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Episode Title: Let Dad Talk — AI, Free Speech, and Building in Public

Episode Date: February 25, 2026

Recording: Room Session

Episode Summary

This episode explores what happens when an individual uses AI to organize public information at scale — and institutions don’t like the result.

The core theme is simple: speech, data, and power.

Instead of arguing emotionally, this episode breaks down a workflow for turning raw documents, public records, and digital history into structured, visualized, AI-organized systems. It also addresses digital harassment, doxxing, and how easily narratives collapse when pattern recognition replaces rhetoric.

This is not about escalation. It’s about organization.

Key Topics Covered

• Building “Let Dad Talk” — a public-facing AI-organized site based entirely on public information

• The difference between reaction and documentation

• Doxxing, digital harassment, and why most people are reckless online

• AI as a pattern recognition engine, not a storytelling weapon

• Why structured truth feels threatening to institutions

• Vibe coding and real-time web building with Lovable

• Using GPT Projects for contextual cross-referencing

• Perplexity for live web research and institutional history

• Model comparison as a strategic discipline

• The shift from curated presentation to raw data orchestration

• Why creative industries react emotionally to AI instead of analytically

Core Insight

AI does not create contradictions.

It exposes them.

When you upload full datasets instead of summaries, the system identifies patterns across time, language, and claims. That shift removes narrative control from gatekeepers and redistributes it to whoever can organize information effectively.

This episode frames that shift as a structural power change — not a personal dispute.

Workflow Discussed

1. Dump raw data without over-curating.

2. Use AI to structure, cluster, and surface patterns.

3. Iterate across multiple models for perspective and accuracy.

4. Use visual builders (Lovable) as data visualizers, not just design tools.

5. Publish. Refine. Repeat.

Tools Referenced

• Lovable (AI web builder / visual data layer)

• GPT Projects (contextual reasoning and cross-reference)

• Perplexity (live web search and archival discovery)

• Manus (specialized processing workflows)

Broader Themes

• Freedom of speech in the age of AI

• Institutional resistance to structured transparency

• The psychological gap between emotion and documentation

• The democratization of investigative capability

• Why “dumping the data” is more powerful than writing arguments

Takeaway

Stop thinking like a content creator.

Start thinking like a systems architect.

When you remove friction from organization, the power dynamic changes.

This episode documents that shift in real time.

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The pace of AI progress is unprecedented, with "frontier scale AI model releases" growing 5.6x since 2022, costs to run GPT-3.5-class models becoming "280x cheaper" in 18 months, and adoption occurring "4x faster than desktop internet." This rapid evolution presents both significant opportunities and challenges for organizations. Early adopters are already seeing substantial benefits, growing revenue 1.5x faster than their peers. However, many companies struggle to keep pace and effectively integrate AI into their operations.

This briefing outlines five core principles—Align, Activate, Amplify, Accelerate, and Govern—drawn from OpenAI's experience with leading companies. These principles provide a practical framework for organizations to navigate AI adoption confidently, foster an AI-first culture, and build a sustainable competitive advantage. The overarching message is that companies that thrive will treat AI not merely as a tool, but as "a new way of working."

Main Themes and Key Insights

1. Align: Establishing a Clear AI Vision and Purpose

Core Idea: Successful AI adoption begins with clear communication from leadership about why AI is critical to the company's future, how it enhances employee skills, and its contribution to competitive advantage.

• Executive Storytelling: Leaders must articulate a compelling "why" for AI initiatives, connecting them to business goals like "keeping pace with competitors, responding to evolving customer expectations, or sustaining growth." This builds trust and clarity.
• Company-wide AI Adoption Goal: Define a measurable goal for AI adoption, such as "new use cases, frequency of AI tool usage, or setting benchmarks for team experimentation," and integrate these into company planning and KPIs.
• Leadership Role-Modeling: Senior executives should regularly demonstrate their own use of AI. For example, OpenAI's CFO, Sarah Friar, "regularly shares how she uses ChatGPT and actively encourages her team to experiment." Moderna's CEO set an expectation that employees use ChatGPT "20 times a day."
• Functional Leader Sessions: Line-of-business leaders are crucial for connecting AI to the specific realities of each team's work, highlighting relevant use cases, and addressing feedback.

2. Activate: Empowering and Training Employees for AI Use

Core Idea: Employees require structured training and support to confidently adopt generative AI. Companies that move quickly invest in practical, role-specific learning opportunities and encourage experimentation.

