As AI automates software development tasks such as writing and testing code, the standard for strong engineers is changing. Amazon Web Services (AWS) stressed that it is important to understand the essence of a problem and explore various solutions rather than obsess over specific technologies or implementation methods.

On Nov. 12, Business Insider reported that Matt Wood (매트 우드), AWS chief AI and technology officer, defined good developers in the AI era as people who focus on the problem itself rather than the solution.

Wood said developers should have greater affection for the problem they are trying to solve than for a particular solution. He added that it is important to review different approaches instead of clinging to a single method.

In the past, software development took a lot of time and money, so it was efficient to pick one solution and focus on it. But as AI reduces the burden of writing code, developers can now test and compare multiple solutions at the same time.

Wood stressed that AI should be used not simply as a coding tool but as a means to understand problems more deeply. He said engineers who do not fixate excessively on a specific implementation method can respond more nimbly to change and work faster.

Amazon is also revamping its developer evaluation criteria in line with these changes. On Oct. 27, Amazon revised its guidelines for the software development engineer role and presented an era of the Renaissance Developer, combining AI with human judgement and expertise.

The new guidelines place more weight on long-term results for customers and companies than on AI usage or code output. They warned that setting AI token use or the number of code changes as performance goals could instead lead to higher costs and greater software complexity.

Developers' roles are also changing. As AI supports repetitive coding and testing, humans can spend more time on complex design reviews and technical judgement.

David Yanacek (데이비드 야나체크), an AWS principal engineer, cited as traits of strong developers being proactive in automating repetitive tasks while also being prudent in putting safeguards in place so AI agents operate safely.

In the AI era, a developer's core competitiveness is emerging as the ability to accurately define the problem to be solved, validate results suggested by AI and choose the best solution, rather than how much code they write.