Parimal Savaj (@savaj)

@savajAhmedabad, IndiaJoined June 2026

AI Product Engineer exploring the reality of building with language models. I use this blog to openly share what I learn along the way, turning complex engineering hurdles into practical knowledge for other builders.

@savajAhmedabad, IndiaJoined June 2026

Parimal Savaj

About

Available for

Parimal Savaj's blogs

Recently published

Understanding RAG (Retrieval-Augmented Generation): How It Works, Where It Shines, and Where It Breaks

AI SDK vs Agent SDK: Understanding the Building Blocks of Modern AI Applications

The Production AI Stack: Mastering Streaming, Tool Calling, and Prompt Caching

Structured Output and Guardrails: The Two Pillars of Production-Ready LLM Apps

The Mechanics of LLMs: Context, Caching, Costs, and Evals

Parimal Savaj

About

Available for

Parimal Savaj's blogs

Recently published

Understanding RAG (Retrieval-Augmented Generation): How It Works, Where It Shines, and Where It Breaks

AI SDK vs Agent SDK: Understanding the Building Blocks of Modern AI Applications

The Production AI Stack: Mastering Streaming, Tool Calling, and Prompt Caching

Structured Output and Guardrails: The Two Pillars of Production-Ready LLM Apps

The Mechanics of LLMs: Context, Caching, Costs, and Evals

Parimal Savaj

About

Available for

Parimal Savaj's blogs

Recently published

Understanding RAG (Retrieval-Augmented Generation): How It Works, Where It Shines, and Where It Breaks

AI SDK vs Agent SDK: Understanding the Building Blocks of Modern AI Applications

The Production AI Stack: Mastering Streaming, Tool Calling, and Prompt Caching

Structured Output and Guardrails: The Two Pillars of Production-Ready LLM Apps

The Mechanics of LLMs: Context, Caching, Costs, and Evals

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Parimal Savaj

About

Available for

Parimal Savaj's blogs

Recently published

Understanding RAG (Retrieval-Augmented Generation): How It Works, Where It Shines, and Where It Breaks

AI SDK vs Agent SDK: Understanding the Building Blocks of Modern AI Applications

The Production AI Stack: Mastering Streaming, Tool Calling, and Prompt Caching

Structured Output and Guardrails: The Two Pillars of Production-Ready LLM Apps

The Mechanics of LLMs: Context, Caching, Costs, and Evals