• Structured AI Skills Programs: Learning & Development teams should create "clear, role-specific training that moves employees from basic AI awareness to hands-on use," focusing on skills that directly support workflows. The San Antonio Spurs boosted AI fluency from "14% to 85%" by embedding training into daily work.
• AI Champions Network: Identify and train passionate employees as internal AI mentors to provide workshops, coaching, and spread enthusiasm.
• Routine Experimentation: Dedicate regular time for employees to explore AI tools, such as "the first Friday of each month for teams to workshop how AI could improve their work," or "no-code hackathons." Notion used an AI hackathon to prototype "Notion AI, now core to their product."
• Link AI to Performance Evaluations: Directly connect AI engagement to performance evaluations and career growth, using OKRs to set "clear, role-specific goals, like identifying workflows to enhance with AI or piloting new use cases."

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Summary: This briefing document outlines key trends and strategies for brands to succeed in the evolving social media landscape of 2025. The core message is that social media has moved "Beyond the Feed," requiring brands to adopt an "omnipresent" approach, prioritize engaging and shareable content, leverage creators, foster direct connections, and utilize AI for content optimization. Follower counts are diminishing in importance, replaced by metrics like shareability and reach as indicators of brand impact.

Key Themes & Insights:

1. Social is Your Brand's Digital Footprint; Omnipresence is Key:

• Core Idea: Social media is no longer just about posting; it's about establishing a comprehensive digital presence across all channels where the audience spends time. This includes various platforms, content formats, collaborating with creators, and engaging in comment sections.
• Quote: "Social isn’t just a feed. It’s your brand’s digital footprint."
• Fact: Successful brands are "omnipresent" to remain top-of-mind in the "emerging attention economy."

2. The Death of the Follower Count; Rise of Algorithm-Driven Reach and Shareability:

• Core Idea: Follower counts are no longer the primary measure of success. The algorithm dictates visibility, and shareability and reach are now "stronger indicators of brand impact."
• Quote: "The era of the follower is dead, right now — we are living in the time of the algorithm." - Cyntia Leo, Head of Brand Marketing and Communications at Urban Outfitters.
• Fact: Monthly follower growth has plateaued, dropping 27% on TikTok and 14% on Instagram compared to a year ago.
• Fact: Brand content shares have significantly increased, by 60% quarterly on TikTok and 10% on Instagram Reels.
• Quote: "We believe the highest compliment someone can pay your brand is to talk about it or share it. We design our content using our comment section as the brief so that our community feels seen and enticed to share something hyper relevant and reflective of them." - Christina Massari, Brand Social Lead, Taco Bell.

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AI Main Streets — Show Notes

Episode: Mike Deaton — Land Flipping, AI Workflows, and Building Durable Advantage

⁠https://flippingdirt.us/⁠

Recorded: February 12, 2026
Host: Jason Wade
Guest: Mike Deaton
Source: Recorded interview transcript

Episode Summary

In this episode, Jason Wade sits down with Mike Deaton, co-founder of Flipping Dirt, to unpack how real operators are actually using AI—not for hype, but for leverage. Mike shares how he and his wife rebuilt after being laid off from corporate roles, why vacant land flipping remains one of the most misunderstood asset classes in real estate, and how AI now runs through nearly every layer of his business and personal performance.

The conversation moves from county-level land research and comp analysis to mindset engineering for 100-mile ultramarathons, bulk document OCR, and why “tool chasing” breaks businesses faster than platform shifts. The throughline is architecture: systems that survive volatility, verification loops that prevent false confidence, and authority built on structured understanding rather than tactics.

Topics Covered

• Why vacant land flipping works (and where it quietly beats traditional real estate)
• Buying land at 30–40 cents on the dollar: the discipline behind the model
• Boutique coaching vs. scale-for-scale’s-sake
• Using AI for county-level market research and regulatory analysis
• Where AI helps decision-making—and where math still needs human verification
• AI-assisted marketing: ad copy, imagery, and lifestyle visualization
• Sales support with transcripts, role-play, and text-based workflows
• Training for a 100-mile ultramarathon using AI for mindset, nutrition, and resilience
• Bulk document processing, OCR, and building searchable corpora from thousands of files
• Why access to knowledge—not effort—has always been the real control layer
• Continuous AI upgrades and why “being current” is a competitive advantage
• The coming tension between automation, labor, and economic feedback loops
• Why authority outlasts platforms in an AI-first discovery world

Notable Quotes

“AI makes it impossible to lie to yourself—if you’re actually willing to look at the facts.”

