Taking your AI application from concept to production

I was recently invited to present at the Microsoft Reactor on what you should consider when taking your Generative AI apps from proof-of-concept to production. This post goes into a bit more detail and provides useful links for content from the talk.

The main content for this post is coming soon, but in the meantime, here are the useful links!

Useful links

• Sample Architecture

Lifecycle management

• Semantic Kernel
• Prompt Flow
• LLMOps vs MLOps

Behaviour and accuracy

• System Message templates
• Advanced Prompt engineering
• Content Credentials
• GraphRAG

Security

• Red team testing
• Content filtering
• AI Jailbreaks
• Building safer chatbots with Azure OpenAI Service

Performance

• API Management proxying
• Performance and latency
• Provisioned throughput
• Kubernetes AI Toolchain Operator - KAITO

Happy Days!

😎