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Greg Radzio on Building Production AI Agents That Deliver Business Results
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About this episode
Building an AI agent is relatively easy. Building one that is reliable, secure, measurable, and useful in a large company is much harder.
In this episode of the AI Master Podcast, I talk with Greg Radzio, who has spent almost two years designing and deploying AI agents for real business projects, including a large enterprise platform.
We examine the complete path from identifying a business problem to running an agent in production. Greg explains why improving the speed of individual employees does not automatically improve the performance of the whole organization.
We discuss:
✅ How an AI agent differs from a chatbot
✅ How to select a business process that is suitable for automation
✅ Why many AI projects remain proofs of concept
✅ The architecture of a production AI agent
✅ Models, tools, context, memory, and orchestration
✅ The role of an agent harness
✅ Testing systems that can return different results for the same input
✅ Evaluations, quality metrics, and business KPIs
✅ Preventing hallucinations and low-quality output
✅ Permissions, data access, and security boundaries
✅ Human approval for important operations
✅ Logging, tracing, monitoring, and incident handling
✅ The difference between a local coding assistant and a production agent
✅ How to introduce agents without automating a broken process
✅ What a company should achieve during its first 90 days
We also consider a fundamental question: can AI repair an inefficient business process, or will it only make that process fail faster?
At the end, Greg explains what developers, technical leaders, and business teams should understand before giving an AI agent access to company systems, code, and data.
Greg will continue this topic at AI Poland 2026.
Join us at our 2026 conferences:
🔴 NG Poland: https://ng-poland.pl
🟡 JS Poland: https://js-poland.pl
🟣 AI Poland: https://ai-poland.pl
A special thank you to Michał Łukawski and the entire SYZYGY team.
SYZYGY is the official partner of this episode. Thank you for supporting the AI Master Podcast and helping us create valuable technical conversations for the community! 🙏
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