I think an important point has been made here. In the context of long-term platform development and deployment, the coding itself (design, code, and testing) is just one part of the work. Once that’s done and the program/product is deployed, it needs to be maintained and adapted, taking into account that the platform and standards will evolve and change, and that all of this will significantly impact the development team’s ability to maintain and evolve the code if all the upstream work has been done by AI. There are already many examples on GitHub and other sites with pipelines/workflows integrating LLMs and other fairly complex AI architectures that have been designed for specific tasks but operate in very specific environments. Often these pipelines are used by few others because there is no automatic maintenance and no one necessarily wants to take on the maintenance and update work that is necessary to be able to deploy and use these pipelines. submitted by /u/brainquantum
Originally posted by u/brainquantum on r/ArtificialInteligence