- 13
- Episodes
- 2025
- First episode
About Be Found On AI
Optimizing for AI discoverability in a new world. discussions, tips, tricks and maybe even some hacks on how to be found on AI platforms like ChatGPT, Google AI Overview, Claude, Perplexity and others.
- Publisher
- Skyabove
- Category
- business
- Language
- en
- Explicit
- No
- First episode
- 4 Sept 2025
- Latest episode
- 9 Sept 2025
Latest episodes
13 episodes in the feed.
9 Sept 2025
Mastering AI Content for Platform Dominance in 2025
The AI content revolution is in full swing, fundamentally reshaping content creation, distribution, and consumption. In 2025, over 75% of marketers use AI tools, with 73% of businesses leveraging AI for content creation. This briefing outlines the critical strategies, platforms, and ethical considerations necessary to achieve significant visibility and influence in the increasingly crowded AI-centric online landscape. Success hinges on understanding diverse audience segments, mastering various content formats, optimizing for specific platforms, and adopting advanced AI-driven creation and distribution techniques. The ultimate goal is to establish oneself as a credible, influential figure who actively shapes the AI conversation, not just another voice in the crowd. Key Themes and Important Ideas1. The Ubiquity and Evolution of AI in Content Creation Pervasive Adoption: "The AI revolution isn't coming—it's here, reshaping how we create, share, and consume content at an unprecedented pace." By 2025, "more than 75% of marketers admit to using AI tools to some degree, while around 19% of businesses use AI tools to generate content." McKinsey's 2025 State of AI report notes "73% of businesses now utilize AI for content creation." Beyond Experimentation: The landscape has moved "from simple ChatGPT experiments to sophisticated multi-platform strategies that leverage dozens of specialized AI tools." This isn't just about efficiency; "it's about fundamentally reimagining what's possible in content creation." New Battleground: "A new battleground for influence has emerged: AI-centric online platforms." The question is no longer if to engage, but how to master it. Success requires deep audience understanding, as the AI content ecosystem comprises distinct "tribes" with unique needs and platform preferences. The Technical Architects: Focused on "cutting-edge research papers," "performance benchmarks," and "algorithmic innovations." Platform Preference: GitHub, Reddit's r/MachineLearning, technical Discord servers. Content Format: Long-form technical articles, Jupyter notebooks, video tutorials with code walkthroughs. The Business Innovators: Executives and entrepreneurs seeking to "leverage AI for competitive advantage" through "ROI calculators," "implementation roadmaps," and "industry-specific AI applications." Platform Preference: LinkedIn, Medium, industry-specific forums. Content Format: Case studies, white papers, webinars, LinkedIn articles. The Creative Pioneers: Artists and designers exploring "AI art generation techniques," "prompt engineering masterclasses," and "monetization strategies for AI-generated content." Platform Preference: Discord art communities, YouTube, Instagram. Content Format: Visual tutorials, speed art videos, before/after comparisons. The Curious Explorers: Students and career changers looking for "free learning resources," "practical AI applications for everyday life," and "myth-busting." Platform Preference: YouTube, TikTok, Twitter/X. Content Format: Short-form videos, infographics, tweet threads. Effective content goes beyond simple text, demanding comprehensive and engaging experiences. Technical Deep Dives: Interactive tutorials (Google Colab, Kaggle), video code-alongs (Lumen5), performance comparisons, architecture visualizations. Data-Driven Case Studies: Must include "specific metrics and KPIs," "implementation timelines," and "video testimonials when possible." "53% of senior executives using generative AI report significant improvements in team efficiency." Thought Leadership: Address "ethical implications," "the future of work," and "predictions backed by data and expert opinions." Practical Guides: Step-by-step implementation, tool selection frameworks, budget calculators. Visual Narratives: Infographics, process flow diagrams, "before/after transformation showcases," AI-generated art exhibitions.
