately 3.42 percentage points.
Important distinction: The fundraising numbers represent contributions reported as of October 13, not verified final expenditures. The election results do not establish that any specific consulting activity caused the outcome.
Jason AI Wade is the founder of BackTier, an AI visibility architect, author of AI Visibility: How to Win in the Age of Search, Chat & Smart Customers, and host of the AI Visibility Podcast.
His work focuses on AI Visibility, Generative Engine Optimization (GEO), Answer Engine Optimization (AEO), entity resolution, machine understanding, and strategies that help organizations become more discoverable, credible, and accurately represented across AI-powered systems.
His work also includes research, communications strategy, and AI-assisted organizational systems.
Election and reporting
Florida Division of Elections — https://electionwatchfl.com/
The Ledger's October 13 candidate profile — https://www.theledger.com/story/news/politics/elections/2026/10/13/jon-albert-faces-alethea-pugh-florida-house-48-election-polk-county/92169249007/
OpenSecrets — https://www.opensecrets.org/
Jason AI Wade
Website: https://JasonWade.com
BackTier: https://BackTier.com
Email: [email protected]
A 19-to-1 fundraising disparity and a 3.42-point election margin create an important case for studying political communications, resource allocation, voter engagement, and campaign economics.
Ai for everyone: 30 Years of the Web: From Googlebot to AI Agents Who Is Reading Your Website Now—and What Are They Doing With It?
30 Years of the Web: From Googlebot to AI AgentsWho Is Reading Your Website Now—and What Are They Doing With It?For roughly 30 years, businesses have built websites primarily for two audiences: human visitors …
Show notes
30 Years of the Web: From Googlebot to AI Agents
Who Is Reading Your Website Now—and What Are They Doing With It?
For roughly 30 years, businesses have built websites primarily for two audiences: human visitors and search engine crawlers.
Googlebot visited pages, followed links, indexed content, and helped determine what appeared in search results. Website owners used robots.txt, XML sitemaps, metadata, and SEO to influence how their content was discovered and processed.
The arrangement was relatively straightforward.
But the web is changing.
Today, websites may be accessed by traditional search crawlers, AI training crawlers, AI search retrieval systems, automated browsers, and increasingly autonomous agents operating on behalf of users.
Some are collecting information. Others are retrieving answers. Some are navigating interfaces, filling forms, comparing services, or attempting to complete tasks.
The website is no longer just a destination. It's becoming an information source and an operating environment for machines.
In this episode of POD, we examine how web crawling evolved, what AI crawlers and agents actually do, and why businesses need to rethink how their websites are discovered, understood, and used.
30 Years of Web Crawling: From early search engines and Googlebot to modern AI retrieval and autonomous agents.
How Googlebot Works: Crawling, rendering, indexing, and the relationship between search engines and websites.
Robots.txt: What the Robots Exclusion Protocol does, what it doesn't do, and why it isn't a security mechanism.
The AI Crawler Explosion: How AI companies use different crawlers for training, search, retrieval, and other purposes.
Grok and xAI: How Grok-related systems fit into the changing ecosystem of AI discovery.
AI Browsers and Superagents: Why automated systems increasingly interact with websites rather than simply reading pages.
The New Website Builders: How AI-powered development platforms such as Base44 change the speed and accessibility of website creation.
Agent-Ready Websites: What businesses need to consider when software becomes a website visitor and potential customer representative.
Who Controls Access? The emerging tension between open discovery, content licensing, crawler permissions, and machine access.
Traditional crawlers primarily discover and collect web content.
AI retrieval systems may access content to answer a specific question.
AI agents go further. Depending on their tools and permissions, they may navigate websites, interact with forms, compare products, schedule services, or initiate transactions.
These systems should not all be treated as interchangeable.
A crawler that gathers content for model training has a different purpose from an agent acting on a customer's explicit instructions.
And a website that allows crawling does not automatically authorize every possible automated action.
