I Trained My AI. Then the AI Changed.

The AI you’re using today is a totally different beast from the one you used yesterday – and that’s the main takeaway we’re diving into!In this episode, we unpack the hidden mechanics behind those sneaky AI updates that can turn your reliable workflows into a confusing mess overnight. We chat about Heather's enlightening experience, where she realised the AI she’d trained to perfection overnight decided to throw a tantrum and ignore her carefully crafted instructions.It’s a wild ride through the psychological toll of these silent updates, and we’ll explore how to keep your workflow on track amidst the chaos. So, grab a cuppa and settle in as we figure out how to build a resilient practice that won’t crumble with every sneaky tweak the AI developers throw our way!This Deep Dive podcast is AI generated from the Start With AI Newsletter on LinkedIn - linkedin.com/newsletter/start-with-aiThe Details:Navigating the world of AI can sometimes feel like trying to dance with a partner who keeps changing the steps!In our latest episode, we delve into the complexities of AI updates and the resulting chaos they can wreak on our well-oiled machines. Inspired by Heather's experience detailed in the Start with AI newsletter, we explore the emotional and psychological impact of these abrupt changes.One minute, you’re in rhythm with your AI, and the next, it’s like the music has stopped. We’ll share practical strategies for maintaining your sanity and workflow stability, including how to document your processes meticulously and conduct isolated tests when things go awry.Plus, we discuss the importance of distinguishing between capability and dependability in AI tools. After all, you want a trusty sidekick, not a wild card!Chapters:00:07 - The Evolution of AI: What You Need to Know00:41 - The Disorienting Changes in AI Workflows04:34 - Understanding AI Feedback Loops and User Experience09:26 - The Convergence of AI Platforms14:01 - Mastering Calibration: A Practical Approach17:51 - Understanding the Shift in AI Workflows Takeaways:Today's AI is constantly evolving, meaning your reliable tools could change overnight without notice.The silent updates to AI can disrupt workflows, leaving users feeling confused and frustrated.When AI tools stop working, it's essential to step back and reassess the entire system, not just your inputs.Building resilience in your AI workflows involves version control and testing components in isolation.Understanding the distinction between an AI's capabilities and your workflow's reliability is crucial for effective use.Documenting your processes helps maintain clarity and control over your work, even as tools evolve unexpectedly. Links referenced in this episode:linkedin.com/newsletter/start-with-ai Companies mentioned in this episode:Start with AIClaudeAnthropicOpenAIMicrosoft Copilot