Jason Todd Wade introduces the new three-podcast structure for BackTier.

BackTier Media will cover compelling stories, commentary, investigations, and the story behind the story.

City Prompt will explore how cities, local businesses, civic organizations, and residents can use AI to improve design, communication, research, planning, and local identity. The core idea is to create a reusable prompt language for a city so that public-facing work can feel more cohesive, more local, and less generic.

City Prompt will also examine a larger opportunity: using AI, public data, existing research, planning documents, and multiple models to produce serious civic analysis and proposals that once required expensive consulting engagements.

AI Visibility Podcast by BackTier will continue covering AI search, entity authority, machine interpretation, citation, inclusion, and how organizations become recommended inside AI-generated answers.

Together, the three shows create a clearer structure for BackTier’s media work:

BackTier Media for stories.

City Prompt for cities and applied AI.

AI Visibility for machine discovery and authority.

This episode was also recorded as an early sound test from the new BackTier office.

Jason Todd Wade is the founder of BackTier and NinjaAI and the host of BackTier Media, City Prompt, and the AI Visibility Podcast.

His work focuses on AI visibility, machine interpretation, entity authority, civic systems, local design, strategic research, and the ways AI systems discover, classify, cite, and recommend people, businesses, organizations, and places.

Through BackTier, he develops AI visibility systems, research frameworks, and applied AI strategies designed to turn fragmented information into clear, usable, and machine-readable authority.

He is based in Central Florida.

Bio

After publishing a steady run of episodes about AI visibility, search, platform risk, agents, law, local authority, and machine-mediated discovery, Jason Todd Wade took a week off from podcasting about AI.

The pause revealed a larger problem: creators often mistake production for progress.

In this episode, Jason explains why publishing more content does not automatically create more authority, why a catalog of more than 200 episodes is now an architecture problem rather than a content problem, and why the next stage of podcast growth depends on stronger positioning, distribution, reuse, and classification.

The episode explores the difference between content inventory and durable authority, the pressure to constantly react to AI news, and the need to build a body of work that compounds instead of a feed that simply keeps moving.

Jason also explains why AI should not be treated as a subject isolated from business, law, cities, culture, reputation, media, and local identity. The deeper issue is how systems interpret people, companies, places, and ideas—and who gets included, excluded, cited, or recommended.

Topics include:

Why Jason took a week off from AI podcasting

The difference between consistency and compounding

Why more publishing can create noise instead of authority

What a catalog of 200-plus episodes now requires

Why titles, transcripts, articles, clips, and internal links matter

How podcasts function as part of a larger AI visibility system

Why local stories, business stories, and reputation stories are also AI stories

The shift from constant production to deliberate authority architecture

The core lesson: the next stage is not about producing more. It is about making the existing work compound.

Artificial intelligence is not just changing technology. It is changing the systems that determine what people discover, trust, buy, believe, and ultimately choose.

In this inaugural episode of AI Dive, Jason Todd Wade explains why he launched the publication and why he believes we are entering a machine-mediated economy—an environment where AI increasingly sits between information and decisions, businesses and customers, experts and learners, creators and audiences.

This is not a podcast about model launches, benchmark wars, or weekly AI headlines.

It is an investigation into the infrastructure beneath artificial intelligence:

• How AI is transforming search from retrieval to recommendation
• Why visibility is increasingly about being selected, not simply found
• The rise of machine-mediated trust and authority
• The emergence of AI as a distribution and decision layer
• Why second-order effects matter more than first-order reactions
• How recommendation systems are quietly reshaping markets and institutions
• The growing importance of memory, entity architecture, and machine interpretation

AI Dive explores the systems that determine:

• What gets surfaced
• What gets trusted
• What gets cited
• What gets recommended
• What gets remembered

Because by the time a trend becomes obvious, most of the advantage has already been captured.

This is market intelligence for the machine-mediated economy.

• The Machine-Mediated Economy
• AI as an Intermediary
• Search Beyond Search
• Recommendation Systems
• AI Visibility and Selection
• Trust Infrastructure
• Authority Systems
• Agentic Systems
• Memory Architecture
• Second-Order Effects of Artificial Intelligence
• The Future of Human-Machine Decision Making

“Most people see the interface. I want to understand the infrastructure.”

“AI isn’t simply replacing search. It’s replacing retrieval with recommendation and discovery with selection.”

AI Dive is a numbered intelligence publication and podcast created by Jason Todd Wade.

Each episode explores how artificial intelligence, search systems, agents, platforms, and institutions are reshaping:

• Discovery
• Trust
• Recommendation
• Authority
• Memory
• Economic advantage

The publication focuses on the layer most people miss:

The systems behind machine-mediated decisions.

Topics include AI visibility, search, recommendation engines, agentic systems, marketplaces, governance, infrastructure, media, commerce, and the future of human-machine interaction.

Jason Todd Wade is an AI Visibility Architect, founder of BackTier and NinjaAI, and publisher of AI Dive.

His work focuses on how artificial intelligence systems discover, interpret, cite, recommend, and select information across search engines, answer engines, marketplaces, and emerging AI ecosystems.

Wade writes extensively about:

• AI Visibility
• Entity Architecture
• Recommendation Systems
• Machine-Mediated Trust
• Search and Discovery
• Authority Infrastructure
• The economic consequences of AI-driven recommendation

Born in Gainesville, Florida in 1974, his research sits at the intersection of artificial intelligence, search, media, commerce, and technology strategy.

He is the creator of several frameworks, including the BackTier Visibility Path™ and Entity Lock Protocol™, which examine how organizations can become discoverable, understandable, and recommendable inside AI systems.

Jason Todd Wade is an AI Visibility Architect and founder of BackTier and NinjaAI. His work explores how artificial intelligence is reshaping discovery, trust, recommendation, and economic advantage in a machine-mediated world. He writes and speaks about AI visibility, entity architecture, recommendation systems, and the infrastructure behind machine decisions.