For decades, robots.txt has provided a standardized way for website operators to communicate crawling preferences.
But robots.txt is not authentication, access control, or a guarantee that every automated system will comply.
Modern website operators need to distinguish between search indexing, AI training, live retrieval, and interactive agent access.
Blocking everything may reduce unwanted collection but can also interfere with legitimate discovery.
Allowing everything may improve accessibility while increasing exposure to unwanted automated activity.
The right policy depends on the business, the content, and the purpose of the automated visitor.
Businesses increasingly need websites that are:
Discoverable: Important information can be found by appropriate crawlers and retrieval systems.
Intelligible: Services, products, identities, and relationships are understandable to machines.
Accessible: Pages and interactions use reliable, standards-based interfaces.
Actionable: Authorized agents can complete supported tasks.
AI for Everyone: Building, Creating, and Learning with AI
AI for Everyone: Building, Creating, and Learning with AIAI Visibility Podcast | November 3, 2026Host: Jason AI Wade | Presented by: BackTierArtificial intelligence is making it easier than ever to build …
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AI for Everyone: Building, Creating, and Learning with AI
AI Visibility Podcast | November 3, 2026
Host: Jason AI Wade | Presented by: BackTierArtificial intelligence is making it easier than ever to build businesses, develop software, create content, and turn ideas into reality. But does easier technology automatically produce better results?
Jason AI Wade welcomes Mike Turner and David Raine for a free-flowing conversation about entrepreneurship, creativity, AI tools, robotics, and the importance of actually building things rather than just talking about them.
Mike Turner — Founder, AlamoTech
Marine Corps veteran, technology entrepreneur, and fractional CTO helping small businesses adopt AI, improve IT infrastructure, and develop practical technology solutions. Mike also hosts I'm Up! He Sees Me, I'm Down!, a podcast about leadership, resilience, and personal growth.
Website: https://alamotechllc.com
David Raine — Software Developer, Robotics Developer, and Author
Software developer and science-fiction author exploring AI, robotics, automation, and digital creativity. David discusses MIM, his experimental learning-oriented AI project, and how emerging technology is changing what individuals can create.
AI for small businesses: How AI makes sophisticated software and automation accessible to smaller organizations.
Just build it: Why experimenting, publishing, and learning matter more than perfection.
AI and creativity: Music generation, writing, video, and whether technology changes the meaning of artistic work.
Authenticity in the AI era: Voice cloning, synthetic media, and preserving genuine human connections.
AI meets robotics: The challenges of connecting intelligent software with physical machines.
The creator economy: Podcasting, audience growth, social media metrics, and creating for the right reasons.
ChatGPT, ElevenLabs, Descript, Riverside, Suno, Google Analytics, AI avatars, and emerging robotics technologies.
AI is expanding what individuals and small businesses can accomplish, but the technology alone doesn't create success. Experimentation, persistence, sound judgment, and the willingness to put real work into the world still matter.
Jason AI Wade is the founder of BackTier, an AI visibility architect, author of AI Visibility: How to Win in the Age of Search, Chat & Smart Customers, and host of the AI Visibility Podcast. His work explores how AI systems discover, understand, cite, and recommend people and businesses.
JasonWade.com: https://jasonwade.com
BackTier: https://backtier.comAI Visibility Podcast | AI for Everyone — November 2026
Meet the GuestsIn This EpisodeTools DiscussedKey TakeawayAbout the Host
Ai for everyone: Lake Wales vs. Lake Wailes: One Letter, Local History, and AI
Lake Wales vs. Lake Wailes: One Letter, Local History, and AIAI Visibility Podcast with Jason T AI WadeThe city lost the “i.” The lake kept it. Explaining exactly how that happened takes us into Florida land …
Show notes
Lake Wales vs. Lake Wailes: One Letter, Local History, and AI
AI Visibility Podcast with Jason T AI Wade
The city lost the “i.” The lake kept it. Explaining exactly how that happened takes us into Florida land development, railroad signs, competing historical accounts, and the future of how AI tells our stories.
