Systems | Development | Analytics | API | Testing

Why Fast Analytics Unlocks Smarter Decisions (and AI Readiness)

A few years ago, we looked across many deployments and noticed a pattern: teams would build prototypes, spin up ML pipelines, and then stall. The model’s accuracy dropped. The “aha insights” dried up. The data scientists would get stuck waiting for dashboards to refresh, or data to be cleaned.AI is sexy. It sells. But it doesn’t do itself. The missing piece? Data readiness. Not just fast data.
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Testing AI Code in CI/CD Made Simple for Developers

Generative AI can produce code faster than humans, and developers feel more productive with it integrated into their IDEs. That productivity is only real if CI/CD tests are solid and automated. When not appropriately tested, you may encounter a production issue that you haven't seen before. According to the State of Software Delivery 2025 report, 67% of developers spend more time debugging and resolving security vulnerabilities in code generated by AI. That cancels out the efficient gains that they get from faster AI code generation.

How Microsoft And Snowflake Are Making Open, Interoperable Data Stacks A Reality For The AI Era

Snowflake CEO Sridhar Ramaswamy chats with Microsoft Chairman and CEO Satya Nadella on the market shift toward open, interoperable architectures to enable enterprises to do more with their data. Hear how Microsoft and Snowflake are partnering to help customers build an enterprise-ready data foundation with deeply integrated solutions for migrations, open lakehouses, data sharing and AI.

How AI Agents Actually Call APIs: 5 Common Misconceptions

Ever wondered how AI agents and Large Language Models (LLMs) connect to real-world data and services? It’s not magic—it’s a well-structured process. This video breaks down the five most common misunderstandings about how LLMs call APIs, databases, and other custom tools. We explain the crucial role of the Model Context Protocol (MCP) in creating reliable and powerful AI agents. In this video, we'll cover.

Testing AI with AI: strategies for validating Machine Learning Models

Artificial intelligence is becoming a core part of modern software. From fraud detection to recommendation systems, machine learning models are shaping business outcomes and user experiences. But with this progress comes complexity. Unlike traditional applications, AI systems don’t behave in predictable ways. They adapt, learn, and sometimes make mistakes that are hard to trace.

Snow Report: What's Happening At Snowflake In October

Supercharge your development workflow with Snowflake Workspaces. Find out how it boosts productiivity and enables collaboration in this month's edition of the Snow Report. You'll also find details about this year's Startup Challenge, hosted by Snowflake and the New York Stock Exchange. The grand prize is up to $1,000,000 in investment money. You'll also get all the details about BUILD 2025 as well as information on a host of virtual events, including Startup Demo Day and a workshop titled "Unlocking AI with an Interoperable Data Mesh.".