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The AI Concepts Podcast
by Sheetal ’Shay’ Dhar
Today: #101 in Technology, India on our combined chart.
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Latest episodes
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Module 7: Building an LLM Application End to End
September 12, 2026 · 13 minIn this episode, we bring everything together by following one LLM application from the user's first request to the final response. We see retrieval, context, tools, model calls, state, memory and orchestration working as one system…
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Module 7: Building LLM Applications | LangChain, LangGraph, LlamaIndex and the LLM Application Stack
September 12, 2026 · 8 minIn this episode, we map the modern LLM application stack and explore where frameworks, SDKs, runtimes and protocols actually fit. We look at how tools like LangChain, LangGraph, LlamaIndex, provider SDKs, durable workflows and MCP solve…
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Module 7: Building LLM Applications | State and Memory: How Does an LLM Application Remember?
September 6, 2026 · 13 minThis episode separates two concepts that are often confused: state, which keeps track of what is happening now, and memory, which allows information from the past to become useful later. We explore how applications create continuity around…
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Module 7: Building LLM Applications | What Does Orchestration Actually Mean?
September 6, 2026 · 12 minThis episode breaks down what orchestration actually means, from sequencing and routing to retries, parallel execution and human approvals, and explores the different ways those flows can be managed. Most importantly, we separate…
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Module 7: The LLM Application Loop
August 21, 2026 · 10 minWho actually decides what happens next inside an LLM application? This episode explores the difference between decisions made by code and decisions made by the model, and why real applications often use both. We follow the loop that…
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Module 7: Why Do We Need LLM Frameworks?
August 19, 2026 · 10 minIf LLM applications can be built with regular code and APIs, why do frameworks exist at all? This episode explores what happens as a simple application grows and starts needing retrieval, memory, routing, multiple models, retries and…
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Module 7: Building LLM Applications | What Is an LLM Application, Really?
August 19, 2026 · 11 minWhat actually sits behind an LLM application? This episode takes one simple request and follows it beneath the surface, revealing how the model, application code, APIs, external data and context work together to produce something genuinely…
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Module 6: RAG | Long Context vs RAG - Do You Still Need Retrieval at All
June 12, 2026 · 9 minThis episode closes out Module 6 by tackling the question that has been getting louder since large context windows arrived. If a model can hold hundreds of thousands or even millions of tokens at once, do we still need all the architecture…
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Module 6: RAG | GraphRAG - When Relationships Matter More Than Text
June 10, 2026 · 8 minThis episode addresses the category of questions that vector search fundamentally cannot answer, questions about relationships between things. We explore what a knowledge graph is and why traversing connections between entities requires a…
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Module 6: RAG | Query Transformation - When the Question Is the Bottleneck
June 10, 2026 · 7 minThis episode addresses a retrieval failure that has nothing to do with your index and everything to do with the query itself. We explore the vocabulary gap between how people ask questions and how documents are written, and why even strong…
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Module 6: RAG | Parent-Child Indexing - Search Small, Retrieve Big
June 10, 2026 · 7 minThis episode addresses the fundamental tension between retrieval precision and generation context. We explore why small chunks produce tight embeddings that retrieve well but leave the model without enough surrounding information, and why…
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Module 6: RAG | Reranking - The Second Stage That Gets Retrieval Right
June 10, 2026 · 10 minThis episode addresses the gap between finding candidate chunks and finding the right ones. We explore the bi-encoder bottleneck, why compressing text into a single vector for comparison loses critical nuance, and how cross-encoders fix…
About the show
The AI Concepts Podcast is my attempt to turn the complex world of artificial intelligence into bite-sized, easy-to-digest episodes. Imagine a space where you can pick any AI topic and immediately grasp it, like flipping through an Audio Lexicon - but even better! Using vivid analogies and storytelling, I guide you through intricate ideas, helping you create mental images that stick. Whether you’re a tech enthusiast, business leader, technologist or just curious, my episodes bridge the gap between cutting-edge AI and everyday understanding. Dive in and let your imagination bring these concepts to life!