In this episode, Jason T AI Wade explores the naming history of Lake Wales and Lake Wailes—and why the unresolved details matter. National Register documentation credits government surveyor J. W. Childs with naming the lake for S. I. Wailes in 1879. The town followed decades later, shaped by timber, turpentine, land sales, and railroad access.
The missing letter has a less settled explanation. A 1997 historic-district nomination attributes the shortened spelling on a 1913 depot sign to a suggestion by G. V. Tillman. An earlier National Register document says the reason for the spelling change is unknown—and identifies the business formed in 1911 as the Lake Wales Land Company. The depot story therefore leaves an important question open: when did the shorter spelling actually begin?
That uncertainty becomes the starting point for a larger discussion about artificial intelligence, business identity, and who controls the public record. When sources disagree, will an AI explain the disagreement or produce a smoother story than the evidence supports?
In this episode:
The surveyor and state agent behind the lake’s documented name.
How commercial development and railroad access helped establish the town.
The 1913 depot-sign account and the gap it leaves.
Why removing the “i” today would require a formal geographic-name proposal.
How AI can confuse similar names, merge separate entities, or flatten historical uncertainty.
What businesses can learn about rebrands, outdated listings, conflicting descriptions, and evidence.
A proposed experiment: ask multiple AI systems the same local-history questions and compare their sources and answers.
Could the lake’s spelling change?
USGS allows proposals to change an existing geographic name or spelling, but requires a compelling reason and evidence of support. Local use and acceptance are its most important consideration. A one-letter edit is possible; approval is a separate question.
Research note: This episode examines conflicting historical accounts and proposes an AI comparison. It does not report a completed comparative test or establish that AI systems consistently confuse the two places.
Sources and further reading:
Connect: JasonWade.com · BackTier.com
Have an early map, company document, newspaper clipping, or depot photograph showing either spelling? Share the source and its date. Help document where the story changes.
Ai for everyone: The Corner Challenge: $1,750 in Prizes to Reimagine Downtown Lake Wales AI Visibility Podcast | Hosted by Jason AI Wade, Founder BackTier - Your Town. Your Corner. Your Idea.
The Corner Challenge: $1,750 in Prizes to Reimagine Downtown Lake WalesAI Visibility Podcast | Hosted by Jason AI WadeYour Town. Your Corner. Your Idea.What would you do with a downtown property if you had the …
Show notes
The Corner Challenge: $1,750 in Prizes to Reimagine Downtown Lake Wales
AI Visibility Podcast | Hosted by Jason AI Wade
Your Town. Your Corner. Your Idea.
What would you do with a downtown property if you had the chance to pitch your vision to local business, government, and real estate leaders?
On January 13, 2027, Lake Wales Startup Night presents The Corner Challenge, a community entrepreneurship competition focused on new possibilities for 124 East Orange Avenue in downtown Lake Wales.
Students, entrepreneurs, business owners, artists, and residents are invited to imagine what could work at The Corner, explain how their idea would benefit the community, and compete for a proposed $1,750 in prizes.
In this episode, Jason AI Wade explains why The Corner Challenge is about more than a single downtown property. It's an experiment in grassroots economic development, youth entrepreneurship, adaptive reuse, and giving residents a meaningful voice in the future of their community.
The Corner Challenge: Why Lake Wales Startup Night is organizing a competition around a real downtown location.
The $1,750 Prize Pool: Proposed awards of $1,000 for first place, $500 for second, and $250 for third.
Two Competition Divisions: A Youth Division for K–12 students and an Open Division for adults and entrepreneurs.
Five Invited Community Leaders: Perspectives from business, local government, commercial real estate, development and construction, and entrepreneurship.
Three Minutes to Pitch: How participants can explain their concepts without a formal business plan or elaborate presentation.
What Downtown Needs: Ideas ranging from specialty food businesses and youth activities to creative spaces, coworking, entertainment, and shared retail.