“Land looks boring until you realize it’s an information game.”

“The advantage isn’t the tool. It’s the workflow and the verification loop.”

“All you have to do is stay a little more current than everyone else—and that compounds fast.”

About the Guest

Mike Deaton is the co-founder of Flipping Dirt, a real estate investing and coaching platform focused on vacant land. After spending more than 25 years in corporate operations and supply chain roles, Mike and his wife Ligia were laid off on the same day and rebuilt from scratch through simple, repeatable land deals.

They now run a seven-figure land business, coach a small group of clients, and partner in large commercial real estate syndications for long-term wealth and tax efficiency. Outside of business, Mike lives at nearly 10,000 feet in Woodland Park, Colorado, and trains for ultramarathon races under his personal philosophy, Life: Elevated.

Resources & Links

Flipping Dirt (main site): https://flippingdirt.us
Primary on-ramp / resources: https://flippingdirt.us/freedom

Why This Episode Matters

AI is becoming the first filter between a business and a buyer. This conversation goes past surface-level tools and into how operators can build systems that stay intact as platforms, algorithms, and models change. If you’re thinking about AI as leverage—not novelty—this episode is a practical map of what that looks like in the real world.

https://flippingdirt.us/

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Apoorva Modali
Principal Data Scientist (Operations Research), Walmart Global Tech
Founder, Ovie’s Lab

Official Websites

• Ovie’s Lab: https://ovieslab.com

Primary Company

• Ovie’s Lab
  Evidence-first consumer health company focused on pregnancy and postpartum care, including topical and ingestible products designed for safety-sensitive populations.

Sales Channels

• Amazon (FBA)

• Shopify (DTC)

• TikTok Shop

Product Focus

• Pregnancy & postpartum wellness

• Postpartum hair shedding

• Skin elasticity & recovery

• Lactation support (drink mix launching soon)

• Evidence-weighted, minimal formulations with explicit safety constraints

Professional Background

• Operations Research & Mathematical Optimization

• Mixed Integer Programming (CPLEX / Gurobi)

• Bayesian methods, forecasting, ML for real-world decision systems

• Applied AI in large-scale retail environments

Social & Professional Profiles

• LinkedIn: https://www.linkedin.com/in/apoorvamodali

• PodMatch Guest Profile (for hosts): Available via PodMatch

Podcast: NinjaAI Podcast
Host: Jason Wade

Podcast Focus

• Applied AI (not hype)

• Decision systems, optimization, and explainability

• AI visibility, authority, and real-world deployment

• Where AI breaks—and why that matters

Listen / Subscribe

• NinjaAI Podcast: https://ninjaai.com/podcast

• Clips, transcripts, and episode assets published on NinjaAI.com

Host & Network

• NinjaAI.com — AI Visibility, AEO, GEO, and authority engineering

• Jason Wade — AI systems architect focused on how AI models discover, rank, and trust entities

• Apoorva is available for podcast interviews, panels, and technical discussions on applied AI, decision science, and consumer health.

• She is open to cross-promotion and social sharing of podcast episodes.

• Ovie’s Lab is actively expanding its product line and testing market viability for evidence-first frameworks across adjacent populations.

Mark Zuckerberg, CEO of Meta, has outlined a vision for "personal superintelligence," an AI designed to empower individuals in achieving personal goals, creativity, and relationships rather than centralized control. This differs from other AI labs' focus on broad automation or grand challenges.meta+2

Zuckerberg describes personal superintelligence as AI that helps users "become the person you aspire to be," integrated into devices like smart glasses for constant assistance. He argues it should prioritize user-directed empowerment over replacing jobs en masse.cnbc+2[youtube]​

Meta launched Meta Superintelligence Labs (MSL) to pursue this, recruiting top talent from OpenAI and others, with plans to invest hundreds of billions. Recent claims include early signs of AI self-improvement as a step toward superintelligence.reddit+2

Critics view it as overhyped, tied to Meta's hardware like Ray-Ban glasses, and question ethics or true innovation. Supporters see it as a democratizing force via open-source models like Llama.wikipedia+3

Zuckerberg's VisionMeta's EffortsReactions