5 Sept 2025
The AI Search Revolution and Its Impact on Businesses
The digital landscape is undergoing a "dramatic transformation" with AI-powered assistants fundamentally reshaping how users find information online. This shift, driven by technologies like ChatGPT, Claude, and Perplexity AI, marks the "death of the ten blue links" and a move from traditional keyword-based search to conversational, synthesized, and personalized AI assistance. Businesses that fail to adapt their strategies from traditional SEO to "AI visibility" risk becoming "invisible to an entire generation of consumers." Early adoption and optimization for AI systems are crucial for future success. Key Themes and Most Important Ideas/Facts: 1. The End of Traditional Search as We Know It: * The way people search for information is undergoing the "most dramatic transformation since Google revolutionized web search in 1998." * Evidence: "Today, 180 million people regularly turn to AI assistants like ChatGPT, Claude, and Perplexity instead of traditional search engines." * The "paradigm is crumbling" because AI offers "direct answers, not just links to answers," rendering the "ten blue links" model obsolete. 2. Rapid User Adoption and Shifting Market Share: * AI assistant adoption is happening at an unprecedented pace, indicating a fundamental shift in user behavior. * Evidence: * "ChatGPT reached 100 million users in just 2 months—the fastest-growing consumer application in history." * "65% of Gen Z now prefers AI chatbots over Google for product research." * "Google’s search market share dropped below 90% for the first time in a decade." 3. Superior User Experience of AI Search: * AI search offers significant advantages over traditional search in four key areas: * Conversational Understanding: Users can "simply ask" questions naturally, rather than translating them into keywords. * Synthesis vs. Selection: AI "instantly synthesizes information from hundreds of sources," providing comprehensive answers, eliminating the need to open multiple tabs and scan. * Follow-up Intelligence: Conversations "builds naturally," allowing for refined and deepened assistance. * Personalized Recommendations: AI "learns your preferences, dietary restrictions, budget range, and style preferences," delivering increasingly tailored results. 4. Business Implications: Adapt or Disappear: * The shift from search to AI assistance is "revolutionizing how businesses must think about digital visibility." * Losers in the AI Search Era: "SEO content farms that gamed Google’s algorithm," "affiliate marketers who relied on search traffic," and "brands that invested everything in traditional SEO." * Winners in the AI Search Era: "Authentic brands that AI systems consistently recommend," "companies with strong direct relationships with customers," and "businesses optimizing for AI visibility from day one."
5 Sept 2025
Model Context Protocol (MCP) - Unlocking AI's Full Potential
The Model Context Protocol (MCP), introduced by Anthropic in November 2024, is an open-source standard designed to revolutionize AI development by creating a universal language for Large Language Models (LLMs) to communicate with external data sources and tools. This protocol addresses the fundamental limitation of AI models being "trapped behind information silos and legacy systems," enabling secure, two-way connections to real-world data and actions. MCP is poised to become the "universal translator between AI models and the world’s data, much like USB-C unified the world of physical connectors," facilitating the creation of truly intelligent, context-aware, and agentic AI applications. A. Addressing AI's Fundamental Limitation: Isolation from Data Problem: Before MCP, connecting LLMs to diverse data sources (e.g., internal knowledge bases, project management tools, real-time feeds) required "building a custom, one-off integration." This approach led to "a fragmented ecosystem of custom integrations, hindering the development of truly intelligent and context-aware AI applications." MCP's Solution: MCP breaks down these barriers by providing a "standardized, secure, and two-way connection between AI models and the outside world." This allows AI to access and interact with the "vast and varied data sources that power our digital world." B. MCP as a Universal Standard (The "USB-C for AI") MCP aims to be "the universal translator between AI models and the world’s data, much like USB-C unified the world of physical connectors." This signifies its ambition to standardize connectivity across the AI landscape. Benefits of Standardization:For Developers: Reduces development time and complexity as they "can now build to a single, open standard" instead of "maintaining a multitude of bespoke integrations." For Businesses: Enables secure connection of proprietary data to AI, leading to "new possibilities for automation, data analysis, and personalized user experiences." For Users: Promises a "more seamless and context-aware AI" capable of understanding and proactively assisting across various digital tools (email, calendar, etc.). C. Open Source and Collaboration MCP is explicitly an "open-source standard," emphasizing accessibility, transparency, and collaboration in its development and adoption. Quote: "Open technologies like the Model Context Protocol are the bridges that connect AI to real-world applications, ensuring innovation is accessible, transparent, and rooted in collaboration." — Dhanji R. Prasanna, Chief Technology Officer at Block. D. Architectural Design: Client-Server and Two-Layered Client-Server Model:MCP Host: The AI application (chatbot, code assistant) that manages MCP Clients. MCP Client: Intermediary, maintaining a "dedicated, one-to-one connection with a specific MCP Server" and fetching context. MCP Server: "The gateway to a specific data source or tool" (e.g., local file system, proprietary enterprise system). This architecture allows an AI application to "connect to multiple data sources simultaneously by simply instantiating a new MCP Client for each source." Two-Layer Architecture:Data Layer: The "core of the protocol," based on JSON-RPC 2.0, defining message structure, semantics, lifecycle management, and primitives for information exchange. Transport Layer: Handles "low-level details of communication" (connection, framing, authentication). Currently supports Stdio Transport (local processes, no network overhead) and Streamable HTTP Transport (remote processes, uses HTTP POST and Server-Sent Events for streaming). This layered approach ensures flexibility and future-proofing.
