As AI reshapes the software development lifecycle (SDLC), platform teams are facing a double challenge: they must integrate AI-native capabilities to stay competitive while simultaneously building specialized "platforms for AI" to host complex data and ML workloads.
This new course from Mallory bridges that gap, teaching you how to move beyond simple automation into the era of agentic platforms and AI-driven operations.
Why platform teams need AI training now
According to our research, 86% of practitioners report that platform engineering is essential to realizing AI's business value.
The shift is twofold. First, there is the AI-enhanced platform: using AI to accelerate builds, enable self-healing CI/CD, and move from "dashboard staring" to conversational observability. Second, there is the platform for AI: designing reference architectures that can handle the specific compute, compliance, and FinOps requirements of model training and high-availability inference.
As AI workloads move from experimental notebooks to enterprise production, platform engineers are the ones tasked with managing GPU resources, monitoring model drift, and securing the AI supply chain.
What makes this course different
The course spans eight modules, moving from the "trust paradox" of AI adoption to the future of the platform engineering role. Unlike generic AI courses, this is built specifically for the platform engineering community.
Module highlights include:
- The dawn of AI-native platforms: Navigating the shift from manual configuration to AI orchestration and governance
- Agentic coding: Moving from simple coding assistants to multi-agent workflows for autonomous software reviews
- Conversational observability: Democratizing access to system health through natural language interfaces
- Platforms for AI workloads: Managing specialized compute (GPUs/TPUs) and balancing training vs. inference requirements
- AI reference architectures: Blueprints for modern AI/Data platforms with a focus on compliance and rigorous model provenance
Who should take this course
This course is designed for three groups looking to future-proof their careers:
- Practitioners (DevOps & SREs): Those who want to integrate AI into their workflows, automate complex tasks, and move into AI-native engineering environments
- Platform Engineers: Individual contributors looking to build next-gen AI platforms and manage AI/ML workloads at scale
- Leaders (Heads of Platform Engineering, Team Leads, Directors, etc.): Those tasked with driving AI transformation strategies and managing the architectural shifts toward AI-native setups
How this fits into your learning path
AI in Platform Engineering is a specialized domain course within the Platform Engineering University ecosystem. Whether you are already a Certified Practitioner, Professional, Leader or pursuing your Architect certification, this course provides the deep-dive expertise needed to handle the fastest-growing segment of the industry.
Getting started
The first cohort kicks off on April 2nd. The course is delivered via self-paced modules, and live Q&A sessions.
Enroll in AI in Platform Engineering today and start building the platforms of the future. See you there!
