Summary In today's episode, I explain how to justify escalating AI API costs to your CFO when direct revenue ROI isn't apparent, using a blender analogy to reframe the question. Here's what this means for you. You need a measurement strategy that proves your AI spend is making the company money faster than it's costing…
It is difficult to overstate how big a deal Qwen3.8 27B is as an AI model. For those new to open weights models, traditionally, open weights models have lagged behind state of the art models by 6-12 months. Using an open weights model (usually for cost reasons) meant sacrificing capabilities for cost. The team at…
Summary In today's episode, I break down the strategic case for balancing commercial AI providers like OpenAI against self-hosted open source LLMs, using a "plan big, act small" framework. Here's what this means for you. You'll gain a business continuity playbook that hedges against major AI vendors inevitably tripling prices to cover their massive losses.…
Summary In today's episode, I break down how to choose between building a cheap local AI inference box and setting up a low-cost orchestration computer that hands the heavy lifting to a cloud provider. Here's what this means for you. You'll get a clear framework for matching your budget, power budget, and privacy needs to…
Another week, another Pareto distortion in AI. Two new AI models came out on the scene this week, Qwen3.8-Flash-Next and zAI GLM-5.3-Flash. Both of these are Flash models, meaning that they’re smart but optimized for speed. Both of them score higher on Artificial Analysis independent benchmarks than Claude Sonnet 5 and Opus 4.7. They’re both…
Five new AI models hit the field this week, and only one of them is probably worth your time. Let’s take a look. Contender 1: Muse Glimmer. This is Meta’s newest open weights model, a 30 billion parameter dense model. It’s fast, it’s cheap, and it’s slightly smarter than Claude Haiku. If you have nice…
Summary In today's episode, I explain how to build a blended scoring rubric by combining different stakeholder definitions of quality so AI can balance competing objectives like marketing appeal, technical depth, and legal safety. Here's what this means for you. You'll learn to push stakeholders into quantifying what success looks like rather than relying on…
“Every website AI designs looks the same.” “AI writing all reads the same – ‘that X is the point’ etc.” “AI music sounds so bland.” Yes, of course. A probability engine designed to predict the highest probability is going to converge on the middle of the bell curve. Absent strict guidance about what to do…
Summary In today's episode, I walk through how to build a proactive AI agent that identifies wasted ad spend and redistributes budget without manual prompting. Here's what this means for you. You'll see how documented standard operating procedures become the foundation that lets any agentic system function reliably. You'll also learn these concepts: the 5P…
