Most People Miss This About AI Models
🕓 Read time: ~4 min
Last week, we looked at why it doesn’t matter which brand AI you use - ChatGPT, Claude, or Gemini. What matters way more is the choice of model avaiable within your GenAI.
And that's exactly where I see one of the biggest sources of confusion, even among more seasoned AI users.
Most stick with whatever is set to be the default. Few know there's other models to chose from and even fewer would know which one to chose.
But here's the thing: Not all AI models work the same way. And that’s the focus of this week’s edition.
🔁 Language Models vs. Reasoning Models: What's The Difference?
'Traditional' language models are experts at communication and content creation. They basically predict what comes next in a conversation, making them perfect for drafting content, summarizing research and brainstorming.
Examples:
- Communication and content creation
- Pattern recognition
- Speedy answers and broad knowledge
Reasoning models, on the other hand, are designed to think things through. They break down complex problems, process information step-by-step, and help you reason your way to a decision or strategy.
Examples:
- Analyzing complex business problems
- Structuring plans or workflows
- Diagnosing root causes and evaluating options
Why Does This Matter For You?
Because when you match the right model to the right job, you get much better results and much less frustration. If you’ve ever felt disappointed by an AI’s answer, it may simply be that you used a “language” model for a “reasoning” task (or vice versa).
🎥 See the Difference in Action!
Watch my quick Loom walkthrough: https://www.loom.com/share/5b9f15d608ec443ea6aa7c19151d9f84?sid=9ac2c8d6-e1a2-4b2c-809a-f4ee993fc008
🧪 Or Try This Experiment
- Pick a real business problem or client scenario.
- Use the default model in your GenAI of choice to 'solve' it.
- Open a new chat and select a 'reasoning model'. Feed it the exact same prompt.
- Notice the difference in approach? In output?
- Which model feels more helpful for the job at hand?
Key Takeaway
It’s not the brand of AI that makes the difference. It’s the type of model and how you use it.
Knowing the difference takes you from overwhelmed to in control. And can save you a lot of time!
Til next time, keep experimenting,
Elena
P.S.: Stuck on a specific task and unsure which model to use? Hit reply, let me know what you’re working on, and I’ll get back to you with a personalized recommendation. I'm currently unpluggin or a little digital reset, so responses might take a bit longer than usual.
