Prompt Engineering Tips and Tricks

This article explains what agentic means and what an agentic system is in the context of AI and LLM system development.

This article explains the difference between langchain, langgraph and langsmith and how they relate to each other.

This article will answer the question - why is it important to specify the desired format or structure of the response?

This article explains the difference between generative AI vs AI in general.

--

Generative AI is a subset of Artificial Intelligence (AI) that focuses on creating new content, rather than simply analyzing or interpreting existing data.

AI in general refers to any system that can perform tasks that would normally require human intelligence, such as learning, reasoning, problem-solving, and perception. This encompasses a wide range of technologies, from simple rule-based systems to complex neural networks.

Generative AI specifically uses machine learning models to generate new data, such as text, images, music, or code. It learns patterns from existing data and then uses that knowledge to create something original.

Here's a breakdown of the key differences:

Focus: AI focuses on a broad range of tasks, while generative AI is specifically focused on content creation.   Process: AI can use various techniques, while generative AI often relies on deep learning models.   Output: AI can produce various outputs, while generative AI produces new content.   | Term | Definition | |

This article explains how to force Google Gemini to output JSON.

This article will compare the two most popular LLM development frameworks in 2024. Discussing each of their focus areas, architecture, ease of use and ideal use cases.

This article will delve into the purpose of prompt engineering, explore various prompt types and their applications, and highlight the importance of specificity in obtaining consistent results.

This article introduces Instructo and the purpose of this blog.