<?xml version="1.0" encoding="utf-8" standalone="yes"?>
<rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom" xmlns:content="http://purl.org/rss/1.0/modules/content/">
  <channel>
    <title>LLM on Manvendra Rajpoot</title>
    <link>https://blog.rajpoot.dev/tags/llm/</link>
    <description>Recent content in LLM on Manvendra Rajpoot</description>
    <image>
      <title>Manvendra Rajpoot</title>
      <url>https://blog.rajpoot.dev/img/personal/cover.png</url>
      <link>https://blog.rajpoot.dev/img/personal/cover.png</link>
    </image>
    <generator>Hugo</generator>
    <language>en</language>
    <copyright>Manvendra Rajpoot</copyright>
    <lastBuildDate>Sun, 17 May 2026 17:50:46 +0530</lastBuildDate>
    <atom:link href="https://blog.rajpoot.dev/tags/llm/index.xml" rel="self" type="application/rss+xml" />
    <item>
      <title>AI/LLM Cheatsheet 01 — LLM Basics</title>
      <link>https://blog.rajpoot.dev/cheatsheets/ai-llm/01-basics-cheatsheet/</link>
      <pubDate>Tue, 26 May 2026 06:00:00 +0530</pubDate>
      <guid>https://blog.rajpoot.dev/cheatsheets/ai-llm/01-basics-cheatsheet/</guid>
      <description>LLM basics — OpenAI, Anthropic, prompts, tokens, costs.</description>
    </item>
    <item>
      <title>AI/LLM Cheatsheet 02 — Prompt Engineering</title>
      <link>https://blog.rajpoot.dev/cheatsheets/ai-llm/02-prompts-cheatsheet/</link>
      <pubDate>Tue, 26 May 2026 06:10:00 +0530</pubDate>
      <guid>https://blog.rajpoot.dev/cheatsheets/ai-llm/02-prompts-cheatsheet/</guid>
      <description>Prompt engineering — patterns, structure, few-shot, CoT.</description>
    </item>
    <item>
      <title>AI/LLM Cheatsheet 03 — Tool Use / Function Calling</title>
      <link>https://blog.rajpoot.dev/cheatsheets/ai-llm/03-tools-cheatsheet/</link>
      <pubDate>Tue, 26 May 2026 06:20:00 +0530</pubDate>
      <guid>https://blog.rajpoot.dev/cheatsheets/ai-llm/03-tools-cheatsheet/</guid>
      <description>Tool use — OpenAI, Anthropic, parallel calls.</description>
    </item>
    <item>
      <title>AI/LLM Cheatsheet 04 — Embeddings</title>
      <link>https://blog.rajpoot.dev/cheatsheets/ai-llm/04-embeddings-cheatsheet/</link>
      <pubDate>Tue, 26 May 2026 06:30:00 +0530</pubDate>
      <guid>https://blog.rajpoot.dev/cheatsheets/ai-llm/04-embeddings-cheatsheet/</guid>
      <description>Embeddings — OpenAI, Cohere, BGE, local.</description>
    </item>
    <item>
      <title>AI/LLM Cheatsheet 05 — RAG Patterns</title>
      <link>https://blog.rajpoot.dev/cheatsheets/ai-llm/05-rag-cheatsheet/</link>
      <pubDate>Tue, 26 May 2026 06:40:00 +0530</pubDate>
      <guid>https://blog.rajpoot.dev/cheatsheets/ai-llm/05-rag-cheatsheet/</guid>
      <description>RAG — retrieve &#43; generate, hybrid, rerank, citations.</description>
    </item>
    <item>
      <title>AI/LLM Cheatsheet 08 — Streaming Patterns</title>
      <link>https://blog.rajpoot.dev/cheatsheets/ai-llm/08-streaming-cheatsheet/</link>
      <pubDate>Tue, 26 May 2026 07:10:00 +0530</pubDate>
      <guid>https://blog.rajpoot.dev/cheatsheets/ai-llm/08-streaming-cheatsheet/</guid>
      <description>LLM streaming — SSE, token-by-token, frontend handling.</description>
    </item>
    <item>
      <title>AI/LLM Cheatsheet 09 — Function Calling Patterns</title>
