---
title: "Yash Prashant Sonawane (@yash12991) | Hashnode"
description: "Yash Prashant Sonawane (@yash12991) writes on Hashnode. Read their latest articles and follow their work."
url: "https://hashnode.com/@yash12991"
---

@yash12991

# Yash Prashant Sonawane

@yash12991 · Joined August 2025

### [🧠 Agentic AI: Agents & Tools Explained](https://agenticaiforeverone.hashnode.dev/agentic-ai-agents-and-tools-explained?utm_source=hashnode&utm_medium=feed)

The AI world is moving from static chatbots to dynamic, tool-using agents. Instead of just answering with text, Agentic AI can take actions—query a database, schedule meetings, run code, or even chain multiple tools together to solve complex problems...

4 min read · [agenticaiforeverone.hashnode.dev](https://agenticaiforeverone.hashnode.dev/agentic-ai-agents-and-tools-explained?utm_source=hashnode&utm_medium=feed)

[Aug 31, 2025](https://hashnode.com/posts/agentic-ai-agents-and-tools-explained/68b465287d43e3cf384fe8b7)

### [Advanced RAG Patterns & Production Pipelines](https://ragpipelinesforeveryone.hashnode.dev/advanced-rag-patterns-and-production-pipelines?utm_source=hashnode&utm_medium=feed)

Retrieval-Augmented Generation (RAG) pairs a retriever (finds evidence) with a generator (LLM that writes the answer). Basic RAG works, but at scale you’ll hit accuracy, speed, and maintenance limits. This guide distills the advanced patterns you can...

6 min read · [ragpipelinesforeveryone.hashnode.dev](https://ragpipelinesforeveryone.hashnode.dev/advanced-rag-patterns-and-production-pipelines?utm_source=hashnode&utm_medium=feed)

[Aug 31, 2025](https://hashnode.com/posts/advanced-rag-patterns-and-production-pipelines/68b463bc76b31fe579650c9b)

### [🔍 Retrieval-Augmented Generation (RAG): A Complete Guide](https://ragbasics.hashnode.dev/retrieval-augmented-generation-rag-a-complete-guide?utm_source=hashnode&utm_medium=feed)

1\. What it is Retrieval-Augmented Generation (RAG) is an advanced AI framework that combines retrievers (for fetching knowledge) with generators (for producing natural language responses). Instead of relying only on pre-trained knowledge, RAG can pul...

2 min read · [ragbasics.hashnode.dev](https://ragbasics.hashnode.dev/retrieval-augmented-generation-rag-a-complete-guide?utm_source=hashnode&utm_medium=feed)

[Aug 31, 2025](https://hashnode.com/posts/retrieval-augmented-generation-rag-a-complete-guide/68b46243670a6cffa7509a6b)

### [Where RAG Fails](https://ragfailureforeveryone.hashnode.dev/where-rag-fails?utm_source=hashnode&utm_medium=feed)

⚠️ Common RAG Failure Cases and How to Fix Them Retrieval-Augmented Generation (RAG) has become one of the most effective techniques for grounding Large Language Models (LLMs) in external knowledge. Instead of relying only on pre-trained data, RAG re...

3 min read · [ragfailureforeveryone.hashnode.dev](https://ragfailureforeveryone.hashnode.dev/where-rag-fails?utm_source=hashnode&utm_medium=feed)

[Aug 31, 2025](https://hashnode.com/posts/where-rag-fails/68b45fecd673a53e13866765)

### [🧠 Building Thinking Models from Non-Thinking Models with Chain-of-Thought (CoT)](https://cotforeveryone.hashnode.dev/building-thinking-models-from-non-thinking-models-with-chain-of-thought-cot?utm_source=hashnode&utm_medium=feed)

Generative AI has made impressive progress in producing human-like text. However, many AI models can appear like “non-thinking parrots” — they generate answers quickly but without real reasoning. This is where Chain-of-Thought (CoT) prompting comes i...

3 min read · [cotforeveryone.hashnode.dev](https://cotforeveryone.hashnode.dev/building-thinking-models-from-non-thinking-models-with-chain-of-thought-cot?utm_source=hashnode&utm_medium=feed)

[Aug 15, 2025](https://hashnode.com/posts/building-thinking-models-from-non-thinking-models-with-chain-of-thought-cot/689f44a07e267045d9cfb0e8)