{"id":876,"date":"2023-04-18T13:49:00","date_gmt":"2023-04-18T11:49:00","guid":{"rendered":"https:\/\/itsonix.laolaweb.com\/?p=876"},"modified":"2026-05-18T09:00:20","modified_gmt":"2026-05-18T07:00:20","slug":"help-me-ai-is-taking-my-job","status":"publish","type":"post","link":"https:\/\/itsonix.eu\/en\/blog\/help-me-ai-is-taking-my-job\/","title":{"rendered":"Help me\u2014AI is taking my job!"},"content":{"rendered":"

Artificial intelligence (AI) is increasingly influencing our daily lives. Speech recognition and translation, virtual assistants such as Siri and Alexa, self-driving cars, and even medical diagnoses and treatments are benefiting from advances in AI research. AI is also becoming increasingly important in software development, as it can help us work faster and more efficiently. I\u2019d like to take a look with you at how AI can be used for code generation, automated testing, and much more. Let\u2019s dive into the world of artificial intelligence and learn how it can revolutionize work in the field of software development.<\/p>\n\n\n\n

You may have already guessed it. ChatGPT wrote this paragraph for us, and the result is quite impressive. Admittedly, this kind of opening is unlikely to elicit much more than a wry smile these days, but back in early 2022, the quality of this AI output would certainly have left many people in a state of incredulous amazement.<\/p>\n\n\n\n

But let's put aside this first attempt to impress ChatGPT and instead try starting off the old-fashioned way\u2014with a joke. So, ChatGPT, please generate a joke about how AI will change software development in the future.<\/p>\n\n\n\n

Why won't developers get tired anymore in the future? Because AI systems will take over all the repetitive work, while developers sit back and watch them improve the programs!<\/em><\/p>\n\n\n\n

While the comedy industry seems safe from ChatGPT for the time being, some software developers may already be worrying about their future. However, based on the current state of development, AI tools will not be able to build complex, secure, and high-quality software systems without human assistance in the foreseeable future. That said, anyone who persistently refuses to work with AI tools such as ChatGPT or GitHub Copilot may quickly fall behind the competition in terms of speed and efficiency.<\/p>\n\n\n\n

In case there are actually still people who aren't familiar with ChatGPT, we've summarized the most important facts here:<\/h5>\n\n\n\n

On November 30, 2022, the American company OpenAI released the ChatGPT chatbot. Because of its ability to understand natural language contextually and respond in natural language based on vast amounts of data, many researchers see this as the beginning of disruptive changes in countless industries. However, it remains to be seen how quickly and to what extent these changes will occur. One thing is certain, though: ChatGPT has sparked great interest. Microsoft, OpenAI\u2019s largest investor, has also equipped its Bing search engine with a chatbot based on the same model as ChatGPT. It is noteworthy that these chatbots were also trained on code and are therefore capable of generating and understanding code.<\/p>\n\n\n\n

OpenAI and Microsoft also play an important role in the second AI tool we\u2019ll be focusing on here: GitHub Copilot. Unlike ChatGPT, this tool was specifically trained and developed for coding. Copilot is based on the OpenAI model Codex, and GitHub (part of the Microsoft empire) released this AI assistant on June 21, 2022, and has since gained well over a million active users.<\/p>\n\n\n\n

Useful Helpers<\/h3>\n\n\n\n

In the following, we\u2019d like to take a closer look at the use cases where AI tools can provide valuable support in coding. The most obvious scenario is probably wanting to program something and having an AI generate the code for you. The clearer or more general the task is, the higher the chances that this approach will succeed. Every program consists largely of code that a large number of people have already written in this or a similar form. And this is precisely where the strengths of generative AI tools lie. They can adapt this code to the specific context and make it available. Thanks to their vast knowledge base and the context contributed by users, this task falls squarely within their core competency. An example of this could be removing unexpected blank lines from a CSV file. A precise question to ChatGPT is all it takes, and executable code is returned as the answer.<\/p>\n\n\n\n

\"\" Source: ChatGPT<\/a><\/p>\n\n\n\n

\"\" Source: GitHub Copilot<\/a><\/p>\n\n\n\n

However, the same principle applies here as it did before the AI revolution: If there is a suitable software library that can solve the problem at hand, we recommend using it. When in doubt, the code is maintained there, and any potential security vulnerabilities are patched. Sometimes, however, it\u2019s worth taking a shortcut and using AI tools\u2014especially when, for example, boilerplate code needs to be written.<\/p>\n\n\n\n

Boilerplate code refers to those sections of code that do not actually solve the core problem and are often copied from existing code and adapted to ensure smooth functionality. These sections are often similar across different projects. Modern programming languages and frameworks are designed to minimize boilerplate code. Nevertheless, this code cannot be completely avoided, and this is precisely where the use of AI tools can significantly help reduce the workload.<\/p>\n\n\n\n

Another use case\u2014for example, from the Java Spring ecosystem\u2014could involve securing requests to an application. Software developers with experience in Spring Security know all too well that there is a lot of boilerplate code in this area that has to be searched for and copied over and over again. This task could just as easily be outsourced, with the initial design generated by an AI tool.<\/p>\n\n\n\n

Of course, the greatest possible synergy is achieved when the AI tool is integrated directly into the development environment, as is the case with GitHub Copilot, for example, but IDE plugins are already available for ChatGPT as well. All you have to do is enter the name of the method, and Copilot promptly provides suggestions on how to implement it. When given comments in natural language, Copilot attempts to implement the logic described in them. Anyone who hasn\u2019t yet tried this or similar AI tools should be prepared for some truly impressive results.<\/p>\n\n\n\n

