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5 Things AI Code Writing Can’t Do in DevOps: Why Human Developers Remain Essential

Written by Miguelito Balba

May 23, 2023

Artificial intelligence (AI) has become an increasingly popular tool for automating repetitive tasks and increasing efficiency across various industries. In the realm of software development, AI is often used to generate code, automate testing, and even deploy applications. 

While AI has certainly made significant strides in this area, there are still some things that only humans can do when it comes to coding and DevOps. This blog post will explore what AI code writing can’t do that only humans can.

1. Expressing Creativity

One of the essential things AI code writing can’t do is exercise creativity. While AI can certainly generate code based on predetermined rules and patterns, it lacks the ability to come up with truly original ideas. This is because creativity is a uniquely human trait influenced by factors such as personal experience, emotions, and intuition.

In DevOps, creativity is essential for tasks such as problem-solving and innovation. For example, if a software application encounters a problem, an AI algorithm may be able to suggest solutions based on previous instances of the same issue. However, a human developer can come up with a completely new and innovative approach that an AI algorithm could not have predicted.

2. Understanding the Big Picture

Another thing AI code writing needs help with is understanding the big picture. While AI can certainly analyze and process vast amounts of data, it cannot comprehend the broader context in which that data exists. This is particularly important in DevOps, where a software application is typically just one part of a more extensive system or ecosystem.

Human developers can consider the larger context of a software application and how it interacts with other systems and stakeholders. This allows them to make decisions that are in the best interest of the entire system rather than just optimizing for a single metric or objective.

3. Empathy

Empathy is another trait that AI code writing can’t replicate. While AI can simulate human conversation and interaction to a certain extent, it cannot truly understand and respond to human emotions. This is particularly important in DevOps, where developers often work with end-users or stakeholders who may have strong emotions or opinions about the software they are using.

Human developers can empathize with end-users and stakeholders and respond to their needs and concerns. This allows them to build software that meets functional requirements and provides a positive user experience.

4. Common Sense

While AI algorithms are becoming increasingly sophisticated, they still lack the common sense humans possess. Common sense is the ability to make practical judgments based on experience and knowledge of the world. This is particularly important in DevOps, where developers often face complex problems that require practical solutions.

Human developers can apply their common sense to find practical solutions to complex problems that AI algorithms may struggle with. This allows them to make decisions that are not only technically sound but also practical and effective.

5. Adaptability

Finally, AI code writing can’t match the adaptability of human developers. While AI algorithms can certainly be programmed to adapt to new situations, they lack the ability to learn and adapt on their own. This is particularly important in DevOps, where the software development landscape constantly evolves.

Human developers are able to adapt to new situations and learn from their experiences. This allows them to stay up-to-date with the latest trends and technologies and make informed decisions about building and deploying software applications.

While AI code writing has undoubtedly made significant progress in recent years, there are still some things that only humans can do when it comes to coding and DevOps. 

Human developers will continue to play a critical role in the future of software development, working collaboratively with AI algorithms to augment human creativity and productivity. 

By leveraging the strengths of AI and human developers, we can build more innovative and efficient software applications that meet functional requirements and provide a positive user experience.

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