      <link>https://blog.rajpoot.dev/cheatsheets/ai-llm/09-function-calling-cheatsheet/</link>
      <pubDate>Tue, 26 May 2026 07:20:00 +0530</pubDate>
      <guid>https://blog.rajpoot.dev/cheatsheets/ai-llm/09-function-calling-cheatsheet/</guid>
      <description>LLM function calling patterns — schemas, validation, parallel.</description>
    </item>
    <item>
      <title>AI/LLM Cheatsheet 10 — Evaluation</title>
      <link>https://blog.rajpoot.dev/cheatsheets/ai-llm/10-eval-cheatsheet/</link>
      <pubDate>Tue, 26 May 2026 07:30:00 +0530</pubDate>
      <guid>https://blog.rajpoot.dev/cheatsheets/ai-llm/10-eval-cheatsheet/</guid>
      <description>LLM evaluation — datasets, LLM-as-judge, regression tests.</description>
    </item>
    <item>
      <title>AI/LLM Cheatsheet 11 — Cost Optimization</title>
      <link>https://blog.rajpoot.dev/cheatsheets/ai-llm/11-costs-cheatsheet/</link>
      <pubDate>Tue, 26 May 2026 07:40:00 +0530</pubDate>
      <guid>https://blog.rajpoot.dev/cheatsheets/ai-llm/11-costs-cheatsheet/</guid>
      <description>LLM cost optimization — caching, batching, smaller models.</description>
    </item>
    <item>
      <title>AI/LLM Cheatsheet 12 — Local LLMs (Ollama, vLLM)</title>
      <link>https://blog.rajpoot.dev/cheatsheets/ai-llm/12-local-llms-cheatsheet/</link>
      <pubDate>Tue, 26 May 2026 07:50:00 +0530</pubDate>
      <guid>https://blog.rajpoot.dev/cheatsheets/ai-llm/12-local-llms-cheatsheet/</guid>
      <description>Local LLMs — Ollama, vLLM, llama.cpp.</description>
    </item>
    <item>
      <title>AI/LLM Cheatsheet 13 — Fine-tuning</title>
      <link>https://blog.rajpoot.dev/cheatsheets/ai-llm/13-finetuning-cheatsheet/</link>
      <pubDate>Tue, 26 May 2026 08:00:00 +0530</pubDate>
      <guid>https://blog.rajpoot.dev/cheatsheets/ai-llm/13-finetuning-cheatsheet/</guid>
      <description>Fine-tuning — LoRA, QLoRA, OpenAI fine-tune.</description>
    </item>
    <item>
      <title>AI/LLM Cheatsheet 14 — Multimodal LLMs</title>
      <link>https://blog.rajpoot.dev/cheatsheets/ai-llm/14-multimodal-cheatsheet/</link>
      <pubDate>Tue, 26 May 2026 08:10:00 +0530</pubDate>
      <guid>https://blog.rajpoot.dev/cheatsheets/ai-llm/14-multimodal-cheatsheet/</guid>
      <description>Multimodal — image, audio, video LLMs.</description>
    </item>
    <item>
      <title>AI/LLM Cheatsheet 15 — Security and Prompt Injection</title>
      <link>https://blog.rajpoot.dev/cheatsheets/ai-llm/15-security-cheatsheet/</link>
      <pubDate>Tue, 26 May 2026 08:20:00 +0530</pubDate>
      <guid>https://blog.rajpoot.dev/cheatsheets/ai-llm/15-security-cheatsheet/</guid>
      <description>LLM security — prompt injection, data leaks, jailbreaks.</description>
    </item>
    <item>
      <title>AI/LLM Cheatsheet 17 — Observability for LLMs</title>
      <link>https://blog.rajpoot.dev/cheatsheets/ai-llm/17-observability-cheatsheet/</link>
      <pubDate>Tue, 26 May 2026 08:40:00 +0530</pubDate>
      <guid>https://blog.rajpoot.dev/cheatsheets/ai-llm/17-observability-cheatsheet/</guid>
      <description>LLM observability — LangSmith, Helicone, traces, metrics.</description>
    </item>
    <item>
      <title>AI/LLM Cheatsheet 18 — LLM Application Patterns</title>
