[{"data":1,"prerenderedAt":170},["ShallowReactive",2],{"glossary-page-\u002Fglossary\u002Fai-sdlc":3},{"id":4,"title":5,"body":6,"description":158,"extension":159,"meta":160,"navigation":165,"path":166,"seo":167,"stem":168,"__hash__":169},"docs\u002Fglossary\u002Fai-sdlc.md","AI-SDLC",{"type":7,"value":8,"toc":149},"minimark",[9,15,20,26,29,33,36,61,64,68,71,97,100,104,137,141],[10,11,12],"glossary-title",{},[13,14,5],"p",{},[16,17,19],"h2",{"id":18},"what-is-ai-sdlc","What Is AI-SDLC?",[13,21,22,25],{},[23,24,5],"strong",{}," means applying artificial intelligence across the software development lifecycle, from planning and coding to review, testing, deployment, security, and operational feedback.",[13,27,28],{},"In practice, AI-SDLC is not only about using an AI coding assistant in the IDE. It is about understanding how AI-assisted work moves through the full delivery system and whether it improves speed, quality, reliability, and developer experience.",[16,30,32],{"id":31},"why-ai-sdlc-matters","Why AI-SDLC Matters",[13,34,35],{},"AI can increase coding activity very quickly, but more generated code does not automatically mean better delivery. Engineering leaders need visibility into how AI affects:",[37,38,39,43,46,49,52,55,58],"ul",{},[40,41,42],"li",{},"cycle time and lead time,",[40,44,45],{},"pull request review load,",[40,47,48],{},"rework and code churn,",[40,50,51],{},"defect and vulnerability trends,",[40,53,54],{},"test coverage and CI\u002FCD results,",[40,56,57],{},"developer experience,",[40,59,60],{},"governance and policy exceptions.",[13,62,63],{},"Without AI-SDLC visibility, teams may see higher output while hidden bottlenecks, quality risks, or governance gaps grow elsewhere in the workflow.",[16,65,67],{"id":66},"how-ai-sdlc-is-measured","How AI-SDLC Is Measured",[13,69,70],{},"AI-SDLC maturity is usually measured by connecting AI usage and code-origin signals with delivery, quality, and governance data. Useful signals include:",[37,72,73,76,79,82,85,88,91,94],{},[40,74,75],{},"adoption of AI coding assistants,",[40,77,78],{},"AI-assisted and human-authored code attribution,",[40,80,81],{},"pull request cycle time,",[40,83,84],{},"review pass rates,",[40,86,87],{},"automated test outcomes,",[40,89,90],{},"DORA metrics,",[40,92,93],{},"SPACE-style developer experience signals,",[40,95,96],{},"policy exceptions and approval paths.",[13,98,99],{},"The goal is to measure AI impact across the system, not only AI activity inside the IDE.",[16,101,103],{"id":102},"related-terms","Related Terms",[37,105,106,113,119,125,131],{},[40,107,108],{},[109,110,112],"a",{"href":111},"\u002Fglossary\u002Fai-code-attribution","AI Code Attribution",[40,114,115],{},[109,116,118],{"href":117},"\u002Fglossary\u002Fai-code-generation","AI Code Generation",[40,120,121],{},[109,122,124],{"href":123},"\u002Fglossary\u002Fai-code-completion","AI Code Completion",[40,126,127],{},[109,128,130],{"href":129},"\u002Fglossary\u002Fdora-metrics","DORA Metrics",[40,132,133],{},[109,134,136],{"href":135},"\u002Fglossary\u002Fdeveloper-productivity","Developer Productivity",[16,138,140],{"id":139},"related-assessment","Related Assessment",[13,142,143,144,148],{},"Use the ",[109,145,147],{"href":146},"\u002Fai-sdlc-maturity-assessment","AI-SDLC Maturity & Visibility Assessment"," to evaluate how ready your engineering organization is for AI-assisted delivery.",{"title":150,"searchDepth":151,"depth":151,"links":152},"",2,[153,154,155,156,157],{"id":18,"depth":151,"text":19},{"id":31,"depth":151,"text":32},{"id":66,"depth":151,"text":67},{"id":102,"depth":151,"text":103},{"id":139,"depth":151,"text":140},"AI-SDLC describes a software delivery lifecycle where AI-assisted coding, testing, review, governance, and delivery signals are measured across the full engineering workflow.","md",{"category":161,"tags":162},"A",[5,163,164],"AI-Assisted Development","Engineering Intelligence",true,"\u002Fglossary\u002Fai-sdlc",{"title":5,"description":158},"glossary\u002Fai-sdlc","Kv3ZmBzcVQdJNKlmki3IIMrQEw_oZwDM9l99g_-_EnU",1787144725672]