Romano Roth
AI-Augmented DevOps with Platform Engineering
#1about 6 minutes
Questioning the current hype cycle around AI development
The current AI trend mirrors the dot-com bubble, with massive investment outpacing real value and leading to unrealistic expectations about replacing developers.
#2about 4 minutes
Building a cybernetic enterprise with platform engineering
The goal is a cybernetic enterprise where processes, organization, and technology operate in a feedback loop, enabled by a platform engineering model that reduces cognitive load on product teams.
#3about 5 minutes
Using the floating platform pattern to integrate tools
The floating platform pattern involves integrating all tools, cloud providers, and DevOps platforms directly without abstraction, treating AI as just another capability exposed to product teams.
#4about 8 minutes
A live demonstration of an internal developer platform
This demo showcases a platform's capabilities, including centralized user management, DevSecOps scanning, AI-powered container analysis, integrated observability, and FinOps dashboards.
#5about 1 minute
Moving from ticket ops to a self-service catalog
The future of development involves moving away from manual ticket-based operations to a fully automated, self-service catalog that provides entire development environments on demand.
#6about 2 minutes
AI-augmented DevOps requires a solid platform foundation
True AI-augmented DevOps is achieved not by chasing hype, but by building a robust internal platform that integrates AI as a governed capability for the entire organization.
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Jobs that call for the skills explored in this talk.

DevOps Engineer for AI, Automation and Data Platforms
regio iT gesellschaft für informationstechnologie mbh
Remote
DevOps
Continuous Integration








Implementing DevOps Solutions and Practices using Cisco Platforms Schulung (DEVOPS)
Incas Gmbh
GIT
Bash
Linux
DevOps
Python
+3