To trust ChatGPT’s recommendations, we need to be familiar with the programming language before we start. ChatGPT is the next holy grail, making developers obsolete.
ChatGPT and any LLMs will not make you a genius instantly or increase productivity.
It is dangerous for everyone, and it can be a waste of time to just copy code without thinking. If you add code that you don’t know, it could have unintended consequences that can be detrimental to your live projects, either directly or indirectly.
Top 10 Ways to Improve Coding Skills with ChatGPT
1. Avoid Loss of Context
ChatGPT’s text output limit can easily be bypassed by pressing “continue”.
If “continue” returns an incorrect answer, you might need to go back and correct variable names or rearrange parameters in functions.
If you ask too many questions, a discussion will quickly lose its sense. Each new question only covers a small portion of the previous dialogue.
2. Document your Code
ChatGPT can help you create concise and clear README.md files to support your projects and easy-to-understand documentation for your code. It can create detailed documentation explaining how the code works and giving details about the model.
3. Complete the Code
ChatGPT can help with code completion by asking for ideas and submitting code samples. This opens up the possibility of a variety of problem-solving methods. You may create a feedback loop to provide clarity and insight into certain code lines. This helps you understand the code and gives you insights into possible improvements.
4. Be Aware and Conscious of Your Proprietary Work
ChatGPT is built on a Large Language Model, also known as a Generative Pretrained Transformer. The model’s ability to generate new content is what “generative” refers to. Its fundamental principle is to convert large training data sets into mathematical structures. It then learns the pattern to produce the best possible response for each prompt and iteratively predicts one word at a given time. It is possible that all the work you have put into it could be applied to iterative training.
For forensic purposes, there are certain situations in which it is appropriate to provide code samples. Cross-checking errors in open source code that is already available in the public domain, or code fragments which do not explicitly or implicitly disclose confidential business information.
5. Avoid Ignorance
ChatGPT is capable of producing code but it doesn’t mean that it will work immediately. It is possible to create a simple Django Python project by asking ChatGPT to “Write me an easy Django task list app.” This can sometimes be counterintuitive. You’ll need to do more research about the code in order to make it work properly.
ChatGPT’s creations are not immediately applicable in live production environments if you don’t have the knowledge and the code. ChatGPT is not recommended for people who don’t have a basic understanding of the topic they are seeking ChatGPT’s help with.
6. Requesting Test Cases and Test Plans
ChatGPT can be trusted as a source of inspiration in the area of writing test cases, even though it is sometimes questioned, its accuracy can be maintained. Test cases are not necessary for how your code is executed, ChatGPT is extremely little risk involved You can use the inspiration you get to create better code.
7. Keep Prompts Short and Specific
It is better to keep it short and simple than to make things complicated. Sometimes, complicated suggestions can have the opposite effect. If you give it too many tasks or require a long text response, it may not respond.
It is a good idea to give a short description of the software first before requesting each feature individually, please provide prompts that will work with the preceding code. Once you do this, you can achieve the desired result.
8. Style Your Output
If you add the word “list”, your prompt’s output might change. ChatGPT supports the use of the keyword “markdown” in your prompt. ChatGPT is text-based. As we become more aware of the context awareness of ChatGPT, we may continue to ask for adjustments.
We may also be able to continue this context-aware trip by developing more complex logic based on earlier cues and altering the outcome.
9. Prompting for Coding
ChatGPT can respond to commands as a SQL terminal. It would be better to learn SQL IDEs like DBeaver. This is a good option for testing.
10. Boilerplate the Boring Repeated Productivity Code
Even if you’re an experienced developer, there are certain situations where it is logical to use the tool. For example, boring tasks that require little mental effort.