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…
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…
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…
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…
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…
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…
Summary In today's episode, I tackle the question of whether falsifying CRM data using AI is a performance problem or a technology problem and explain why accountability always lands on a human. Here's what this means for you. You'll walk away knowing that no AI system acts on its own and that building proper governance…
Summary In today's episode, I answer how agencies scale output and margins without scaling headcount by handing templated tasks to AI. Here's what this means for you. You gain a clear rule for identifying which work to automate and which to keep with humans, so you build a leaner, faster agency. You'll also learn these…
