Category: Data

  • Why AI Shouldn’t Replace Your White Belt Skills in the Journey to Mastery

    You can’t become a black belt if you never practice white belt techniques. They’re basic. They can seem boring. Punch. Punch. Kick. Kick. Evade. But those white belt techniques become green belt techniques, become brown belt techniques, until one day, years after you’ve stepped through the door of the dojo for the first time, you…

    Continue reading →

  • How Adversarial AI Systems Are Making Generative AI Safer for Business Use

    It is becoming clear that generative AI exposed to the public must be an adversarial system. From jailbreaks to prompt injection to inherent bias in the models themselves, there is no model on the market today that can be put into customer-facing production, as is, with no supervision. None. Not GPT-5, not Gemini, not WatsonX,…

    Continue reading →

  • Can You Really Trust AI-Generated Content? The Truth About Watermarks and Authenticity

    Proving content authenticity is going to be a matter of lineage. Here’s what I mean. AI companies in consumer interfaces are adding things like watermarks & fingerprints. But when you dig into the architecture, these artifacts are added AFTER the generation. If you use the actual models themselves, these fingerprints are not part of the…

    Continue reading →

  • Unlocking AI’s True Potential: How Collaboration Between Domain Experts and AI Specialists Creates Game-Changing Use Cases

    People need to see use cases to understand a new technology. People who understand the technology often don’t have the domain expertise, so it’s difficult to create the use case. That’s why so many of the use cases you see publicly for generative AI are so… mundane. Write some blog posts. Write some emails. Write…

    Continue reading →

  • AI Just Won a Major Copyright Battle: Why This Ruling Could Change Everything

    This is a very big deal. Bartz, Graeber, Johnson v. Anthropic PBC ruling in the US District Court, Northern California District has ruled that training an LLM on copyrighted works does NOT constitute infringement because it is “spectacularly transformative”. DISCLAIMER: I AM NOT A LAWYER. I CANNOT GIVE LEGAL ADVICE. CONSULT AN ATTORNEY IN YOUR…

    Continue reading →

  • Mind Readings: How to Build MCP Services, Part 1

    Summary In today's episode, I introduce the Model Context Protocol and explain how these extensions enhance generative AI capabilities. Here's what this means for you. You can expand the functionality of your AI tools beyond their native limits to handle specialized tasks like math or data retrieval. You'll also learn these concepts: the difference between…

    Continue reading →

  • So What? How To Use AI as a Sales Copilot

    Summary In today's episode, I walk through how to use AI as a sales co-pilot to transform raw CRM data into actionable pipeline insights. Here's what this means for you. You gain a practical workflow for building dashboards, scoring deals, and generating next-best-actions without expensive consulting or complex software. You'll also learn these concepts: how…

    Continue reading →

  • The Trust Insights AI-Ready Marketing Strategy Kit

    Summary In today's episode, I explain the importance of building a solid foundation for AI and introduce a free marketing strategy kit. Here's what this means for you. You can prepare your organization for successful AI implementation by mastering essential basics before chasing buzzwords. You'll also learn these concepts: why data governance and process management…

    Continue reading →

  • Why AI Doesn’t Sound Like You (And How to Fix It)

    “Why doesn’t AI sound like me?” The recent academic paper “From Tokens to Thoughts” explains exactly why, albeit in a technical way. LLMs – the engines that power tools like ChatGPT – are compression engines. They take big data and compress it into small data so that AI can efficiently predict the next set of…

    Continue reading →

  • Foundation Principles of Generative AI, Part 1

    Summary In today's episode, I introduce the first foundational principle of generative AI. Here's what this means for you. You can master AI by applying it to every possible task until you discover its limits. You'll also learn these concepts: how to test AI across various workflows, how to manage data privacy risks, and why…

    Continue reading →