      <link>https://blog.rajpoot.dev/cheatsheets/ai-llm/18-patterns-cheatsheet/</link>
      <pubDate>Tue, 26 May 2026 08:50:00 +0530</pubDate>
      <guid>https://blog.rajpoot.dev/cheatsheets/ai-llm/18-patterns-cheatsheet/</guid>
      <description>LLM app patterns — classification, extraction, summarization, chat.</description>
    </item>
    <item>
      <title>FastAPI Cheatsheet 18 — Streaming and LLM Integration</title>
      <link>https://blog.rajpoot.dev/cheatsheets/fastapi/18-streaming-llm-cheatsheet/</link>
      <pubDate>Mon, 11 May 2026 08:50:00 +0530</pubDate>
      <guid>https://blog.rajpoot.dev/cheatsheets/fastapi/18-streaming-llm-cheatsheet/</guid>
      <description>FastAPI LLM streaming cheatsheet — Anthropic / OpenAI / vLLM streaming, tool calls, cancellation.</description>
    </item>
    <item>
      <title>AI/LLM Cheatsheet 19 — Building Chat UI</title>
      <link>https://blog.rajpoot.dev/cheatsheets/ai-llm/19-chat-ui-cheatsheet/</link>
      <pubDate>Tue, 26 May 2026 09:00:00 +0530</pubDate>
      <guid>https://blog.rajpoot.dev/cheatsheets/ai-llm/19-chat-ui-cheatsheet/</guid>
      <description>Chat UI — streaming, markdown, tool indicators.</description>
    </item>
    <item>
      <title>AI/LLM Cheatsheet 20 — Production LLM App</title>
      <link>https://blog.rajpoot.dev/cheatsheets/ai-llm/20-production-cheatsheet/</link>
      <pubDate>Tue, 26 May 2026 09:10:00 +0530</pubDate>
      <guid>https://blog.rajpoot.dev/cheatsheets/ai-llm/20-production-cheatsheet/</guid>
      <description>Production LLM app — architecture, ops, security.</description>
    </item>
    <item>
      <title>Self-Hosting LLMs in 2026 — When the Math Actually Works</title>
      <link>https://blog.rajpoot.dev/posts/ai/llm-self-host-economics-2026/</link>
      <pubDate>Tue, 05 May 2026 08:30:00 +0530</pubDate>
      <guid>https://blog.rajpoot.dev/posts/ai/llm-self-host-economics-2026/</guid>
      <description>Self-hosting LLMs in 2026 — vLLM, GPU economics, break-even, and when self-host beats API.</description>
    </item>
    <item>
      <title>Synthetic Data with LLMs in 2026 — Use Cases, Risks, and the Patterns That Work</title>
      <link>https://blog.rajpoot.dev/posts/ai/synthetic-data-2026/</link>
      <pubDate>Tue, 05 May 2026 06:10:00 +0530</pubDate>
      <guid>https://blog.rajpoot.dev/posts/ai/synthetic-data-2026/</guid>
      <description>Synthetic data generation with LLMs in 2026 — when it helps, model collapse risk, eval set generation, and production patterns.</description>
    </item>
    <item>
      <title>LLM Tool Use Patterns in 2026 — Schemas, Validation, and the Loop</title>
      <link>https://blog.rajpoot.dev/posts/ai/llm-tool-use-patterns-2026/</link>
      <pubDate>Mon, 04 May 2026 06:00:00 +0530</pubDate>
      <guid>https://blog.rajpoot.dev/posts/ai/llm-tool-use-patterns-2026/</guid>
      <description>LLM tool use in 2026 — designing tool schemas, parallel calls, error handling, and the patterns from production agents.</description>
    </item>
    <item>
      <title>LLM Batch Processing in 2026 — Anthropic / OpenAI Batch API for 50% Off</title>
      <link>https://blog.rajpoot.dev/posts/ai/llm-batch-processing-2026/</link>
      <pubDate>Sun, 03 May 2026 06:20:00 +0530</pubDate>
