Don’t Build the Thing, Build the Thing That Builds the Thing!



  • Author: Scott Martens
  • Full Title: Don’t Build the Thing, Build the Thing That Builds the Thing!
  • Document Note: Dev-GPT is an AI automation tool that uses OpenAI’s GPT-3.5-turbo or GPT-4 to build microservices. It replaces the traditional software development process with an AI-driven approach that eliminates tickets and scrums, so developers can focus on strategic questions that demand creativity. Dev-GPT generates microservices in minutes, saving time and reducing costs. Companies can bring new services online quickly in response to new needs and market changes.
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  • The focus of software development shifted from building the thing we need, to building the thing that builds the thing we need. The introduction of large language models moved software engineering to a higher level of abstraction (View Highlight)
  • The whole history of programming is a history of rising to higher levels of abstraction, letting software handle more and more of the details. As far back as the 1940s, assembly language abstracted from hand-coded 0’s and 1’s. Early programming languages abstracted from assembly language. Progressively higher-level languages took greater charge of the details that humans previously dealt with directly. (View Highlight)
  • Dev-GPT instantiates three AI agents: • Product Manager: The Product Manager interacts with you to clarify the requirements and make sure even the corner cases are well-defined. • Developer: The refined requirements are then handed over to the Developer agent, which writes code to implement the microservice, writes test cases, and debugs the code until the tests pass. • DevOps: Finally, the DevOps agent deploys the microservice and monitors it. (View Highlight)
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  • The way Dev-GPT uses AI models in programming signals a change of paradigm for software developers. It is a major break from traditional, labor-intensive coding processes. Instead, Dev-GPT deploys the power of the latest large language models to ensure that the microservices generated are robust and efficient (View Highlight)