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How Generative AI Is Making Software Engineers Superhuman

How Generative AI Is Making Software Engineers Superhuman

New mobile apps to keep an eye on

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Questions Raised:

  1. What are the implications of LLMs for software engineers?
  2. How does AI affect the software value chain?
  3. What are the benefits of using generative AI apps?
  4. How can humans and AI work together to complete tasks?

In the past few months, an AI-powered tool called GitHub Copilot has been making waves in the software engineering world for its ability to suggest the next few lines of code for a programmer based upon what they have already written. This technology has immense implications for the software engineering industry, as it has revolutionized the way software engineers think about and code software. It has also opened up the possibility for novice coders to write complex code with limited experience. Together with art app Midjourney, generative AI is helping to make software engineers superhuman.

How Generative AI is Changing the Way Software Engineers Work

Generative AI has fundamentally changed the nature of what software engineers do. Whereas before a software engineer had to remember, search for, or infer all low level functionalities of their program, they can now describe what they would like a snippet of their program to do in plain language, and if it’s within the capacity of the language model, synthesize it from nothing! This has made it incredibly easy to learn a new programming language or write unfamiliar programs with limited experience. With generative AI, no software engineer will be running solo anymore.

The Benefits of Human-AI Complementarity

Generative AI has vastly enhanced a certain layer of the software value chain. Humans are good at reasoning about business logic, but their brains aren’t built to remember an enormous environment of implementation details. As such, generative AI has not only raised the productivity of individual programmers, but created more programmers generally.

The Limitations of Generative AI

Generative AI is quite good at certain parts of the value chain of knowledge work, but it still thinks quite differently from humans. There is still a limit of narrative abstraction to the text prompt after which it loses its grip and starts spitting out nonsense. It’s up to the artist to distill a creative motive, an inspiration, into simpler ideas a machine can understand, and iterate on this. Moreover, the AI may screw up certain details that a human must then go back and fix up.

With generative AI, software engineers are becoming superhuman

Generative AI is revolutionizing the way software engineers work, allowing them to work more efficiently and with more flexibility. However, it still has its limits and requires humans to provide the creative guidance and to fix any mistakes the AI may have made. With generative AI, software engineers are becoming superhuman by having a superhumanly knowledgeable, but idiosyncratic pair programmer built into their tools.

Key Points to Remember:

  1. LLMs can synthesize code from plain language descriptions.
  2. AI can reduce the need for software engineers to remember implementation details.
  3. Generative AI apps can create digital art from text descriptions.