      <guid>https://blog.rajpoot.dev/posts/ai/llm-batch-processing-2026/</guid>
      <description>LLM batch APIs in 2026 — Anthropic, OpenAI, Bedrock batch processing for 50% discount, when to use them, and the patterns that work.</description>
    </item>
    <item>
      <title>LLM Deployment Patterns in 2026 — Inference Servers, Routing, and Production Architectures</title>
      <link>https://blog.rajpoot.dev/posts/ai/llm-deployment-patterns-2026/</link>
      <pubDate>Sun, 03 May 2026 06:10:00 +0530</pubDate>
      <guid>https://blog.rajpoot.dev/posts/ai/llm-deployment-patterns-2026/</guid>
      <description>LLM deployment patterns in 2026 — vLLM, TGI, Ollama, hybrid API&#43;self-hosted, routing layers, and the production architectures that actually work.</description>
    </item>
    <item>
      <title>Prompt Engineering in 2026 — What Still Works, What Doesn&#39;t, and What Changed</title>
      <link>https://blog.rajpoot.dev/posts/ai/llm-prompt-engineering-2026/</link>
      <pubDate>Sun, 03 May 2026 06:00:00 +0530</pubDate>
      <guid>https://blog.rajpoot.dev/posts/ai/llm-prompt-engineering-2026/</guid>
      <description>Prompt engineering in 2026 — patterns that still work, what&amp;#39;s been obsoleted by better models, structured prompts, and production discipline.</description>
    </item>
    <item>
      <title>LLM Context Windows in 2026 — Long Context, Cache, and the Limits of &#39;Just Add More&#39;</title>
      <link>https://blog.rajpoot.dev/posts/ai/llm-context-windows-2026/</link>
      <pubDate>Sat, 02 May 2026 11:00:00 +0530</pubDate>
      <guid>https://blog.rajpoot.dev/posts/ai/llm-context-windows-2026/</guid>
      <description>LLM context windows in 2026 — what 200k / 1M context can and can&amp;#39;t do, prompt caching, retrieval, and patterns from production.</description>
    </item>
    <item>
      <title>Multimodal LLMs in 2026 — Vision, Audio, and What&#39;s Actually Useful</title>
      <link>https://blog.rajpoot.dev/posts/ai/multimodal-llms-2026/</link>
      <pubDate>Sat, 02 May 2026 09:30:00 +0530</pubDate>
      <guid>https://blog.rajpoot.dev/posts/ai/multimodal-llms-2026/</guid>
      <description>Multimodal LLMs in 2026 — vision input, audio input, generation, real-world use cases, and the patterns that work in production.</description>
    </item>
    <item>
      <title>LLM Observability in 2026 — Tracing, Evals, and the Things You Can&#39;t Skip</title>
      <link>https://blog.rajpoot.dev/posts/ai/llm-observability-2026/</link>
      <pubDate>Sat, 02 May 2026 07:30:00 +0530</pubDate>
      <guid>https://blog.rajpoot.dev/posts/ai/llm-observability-2026/</guid>
      <description>Production LLM observability in 2026 — distributed tracing, eval pipelines, Langfuse, Arize, and the patterns that turn black-box LLMs into operable systems.</description>
    </item>
    <item>
      <title>LLM Cost Optimization in 2026 — From Bills That Hurt to Bills That Don&#39;t</title>
      <link>https://blog.rajpoot.dev/posts/ai/llm-cost-optimization-2026/</link>
      <pubDate>Sat, 02 May 2026 07:20:00 +0530</pubDate>
      <guid>https://blog.rajpoot.dev/posts/ai/llm-cost-optimization-2026/</guid>
      <description>Cutting LLM costs in 2026 — prompt caching, routing, batching, fine-tunes, and the patterns that drop bills 5-20× without quality loss.</description>
