LLMs and AI agents

Practical guides on structured extraction, LangGraph agents, and automation with language models.

Useful for teams building internal assistants, document automation, data copilots, or tool-using agents.

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Jun 2026 · LLMs & Agents

Structured Data Extraction from Text with LLMs

Use Python, Pydantic, and the Instructor library to extract structured data from unstructured text. Parse invoices and job postings into typed, validated Python objects reliably and at scale.

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Jun 2026 · LLMs & Agents

AI Agents with LangGraph for Data Analysis

Build an autonomous data analysis agent using LangGraph. Learn how agents differ from RAG, and implement the ReAct loop with tools for querying and summarizing data.

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Jan 2026 · LLMs & Agents

How to Build a RAG System with LangChain and Python

Build a Retrieval-Augmented Generation system with LangChain, ChromaDB, and OpenAI. Cover document indexing, MMR-based retrieval, evaluation with RAGAS, and production optimizations like re-ranking and semantic caching.

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Are you building an AI or data platform?

I design and build critical systems end to end: architecture, data, models, and product. If that is the scale you are working at, let us talk.

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