riya bansal

Reading list Remember Claude Mythos Preview? Yes, the very AI model that Anthropic had announced earlier this year, one that sent even the governments around the world into a frenzy. The model that found security loopholes in almost any network it was tested on, and was so powerful that had to be kept limited within a very controlled environment of existing Anthropic partners. Well, it has now found its way to a larger pool of users in new forms. Meet Claude Fable 5 and Claude Mythos 5.

We have all been in an emergency where every second matters. Someone’s life is at risk but there you’re panicking. Now, imagine in this situation of distress when a helpline asks you to press numbers on your keypad to connect with the right agent? Pure chaos, right? Here, we just need someone to listen and act immediately instead of passing it on and that too without dropping the call. In this blog, we’ll be solving this huge challenge by building our very own AI Emergency Helpline voice agent.

Reading list Your AI agent works great in testing. Then you ship it, and something kinda breaks. A tool called loops forever, like it never learns. A retrieval step returns garbage and costs spike. You have no idea why, at all. That’s the agent observability problem. And if you’re building with LLMs, you need to solve it before production, not after. This post kinda breaks down three of the most-used observability tools: LangSmith, Langfuse and Arize.