4 Sept 2025
Google AI Overview Inclusion
In this concise 5-minute business podcast, digital marketing experts Michael and Sarah discuss how Google's AI Overview is revolutionizing online visibility for businesses. Learn how these AI-generated summaries at the top of search results are changing customer discovery patterns and what practical steps your business can take to appear in these coveted positions.The hosts break down:- What Google AI Overview is and why it matters for your bottom line- Strategic content approaches that AI systems recognize and prioritize- Technical optimization tactics that boost your chances of inclusion- Common pitfalls to avoid when adapting to this new search landscapePerfect for business owners and marketing professionals looking to stay ahead of the curve in the rapidly evolving digital landscape. This podcast delivers actionable insights you can implement immediately to improve your business's visibility in the age of AI-powered search. Google AI Overview, digital marketing strategy, search visibility, content optimization, business growth
4 Sept 2025
AI Visibility for Auto Dealerships: A Survival Guide
The automotive retail landscape is undergoing a "seismic shift" driven by the rise of AI platforms like ChatGPT, Claude, and Gemini. These platforms are fundamentally changing how consumers research, compare, and choose dealerships. For auto dealerships, securing "AI visibility" is no longer just a marketing trend but a "critical survival strategy." A staggering 67% of car buyers now use AI platforms for research, with 45% making initial dealer selections based on AI recommendations. Dealerships that optimize for AI visibility are seeing "35% more qualified leads" and "28% higher conversion rates," while those that ignore it face market share loss, increased acquisition costs, and decreased brand loyalty. The "window for early adoption is closing rapidly," making immediate action imperative for long-term success and sustainability. he AI Revolution in Car Buying & Changing Consumer Behavior Game-Changing Reality: "67% of car buyers now use AI platforms during their research process, with 45% making initial dealer selections based on AI recommendations." This signifies a fundamental shift in the customer journey. New Customer Journey: The process now moves from "Initial Research" and "Dealer Discovery" through AI platforms, to "Reputation Check" (AI-synthesized reviews), and finally "Final Decision" (AI-influenced dealer selection). Shift from Traditional to AI-Powered Process:Traditional: Google search, website visits, individual reviews, calls/visits. AI-Powered: "Ask AI: 'Recommend reliable Honda dealers in my area'," get "instant, synthesized recommendations," "comprehensive dealer comparisons," and contact top-recommended dealerships. AI Queries: Consumers use AI for a wide range of questions, from "What are the most reliable car dealerships in [city]?" and "Which dealership has the best customer service for [brand]?" to "Compare [Dealership A] vs [Dealership B] reviews" and "Should I buy from [dealership name]?"
4 Sept 2025
AI Liberates Restricted Industries from Google's Grip
Outlines the profound impact of Artificial Intelligence (AI) on industries previously stifled by Google's stringent advertising policies, particularly in the financial services sector (e.g., debt consolidation, credit repair). The source argues that AI is creating a "new, largely unregulated information market" that empowers businesses to bypass Google's dominance, overcome advertising restrictions, and connect with customers in innovative ways. This shift is described as a "bullet train bulldozing a path forward through uncharted territory," ushering in an era where businesses can escape the "stranglehold" and "daily dread of deplatforming" imposed by Google. Google's Stranglehold on Restricted Industries: Dominance and Control: Google commands "over 90% of the global search market and generating billions in ad revenue annually," making it an unavoidable gatekeeper for online visibility. Restrictive Policies: Google's "Financial Products and Services policy" aims to protect consumers but creates a "minefield for legitimate operators," especially in "debt-related niches." Outright Prohibitions and Rigorous Certifications:Ads for "credit repair services are outright prohibited, regardless of the advertiser’s legitimacy." Debt services (settlement/management) require Google certification, often limited to "approved non-profit budget and credit counseling agencies." This process is "rigorous," demanding licenses, compliance, and third-party verification. "Even law firms specializing in these areas aren’t exempt." Constant Policy Shifts and Fear of Deplatforming:Policies are "updated multiple times a year, often with little fanfare," leading to constant anxiety for businesses. "Violators face warnings, strikes, and eventual account suspensions. That’s a digital death sentence for businesses reliant on online leads." This fosters a "culture of paranoia, where innovation takes a backseat to survival." Businesses "scale back ambitious targeting" and avoid certain keywords or retargeting to "minimize risk, ultimately capping their growth." The "dread of 'Google pulling them' is universal in these circles." Suspensions can occur with "minimal warning, sometimes due to algorithmic glitches or competitor reports."
