Autonomous AI agents can write code, debug issues, and ship features. Here's what actually works, what doesn't, and how to give agents the context they need.
DevSecOps is shifting from rule-based scanning to AI-powered analysis. Here's what actually works when securing modern codebases at scale.
Enterprise orchestration platforms promise unified workflows but ignore the code underneath. Here's why context matters more than coordination.
CrewAI makes multi-agent systems accessible, but real implementation hits friction fast. Here's what you'll actually encounter building your first agents.
Model version control isn't just git tags. Learn what actually works for ML teams shipping fast—from artifact tracking to deployment automation.
Git won't save you when your production model breaks. Here's how to actually version AI models and the code that depends on them — with automation that works.