Romano Roth

AI-Augmented DevOps with Platform Engineering

AI will not fix your broken processes. Discover the platform engineering foundation you need to build a truly effective, AI-augmented DevOps practice.

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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