AI Meat Proxies and Workslop

Someone on your team ran a task through AI and forwarded the output without reviewing it. That person was a Meat Proxy and just generated Workslop. Yuck!

Alane Boyd and Micah Johnson break down these two terms, which sound like they should be in food manufacturing, and describe exactly what can go wrong inside AI-forward companies.

In this episode, you’ll learn:

• How to tell a meat proxy from someone using AI well and why knowing the desired outcome is the whole difference
• What your colleagues actually think when they spot unread AI output, backed by the numbers on trust and credibility
• The tells that give workslop away, from verbose answers to ignored brand guidelines
• Why “train your team” isn’t enough unless you define what the right way to use AI looks like at your company
• How making AI use visible turns a shameful shortcut into a useful handoff
• The one requirement that forces people to read the output before it leaves their desk

If your team is moving fast with AI and you’ve started to notice the quality slipping, this conversation names the problem and gives you several things to change today.