The software industry is collectively hallucinating a familiar fantasy. We visited versions of it in the 2000s with offshoring and again in the 2010s with microservices. Each time, the dream was identical: a silver bullet for developer productivity, a lever managers can pull to make delivery faster, cheaper, and better. Today, that lever is generative AI, and the pitch is seductively simple: If shipping is bottlenecked by writing code, and large language models can write code instantly, then using an LLM means velocity should explode.
JFrog today expanded its Software Supply Chain Platform with a new feature called Shadow AI Detection, designed to give enterprises visibility and control over the often-unmanaged AI models and API calls creeping into their development pipelines.
Almost half of respondents to Ocient's "From Roadmap to Reality" report say that their companies have not experienced meaningful revenue growth from artificial intelligence (AI) investments due to "poor data quality and overtaxed infrastructures." The data analytics firm further found that "security and compliance pressures" are "shaping enterprise deployment strategies that prioritize flexibility and cost savings, driving movement away from the cloud."