AI Engineering Resources

Master the variable-size sliding window technique - a dynamic approach that automatically adjusts window boundaries to find optimal subarrays efficiently.

Master the Two Pointers technique for efficient array and string manipulation. Learn how converging pointers eliminate redundant comparisons and solve problems in linear time.

Master Kadane's Algorithm for finding the maximum sum contiguous subarray. Learn the core insight, decision framework, and practical applications with clear examples.

Master the sliding window technique for fixed-size windows. Learn how to efficiently process contiguous subarrays without redundant calculations.

Comprehensive guide to advanced prompting techniques for AI models, covering core principles, reasoning enhancement, tool use patterns, and optimization strategies.

Learn how to build production-ready multi-agent systems with Agent-to-Agent communication using TypeScript, LangGraph, and Vercel's serverless platform.

Learn how to implement comprehensive evaluation and monitoring systems for AI agents in production. We'll build observable, testable, and optimizable agent systems using TypeScript, LangChain, and LangGraph on the Vercel platform.

Build autonomous exploration and discovery agents using TypeScript, Next.js 15, LangChain, and LangGraph on Vercel's serverless platform. Create agents that proactively seek novel information, uncover hidden patterns, and generate new insights.

Implementing robust safety guardrails for LLM agents to prevent harmful outputs, prompt injections, and maintain reliable operation in production TypeScript/Vercel environments.

Build intelligent agents that know when to ask for help. This guide shows how to implement Human-in-the-Loop (HITL) patterns in TypeScript using LangGraph and LangChain on Vercel's serverless platform.

Learn how to build intelligent task prioritization systems using LangChain and LangGraph in TypeScript, optimized for Vercel's serverless platform. This guide demonstrates implementing dynamic priority queues, weighted scoring algorithms, and adaptive task management for production AI agents.

Build sophisticated RAG systems from basic retrieval to advanced agentic patterns with self-correction, intelligent routing, and complex multi-step reasoning using TypeScript, Next.js 15, LangChain, and LangGraph on Vercel.

Learn how to implement advanced reasoning techniques including Chain-of-Thought (CoT), Tree-of-Thought (ToT), Graph-of-Thought (GoT), and Self-Reflection patterns using LangChain, LangGraph, and TypeScript in serverless environments.

Build efficient AI agents with resource management patterns. Learn token optimization, memory management, batch processing, and serverless strategies using TypeScript, LangChain, and LangGraph on Vercel.

Comprehensive guide to implementing Tool Use (Function Calling) patterns for AI agents. Learn how to enable agents to interact with external systems, APIs, and databases using LangChain and LangGraph on Vercel.

Master the art of building fault-tolerant AI agents that gracefully handle errors, recover from failures, and maintain reliability in production using TypeScript, LangChain, LangGraph, and Vercel's serverless platform.

Build intelligent agents that can autonomously decompose complex objectives, track progress, and adapt strategies - all while running efficiently on Vercel's serverless infrastructure.

Learn how to build agents that genuinely improve through experience using TypeScript, LangGraph, and modern memory architectures optimized for Vercel's serverless platform.

Learn how to implement the Model Context Protocol (MCP) to create standardized, interoperable AI agents that can dynamically discover and interact with external tools, services, and data sources in Next.js 15 on Vercel's serverless platform.

Building AI agents that remember past interactions, maintain context across sessions, and learn from experience using TypeScript, LangChain, LangGraph, and Vercel's serverless platform.

Learn how to build sophisticated multi-agent systems with LangGraph and Gemini. Implement supervisor-worker patterns, parallel collaboration, and consensus building for complex AI problem-solving.

Learn how to build high-performance AI agents that execute multiple tasks simultaneously using LangChain, LangGraph, and Next.js 15 on Vercel's serverless platform.

Learn how to implement planning patterns that enable AI agents to decompose complex tasks, create multi-step strategies, and execute sophisticated workflows using TypeScript, LangChain, LangGraph, and Google Gemini models on Vercel's serverless platform.

Build production-ready sequential AI workflows that decompose complex tasks into manageable steps, passing outputs between specialized prompts to achieve sophisticated reasoning and processing capabilities in your Next.js applications.

Learn how to implement self-improving AI agents using the Reflection pattern with LangChain, LangGraph, and TypeScript on Vercel's serverless platform.

Build intelligent routing systems that dynamically direct queries to specialized agents, moving beyond linear workflows to create adaptive, context-aware AI applications.

Complete guide to configure Langchain and Langraph in Next.js 15 for Vercel deployment using Google's Gemini models for building AI agents with TypeScript

A comprehensive guide to developing and deploying MCP servers on Vercel, from concept through production, incorporating best practices and real-world patterns for 2025.

A comprehensive guide to JSON Schema implementation patterns in MCP servers, covering Zod integration, validation strategies, and production best practices

Understanding and solving one of React's most subtle challenges - when functions capture outdated state values leading to unexpected behavior

Comprehensive guide to using Zod for type-safe validation in MCP servers. Learn primitive validation, object schemas, transformations, refinements, and real-world patterns.