AI tools are also particularly useful when you want to explore a new programming language or framework. Every beginning is difficult, but it\u2019s a little easier when you can take those first steps with AI code completion. GitHub Copilot is often described by its users as autocomplete on steroids\u2014a phrase that\u2019s quite apt. Once you\u2019ve gotten used to the Copilot rocket, any standard autocomplete feels like a horse-drawn carriage by comparison.<\/p>\n\n\n\n

Other aspects that might not immediately come to mind in connection with AI tools are automated testing and documentation. It\u2019s always surprising how much time is spent on test automation during development\u2014and usually for one reason: Tests ensure stability and a low error rate, even as the product continues to grow. Unit tests in particular (tests of small, self-contained logical units) consistently prove to be especially time-consuming, since dependencies on other parts of the program must be simulated (mocking).<\/p>\n\n\n\n

If you send the code you want to test to ChatGPT, it can generate an initial template for a unit test. As a rule, the result won\u2019t immediately look exactly the way you want it to. However, depending on the complexity of the method being tested, it can be significantly faster to adapt this AI template than to write everything from scratch. The process works similarly with documentation. By asking for appropriate documentation, you send the code to the AI tool and receive an initial result in response. Usually, the AI tool also adheres to the formatting conventions of the relevant programming language. Often, you can achieve a satisfactory result more quickly on this basis than if you were working without any template at all.<\/p>\n\n\n\n

When using ChatGPT, it is essential to carefully consider what code you share with the AI system via the web application. OpenAI\u2019s current Terms of Service state that inputs to ChatGPT are visible to OpenAI employees. Sensitive information and critical code segments should therefore not be shared with ChatGPT without reservation. For the GPT API, on the other hand\u2014which is also provided by OpenAI\u2014the principle applies that the content is not stored in a way that is accessible to OpenAI. As a company, you should therefore consider whether to offer your own internal version of ChatGPT\u2014for example, via the API\u2014to safely increase productivity in software development.<\/p>\n\n\n\n

By the way, AI tools are also great for research when you want to get an initial overview. With ChatGPT, for example, you can not only find relevant literature recommendations on a specific topic but also generate summaries of entire books.<\/p>\n\n\n\n

Focus on the Core of the Problem<\/h3>\n\n\n\n

As a general rule, code written by AI tools should always be reviewed. The generated code may contain errors or be slow, and it may also contain security vulnerabilities. Even code that works should not be accepted without question, but only if it is understood and is the best possible solution to the actual problem.<\/p>\n\n\n\n

\"\"<\/figure>\n\n\n\n

As impressive as generative AI tools may be, these models do not yet have the ability to examine causal relationships and ensure the accuracy or functionality of the output. In the foreseeable future, however, it is very likely that AI tools will be developed that can automatically execute and test generated code. Even then, however, there is no guarantee that this code will actually meet specific requirements. Therefore, we recommend verifying and understanding every solution before implementing it.<\/p>\n\n\n\n

Anyone who explores current AI tools will quickly realize that they can be very helpful in key aspects of software development. However, their use is limited in those areas that stakeholders value most highly or that are decisive for awarding a contract. The core functionality and unique features of a program\u2014or the very reason why something needs to be programmed in the first place rather than simply using an existing product\u2014are difficult to delegate to an AI tool.<\/p>\n\n\n\n

The closer you get to the core logic of the code, the less helpful AI tools generally become. ChatGPT will rarely provide an answer for a creative solution\u2014such as shaving a few milliseconds off complex processes. And even though user-friendly interfaces can currently be generated by AI tools, truly innovative designs still require people to give them that special touch. Software is created by people using these tools\u2014not the other way around.<\/p>\n\n\n\n

Things may be different in a few years, but for now, software development is still best left in human hands. However, AI tools can be a huge help in automating repetitive and time-consuming programming tasks. This allows developers to focus on more exciting tasks and handle the rest more efficiently\u2014an advantage that shouldn\u2019t be underestimated.<\/p>\n\n\n\n

We\u2019d like to conclude our blog post on the potential applications of AI tools in software development\u2014just as we began it\u2014with ChatGPT. We asked the tool to summarize in one sentence what it thinks of all this:<\/p>\n\n\n\n

AI tools optimize software development, but human creativity and critical thinking remain indispensable for top-notch solutions<\/em>.<\/p>","protected":false},"excerpt":{"rendered":"

K\u00fcnstliche Intelligenz (KI) beeinflusst zunehmend unser t\u00e4gliches Leben. Spracherkennung und -\u00fcbersetzung, virtuelle Assistenten wie Siri und Alexa, selbstfahrende Autos und sogar medizinische Diagnosen und Behandlungen profitieren von den Fortschritten in der KI-Forschung. In der Softwareentwicklung wird KI ebenfalls immer wichtiger, da sie dabei helfen kann, schneller und effizienter zu arbeiten. Ich m\u00f6chte mit euch einen […]<\/p>\n","protected":false},"author":4,"featured_media":880,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"footnotes":""},"categories":[5],"tags":[],"class_list":["post-876","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-softwareentwicklung"],"acf":[],"yoast_head":"\nHelp me, AI is taking my job! | IT Sonix - Ihr Partner f\u00fcr individuelle Softwarel\u00f6sungen<\/title>\n<meta name=\"description\" content=\"IT Sonix Blog: Help me, AI is taking my job!\" \/>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/itsonix.eu\/en\/blog\/help-me-ai-is-taking-my-job\/\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Help me, AI is taking my job! 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