How to Combine LLMs for Your Breakthrough AI Learning Stack
A cognitive science approach on when to use ChatGPT, Claude, Qwen, DeepSeek, Gemini or Grok.
What if you could have a personal team of AI tutors, each specializing in a different aspect of learning? One breaking down complex ideas, another fact-checking through the latest research, and yet another providing vocal feedback on your performance.
This guide shows you how to match each model's unique capabilities to specific learning processes—creating a personalized system that's greater than the sum of its parts.
Caveat: I’ve researched this over the past week and am publishing it on March 10. AI moves fast—new releases, little documentation. I might get things wrong, or you might disagree (please let me know in the comments!).
🔎 Overview
For this research, I focused on the latest releases of the below LLMs:
I did not include Perplexity AI—not because it’s bad (I use it daily), but because it’s not an LLM. Perplexity acts more like a supercharged Google search, using multiple LLMs to find answers.
Here’s a breakdown of each category—so you can confidently choose the right AI for your needs. By the end, you’ll be LLM-literate and know exactly which model to use (plus, I’ll share specific examples you can apply right away).