AI Sheep & AI Lions - how do we stop low-quality AI work from creeping into our teams' output?

AI Sheep Vs AI Lions Podcast Show Notes AI Moment Podcast 25 In this week's mailbag episode, Jonathan and I dive into a question that's on many leaders' minds: How do we stop low-quality AI work from creeping into our teams' output? It’s a challenge I’m seeing more frequently – team members using AI to simply tick a box, rather than to elevate their work, which can lead to a noticeable dip in quality.We had a great chat about shifting this dynamic. A key idea we explored was Jonathan's concept of 'AI Sheep' versus 'AI Lions'. Are we passively accepting what AI gives us, or are we actively using it to challenge our ideas and become better at what we do?Our discussion centred on practical steps to encourage the 'lion' mindset. We believe it starts with creating a solid framework. This includes developing an AI manifesto with clear guardrails, establishing an AI style guide with best-practice examples, and building a library of high-quality prompts for common tasks. It's not about policing AI use, but about setting a clear standard for excellence.We also touched on a simple yet powerful habit: the 'two Vs' – always validate the output and verify the sources. This builds a crucial layer of accountability.Ultimately, our core takeaway was this: you own your output. No matter what tools you use, the work that leaves your desk is a reflection of you. It’s about taking pride in what you produce and always being the essential "human in the loop." We need to foster a culture where AI is seen as a collaborator that helps us think deeper and produce better work, not a shortcut that compromises quality.Got Questions?Want to go deeper on our newsletter that supports each and every episode at ⁠⁠dannydenhard.com/aipod⁠⁠Got questions contact us on [email protected] or via our site ⁠dannydenhard.com/aipodConnect With Us On LinkedInDanny on LinkedIn - https://www.linkedin.com/in/dannydenhard/Jonathan on LinkedIn - https://www.linkedin.com/in/wagstaffe/