Best of Daily Dose of Data Science | Avi Chawla | Substack — September 2025

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    Article
    Avatar of dailydoseofdsDaily Dose of Data Science | Avi Chawla | Substack·30w

    The Open-source RAG Stack

    A comprehensive guide to building production-ready RAG systems using open-source tools. Covers the complete technology stack from frontend frameworks to data ingestion, including LLM orchestration tools like LangChain and CrewAI, vector databases like Milvus and Chroma, embedding models, and retrieval systems. Also showcases 9 practical MCP (Model Context Protocol) projects for AI engineers, ranging from local MCP clients to voice agents and financial analysts.

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    Article
    Avatar of dailydoseofdsDaily Dose of Data Science | Avi Chawla | Substack·30w

    Building a Full-stack Agentic App

    AG-UI is an open-source protocol that enables communication between AI agents and frontend interfaces through event-based messaging. The tutorial demonstrates building a stock portfolio agent using CrewAI Flows for the backend and CopilotKit for the frontend, featuring real-time streaming, human-in-the-loop approval, and reactive UI updates. The implementation includes a 5-step workflow covering portfolio initialization, investment parameter extraction, stock data simulation, allocation calculation, and insights generation.

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    Article
    Avatar of dailydoseofdsDaily Dose of Data Science | Avi Chawla | Substack·32w

    8 Key LLM Development Skills for AI Engineers

    Outlines eight essential skills for AI engineers working with Large Language Models in production environments: prompt engineering, context engineering, fine-tuning, RAG systems, agents, deployment, optimization, and observability. Each skill covers practical techniques from crafting structured prompts to implementing monitoring systems, with emphasis on moving beyond basic prompting to building scalable, production-grade LLM applications.

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    Article
    Avatar of dailydoseofdsDaily Dose of Data Science | Avi Chawla | Substack·29w

    Get Free Lifetime Access to Our Premium Resources

    A comprehensive 10-step roadmap for becoming a full-stack AI engineer, covering everything from coding fundamentals and Python basics to advanced topics like LLM APIs, RAG systems, AI agents, production deployment, observability, security, and advanced workflows. The roadmap progresses from beginner concepts to expert-level implementation of production-ready AI systems.

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    Article
    Avatar of dailydoseofdsDaily Dose of Data Science | Avi Chawla | Substack·28w

    ​6 Popular Agentic Design Patterns Used in AI Products!​

    Explores six key agentic design patterns that power modern AI systems: ReAct (reasoning and action), CodeAct (direct code execution), Modern tool use (external API integration), Self-reflection (error correction), Multi-agent workflows (specialized agent collaboration), and Agentic RAG (intelligent data retrieval). Each pattern addresses specific challenges in AI agent development, with real-world examples from companies like CrewAI, Cursor, and Perplexity demonstrating their practical applications.

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