A new role for software managers: Generative AI supervisor

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  A new role for software managers: Generative AI supervisor

Generative AI will become an integral part of software work in the near future, and not just for code generation. According to a recent Gartner analysis, the majority of leaders in the software industry will soon integrate generative AI into their daily work.

By 2025, more than half of the job descriptions for software engineering managers will explicitly require the supervision of generative AI, estimates the consulting firm. It is therefore urgent to extend the function of software manager (often called lead dev) well beyond the limits of application development and maintenance.

Team management, talent management, development and respect for ethics will be part of the supervision of generative AI, according to Gartner analyst Haritha Khandabattu. Generative AI will not replace developers, but it has the ability to automate certain aspects of software engineering,” she adds. Although it “cannot reproduce the creativity, critical thinking and problem-solving abilities that humans possess,” it serves as a force multiplier.

Generative AI is not only a productivity tool for developers

Industry leaders agree that generative AI is not just a productivity tool for developers. It also represents commercial opportunities. “AI projects are not just technology projects,” says John Roese, chief technology officer at Dell Technologies. “Good projects are aligned with the company’s results. AI projects almost inevitably break organizational structures, and these are not technical decisions. Each investment and transition to automation leads to the disappearance of existing jobs and creates new jobs responsible for making this automation work.”

Expect an expansion of the teams in which lead devs participate or that they lead. “AI breakthroughs have given rise to a new level of technical expertise, such as AI specialists and machine learning engineers, who develop and deploy AI algorithms and neural networks,” says Bryan Madden, head of AI marketing at AMD. “AI and its deployment are evolving at a rapid pace. AI projects require a holistic approach to ensure that not only practical and technological factors are taken into account, but that governance, politics and ethics also follow.”

While most AI efforts are led by the CEO, CIO or head of engineering, “employees from different departments should collaborate together, developing internal use cases in order to accelerate product capabilities for customers,” says Naveen Zutshi, Databricks CIO. “The business teams can work with the engineers, those who depend on the CIO and IT, to build internal LLM models that improve the company’s processes in all departments.”

There is an increasing emphasis on learning in context

As a result, the success of AI “will depend on partnerships and collaboration between technology, companies and society,” says Madden. “As AI becomes more ubiquitous in sectors such as healthcare, finance and education, experts will be needed to provide context and information to AI application developers. This knowledge will help to refine the application of AI in the best possible way, for the greatest benefit of their customers”.

According to Mr. Zutshi, there is also an increasing emphasis on prompt engineering or learning in context. “This is a new ability for developers to optimize prompt messages for large language models and create new capabilities for customers.

AI ethics is another area where software engineering managers must take the initiative. They “need to work with an AI ethics committee, or create one, in order to develop guidelines that will help teams responsibly use generative AI tools for design and development,” says Khandabattu. They will have to identify and help “mitigate the ethical risks of any generative AI product developed in-house or purchased from third-party suppliers”.

Recruitment, development and talent management will also be stimulated by generative AI, adds Khandabattu. Generative AI applications can speed up recruitment and hiring tasks, such as analyzing positions and transcribing interview summaries. For example, software managers “may enter a prompt asking for keywords or key phrases related to skills or experience.”In addition to recruitment, generative AI supports the management and development of skills. “This will help software engineering managers rethink roles by identifying skills that can be combined to create new positions and eliminate redundancies.”

Source: “ZDNet.com “

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