AI 赋能开发者：软技能的重要性_AI阅读总结 — 包阅AI

What skills do aspiring developers need to acquire? This question has been debated for decades, back to the ’80s and ’90s, when schools focused their curricula on “hard skills” like advanced knowledge of intricate programming languages. As development environments grew more collaborative, employers emphasized hiring versatile developers with soft skills like teamwork and communication and traditional technical chops.

Today, the integration of AI into development environments is reigniting the skills debate yet again. By giving AI a more significant role in the coding process, organizations are placing greater value on hiring “well-rounded” developers who can think, adapt, solve problems, and coax the best solutions from their AI assistants.

Marco Argenti, CIO for Goldman Sachs, recently wrote about the phenomenon in the Harvard Business Review. He argues that engineers should study philosophy to code successfully in the age of AI. Studying philosophy, he argues, helps aspiring developers think clearly and logically about why they’re doing what they’re doing.

Whether developers need to take philosophy classes or not, the reasoning is sound. Generative AI transformed the way we think and work. Unlike in the past, when developers took instructions from a team lead and executed tasks as individual contributors, now they’re outsourcing problem-solving and code generation to AI tools and models. By partnering with GenAI to solve complex problems, developers who were once individual contributors are now becoming team leads in their own right. This new workflow requires developers to elevate their critical-thinking skills and empathy for end-users. No longer can they afford to operate with a superficial understanding of the task at hand. Now, it’s paramount that developers understand the why that is driving their initiative so that they can lead their AI counterparts to the most desirable outcomes.

Understanding the Problem First

In the new world of GenAI, well-rounded developers must fully understand the problem and required outcome before GenAI-assisted problem-solving begins. Their understanding of the problem space must match that of a product manager or end-user. After all, the wrong prompt could result in a response that perpetuates the problem at hand. Give an image generation tool like Dall-E a basic prompt (show me a developer in an office), and follow up with a detailed prompt (show me a developer in an office coding on a laptop in an urban environment with young co-workers). You’ll end up with two completely different pictures.

Key Soft Skills for Developers

What soft skills matter most in the age of AI? Four that stand out are reasoning, curiosity, creativity, and accountability.

Reasoning and Context Matter

One of the most important lessons I learned from a previous boss is that context matters. Suppose you’re trying to convince someone to do something; explaining “the why” is the most important part. It’s what creates linkage and trust. GenAI doesn’t do that on its own. We’re at a point now where GenAI produces a good but not great output. A human touch is still needed to inject that last 20% of work to push the chatbot and iterate.

You have to treat your GenAI like an intern — someone who needs coaching and context so that they can ultimately help you get what you need and learn more about the process along the way. That means your job is to provide the reason and context to convince the AI/intern to do things correctly.

Embrace Curiosity and Exploration

When they use GenAI, developers have to probe for more information continually. They should think of themselves as reporters uncovering facts. Is there anything else I missed? After AI creates a first take, probe further in a second version, making the questions more action-oriented. Think of it as having a conversation with the GPT. If you’re creating content, tell the GenAI to pretend it’s an employee, share three questions an employee would have, and then answer them. Then, have the GPT rework the draft with the answers again. Using this approach while embracing the diversity of thought with your unique skill set and problem-solving abilities will be essential to effectively serve a diverse set of customers.

Creativity in Developer Prompts

GenAI does what it’s told. It culls information from available sources and applies it systematically based on the prompts that it is given. The creativity a developer exercises in delivering those prompts can encourage an AI tool to present coding options that the organization may not have anticipated. Like writers who keep their works fresh by varying their syntax, pacing, and tone, developers can issue directives in different ways to elicit “out-of-the-box” responses.

Accountability in the Age of AI

We’re on the border of an ethical conundrum, and well-rounded developers will be needed to get us through. Just because developers can get GenAI to do something doesn’t mean they should. Developers are now co-creating IP. Who owns the IP? Does the prompt engineer? Does the GenAI tool? If developers write code with a certain tool, do they own that code? In an industry where tool sets are moving so quickly, it varies based on what tool you’re using, what version of the tool, and what different tools within certain vendors even have different rules. Intellectual property rights are evolving. It’s like the wild, wild west. Reasoning through that and understanding the context of what developers should get their tools to do is an important skill.

Conclusion

For top-performing developers, the increasing integration of GenAI into development workflows does not diminish the importance of hard skills. However, for developers who seek to advance their careers and contributions, up-leveling their soft skills like customer empathy and critical thinking will go a long way in making them well-rounded developers in a post-GenAI landscape.

The advancement of developers’ soft skills will not only make them more effective collaborators in the workplace. Still, it will also reinforce their value to organizations exploring leveraging GenAI to achieve new levels of productivity and success.