AI as Code Writer — AI as Life Saver
After the emergence of ChatGPT, the landscape of artificial intelligence and programming underwent a significant transformation. Initially met with skepticism and apprehension from some quarters of the programming community, ChatGPT and similar LLMs quickly gained atraction and acceptance due to their remarkable capabilities in generating code and aiding developers in their tasks.
While skeptics continued to insist that LLM’s only produces boilerplate code, developers worldwide, whether junior or senior, had already begun developing code using tools like ChatGPT or Copilot. Despite what the programming gurus might say, the Pandora’s box had been opened.
Perhaps those who vehemently opposed LLM’s ability to write code would feel angered by the sudden loss of the privileges they had held for years. Regardless of the reason, there is no understandable justification for opposing such a powerful tool. In fact, if tools like ChatGPT and Copilot are unable to write code at the level expected today, it is clear that they will do so in the very near future. I will explain the reasons for this in another article.
AI in Action
If you are a programmer and have not tried yet, please just open ChatGPT (or your favorite AI chatbot) and ask it to write some code for you. Or a better way, provide it some piece of your code and tell it what to do with that code. Do not wait miracles but I promise you will get satisfied with the results.
Denying the existence of AI coding assistance is akin to denying the existence of search engines.
Just as search engines have revolutionized information retrieval by providing quick access to vast amounts of data, AI coding assistance tools have transformed the way developers write code by offering intelligent suggestions, automating repetitive tasks, and enhancing productivity. These tools leverage advanced machine learning algorithms to understand code patterns, predict potential errors, and offer contextually relevant recommendations, ultimately empowering developers to write cleaner, more efficient code in less time.
To deny the existence and impact of AI coding assistance is to overlook a fundamental shift in the development landscape, one that promises to reshape the future of software engineering.
AI undeniably reduces the time and effort required by code writers — a fact that is increasingly evident in the development landscape. In certain scenarios, AI is capable of generating code that may surpass what an individual coder could produce independently.
The efficacy of AI in code generation is contingent upon the coding skills of both the developer and the AI tool being utilized.
The effectiveness of AI in code generation hinges on the proficiency of both the developer and the AI tool in use. Contrary to misconceptions, AI is not intended to replace or surpass the coding skills of real developers. Rather, it serves as a powerful ally, refining and amplifying their existing abilities. By leveraging AI tools, developers can streamline routine tasks, receive intelligent suggestions, and identify potential errors, allowing them to allocate more time and energy to tackle complex challenges. In essence, AI complements and enhances developers’ skills, enabling them to focus on higher-level tasks and innovation while ensuring code quality and efficiency. Thus, the true value of AI in coding lies in its ability to empower developers, not overshadow them.
Blaming the tool alone for any perceived shortcomings in output is unfair. Instead, grasping the intricacies of the dynamic interplay between human expertise and AI capabilities is crucial to unlocking the full potential of AI in software development. By recognizing the collaborative nature of this relationship, developers can optimize their utilization of AI tools, effectively leveraging their strengths while mitigating limitations. This nuanced understanding fosters a more productive and harmonious integration of human intelligence and AI technology, ultimately driving innovation and advancing the field of software development.
Now lets do it even more easy for you, let me give you some trick, so far I see ChatGPT is good writting code especialy with Python, Javascript and html languages. Since python is an interpreted language and it is the common language of Data Science, its natural ChatGPT is very good at python. You can freely ask write codes in Python, options are endless. ChatGPT is realy good at html too, thank to its simple structure. Html is script language for web, and ChatGPT is produces advanced results, and reduces time for bulk tasks. For example you can ask ChatGPT to write a comple article with titles and so on, and you can ask to write in html. It will arrange allheaders, paragraphs, bold words, everything for you in html format. After that you can directly place that html code in your website or project. In some AI tools, the AI tool directly produces the html files also, no need to copy paste codes! Nowadays there many no-code html page/elements builders on the web, and that is the reason behind it.
