Many programmers believe that the current wave of artificial intelligence threatens their survival, but this wave also brings them more opportunities. Kent Beck, an advocate of agile software development, once wrote on Twitter, “I reluctantly tried to write code with AI and found that it could replace 90% of my skills, but it can Let the remaining 10% of my skills amplify a thousand times." Do you agree with this view?
Regarding the use of large models in programming or systems engineering, it is definitely a positive for experienced engineers to increase productivity by leveraging GPT or other large models. However, for novice programmers, relying entirely on large models can cause a series of problems. Because they need to learn how to organize errors, design systems, and structure programs. Programming is not just about writing simple functions, but also about how to design the framework of the code and system to ensure its robustness. Large models are of limited help because of the obvious differences between designing and writing code snippets.
It is recommended that entry-level programmers avoid relying entirely on large models and instead write the code themselves whenever possible, as this helps develop their skills. Due to their lack of experience and expertise, they may have difficulty detecting errors and glitches in large models.
However, for an experienced programmer or systems engineer, the situation is different. They can increase productivity by handling tasks that large models could never accomplish, including high-level work such as code structure, software design, and software architecture, which are the bread and butter of systems engineers.
In agile software development, people emphasize the ability to continuously improve and adapt to changes, rather than relying entirely on skills and knowledge. AI can automate many coding tasks, such as code generation, testing, and code quality analysis, but it cannot replace human creativity and judgment, especially in solving complex problems and designing architectures. AI can help developers become more efficient, giving them more time to focus on innovative and strategic tasks.
As we all know, before software is developed, the application framework needs to be designed, but in reality, the technical team does not invest more energy in architectural design. In addition, architects who play an important role in the software design process are very scarce in the industry. Companies need to spend more financial resources and time to recruit such high-end talents. This has even led to the fact that the architectural design link that should have been the most important in the software development process has been increasingly ignored.
How to solve it? The design concept of emphasis on design, light development and light testing may provide new ideas. This coincides with the product design concept of SoFlu software robot. SoFlu is a software that automatically completes software back-end development, front-end development, testing, and operation and maintenance through human-machine collaboration, helping developers achieve "software development that improves efficiency tenfold."
According to its chief designer Chen Dingwei, SoFlu's software robot integrates a large amount of Internet development experience and implements these experiences into a set of standards through platform tools. Control every process of the software development life cycle through tool standardization and automation. By lowering the technical entry threshold for the software development process, junior engineers can also develop high-quality module functions, shorten the testing and operation and maintenance cycles, and effectively implement the excellent ideas in agile and DevOps.
SoFluThe software robot will also carry out quantitative and standardized transformation of the entire software development process. Standardize the output of each process, automatically produce deliverables through the platform, and unify standards among each process module. With the help of SoFlu software robots, developers can quickly complete the tasks delivered. Even junior engineers can complete basic development work faster than before, so that developers can have more time. And energy is used to think about the application framework design of software, thereby alleviating the scarcity of application architects in the software development industry.
As David Patterson, winner of the 2017 Turing Award and an academician of the National Academy of Engineering, the National Academy of Sciences, and the American Academy of Arts and Sciences, said, "The SoFlu software robot allows programmers to jump out of the basic code, say goodbye to 996, and have more Spend more time thinking about business and architecture to better innovate.”
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