Category: Generative AI

  • You Get What You Pay For: Why Supporting Human Authors Beats AI Slop

    Two enduring maxims: Fast. Cheap. Good. Choose any two. You get what you pay for. Earlier today, my friend alerted me about a discussion on X, visible in the photo on this post. TLDR: people said they didn’t want to pay for books because they couldn’t afford them, and thought all authors should be required…

    Continue reading β†’

  • So What? How AI Detectors Work

    Summary In today's episode, I walk through how AI detectors actually work under the hood and why their results are far less trustworthy than most people assume. Here's what this means for you. You gain a critical understanding that AI detection is a statistical assessment of word probability, not a verdict on authorship, quality, or…

    Continue reading β†’

  • Hands-On AI Workshops for Marketers: Why You Need to Attend MAICON 2026

    Back in 2019, Paul Roetzer asked me to speak at a brand new event, the Marketing AI Conference, MAICON hosted by the Marketing AI Institute. This was 3 years before ChatGPT, a full year before the first minimally functional GPT model even existed. How things have changed since then. The first MAICON conference was about…

    Continue reading β†’

  • You Ask, I Answer: Handling AI Context Drift?

    Summary In today's episode, I tackle Cooper's question about handling context drift and hysteresis in long-running persistent agent sessions, explaining why generative AI models cannot remember anything on their own. Here's what this means for you. You gain a clear framework for understanding why memory problems happen in AI agents and how external scaffolding solves…

    Continue reading β†’

  • Stop the SaaS Trap: How to Use FOSS and AI to Build Custom Software You Actually Own

    A reminder that there is a 3rd way between “vendor lock-in” and “YOLO vibe code an alternative”. That way is called FOSS: Free, Open Source Software. Free, Open Source Software that bears either an Apache, BSD, or MIT license can be used for commercial purposes without restriction. AGPL and GPL licensed software can be used…

    Continue reading β†’

  • You Ask, I Answer: Multi Agent AI Orchestration Costs?

    Summary In today's episode, I break down why complex multi-agent orchestrations are wildly expensive and share practical model selection strategies to slash those costs. Here's what this means for you. You'll discover that matching lighter, cheaper AI models to simpler tasks like documentation saves a fortune without sacrificing quality. You'll also learn these concepts: why…

    Continue reading β†’

  • The Truth About AI Bias: Why It Can Never Be Completely Removed

    There is no such thing as removing bias from generative AI completely. None. Zero. Anyone making that claim is lying, period, end of story. Here’s why. A lot of people – with good intentions, and with good effect – can REDUCE bias by giving today’s language models clear guidelines about what constitutes inclusive language versus…

    Continue reading β†’

  • The AI Hypocrisy: Why Secretive Use of Generative AI is Fueling Creator Backlash

    Many more people are using AI than you thought. This is the conclusion from the fan fiction kerfuffle of yesterday, when a Claude formatting tag was copied by authors unwittingly into their fan fiction published on Archive of Our Own (AO3). Folks are hastily editing their stories, and in some cases, removing them from Archive.org…

    Continue reading β†’

  • Almost Timely News: πŸ—žοΈ How to Demonstrate Your AI Chops in Job Hunting (2026-07-26)

    _Almost Timely News: πŸ—žοΈ How to Demonstrate Your AI Chops in Job Hunting (2026-07-26) :: View in Browser_ The Big Plug πŸ‘‰ New book! 21 Use Cases of Generative AI For Marketers Content Authenticity Statement 90% of this week’s newsletter was made by me, the human. You’ll see multiple outputs from Claude Opus 5 including…

    Continue reading β†’

  • Why AI Editing Is Making Your Writing Boring and How to Fix It

    A reminder that editing with AI makes works read more like AI. When GenAI works on text, it works in probabilities. That’s literally how it works at its heart, figuring out the most probable next item in a sequence based on the data in the sequence. It’s why it’s so good at things like predicting…

    Continue reading β†’