AI Engineering Day 4: Using Delimiters to Improve LLM Reliability

Welcome to Day 4 of 100 Days of AI Engineering! 🚀

🚀 Join the Community & Get the Challenges: https://www.skool.com/learnwithparam

One of the most common mistakes developers make when calling LLM APIs is "smearing" instructions and data together. In Day 4, I explain why separating these two is the secret to getting perfect summaries and reliable agent behavior.

What you’ll learn today:
🔹 The YouTube Summary Example: Why providing a 1-hour transcript without clear boundaries leads to missed information.
🔹 The Power of Delimiters: How using triple backticks, slashes, or specific headers helps the LLM distinguish between "What to do" and "What to process."
🔹 Small vs. Large Models: Why structured prompts are absolutely crucial when using smaller, faster models for AI agents.
🔹 Architecture Tip: How a simple structural change in your prompt can drastically improve your system's output quality.

Don't let your AI get confused by its own input. Over the next 96 days, we’ll move from these structural basics to building high-scale AI systems. Follow along and upskill!

#aiengineering #100daysofcode #promptengineering #llm #softwareengineering #generativeai #learnwithparam #backenddeveloper #systemdesign #aiagents

Видео AI Engineering Day 4: Using Delimiters to Improve LLM Reliability канала learnwithparam - AI Engineering Society