From Ideas to Opportunities: How community feedback, feasibility, partnerships, and local investment can help develop stronger business concepts.
Why Young People Matter: Giving students opportunities to participate in entrepreneurship and help imagine the future of their hometown.
Beyond the Winning Idea: How participation can lead to business relationships, mentorship, potential locations, and new entrepreneurial opportunities.
What's your idea? Describe the business, activity, or community concept you envision.
Who's it for? Explain who would visit, use, or benefit from it.
How would it benefit Lake Wales? Identify the value for residents, visitors, local businesses, or downtown activity.
How could it work? Explain how the concept might operate, attract customers, generate revenue, or secure support.
No existing business or formal business plan is required.
The Corner Challenge: Reimagine 124 E. Orange Avenue
Date: Wednesday, January 13, 2027
Time: 6:00–8:00 PM EST
Check-in: 5:45 PMEvent Venue: Lake Wales Latte Lounge Coffee and Bookshop
229 East Stuart Avenue, Lake Wales, FL 33853Competition Focus: 124 East Orange Avenue, Lake Wales, Florida
Admission: Donation-based
Competition Entry: Planned to be free
Age Groups: Youth Division (K–12) and Open Division
Organizer: Lake Wales Startup Night, presented by BackTierProposed Prize Awards
First Place: $1,000
Second Place: $500
Third Place: $250
Prize funding, guest participation, and final competition rules are subject to confirmation. Proposals must respect existing businesses and property arrangements. Winning does not guarantee property access, financing, development approval, or implementation.
Register and learn more:
Economic development is often discussed by property owners, developers, government agencies, and investors. But residents possess valuable knowledge about what their communities need.
Ai for everyone: Ai for everyone: How to Start a Business in Lake Wales, Florida: The Right Order, Real Fees, and Required Steps
How to Start a Business in Lake Wales, Florida: The Right Order, Real Fees, and Required StepsStarting a business in Lake Wales, Florida, shouldn't require searching through half a dozen government websites …
Show notes
How to Start a Business in Lake Wales, Florida: The Right Order, Real Fees, and Required Steps
Starting a business in Lake Wales, Florida, shouldn't require searching through half a dozen government websites just to figure out what to do first.
But that's often the reality.
In this practical episode of the AI Visibility Podcast, Jason A.I. Wade walks through the process of starting a business in Lake Wales, including the registrations, licenses, taxes, permits, and government agencies involved.
Rather than another discussion about AI, this episode focuses on helping local entrepreneurs navigate the requirements in the right order, avoid unnecessary expenses, and understand which fees may apply.
From registering a business with the State of Florida and obtaining an EIN to determining whether city and county business tax receipts, zoning approval, or additional permits are required, Jason explains how the pieces fit together.
The objective: Give Lake Wales entrepreneurs a clearer path from business idea to legally operating business without wasting time or money navigating conflicting instructions.
Exact costs depend on business structure, location, and activities. Always verify current fees and requirements with the responsible agencies.
Jason A.I. Wade is an AI Visibility architect based in Orlando, Florida, helping businesses get found, cited, and recommended by artificial intelligence systems.
He is the founder of BackTier, which implements AI for law firms, and works through NinjaAI.com on AI SEO, Generative Engine Optimization (GEO), Answer Engine Optimization (AEO), and digital business discovery.
Jason hosts the AI Visibility Podcast, covering artificial intelligence, entrepreneurship, technology, and practical issues affecting businesses in Central Florida.
- Florida Sunbiz — Business Registration: https://dos.fl.gov/sunbiz/
- IRS — Employer Identification Number (EIN): https://www.irs.gov/businesses/small-businesses-self-employed/get-an-employer-identification-number
- City of Lake Wales: https://www.lakewalesfl.gov/
- Polk County Tax Collector: https://www.polktaxes.com/
- Florida Department of Revenue: https://floridarevenue.com/
- Florida DBPR — Professional Licensing: https://www.myfloridalicense.com/
NinjaAI: https://ninjaai.com
BackTier: https://backtier.com
Jason Wade: https://jasonwade.comThe AI Visibility Podcast is produced by BackTier Media, covering artificial intelligence, entrepreneurship, technology, and the changing business environment in Central Florida.