    </item>
    <item>
      <title>LLM Guardrails in 2026 — Input Filtering, Output Validation, and Safety Nets</title>
      <link>https://blog.rajpoot.dev/posts/ai/llm-guardrails-content-safety-2026/</link>
      <pubDate>Fri, 01 May 2026 07:10:00 +0530</pubDate>
      <guid>https://blog.rajpoot.dev/posts/ai/llm-guardrails-content-safety-2026/</guid>
      <description>Practical LLM guardrails in 2026 — input filtering, output validation, NVIDIA NeMo, Guardrails AI, and the patterns that prevent embarrassments.</description>
    </item>
    <item>
      <title>Fine-Tuning LLMs in 2026 — LoRA, QLoRA, and the Cheap Path to Specialized Models</title>
      <link>https://blog.rajpoot.dev/posts/ai/llm-fine-tuning-lora-qlora-2026/</link>
      <pubDate>Fri, 01 May 2026 06:00:00 +0530</pubDate>
      <guid>https://blog.rajpoot.dev/posts/ai/llm-fine-tuning-lora-qlora-2026/</guid>
      <description>Practical LLM fine-tuning in 2026 — LoRA, QLoRA, training data prep, evaluation, and the patterns from teams shipping fine-tuned models.</description>
    </item>
    <item>
      <title>OpenAI vs Anthropic vs Google for Production AI in 2026</title>
      <link>https://blog.rajpoot.dev/posts/ai/openai-vs-anthropic-vs-google-2026/</link>
      <pubDate>Fri, 01 May 2026 03:00:00 +0530</pubDate>
      <guid>https://blog.rajpoot.dev/posts/ai/openai-vs-anthropic-vs-google-2026/</guid>
      <description>Honest comparison of OpenAI vs Anthropic vs Google for production LLM apps in 2026 — model quality, pricing, latency, ecosystem, and how to pick.</description>
    </item>
    <item>
      <title>LLM Prompt Caching Deep Dive — Anthropic, OpenAI, and the Patterns That Save 90%</title>
      <link>https://blog.rajpoot.dev/posts/ai/llm-prompt-caching-deep-dive-2026/</link>
      <pubDate>Fri, 01 May 2026 00:30:00 +0530</pubDate>
      <guid>https://blog.rajpoot.dev/posts/ai/llm-prompt-caching-deep-dive-2026/</guid>
      <description>Prompt caching mechanics in 2026 — Anthropic&amp;#39;s ephemeral cache, OpenAI&amp;#39;s automatic caching, breakpoint placement, hit-rate measurement, and the patterns that save real money.</description>
    </item>
    <item>
      <title>LLM Evaluation Frameworks in 2026 — Braintrust, LangSmith, Ragas, DeepEval</title>
      <link>https://blog.rajpoot.dev/posts/ai/llm-evaluation-frameworks-2026/</link>
      <pubDate>Thu, 30 Apr 2026 23:59:00 +0530</pubDate>
      <guid>https://blog.rajpoot.dev/posts/ai/llm-evaluation-frameworks-2026/</guid>
      <description>Picking an LLM evaluation framework in 2026 — Braintrust vs LangSmith vs Ragas vs DeepEval. What each does, when each fits.</description>
    </item>
    <item>
      <title>Context Engineering for LLMs in 2026 — The Discipline Beyond Prompting</title>
      <link>https://blog.rajpoot.dev/posts/ai/llm-context-engineering-patterns-2026/</link>
      <pubDate>Thu, 30 Apr 2026 21:00:00 +0530</pubDate>
      <guid>https://blog.rajpoot.dev/posts/ai/llm-context-engineering-patterns-2026/</guid>
      <description>Context engineering for LLMs in 2026 — what to put in context, what to leave out, ordering, compression, and the patterns that make agents work.</description>
    </item>
    <item>