AI as a Life Saver
Let’s reminisce about the early days of Google and other search engines. Back then, when we encountered a software problem we couldn’t solve, seeing how others who had experienced the same issue resolved it was a life saver for us.
Some are concerned about the malicious use of artificial intelligence as well. When I read those concerns, I remember my univesity days.In those days, there were also those who used technology for malicious purposes. When I was in University, we’ve heard about some students who directly outsourced their coding assignments to platforms or individuals whom they found on the internet with search engines. Coding platforms like RentACoder were doing coding assignments for students in return of a little money. I even remember a professor warning us not to waste money on such platforms by saying, “We check those sites, don’t pay for assignments unnecessarily.”
In a very near future, probably, university professors will need to assign coding assignments to their students at levels that Artificial Intelligence cannot easily accomplish.
A similar situation is happening today with AI-powered code writing. In many cases, AI coding assistance is a lifesaver. However, many people still hesitate to trust it, saying things like “AI can’t write code” or “AI shouldn’t write code.” Again and again, you need to undertand that AI will not do your coding task but it will help you, just like tthe search engines are already doing more than 20 years.
Tool Recommendation
When it comes to tool recommendations, there are several options that immediately come to mind, each offering unique benefits to streamline and enhance the coding process.
I think , at the forefront is GitHub CoPilot, since Github is owned buy Microfost, Copilot so. Let have a look at the list and see the most known tools ddeveloped espeialy for Code generation.
Microsoft’s CoPilot: The innovative AI-powered tool that provides intelligent code suggestions and automates repetitive tasks, significantly boosting developer productivity. Remember, Microsoft integrated ChatGPT4 as CoPilot into its product group. You can purchase Copilot for Microsoft 365 licenses. Microsoft also offers a free version for CoPilot. Microsoft recentely upgraded Copilot’s free version to GPT-4 Turbo.
Amazon’s CodeWhisperer: CodeWhisperer stands out for its advanced code analysis capabilities and insightful recommendations, tailored to optimize code quality and efficiency.
Apple’s coding assistant: Apple’s AI-powered coding assistant for Xcode also has generated significant interest within the developer community. It is designed to enhance the coding experience within Apple’s integrated development environment, Xcode, offers intriguing possibilities for streamlining development workflows. Time and practical usage will reveal the true value of Apple’s AI-powered coding assistant for Xcode.
Meta’s V-JEPA: V-JEPA is a virtual assistant developed by Meta (formerly Facebook), powered by advanced natural language processing (NLP) and machine learning algorithms. It is designed to enhance user interactions within Meta’s virtual reality (VR) and augmented reality (AR) platforms, providing personalized assistance and recommendations.
Google’s Gemini 1.5 PRO: Gemini 1.5 PRO is an updated version of Google’s Gemini AI platform, which offers advanced capabilities for data analysis, predictive modeling, and machine learning. It provides tools for building and deploying AI models at scale, with enhanced performance, reliability, and scalability.
Magic Dev’s AI Software Engineer: Magic Dev is launching an AI-powered software engineer tool that automates various aspects of software development, including code generation, debugging, and optimization. It aims to streamline the development process and improve productivity for software engineers.
Devin — The AI software developer: Devin is an AI-powered software developer tool that assists developers in writing code, debugging applications, and optimizing performance. It leverages advanced machine learning algorithms to analyze code patterns, detect errors, and suggest improvements, helping developers build high-quality software more efficiently.
Sourcery is another invaluable tool, offering powerful code generation and refactoring features to expedite development tasks and maintain codebase integrity.
Lastly, Replit Ghostwriter offers a seamless coding experience with its intuitive interface and collaborative features, allowing developers to focus on writing high-quality code without distractions.
Conclusion
All these tools, while diverse in their functionality, share a common goal: empowering developers to write cleaner, more efficient code with ease and confidence.
These are the first tools come to my mind, but remember you can just use copy paste from chatbots to write to some for you as well. Have a nice AI Coding !
