ChatGPT is my Rubber Duck

Not just ChatGPT but Google Bard and other Large Language Models (LLM) are like a rubber duck for programmers because it can help programmers to debug their code by explaining it in plain English. When a programmer is stuck on a bug, they can explain their code to a LLM and the LLM can try to understand the problem and suggest a solution. This can be a very helpful way to debug code, as it can help programmers to see their code from a different perspective and to identify errors that they might have missed.

Rubber duck debugging is a technique where a programmer explains their code to a rubber duck, or any inanimate object, in order to help them to identify and fix bugs. The idea is that by explaining the code out loud, the programmer is forced to think about it in a different way and this can help them to see the problem more clearly.

LLMs can be used for rubber duck debugging in a similar way. By explaining their code to LLMs, programmers can get a second opinion on their code and this can help them to identify and fix bugs. You don't have to send your code to a LLM, remember you are sharing concepts and ideas not propriety code.

Some of the benefits of using LLMs for rubber duck debugging:

• It can help programmers to identify and fix bugs more quickly.
• It can help programmers to improve their code.
• It can help programmers to learn new programming concepts.
• Have some fun and pretend you're Tony Stark talking to Jarvis.

If you are a programmer, I encourage you to try using LLMs for rubber duck debugging. It is a great way to improve your coding skills and to write better code.

At Concured we encourage the use of technology as an aid to development. Why would we not, when we're creating a platform that enables customers to quickly index their content and present personalised recommendation back to their users using the power of AI.