AI in Production

Описание: In this episode, we explore what happens when AI leaves the lab and enters real-world production. We examine why most AI projects fail at deployment, how production systems differ fundamentally from research models, and what it takes to operate large language models reliably at scale.
The discussion focuses on the engineering, organizational, and governance challenges of deploying probabilistic systems, along with the emerging architectures that turn LLMs into agents capable of planning, tool use, and autonomous action.
This episode covers:
Why most AI projects fail in productionResearch vs. production AI: reliability, consistency, and scaleBuild vs. buy trade-offs for LLMsHidden costs: prompt drift, prompt engineering, and inferenceEvaluation, monitoring, and governance in real systemsAgent architectures and AI as infrastructure
This episode is part of the Adapticx AI Podcast. Listen via the link provided or search “Adapticx” on Apple Podcasts, Spotify, Amazon Music, or most podcast platforms.
Sources and Further Reading
Additional references and extended material are available at:
https://adapticx.co.uk