Marcel Scherenberg
Infrastructure as Prompts: Creating Azure Infrastructure with AI Agents
#1about 3 minutes
The challenge of translating business needs to cloud infrastructure
Broad business requests for cloud and AI adoption create a vast and confusing solution space, often leading to choice paralysis for clients.
#2about 4 minutes
Shifting from technology-first to problem-first AI adoption
Instead of starting with AI technology and searching for a problem, the focus should be on defining a business problem first to create real value.
#3about 3 minutes
The slow and complex manual infrastructure deployment workflow
The traditional process for deploying cloud infrastructure involves a slow, iterative cycle between roles like architects, engineers, and SecOps, often taking weeks.
#4about 3 minutes
How AI agents can accelerate infrastructure deployment
AI agents can accelerate the initial deployment phase by translating natural language business requirements into infrastructure code, reducing communication costs and enabling rapid experimentation.
#5about 4 minutes
Designing a multi-agent system for Azure infrastructure
The proposed multi-agent system mirrors real-world roles like cloud architect, engineer, and SecOps, using tools like the Azure CLI and Terraform to automate deployment.
#6about 7 minutes
Live demonstration of deploying Azure resources from a prompt
A live demo showcases how AI agents collaborate to interpret a natural language request, generate and correct Terraform code, validate it for compliance, and prepare it for deployment.
#7about 3 minutes
Key takeaways for implementing AI agent solutions
Focus on creating real-world value by providing agents with the right tools and knowledge, defining a clear scope, and building modular, reusable solutions.
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