Is Automation an Existential Threat to Developers?

 

Automation has a long and successful history in the business, not just in DevOps. However, If AI can code, the roles of developers will change. More organizations are increasing Automation across the company, and DevOps is not an exception. Indeed Software teams in development have been automating various kinds of tests for a long time. Modern Automation is spreading to other aspects within the SDLC, as evident by CI/CD pipelines, completely automated from end to end. Nowadays, it's not just about testing more frequently or at an increased scale. Still, it's about speeding up the delivery of value and improving the quality of products, and enhancing DevOps team efficiency at the same time.

Automation poses a threat for Developers, or is it not?

1- Initially, AI will augment developers, but eventually, it could replace many. ML/DL/AI can help automate repetitive tasks, detect mistakes, fix them, and drastically reduce the time required to develop an efficient project. These improvements will significantly boost productivity and reduce a lot of the time developers for a particular project. Automating tasks is becoming simpler to perform than it was. Although automation scripting isn't a forgotten art form, many tools don't require the use of code. There's an appropriate name for test automation: "codeless test automation."

2- In 2017, Microsoft introduced IntelliSense. An artificial intelligence feature added to Visual Studio that enables "autocomplete" capabilities. It can automatically determine what the programmer is typing, similar to Google search. In the last few months, Microsoft introduced a new low-code open-source option known as Power Fx, an extension of Excel. The goal for Power Fx is to enable citizens to develop applications using natural language that's even simpler to create applications that use visual programming. In reality, Power Fx integrated into the Microsoft Power Apps visual low-code environment.

3- Additionally, GitHub and OpenAI launched the technical preview of Copilot, an AI tool that can auto-complete code. "[Copilotcould be able to replace a lot of searching for information on how to remove JSON.' Sites such as Stack Overflow will not be needed often since IDEs such as Visual Studio Code will auto-suggest proficient codes (from what we've observed)," says Joseph Spurrier, CTO of the software company Cloudtamer.io. "ML could become an accelerator for teams working on development. 

4- Another potential is to improve the code already written that is, in essence, finding and fixing logic bugs in a way that is automatic, resulting in less bug-ridden systems in the business and billions to millions of dollars in savings."

5- Therefore, AI isn't an existential threat to developers, at the very least not yet. Be aware that today's AI capabilities may not be as effective as tomorrow's AI capabilities. The line between developers' tasks and what AI does will change. "DevOps demands for skills are so high that I can't notice anything people are concerned about. DevOps automatization is the finest example of human + machine enhancement. Someone needs to be aware of all the pieces in the picture."

The Benefits of Automation:

Improve software quality:

What can be automated in an enterprise and DevOps that is monotonous, boring to be done mannerly, and at a scale that humans cannot manage at the lowest cost? In the case of software development, Automation's primary goal is to improve the speed of release and quality. But, what AI cannot do is create an application from nothing, especially without any context.

Database Design:

You can design databases, create algorithms, and create functions -- all of it, however, when you have to know the user's requirements or the appropriate functional requirements. And the applicable requirements keep evolving."

AI usage in Human-centric context:

As with any other use of AI in a human-centric context, AI is merely assistive. Companies can benefit from both options by separating what AI is proficient in (pattern recognizance) and what humans excel at (creative problem-solving).

Making use of Automation Strategically:

1- When you're creating a feature in the software, and 80percent of your time is spent creating common services features, e.g., cloud infrastructure, but this Stack doesn't provide much difference or value to the user. Advanced features and innovations are about 20%. They are trying to turn this to 20/80 with AI/ML automation. So that developers can focus on advanced features and innovation.

2- Unlike Lenovo programmers configuring and managing the environment on their own, AI handles it by considering the contexts of the developer's behavior and the project in which they work components and the requirements for infrastructure. The software is constantly updating by modeling the environment and then comparing that modeled environment to the real-world environment and then taking proactive action to address problems.

3- I believe that machine learning and AI are incredibly effective technologies. What is the number of wasted dollars on infrastructure we're not using in a virtualized system or a cloud-based environment? What should be the ratio of time-saving if you utilize the model of spinning the machine up to down the device? And security, you can be proactive and predictive in the face of attacks, anomalies, and triggers by automating the shutdown of ports, back doors, etc.

4- Lenovo also created a machine learning model utilized for R&D... They collaborated with Microsoft, Intel, and Amazon to create an environment for modeling devices, trying to anticipate the source of an issue to fix it before the issue is developed.

Wrap It Up:

Machine learning and AI can Machine learning, and AI saves DevOps teams money and time, both of which they require urgently. Today's technology will only improve, which means that AI will be able to take over more tasks previously performed by developers. In the near term, AI will create more time to do the tasks developers are most qualified to do.