Critical Thinking in an AI Powered World

We will talk about the AI Assistant, its strengths and weaknesses, examples of edge cases, and strategies to get better results from the JetBrains AI Assistant.

View at original site


Author: Khalid Abuhakmeh

JetBrains AI Assistant, which is based on Large Language Models (LLMs). The author explains the strengths and weaknesses of LLMs, such as their ability to summarize text, generate code, and classify information, but also their limitations in terms of timeliness and non-deterministic responses.

Khalid provides strategies for getting better results from the AI Assistant, such as creating custom prompts and clarifying code suggestions. They emphasize the need to be skeptical of the AI Assistant's responses and to verify the results. Khalid concludes by highlighting the combination of artificial intelligence and human expertise in software development, and encourages readers to ask questions and provide comments.

Related Resources

Full Line Code Completion in JetBrains IDEs, All You Need to Know
What is full line code completion is, how does it work, what languages are supported, and how can you get started
Local and Fast AI comes to your developer workflow - Full Line Code Completion
Full line code completion is available for Java, Kotlin, Python, JavaScript, TypeScript, CSS, PHP, Go, and Ruby.
Stop using LLMs for these tasks!
Discover the ins and outs of large language models (LLMs) with Dr. Jodie Burchell.