      <title>LLM Streaming with Cancellation — Patterns That Don&#39;t Waste Tokens</title>
      <link>https://blog.rajpoot.dev/posts/ai/llm-streaming-cancellation-patterns-2026/</link>
      <pubDate>Thu, 30 Apr 2026 20:40:00 +0530</pubDate>
      <guid>https://blog.rajpoot.dev/posts/ai/llm-streaming-cancellation-patterns-2026/</guid>
      <description>How to implement LLM streaming with proper cancellation in 2026 — SSE patterns, abort signals, server-side cancel, and not paying for tokens the user doesn&amp;#39;t want.</description>
    </item>
    <item>
      <title>LLM Routing in 2026 — Use Haiku to Save 80% on Sonnet/Opus Bills</title>
      <link>https://blog.rajpoot.dev/posts/ai/llm-routing-classification-haiku-2026/</link>
      <pubDate>Thu, 30 Apr 2026 19:40:00 +0530</pubDate>
      <guid>https://blog.rajpoot.dev/posts/ai/llm-routing-classification-haiku-2026/</guid>
      <description>How LLM routing with a small classifier (Haiku) saves 80% on Sonnet / Opus / GPT-5 bills in 2026 — patterns, accuracy, and how to wire it in.</description>
    </item>
    <item>
      <title>1M-Token Context Windows in 2026 — When They Help, When They Hurt</title>
      <link>https://blog.rajpoot.dev/posts/ai/long-context-1m-tokens-2026/</link>
      <pubDate>Thu, 30 Apr 2026 13:10:00 +0530</pubDate>
      <guid>https://blog.rajpoot.dev/posts/ai/long-context-1m-tokens-2026/</guid>
      <description>Practical guide to 1M-token context windows in 2026 — when long context replaces RAG, when it doesn&amp;#39;t, prompt caching, and the cost reality.</description>
    </item>
    <item>
      <title>Agentic RAG in 2026 — When Retrieval Becomes a Tool, Not a Pipeline</title>
      <link>https://blog.rajpoot.dev/posts/ai/agentic-rag-2026/</link>
      <pubDate>Thu, 30 Apr 2026 13:00:00 +0530</pubDate>
      <guid>https://blog.rajpoot.dev/posts/ai/agentic-rag-2026/</guid>
      <description>Agentic RAG explained — when the agent decides what and when to retrieve, multi-step reasoning, query rewriting, self-reflection, and the patterns that beat naive RAG.</description>
    </item>
    <item>
      <title>LLM Security in 2026 — Prompt Injection, Data Exfiltration, and Defense in Depth</title>
      <link>https://blog.rajpoot.dev/posts/ai/llm-security-prompt-injection-2026/</link>
      <pubDate>Thu, 30 Apr 2026 12:50:00 +0530</pubDate>
      <guid>https://blog.rajpoot.dev/posts/ai/llm-security-prompt-injection-2026/</guid>
      <description>How to defend against LLM-specific attacks in 2026 — prompt injection, indirect injection, data exfiltration, jailbreaks, and the layered defenses that work.</description>
    </item>
    <item>
      <title>Voice Agents and Realtime LLM APIs in 2026 — How They Actually Work</title>
      <link>https://blog.rajpoot.dev/posts/ai/voice-agents-realtime-llm-2026/</link>
      <pubDate>Thu, 30 Apr 2026 12:10:00 +0530</pubDate>
      <guid>https://blog.rajpoot.dev/posts/ai/voice-agents-realtime-llm-2026/</guid>
      <description>How voice agents work in 2026 — Realtime APIs from OpenAI / Anthropic / Google, latency budgets, ASR, TTS, interruption handling, and production architecture.</description>
    </item>
    <item>
      <title>LLM Cost Optimization in 2026 — Tactics That Cut Bills 50–90%</title>
