Post by Ewake

🔍 What We Learned Bringing AI Into Large-Scale Reliability Operations We embedded Ewake into large-scale engineering environments to reduce SRE operational toil, cut through alert noise faster, and strengthen reliability practices across teams. Here are some of the most valuable insights that emerged: 1. AI agents must adapt to existing workflows — not force new ones.  Ewake delivered value quickly by embedding directly into existing observability stacks, CI/CD pipelines, and collaboration channels. Meeting engineers where they already work minimized disruption, reduced toil, and avoided adding cognitive overhead. 2. Imperfect but consistent assistance compounds value over time. Across thousands of real operational interactions in critical production environments, Ewake achieved more than 60% satisfaction among experienced engineers—reinforcing that fast, reliable support, even when not flawless, can meaningfully improve engineering efficiency and reduce day-to-day operational friction at scale. 3. The AI SRE agent is no longer theoretical. When paired with a strong DevOps foundation and humans in the loop, AI agents become practical reliability multipliers—helping reduce MTTR, lower operational load, and scale best practices across complex production environments. If you’re interested in seeing how these insights played out in real operations, you can dive into the full case study here 👇 https://lnkd.in/d7iquwVB