This episode is part of an effort to make practical business information more accessible to entrepreneurs in Lake Wales and surrounding communities.
Educational information only. Government fees and regulatory requirements may change.
Ai for everyone: Three Forces Ending the Checkout | How AI Is Changing the Way We Buy
Podcast TitleThree Forces Ending the Checkout | How AI Is Changing the Way We BuyThe traditional online checkout is facing a fundamental transformation.For decades, digital commerce followed a familiar process …
Show notes
Podcast Title
Three Forces Ending the Checkout | How AI Is Changing the Way We Buy
The traditional online checkout is facing a fundamental transformation.
For decades, digital commerce followed a familiar process: search for a product, visit a website, compare options, add something to a cart, and complete the purchase.
Artificial intelligence is changing that model.
In this episode of the AI Visibility Podcast, Jason A.I. Wade examines three forces reshaping online commerce: AI-powered product discovery, autonomous shopping agents, and integrated purchasing experiences.
As AI systems increasingly help consumers discover, compare, select, and purchase products, the conventional checkout page may become less central to the transaction.
That shift has significant implications for businesses, retailers, marketers, and the future of SEO.
If consumers no longer need to visit your website to make a purchase, how does your business compete?
Jason explores the emerging relationship between AI visibility, product data, machine-readable information, and the systems that increasingly influence purchasing decisions.
The checkout isn't necessarily disappearing. It's moving closer to the moment AI makes a recommendation.
Jason A.I. Wade is the founder of BackTier, which implements AI solutions for law firms, and NinjaAI.com, focused on AI Visibility, AI SEO, Generative Engine Optimization (GEO), and Answer Engine Optimization (AEO).
As an AI visibility architect, Jason explores how artificial intelligence is changing business operations, digital discovery, consumer behavior, and the way companies establish authority online.
He is the host of the AI Visibility Podcast.
NinjaAI — AI Visibility: https://ninjaai.com
BackTier — AI for Law Firms: https://backtier.com
Jason A.I. Wade: https://jasonwade.com
Further Reading:
Google — Universal Commerce Protocol
OpenAI — Agentic Commerce Protocol
The AI Visibility Podcast is produced by BackTier Media, covering artificial intelligence, AI visibility, business automation, emerging technology, and the transformation of digital commerce.
The podcast examines how AI systems increasingly influence what consumers discover, which businesses they trust, and what they ultimately purchase.
The future of commerce isn't just about getting customers to your website. It's about being the business AI chooses to recommend.
Your Company's Best Information Is Probably Buried in Its Files AI Search, RAG, and the Hidden Value of What Your Business Already Knows
Your Company's Best Information Is Probably Buried in Its FilesAI Search, RAG, and the Hidden Value of What Your Business Already KnowsSome of the most valuable information in your company may never have …
Show notes
Your Company's Best Information Is Probably Buried in Its Files
AI Search, RAG, and the Hidden Value of What Your Business Already Knows
Some of the most valuable information in your company may never have appeared on your website.
It's buried in old proposals, project reports, client presentations, spreadsheets, research documents, meeting notes, and years of internal files.
Your company may have already written the perfect explanation, solved a difficult problem, documented an important result, or developed a valuable process.
But nobody can find it.
Now AI is changing how businesses search, retrieve, and use their own knowledge.
What if the best answer your company needs has already been written—and AI can finally find it?
The Hidden Knowledge Problem: Why valuable business information gets lost across folders, documents, emails, and disconnected systems.
Your Best Work Is Already Written: How past proposals, case studies, reports, and research can become reusable business assets.
What Is RAG? Retrieval-Augmented Generation: a method that retrieves relevant information from documents or other sources and supplies it to an AI model when generating an answer.
