Jonathan Pedoeem

6 posts

How to Evaluate LLM Prompts Beyond Simple Use Cases

A common question we get is: "How can I evaluate my LLM application?" Teams often push off this question because there is not a clear answer or tool for them to use to address this challenge. If you're doing classification or something that is programmatic like

Unlocking the Human Tone in AI

I have a confession: I talk to robots. A lot. Not the shiny, sci-fi kind (though I wouldn't say no), but the digital minds behind the chatbots, the writing assistants, the AIs that are weaving themselves into the fabric of our daily lives. And for a long time,

The Prompt Engineering Triangle – the Future of GenAI

In his landmark paper 'A Mathematical Theory of Communication,' Claude Shannon laid the foundation of information theory. In this seminal work, Shannon described the concept of information entropy. Information entropy is the idea that we can measure how much content is in a signal. Shannon then goes on

Prompt Engineering Guide to Summarization

Summarizing information effectively is one of the most powerful ways we can use language models today. But creating a truly impactful summarization agent goes far beyond a simple "summarize this" command. In this guide, we’ll dive into advanced prompt engineering techniques that will turn summarization agents into

Understanding prompt engineering

Imagine chatting with a brilliant friend who knows almost everything and is always ready to help — be it answering a tricky question, summarizing a lengthy article, or generating creative content. Sounds incredible, right? Welcome to the world of Large Language Models (LLMs). These AI models have revolutionized how we interact

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