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In this episode of we dive into the emerging discipline of context engineering: the practice of curating and managing the information that AI systems rely on to think, reason, and act.

We unpack why context engineering is becoming important, especially as the use of AI shifts from static chatbots to dynamic, multi-step agents. You'll learn why hallucinations often stem from poor context, not weak models, and how real-world systems like McKinsey's "Lilly" are solving this problem at scale.

From strategies like write, select, compress, and isolate to key challenges around data fragmentation and semantic unification, this episode breaks down how to design smarter, more reliable AI by managing information, not just prompts.

Sources:

• "Beyond Prompts: The Rise of Context Engineering​​" by Rahul Singh
• "The rise of context engineering" by LangChain 
• "Context Engineering is the New Vibe Coding" by Analytics India Magazine
• "Why Context Engineering Matters More Than Prompt Engineering" by TowardsAI