Search Your Files With AI: How employees can ask questions in natural language instead of guessing filenames or keywords.
From Documents to Answers: How AI can locate relevant passages, summarize findings, and connect information across multiple files.
The Source Matters: Why a useful business AI system should identify the documents and passages supporting its answers.
The Hallucination Problem: Why RAG can reduce unsupported answers but doesn't eliminate AI errors or misinterpretations.
Security and Permissions: Why internal AI search must respect document access controls, confidentiality, and data retention requirements.
The Knowledge Advantage: How companies can turn years of accumulated experience into accessible, reusable institutional knowledge.
From Internal Knowledge to AI Visibility: How verified internal results can become public case studies, original research, and evidence that external AI systems may discover.
Most businesses don't have an information shortage.
They have an information retrieval problem.
The answer may exist in a document written five years ago, a spreadsheet nobody remembers, or a proposal created by an employee who has since left the company.
Traditional file search depends heavily on filenames, keywords, and knowing where to look.
AI-powered retrieval can help people search by meaning, ask follow-up questions, and find relevant information across large document collections.
But the quality of the results depends on the underlying documents, indexing, retrieval methods, permissions, and verification.
Imagine asking your company's AI assistant:
"What was the most successful project we completed for a restaurant, and what measurable results did we achieve?"
Instead of searching hundreds of folders, the system retrieves relevant project reports, performance spreadsheets, and client presentations.
It identifies the documented results and links back to the original evidence.
That information could support a new proposal, sales presentation, or case study—after someone verifies the findings and confirms the information can be shared.
Before asking AI to create something new, ask whether your company has already created something better.
Your business may be sitting on years of valuable knowledge that employees cannot easily access.
AI-powered search and RAG can help turn scattered files into a usable knowledge system.
The next breakthrough for your business might not come from generating more content. It might come from finally finding what you already know.
Presented by BackTier | NinjaAI.com
Nobody Owes You the Click Penske Media vs. Google: AI Overviews and the End of the Search Traffic Bargain
Nobody Owes You the ClickPenske Media vs. Google: AI Overviews and the End of the Search Traffic BargainFor nearly 30 years, publishers created content, Google indexed it, and websites competed for traffic.AI …
Show notes
Nobody Owes You the Click
Penske Media vs. Google: AI Overviews and the End of the Search Traffic Bargain
For nearly 30 years, publishers created content, Google indexed it, and websites competed for traffic.
AI Overviews are changing that arrangement. Google can now answer questions directly, potentially eliminating the need to visit the websites supplying the information.
In September 2026, a federal judge dismissed antitrust claims brought by Penske Media and Chegg against Google. The ruling highlighted a critical distinction: expecting search traffic isn't the same as having an enforceable agreement to receive it.
Penske vs. Google: What the publishers alleged and why the judge dismissed their antitrust claims.
Nobody Owes You the Click: Why rankings and citations don't guarantee website traffic.
The AI Overviews Problem: When Google answers the question instead of sending visitors to publishers.
The Broken Traffic Bargain: How AI changes the economics of publishing and search.
Citation Isn't Compensation: Why supplying information doesn't automatically generate revenue.
From Ranking to Resolution: Why AI increasingly delivers answers rather than lists of websites.
The New AI Visibility Metrics: Citation, Inclusion, Selection (CIS)—and whether those outcomes actually produce business.
SEO isn't dead. The finish line has moved.
Ranking isn't recommending. Citation isn't compensation. And visibility doesn't guarantee traffic.
The Penske ruling doesn't settle every legal question about AI content use, but it reinforces a commercial reality:
Nobody owes you the click. Your business needs to create value even when the click never happens.
Presented by BackTier | NinjaAI.com
Topics: Google AI Overviews, Penske Media, AI Search, Zero-Click Search, Publisher Economics, AI Visibility, GEO, AEO, Citation Inclusion Selection.
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