In the previous two posts of this series, I shared my experiences with using ChatGPT to create a coding project, which involved some ups and downs. It took 78 prompts and a total of 350 lines of prompts to create a 118-line Typescript project. Moreover, the process took four times longer than coding it by hand. Nevertheless, this was only the beginning of my exploration of the potential of Large Language Models (LLMs) in programming.
Read MoreAuthor: Johannes Neubauer
The ChatGPT Programming Experience: A Second Attempt
Welcome back to my series on using ChatGPT for programming (written with help of ChatGPT)! In this second installment, I’ll share my experiences using ChatGPT to build a small software project.
Here you can find the chats: https://github.com/juangamnik/chatgpt-schedule/tree/main/chatgpt
I set out with the premise that I would not write more than a few lines of code, leaving most of the work to ChatGPT. Let’s dive into the numbers, the areas where ChatGPT slowed me down, and the moments where it truly shined.
Read MoreLarge Language Models, GPT, and I
This is the first blog post in a row that describes my first experiences with ChatGPT as a pair programmer and assistant for a developer. As you will see, these experiences had some ups and some downs, but all in all – spoiler alert – on the one hand is the advancement in A[G]I (Artificial [General] Intelligence) especially in regard of NLP (Natural Language Processing) using LLM (Large Language Models) and GPT (Generative Pre-trained Transformers) very impressive. On the other hand I had to revise some of the observations (and criticism) I made, just weeks later, since the pace of evolution in the AI scene is so freaking high.
So these are the blog posts of this series:
- This post
- The ChatGPT Programming Experience: A Second Attempt
- The Evolution of Large Language Models in Programming: A Broader Perspective
But let’s start at the beginning (the following text has been created with help of GPT-4)…
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