{"type":"rich","version":"1.0","provider_name":"Transistor","provider_url":"https://transistor.fm","author_name":"Machine Learning Tech Brief By HackerNoon","title":"Architecting AI-SDLC: Five Lessons For DevSecFinOps Teams","html":"<iframe width=\"100%\" height=\"180\" frameborder=\"no\" scrolling=\"no\" seamless src=\"https://share.transistor.fm/e/b113a6b3\"></iframe>","width":"100%","height":180,"duration":407,"description":"\n        This story was originally published on HackerNoon at: https://hackernoon.com/architecting-ai-sdlc-five-lessons-for-devsecfinops-teams.\nUsing AI in enterprises is challenging due to issues like cognitive debt, unpredictable token consumption, and the need for strict governance.\nCheck more stories related to machine-learning at: https://hackernoon.com/c/machine-learning.\n            You can also check exclusive content about #ai, #artificial-intelligence, #software-architecture, #devsecops, #devops, #cloud-computing, #sdlc, #ai-sdlc-intelligence,  and more.\nThis story was written by: @krishnaduttpanchagnula. Learn more about this writer by checking @krishnaduttpanchagnula's about page,\n            and for more stories, please visit hackernoon.com.\nUsing AI in enterprises is challenging due to issues like cognitive debt, unpredictable token consumption, and the need for strict governance. To succeed, teams must overhaul their SDLC, prioritize deep comprehension, and implement FinOps, live hooks, and a hierarchical topology to manage AI-induced complexity.","thumbnail_url":"https://img.transistorcdn.com/KyA01h2FD2insgk-wX_xzV6vbJnTNl2BvPYVL-XaI9A/rs:fill:0:0:1/w:400/h:400/q:60/mb:500000/aHR0cHM6Ly9pbWct/dXBsb2FkLXByb2R1/Y3Rpb24udHJhbnNp/c3Rvci5mbS9zaG93/LzQxMjcyLzE2ODM1/ODI0ODgtYXJ0d29y/ay5qcGc.webp","thumbnail_width":300,"thumbnail_height":300}