Structured Output: with_structured_output and When You Still Need a Parser
Free text is unusable in a pipeline. This post covers getting validated objects back with Pydantic, and the narrower cases where an output parser is still the right tool.
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View allModel Inputs in LangChain: Messages, Prompt Templates and Few-Shot Examples
LangChain's first real abstraction is the input side: typed messages, reusable prompt templates, and few-shot examples that teach a model by showing instead of telling.
The OpenAI API Before LangChain: Roles, Temperature, Max Tokens and Streaming
Before reaching for a framework, call the API directly. System, user and assistant roles, a sarcastic chatbot, and what temperature and streaming actually control.
Tokens, Models and Prices: What an LLM Call Actually Costs
Tokens are the unit you are billed in, and they are not words. This post covers tokenization, counting before you send, model tiers, and how the costs really add up.
LangChain v1: What Changed, What Moved, and Why Old Tutorials Break
Most LangChain tutorials online were written before v1 and no longer run. Here is what moved, what landed in langchain-classic, and how to read old code safely.
LangChain Explained: What It Solves, Where It Helps, and What This Series Covers
LangChain is widely used and widely misunderstood. This post explains the problems it actually solves, where it earns its complexity, and what this series will build.
Latest
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AI & Tools
16 min read
Structured Output: with_structured_output and When You Still Need a Parser
Free text is unusable in a pipeline. This post covers getting validated objects back with Pydantic, and the narrower cases where an output parser is still the right tool.
AI & Tools
27 min read
Model Inputs in LangChain: Messages, Prompt Templates and Few-Shot Examples
LangChain's first real abstraction is the input side: typed messages, reusable prompt templates, and few-shot examples that teach a model by showing instead of telling.
AI & Tools
18 min read
The OpenAI API Before LangChain: Roles, Temperature, Max Tokens and Streaming
Before reaching for a framework, call the API directly. System, user and assistant roles, a sarcastic chatbot, and what temperature and streaming actually control.
AI & Tools
8 min read
Tokens, Models and Prices: What an LLM Call Actually Costs
Tokens are the unit you are billed in, and they are not words. This post covers tokenization, counting before you send, model tiers, and how the costs really add up.
AI & Tools
7 min read
LangChain v1: What Changed, What Moved, and Why Old Tutorials Break
Most LangChain tutorials online were written before v1 and no longer run. Here is what moved, what landed in langchain-classic, and how to read old code safely.
AI & Tools
6 min read
LangChain Explained: What It Solves, Where It Helps, and What This Series Covers
LangChain is widely used and widely misunderstood. This post explains the problems it actually solves, where it earns its complexity, and what this series will build.
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Completed
6 posts
LangChain Fundamentals: From the OpenAI API to Your First RAG App
Eight posts taking LangChain from first principles to a working RAG pipeline — token costs, the raw OpenAI API, messages, prompt templates, structured output and LCEL.
Oct 2026 – Oct 2026
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Completed
6 posts
Algorithm Interview 2026: Data Structures — Know Your Tools
Master the 6 data structures that appear in 80% of technical interviews. Each post goes deep on one structure — how it works under the hood, every interview pattern it unlocks, and the exact templates that win offers.
Mar 2026 – Mar 2026
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6 posts
Part 7 — Routing, Hooks, and Build Optimizations (Vite/Webpack)
Learn how to structure routing, master custom hooks, and optimize React builds using Vite and Webpack for production-grade apps.
Jan 2026 – Feb 2026
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Part 0 — Web Fundamentals for Modern Full-Stack
Build a rock-solid foundation in HTML, CSS, JavaScript, and modern tooling to prepare for a professional full-stack journey using React, NestJS, and PostgreSQL.
Nov 2025 – Nov 2025
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