How to guide ChatGPT/LLMs to think and reason like salespeople before they write!

A few weeks ago, I hosted an insightful webinar on a critical topic for those exploring the use of Large Language Models (LLMs) like ChatGPT. For those who couldn't join us live or wish to revisit the discussions, here's the full video:

Here's a quick overview of what we covered:

1. LLMs vs. Human Brains: We began by comparing LLMs to human brains, highlighting how LLMs typically respond swiftly to user inputs. This quick response mechanism often leads to less nuanced and inconsistent results, akin to the "System 1" thinking in humans.

2. Encouraging Deeper Thinking: The core focus of our session was on techniques to "slow down" LLMs, essentially triggering a "System 2" mode of thinking. Numerous research studies and practical projects show that this approach can help LLMs reason more accurately, and interestingly outperform humans in various simple reasoning tasks.

3. Advanced Prompting Techniques: We discussed a few prompting techniques that encourage LLMs to think and reason more deeply before responding. This involves explicitly directing the models on how to process information, think aloud, and construct their answers.

4. Multi-Agent Design: An exciting part of our webinar was exploring the Multi-Agent design for LLMs. We examined how to break down complex tasks into smaller, manageable parts and build specialized LLM agents. These agents are designed to excel at specific tasks and collaborate seamlessly to tackle larger, more complex challenges.

5. Live Demos in Personize Studio: We wrapped up with live demonstrations on our Personize Studio platform, where participants could see all the discussed techniques in action, including the multi-agent design.

Your Feedback Matters!

I'm eager to hear your thoughts on the webinar and any insights you might have. Your feedback is invaluable for refining our approach and making our future sessions even more impactful. Feel free to share your views and suggestions.