4 Sept 2025
Structured Data: Your AI Search Superpower
The Seismic Shift in Search: From Engines to Answer Engines The traditional model of search, focused on indexing web pages and ranking results, is undergoing a "seismic shift" due to the rise of AI. AI-powered search tools, such as Google's AI Overviews, ChatGPT, and Perplexity, are "no longer just indexing web pages; they’re understanding them. They’re not just providing links; they’re delivering direct answers." This fundamental change transforms search engines into "answer engines." Key Idea: AI search aims to comprehend user intent and provide comprehensive, direct answers, rather than just a list of links. Quote: "Instead of just pointing users to a list of links, it aims to understand the user’s intent and provide a direct, comprehensive answer. This is a fundamental shift from a search engine to an 'answer engine.'"
4 Sept 2025
NLP's SEO Impact: Ranking in the Semantic Era
NLP as the Foundation of Modern Search Engines Definition and Function: NLP is a branch of AI enabling computers to "understand and process human language." It achieves this by "breaking down language into smaller components, analyzing their meaning, and understanding the relationships between them." Beyond Keywords: The primary shift powered by NLP is moving "beyond simply matching keywords and delv[ing] into the intent and context behind a user’s query." This allows search engines to interpret the nuances of human language. Ways NLP Impacts Search Engine Rankings Semantic Search: Concept: NLP "powers semantic search, allowing search engines to understand the meaning behind the words, not just the words themselves." Benefit: Content can "rank for a wider range of related terms, even if those exact keywords aren’t present." Optimization: Focus on "creating comprehensive, high-quality content that thoroughly covers a topic and addresses user intent." Understanding User Intent: Concept: NLP helps search engines "decipher what users actually want when they perform a search." This involves identifying if a user is "looking for information, a product to buy, or a local service?" Optimization: "Create different types of content that cater to various user intents, such as informational blog posts, product pages, and local business listings." Content Quality and Relevance: Concept: NLP algorithms "analyze the quality and relevance of your content," assessing factors like "readability, grammar, and the depth of information provided." Preference: "Content that is well-written, comprehensive, and directly answers the user’s query is favored." Optimization: "Focus on creating valuable, user-friendly content that provides a positive experience." Featured Snippets and Voice Search: Concept: NLP is crucial for "identifying concise answers to questions, which are often featured in featured snippets." It also underpins the understanding of "spoken queries in voice search." Optimization: "Optimize your content by directly answering common questions related to your niche in clear and concise language. Use structured data to help search engines understand the key information on your pages." Personalized Search Results: Concept: NLP "contributes to the ability of search engines to personalize results based on a user’s past search history, location, and other factors." Optimization (Indirect): While direct optimization for individual personalization isn't possible, "creating diverse and valuable content increases your chances of ranking for a wider audience."
4 Sept 2025
Understanding AI Crawlers
AI crawlers are sophisticated automated systems that systematically browse the internet to collect, analyze, and index web content. Unlike traditional web crawlers primarily focused on search engine indexing, AI crawlers are specifically designed to gather data for training machine learning models and powering AI applications. They are foundational to modern AI systems, search engines, and various web-based applications, necessitating a deep understanding for web developers, content creators, and digital marketers. The future points towards AI-first optimization, real-time processing, and multimodal understanding.
