Oliver Will
Azure AI Foundry for Developers: Open Tools, Scalable Agents, Real Impact
#1about 5 minutes
The unique challenges of modern AI development
AI projects differ from traditional software development due to high uncertainty and the rapid pace of technological change, requiring flexible solutions.
#2about 3 minutes
Moving from monolithic AI to modular agent architectures
Agent-based systems offer a more flexible and scalable alternative to traditional, intertwined AI architectures by adopting a microservices-like approach.
#3about 3 minutes
Exploring the capabilities of Azure AI Foundry
Azure AI Foundry provides a comprehensive platform for building agents with access to thousands of models, content safety features, and an enterprise-grade SDK.
#4about 4 minutes
Orchestrating diverse agents with Semantic Kernel
Semantic Kernel enables the orchestration of agents from different SDKs, including Azure AI, OpenAI, and even low-code platforms like Copilot Studio.
#5about 3 minutes
Reusing agents and ensuring data storage flexibility
Agents can be reused across different applications like chatbots and automations, while Azure offers flexible data backends like AI Search, Postgres, and Redis.
#6about 5 minutes
Automating AI quality evaluation in DevOps pipelines
Azure AI Foundry's evaluation tools can be integrated into DevOps pipelines to automatically test model quality and ensure consistent performance.
#7about 1 minute
Building a solid foundation for flexible AI solutions
Successful and flexible AI systems require a solid foundation built on a robust data platform, governance, observability, and automated evaluation.
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Future outlook on AI agents and open standards
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Extending AI platforms for custom business solutions
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Solving developer challenges with Azure AI Foundry
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