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Avnish Yadav

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Engineering Notes

Practical guides for AI, automation, and product engineering.

Field notes from systems I build: agents, n8n workflows, developer tools, micro-SaaS, and production architecture.

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AI AgentsUnmasking the Black Box: Mastering LangChain Callbacks for Debugging

Avnish Yadav – February 22, 2026 · 8 MIN READ

Unmasking the Black Box: Mastering LangChain Callbacks for Debugging

Master LangChain callbacks to debug AI agents. Learn to build custom handlers, trace execution flows, and fix 'black box' LLM issues.

AI AgentsFrom Notebook to Production: The Definitive Guide to Deploying LangChain Apps

Avnish Yadav – February 22, 2026 · 6 MIN READ

From Notebook to Production: The Definitive Guide to Deploying LangChain Apps

Moving an LLM application from a Jupyter Notebook to a scalable production environment requires more than just wrapping code in Docker. This guide covers architecture, observability, caching, and evaluation strategies for robust LangChain deployments.

AI AgentsLangChain vs. Custom Code: When to Build Your Own LLM Orchestration Layer

Avnish Yadav – February 22, 2026 · 9 MIN READ

LangChain vs. Custom Code: When to Build Your Own LLM Orchestration Layer

Every developer building with LLMs faces the 'build vs. framework' dilemma. I wasted weeks on custom orchestration before switching. Here's my honest breakdown of when LangChain saves you time and when it's overkill.

EngineeringLangChain vs. LlamaIndex vs. Vanilla: The Builder's Stack Selection Matrix

Avnish Yadav – February 21, 2026 · 7 MIN READ

LangChain vs. LlamaIndex vs. Vanilla: The Builder's Stack Selection Matrix

Stop agonizing over the perfect LLM framework. A pragmatic guide comparing LangChain, LlamaIndex, and Vanilla implementations with decision charts and folder structures for shipping production AI apps.