Balaji Senthilkumar
@iDeveloper_
Stay hungry, stay foolish! 👨💻💙 Fullstack AI engineer
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Traditional RAG vs. HyDE, visually explained! RAG is great, but it has a major problem: Questions are not semantically similar to their answers. Consider an example where you want to find context similar to "What is ML?" It is likely that "What is AI?" will appear more…
🚨 RAG is dead. Long live Agentic RAG. 2025 isn’t about retrieval or generation anymore it’s about decision-making systems that can think, route, reflect, and correct themselves. Every serious AI builder I know is moving from basic RAG pipelines to Agentic RAG architectures…
Context Engineering in Practice A few common agent design principles have emerged -- offload/reduce/isolate agent context. Here, we cover examples of each across popular agents, including our own open source deepagents harness. 📹: youtu.be/XFCkrYHHfpQ
💰🔧 TokenCrush for LangGraph (Made by the LangChain Community) TokenCrush extension reduces LangGraph application costs by up to 90% while preserving meaning. Integrates with LangGraph to optimize RAG pipelines and production AI apps with minimal code changes. Discover how to…
Excellent walkthrough of how to build a streaming agent in @nextjs using LangChain. Clear explanation of server-sent events, UI streaming, and memory via thread IDs. If you’re evaluating production agent architectures, this is a strong reference implementation. 👇 Watch the…
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Build a Streaming LangChain Agent in Next.js with useStream
New video: Build a streaming @LangChainAI agent in @nextjs using useStream + memory 🚀 You’ll learn: - stream AI replies into your UI with useStream - Minimal API route serving SSE - Add conversation memory via thread id + checkpointer 🎥 Watch now: youtube.com/watch?v=piK5WT……
As we've consolidated our docs and shipped 1.0 versions of LangChain and LangGraph, we also rebuilt Chat LangChain from the ground up — now cleaner, faster, and more accurate. Chat LangChain is a chatbot that answers questions about LangChain resources, including our docs and…
Never give up on your dreams Let’s start the week strong!
Cybercab will become ubiquitous
We just released our complete guide to Context Engineering. (These 6 components are the future of production AI apps) Every developer hits the same wall when building with Large Language Models: the model is brilliant but fundamentally disconnected. It can't access your private…
Langchain middleware (new in 1.0) is a super powerful way to modify the core agent loop We’ll be highlighting different use cases and middleware implementations in this new series from @sydneyrunkle First up: human in the loop!
🎬 Starting TODAY: our new LangChain middleware series! One deep-dive video per day covering @LangChainAI's prebuilt middleware options. 👤 Day 1: Human-in-the-Loop Middleware Use this to require human review of risky tool calls before execution! youtube.com/watch?v=SpfT6-…
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Human in the Loop Middleware (Python)
2023: Prompt engineering is a critical skill 2025: Context engineering is a critical strategy My colleagues just dropped a 41-page guide on context engineering. It covers: • Prompting techniques: Choosing the right words still matters • Query Augmentation & Retrieval: Finding…
💥 Top 50 LLM Interview Questions & Answers 🤖📘 Preparing for an AI / ML / LLM interview? This guide covers everything you need — from basics to advanced concepts ⚡ ✅ Prompt Engineering ✅ Fine-tuning & RAG ✅ Transformer Architecture ✅ Tokenization & Attention ✅…
Our 9-part Python + AI live series in October covered LLMs, embeddings, RAG, vision models, structured outputs, safety, tool-calling, agents and MCP. Grab the recordings, slides, and code from: blog.pamelafox.org/2025/10/watch-…
I finally understand the fundamentals of building real AI agents. This new paper “Fundamentals of Building Autonomous LLM Agents” breaks it down so clearly it feels like a blueprint for digital minds. Turns out, true autonomy isn’t about bigger models. It’s about giving an LLM…
Practice any art. Not to get money and fame, but to experience becoming. To make your soul grow.
All, excited to attend the AI coding summit from @AICodingSummit @GitNationOrg Foundation 🥳 . There’s always more to learn in this AI era 🤓. Looking forward for talks on context engineering, multi agents and other best practices.
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