𝗛𝗼𝘄 𝘁𝗼 𝗰𝗼𝗱𝗲 𝘄𝗶𝘁𝗵 𝗚𝗶𝘁𝗛𝘂𝗯 𝗖𝗼𝗽𝗶𝗹𝗼𝘁?

A recent study by GitHub and Microsoft discovered that AI now authors 46% of new code. They also found that overall developer productivity surged by 55%, leading to more efficient coding processes. When we talk about AI-powered coding, we mainly talk about GitHub Copilot.

But 𝗵𝗼𝘄 𝗚𝗶𝘁𝗛𝘂𝗯 𝗖𝗼𝗽𝗶𝗹𝗼𝘁 𝘄𝗼𝗿𝗸𝘀?

The process goes in the following steps:

𝟭. 𝗦𝗲𝗰𝘂𝗿𝗲 𝗽𝗿𝗼𝗺𝗽𝘁 𝘁𝗿𝗮𝗻𝘀𝗺𝗶𝘀𝘀𝗶𝗼𝗻: Your prompts are securely sent to Copilot, ensuring data privacy.

𝟮. 𝗖𝗼𝗻𝘁𝗲𝘅𝘁𝘂𝗮𝗹 𝘂𝗻𝗱𝗲𝗿𝘀𝘁𝗮𝗻𝗱𝗶𝗻𝗴: Copilot analyzes the code around your cursor, the file type, and other open files to offer relevant suggestions.

𝟯. 𝗖𝗼𝗻𝘁𝗲𝗻𝘁 𝗳𝗶𝗹𝘁𝗲𝗿𝗶𝗻𝗴: It filters out personal data and inappropriate content, focusing solely on generating helpful code.

𝟰. 𝗖𝗼𝗱𝗲 𝗴𝗲𝗻𝗲𝗿𝗮𝘁𝗶𝗼𝗻: Based on the intent identified in your prompts, Copilot crafts code suggestions that align with your coding style and project standards.

𝟱. 𝗨𝘀𝗲𝗿 𝗶𝗻𝘁𝗲𝗿𝗮𝗰𝘁𝗶𝗼𝗻: Here, we can decide whether to use, tweak, or reject Copilot's suggestions.

𝟲. 𝗙𝗲𝗲𝗱𝗯𝗮𝗰𝗸 𝗹𝗼𝗼𝗽: Copilot learns from your interactions, improving its suggestions. Every time you tweak or reject its ideas, he knows from it. It employs techniques like zero-shot (asking without examples), one-shot (asking with an example), and few-shot learning (providing multiple examples) to adapt to our instructions, whether you provide examples or not.

𝟳. 𝗣𝗿𝗼𝗺𝗽𝘁 𝗵𝗶𝘀𝘁𝗼𝗿𝘆 𝗿𝗲𝘁𝗲𝗻𝘁𝗶𝗼𝗻: It remembers past prompts and interactions, making future suggestions more accurate.