Why Chaos Engineering is the Missing Layer for Reliable AI Agents in CI/CD

Question

As we integrate AI agents into our deployment pipelines, we're adding a new layer of complexity—and potential failure. Traditional testing isn't enough. My latest article explores why proactive chaos engineering is essential to build resilience, uncover hidden failures, and ensure our AI-driven systems are truly robust before they reach production.

I'll break down:

• The unique failure modes of AI agents in CI/CD
• How chaos experiments differ from standard testing
• A practical framework to start injecting controlled failure
• The mindset shift from "test to pass" to "experiment to learn"

If you're building, deploying, or scaling autonomous AI systems, this is a critical read.

Read the full article here: https://dev.to/franciscohumarang/why-chaos-engineering-is-the-missing-layer-for-reliable-ai-agents-in-cicd-3mnd