What does it really take to move from a GenAI prototype to a production-ready system? In this episode, AWS AI Engineering Specialist Dennis Traub breaks down the hard truths behind scaling, securing, and monitoring AI systems — and why the future belongs to startups who learn how to productionize AI fast.

What You’ll Learn in This Episode:

Why most GenAI prototypes fail when pushed to production
The role of MCP (Model Context Protocol) in securely connecting AI to APIs
How agentic workflows differ from simple prompt chains
Why observability and cost monitoring are non-negotiable for startups
The AWS Bedrock + Agent Core stack for startups scaling AI in Europe
Counterintuitive lessons: when not to use AI

🚀 Meet Our Sponsor

AWS Startups is a proud sponsor of this week’s episode of Startuprad.io. Visit startups.aws to find out how AWS can help you prove what’s possible in your industry.

The AWS Startups team comprises former founders and CTOs, venture capitalists, angel investors, and mentors ready to help you prove what’s possible.

Since 2013, AWS has supported over 280,000 startups across the globe and provided $7Billion in credits through the AWS Activate program.

Big ideas feel at home on AWS, and with access to cutting-edge technologies like generative AI, you can quickly turn those ideas into marketable products.

Want your own AI-powered assistant? Try Amazon Q.

Want to build your own AI products? Privately customize leading foundation models on Amazon Bedrock.

Want to reduce the cost of AI workloads? AWS Trainium is the silicon you’re looking for.

Whatever your ambitions, you’ve already had the idea, now prove it’s possible on AWS.

Visit aws.amazon.com/startups to get started.

Guest: Dennis Traub, AI Engineering Specialist at AWS
Full Blog Post: https://www.startuprad.io/post/how-startups-can-succeed-at-productionizingai-without-breaking-at-scale
Youtube Full Video: https://youtu.be/UkYwxbM_834
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Productionizing AI: AWS Bedrock, MCP & Agentic Workflows for Startups