Imagine your lead Software Engineer walks into your office and says, “Good news! I just deployed that critical update to production. I wrote the code on my personal laptop, didn’t run it through CI/CD, skipped the security scan, and just copied the files directly to the server with a USB drive.” You would fire them. …
Listen to a NotebookLM podcast version of the blog: When Anthropic announced Claude Code’s new security scanning capabilities, following the announcement of OpenAI’s Aardvark, it marked an important moment for the industry. For the first time, expert-level security review is becoming embedded directly into the act of writing code. Subtle, context-dependent vulnerabilities can now …
In the AI era, software and new models are being born at a breakneck pace—but they’re also bringing a lot of “baggage” into the world. While AI coding agents are busy accelerating innovation, they’re also excellent at generating a massive byproduct: “digital dust.” Between obsolete releases, orphaned dependencies, and massive model versions, your repository may …
We are witnessing a fundamental transformation in how software is built. The industry has moved beyond the experimental phase of Machine Learning Operations and entered a complex new reality: the era of the AI Software Supply Chain. The adoption metrics confirm this shift is irreversible. Google reports that 90% of tech workers are now using …
It’s well-known that Databricks is a world-class platform for data engineering and ML experimentation. Yet, for most organizations, the challenge isn’t building models; it’s the complex journey from a model in a notebook to a secure, governed, and production-ready application. In this blog, we’ll show you how integrating the JFrog Platform with Databricks bridges that …
When we first introduced the JFrog AI Catalog, it was our mission to provide the industry with a single system of record for governing the complex landscape of internal, open-source, and external commercial AI models. This foundational step was critical for enterprises to move from uncontrolled innovation to delivering AI with trust and confidence. However, …
The entire world of technology is abuzz about AI/ML. It’s arguably the most disruptive technology to society since the smartphone. In fact, Gartner estimates that the number of companies using open-source AI directly will increase tenfold by 2027. While this rapid advance is fueling quantum leaps in innovation, it also ignites increasing scrutiny from regulatory …
The rapid pace of AI innovation is driving new possibilities for every organization. Yet, for many, the journey from inception to reliable, production-ready AI applications is riddled with hidden challenges: proliferation of models, security blind spots, and a desperate need for consistent governance. You want to harness the power of AI, but not at the …
Although listening to music has its moments, repeating the same songs over and over again can get tedious. With so many great podcasts out there though, there’s no reason why you can’t sub out your regular playlist for something a little more educational and insightful while you hit the gym or drive to work. Podcasts …
Organizations are rapidly investing in MLOps to enhance their productivity and create cutting-edge machine learning (ML) models. MLOps helps to streamline the ML lifecycle by automating repeatable tasks and providing best practices to help ML teams collaborate more effectively. As a result of the growth of MLOps in recent years, there has been an explosion …
