Operations | Monitoring | ITSM | DevOps | Cloud

Say hello to AI Chat Detection! And learn how to receive alerts about potentially risky conversations in your child's ChatGPT, Gemini, and Character.AI.

AI coding agents write code faster than your pipeline can catch mistakes. What if the agent could validate against CI before you ever push? In this 5-minute demo, we set up CircleCI's Chunk CLI and run a microbuild using Chunk sidecars, secure Linux microVMs that spin up in ~1 second in your CircleCI account, mirror your working directory (no git push required), and give your agent CI-grade feedback while it's still in context.

If 90% of code is now AI-generated, what happens to the engineers who never had to write it themselves? The ability to review code well, to catch what the LLM missed, depends on mental models that only come from practice. That tension sits at the center of this conversation.

Your schema changed. Did your masking rules keep up? Here’s how Flyway and Test Data Manager can catch gaps and prevent PII exposure in dev and test. Tony and Tonie discuss how Flyway and Redgate Test Data Manager can work together in a CI pipeline to detect schema changes that introduce unmasked sensitive columns, helping teams keep production-derived test data protected as the database evolves.

What is Azure Cost Management and how can it help you control cloud spending? In this complete beginner's guide, Michael Stephenson explains the fundamentals of Azure Cost Management and walks through the core features available in Azure. You'll learn how Azure organizes billing accounts, subscriptions, resource groups, and management groups, and how these structures affect cost tracking and reporting.

The debate about whether AI can write production code is over. Companies are handing work to fleets of agents, and for many, they write most of the code that ships to production. The next challenge is everything that happens once an entire engineering organization runs this way, at full speed. Teams that generate code 10x faster still review it at human speed, and that mismatch is now the constraint. Code ownership is also becoming an issue, as developers learn to trust agentic processes a little too much. When an agent breaks production, who is responsible?