Building Your AI Roadmap as a DevOps Team
Prioritization framework, quick wins vs long-term bets, and how to get leadership buy-in (Day 29)
Senior Cloud, DevOps, MLOps & ML Platform Engineer | Heading Cloud, DevOps & MLOps for start-ups | AWS Container Hero | Educator | Mentor | Teaching Cloud, DevOps & Programming in Simple Way
Prioritization framework, quick wins vs long-term bets, and how to get leadership buy-in (Day 29)
AI-native IDPs, self-healing infrastructure, and what the "AI-augmented SRE" looks like in 2026 (Day 28)
Data residency, model access controls, audit logging, and responsible AI frameworks for teams (Day 27)
Supervisor patterns, parallel execution, agent-to-agent communication — and when NOT to use them (Day 26)
LLM evaluation frameworks, output monitoring with Langfuse/Helicone, drift detection(Day 25)
Semantic caching, request batching, model cascading — techniques to slash AI infra bills (Day 24)
Example: Kubernetes, Terraform, Docker, AWS, MLOps...