In Part 2 of TCLi’s Micro Learning Series, we break down the evolution from machine learning to today’s large language models (LLMs). You’ll learn how ML algorithms make predictions, how LLMs were trained on decades of human knowledge, and why the rise of ChatGPT felt like a “two-year storm.”
This session explains how LLMs became accessible to everyday users, why multiple vendors (ChatGPT, Perplexity, Claude, Grok, Gemini, Co-pilot) exist, and what actually powers them under the hood. Finally, we introduce the TCLI Prompt Compass — a practical framework that measures your prompting skill from Apprentice to Grandmaster.
If you’re trying to understand LLMs clearly, fast, and without hype, this micro learning session gets you there.
Have questions or ideas for future topics? Add them in the comments below.
👉 Continue Your Learning
TCLi Academy — https://tcliacademy.com
TCLi Advisory — https://tcliadvisory.com
CHAPTERS:
00:00 — How Machine Learning Predicts Real-World Outcomes
00:44 — How Large Language Models Emerged from ML
02:27 — The Two-Year “LLM Storm” and Consumerization of AI
04:17 — A Crash Course on Today’s LLM Vendors
05:57 — Moving from Theory to Practical Prompting
06:38 — Introducing the TCLI Prompt Compass (Skill Levels)
#leadershipdevelopment #leadership #leadershipcoaching #executivecoaching #innovationleadership #leadershipstrategies #businessinnovation #organizationaltransformation #changemanagement #aileadership #leadershipskills #aiforbusiness #transformativeleadership #theconsultinglab #tcli #tcliacademy #professional #professionaldevelopment #professionalgrowth #career #careergrowth
source