      <link>https://blog.rajpoot.dev/posts/ai/llm-cost-optimization-tactics-2026/</link>
      <pubDate>Thu, 30 Apr 2026 12:00:00 +0530</pubDate>
      <guid>https://blog.rajpoot.dev/posts/ai/llm-cost-optimization-tactics-2026/</guid>
      <description>Concrete LLM cost optimization tactics that cut your Anthropic / OpenAI / Gemini bill by 50–90% — caching, model routing, batching, fine-tuning, and the patterns that compound.</description>
    </item>
    <item>
      <title>Structured Output for LLMs in 2026 — Pydantic AI, Instructor, and the End of JSON Parsing</title>
      <link>https://blog.rajpoot.dev/posts/ai/structured-output-pydantic-ai-instructor-2026/</link>
      <pubDate>Thu, 30 Apr 2026 09:10:00 +0530</pubDate>
      <guid>https://blog.rajpoot.dev/posts/ai/structured-output-pydantic-ai-instructor-2026/</guid>
      <description>How to get structured, validated output from LLMs in 2026 — Pydantic AI, Instructor, native tool-calling, OpenAI&amp;#39;s structured outputs API, and the patterns that make extraction reliable.</description>
    </item>
    <item>
      <title>AI Gateways in 2026 — LiteLLM, Portkey, Helicone, and the OpenAI Façade</title>
      <link>https://blog.rajpoot.dev/posts/ai/ai-gateways-litellm-portkey-helicone-2026/</link>
      <pubDate>Thu, 30 Apr 2026 09:00:00 +0530</pubDate>
      <guid>https://blog.rajpoot.dev/posts/ai/ai-gateways-litellm-portkey-helicone-2026/</guid>
      <description>AI gateways explained — why every serious LLM app needs one in 2026, comparison of LiteLLM, Portkey, Helicone, and OpenRouter, and how to add one without rewriting your code.</description>
    </item>
    <item>
      <title>Multi-Agent Systems in 2026 — Production Patterns That Work</title>
      <link>https://blog.rajpoot.dev/posts/ai/multi-agent-systems-production-patterns-2026/</link>
      <pubDate>Thu, 30 Apr 2026 08:50:00 +0530</pubDate>
      <guid>https://blog.rajpoot.dev/posts/ai/multi-agent-systems-production-patterns-2026/</guid>
      <description>Multi-agent systems explained — supervisor / worker, writer / reviewer, hierarchical and swarm patterns, and the production gotchas in 2026.</description>
    </item>
    <item>
      <title>Fine-Tuning vs RAG vs Prompting in 2026 — How to Pick the Right Approach</title>
      <link>https://blog.rajpoot.dev/posts/ai/fine-tuning-vs-rag-vs-prompting-2026/</link>
      <pubDate>Wed, 29 Apr 2026 10:00:00 +0530</pubDate>
      <guid>https://blog.rajpoot.dev/posts/ai/fine-tuning-vs-rag-vs-prompting-2026/</guid>
      <description>When to fine-tune, when to RAG, and when to just prompt — a practical 2026 decision guide for LLM applications, with cost, quality, and ops tradeoffs.</description>
    </item>
    <item>
      <title>Model Context Protocol (MCP) Explained — The USB-C of AI Tools</title>
      <link>https://blog.rajpoot.dev/posts/ai/model-context-protocol-mcp-explained/</link>
      <pubDate>Tue, 28 Apr 2026 21:00:00 +0530</pubDate>
      <guid>https://blog.rajpoot.dev/posts/ai/model-context-protocol-mcp-explained/</guid>
      <description>Model Context Protocol (MCP) explained from first principles — what it is, how it works, why it matters, and how to build an MCP server for your own tools and data.</description>
    </item>
