Large Language Models
What Is a Large Language Model (LLM)?
How LLMs actually generate text, what tokens and context windows really mean, and why models hallucinate — explained without the jargon.
Blog
The Synaptech GenAI Blog
In-depth, practical writing on Generative AI — organized around the topics that actually matter for building real applications: LLMs, RAG, AI agents, vector databases, prompt engineering, evaluation, and production AI.
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Large Language Models
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Retrieval-Augmented Generation (RAG)
Retrieval-Augmented Generation (RAG)
What Is RAG (Retrieval-Augmented Generation)?
Why RAG exists, how a retrieval pipeline actually works, and how it differs from fine-tuning — with the "open-book exam" analogy that makes it click.
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Vector Databases
Vector Databases
Vector Databases Explained
How vector databases power semantic search: embeddings, similarity measures, ANN indexes, and choosing the right one for RAG.
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AI Agents
AI Agents
AI Agents Explained
The mechanics behind AI agents and Agentic AI: tool calling, the agent loop, and why reliability is the hard part.
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Prompt Engineering
Prompt Engineering
Prompt Engineering Guide
Zero-shot to few-shot prompting, structured outputs, instruction hierarchy, and how to evaluate prompts like code — not guesswork.
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LLM Evaluation
LLM Evaluation
LLM Evaluation Guide
Why "it looks right" isn't evaluation, and how to actually test LLM and RAG systems with metrics, LLM-as-judge, and a real test set.
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Production AI
Production AI
Production AI Best Practices
The unglamorous engineering that turns an AI demo into a reliable product: architecture, caching, cost control, logging, and security.