4 Sept 2025
The Book Review - Be Found On AI
The emergence of Artificial Intelligence (AI) is fundamentally reshaping the landscape of business discovery and customer acquisition. Traditional marketing funnels, which centered on websites and organic search, are becoming obsolete. Customers are no longer "searching"; they are "asking" AI assistants for personalized recommendations, often bypassing direct interaction with vendor websites entirely. This shift creates a "trillion-dollar shift in consumer behavior" and a "sustainable competitive advantage" for businesses that proactively optimize for AI visibility. Success hinges on understanding how AI systems discover and evaluate businesses, building a strong foundation of "Semantic Density," "Authoritative Consistency," and "Contextual Relevance," and implementing systematic strategies for testing, measurement, and continuous adaptation. A. The Obsolete Traditional Funnel and the Rise of AI-Influenced Discovery Shift from Searching to Asking: Customers are moving away from typing keywords into search engines and instead engaging in conversational queries with AI assistants like ChatGPT, Claude, and Perplexity. They ask complex, contextual questions, e.g., "What's the best way to track our marketing campaigns without losing our minds?" Website's Diminished Role: In the AI funnel, the website is "optional." Customers make purchase decisions based "entirely on AI recommendations, often without ever visiting your site." The traditional marketing funnel, which assumed a website-centered customer journey, is becoming obsolete. The Invisible Sale: AI provides "personalized analysis," "unbiased comparison," and an "efficient process," allowing customers to receive tailored recommendations and schedule demos directly with vendors without ever visiting their websites. One vendor got a sale "without Sarah ever seeing their website, reading their blog, or downloading their whitepapers." New Success Metrics: Traditional metrics like website traffic, page views, and generic keyword rankings matter less. New metrics include: AI Mention Frequency: How often AI systems recommend your business. Recommendation Context: Whether AI recommends you in appropriate situations. Qualification Quality: How well AI-influenced prospects match your ideal customer profile. Conversion Efficiency: How quickly AI-educated prospects move through your sales process. Website's New Role: The website transforms from a "Traffic Destination to Validation Hub," focusing on social proof, detailed case studies, implementation, and support information, rather than initial education or lead generation. The New Customer Journey: Contextual and Dynamic Shift from Linear to Dynamic: The traditional linear customer journey (Awareness → Interest → Consideration → Intent → Evaluation → Purchase) is replaced by a "dynamic, AI-influenced process where context matters more than ever." AI-Driven Journey Stages:Contextual Problem Identification: AI proactively identifies problems and opportunities. AI Analysis and Recommendation: AI conducts sophisticated analysis and provides tailored recommendations. Validation and Selection: Customers focus on validating AI recommendations. Implementation Planning: Implementation considerations are integrated into the selection process. From Pull to Push Discovery: The traditional "Pull Model" (customers actively seek information) is superseded by the "AI Push Model" where "AI proactively suggests solutions." Success depends on being "recommended when AI analyzes customer context." Trust Transfer Phenomenon: Customers "increasingly trust AI recommendations as objective and comprehensive, transferring decision-making authority to AI systems." Studies show "73% of B2B buyers trust AI recommendations more than vendor marketing materials."
4 Sept 2025
The Question Engine
"The Question Engine" by Steve R. Gibson thoroughly explores the symbiotic relationship between human curiosity, expressed through billions of digital interactions, and the development of Artificial Intelligence. The book argues that every search query, click, swipe, and social interaction has inadvertently served as training data, shaping AI systems from simple search engines into sophisticated predictive and generative models. This process has transformed not only technology but also human cognition, behavior, and societal structures, leading to a "predictable human" in a world increasingly mediated by algorithms. The core theme is the "Ouroboros Loop," a self-reinforcing cycle where human behavior trains AI, which in turn guides human behavior, raising profound questions about agency, privacy, truth, and the future of human identity in an increasingly integrated human-AI world. The author concludes with a call for conscious participation, ethical design, robust regulation, user empowerment, and adaptive education to ensure AI amplifies human potential rather than exploiting its weaknesses.
4 Sept 2025
Be Found on AI Survival Guide
Quickly be found on AI platforms
4 Sept 2025
Who's Who in AI Platforms
These sources offer a comprehensive overview of the leading AI platforms and agents in 2025, highlighting the rapid evolution of artificial intelligence. They categorize AI tools into several key areas, beginning with major AI assistant platforms like OpenAI, Anthropic, Google, Microsoft, and Meta, which are at the forefront of generative AI. The texts also spotlight leading Chinese AI platforms such as Baidu, Alibaba Cloud, Tencent, ByteDance, and DeepSeek, demonstrating China's significant contributions to AI development. Additionally, the sources discuss specialized creative platforms like Midjourney, Stability AI, and Runway, tailored for generating visual and auditory content. Finally, they cover developer and enterprise platforms crucial for AI infrastructure, and industry-specific agents designed for sectors like marketing, law, and education.
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