    <item>
      <title>Self-Hosted LLMs in 2026 — Ollama, vLLM, and When to Skip the API</title>
      <link>https://blog.rajpoot.dev/posts/ai/self-hosted-llms-vllm-ollama-2026/</link>
      <pubDate>Tue, 28 Apr 2026 20:50:00 +0530</pubDate>
      <guid>https://blog.rajpoot.dev/posts/ai/self-hosted-llms-vllm-ollama-2026/</guid>
      <description>When to self-host LLMs in 2026 — Ollama for dev, vLLM and SGLang for production, model choice, hardware sizing, and the latency/cost tradeoffs vs hosted APIs.</description>
    </item>
    <item>
      <title>LLM Evaluations — How to Test Prompts and Agents Like a Pro</title>
      <link>https://blog.rajpoot.dev/posts/ai/llm-evaluations-test-prompts-agents/</link>
      <pubDate>Tue, 28 Apr 2026 16:40:00 +0530</pubDate>
      <guid>https://blog.rajpoot.dev/posts/ai/llm-evaluations-test-prompts-agents/</guid>
      <description>A practical, no-fluff guide to evaluating LLM applications — what to measure, how to build a starter eval set, LLM-as-judge done right, and how to wire evals into CI.</description>
    </item>
    <item>
      <title>Prompt Engineering Patterns That Survive Production</title>
      <link>https://blog.rajpoot.dev/posts/ai/prompt-engineering-production-patterns/</link>
      <pubDate>Tue, 28 Apr 2026 16:30:00 +0530</pubDate>
      <guid>https://blog.rajpoot.dev/posts/ai/prompt-engineering-production-patterns/</guid>
      <description>Prompt engineering patterns that hold up in production — system prompts, structured outputs, few-shot, reasoning steps, role separation, and the anti-patterns that look clever but quietly fail.</description>
    </item>
    <item>
      <title>Anthropic Claude API &#43; Tool Use — A Practical Guide for 2026</title>
      <link>https://blog.rajpoot.dev/posts/ai/anthropic-claude-api-tool-use-guide/</link>
      <pubDate>Tue, 28 Apr 2026 16:20:00 +0530</pubDate>
      <guid>https://blog.rajpoot.dev/posts/ai/anthropic-claude-api-tool-use-guide/</guid>
      <description>A no-fluff guide to the Anthropic Claude API in 2026 — messages, tool use, prompt caching, structured outputs, streaming, and the patterns that ship.</description>
    </item>
    <item>
      <title>AI Agents with LangGraph in 2026 — A Practical Tutorial</title>
      <link>https://blog.rajpoot.dev/posts/ai/ai-agents-with-langgraph-tutorial/</link>
      <pubDate>Tue, 28 Apr 2026 16:10:00 +0530</pubDate>
      <guid>https://blog.rajpoot.dev/posts/ai/ai-agents-with-langgraph-tutorial/</guid>
      <description>Build a real AI agent with LangGraph — tools, state, memory, conditional routing, and the production patterns that separate working agents from demoware.</description>
    </item>
    <item>
      <title>Build a Production RAG App with pgvector and FastAPI in 2026</title>
      <link>https://blog.rajpoot.dev/posts/ai/build-rag-app-pgvector-fastapi/</link>
      <pubDate>Tue, 28 Apr 2026 16:00:00 +0530</pubDate>
      <guid>https://blog.rajpoot.dev/posts/ai/build-rag-app-pgvector-fastapi/</guid>
      <description>A complete, copy-paste guide to building a Retrieval-Augmented Generation (RAG) backend with PostgreSQL &#43; pgvector and FastAPI — chunking, embeddings, hybrid search, and the parts most tutorials skip.</description>
    </item>
  </channel>
</rss>
