Blog: https://arjunnagendran.com/blog/building-trust-safety-and-transparency-in-generative-ai-applications

In this episode of Blogged & Amplified, we dig into how autoencoders can help us better understand what’s happening inside Large Language Models. Instead of treating these systems like mysterious black boxes, we explore how autoencoders can surface meaningful activation patterns and connect them to concepts humans can actually interpret.

We also touch on why this work matters — from improving transparency and reducing hallucinations to building the trust and safety needed for AI to be used in serious, high-impact settings.

Whether you’re curious about the inner mechanics of LLMs or looking for practical ways to make these models more explainable, this episode offers a clear, accessible introduction — including a working example you can try yourself on my blog.