Months of building and shipping AI systems made me realize - one thing that makes agentic workflows work is good old best devops practices.
If you do not have proper tooling, clean (and also well-defined) processes, and ephemeral environments set up, an AI agent cannot run or help you reliably. Be it agentic SDLC, running evals, phased agent rollouts, circuit breakers, database access, or anything else.
Think about what an agent actually needs to do good work. It needs a safe place to run code, a fast feedback loop to know if something broke, and clear boundaries between development, staging, and production.
Most skip this and go straight to “let the agent write and deploy code.” Then they hit weird failures, lose trust in the system (and even AI), and quietly give up on agentic workflows altogether.
The fix is not about AI at all. It is the same old devops discipline that made human engineering teams reliable in the first place.
Good things die hard :)