A practical AI agents handbook covering agent systems, agentic workflows, LangGraph, MCP/A2A, context engineering, agent memory, evaluation, observability, and multi-agent architecture. Current trend focus: coding agent containment, emerging agent runtimes, and production AI workflow patterns.

Hybrid AI is the future of explainable intelligence. This article explores how combining vector search, knowledge graphs, and retrieval-augmented generation (RAG) creates AI systems that can reason, cite, and explain their answers with insights learned from building a real Graph-Powered RAG Engine.

PR Guardian AI automatically reviews pull requests using advanced AI analysis. It identifies code issues, security risks, performance problems, and provides actionable suggestions directly inside GitHub pull requests.

The official implementation of "RouteExplainer: An Explanation Framework for Vehicle Routing Problem" (PAKDD 2024, oral)

An AI-powered Career Navigation Platform that guides a user through their entire career lifecycle: Resume → Skill Gap → Learning Path → Career Simulation → Job Matching → Application Support The system acts as a personal AI career mentor, adapting to each user’s profile instead of forcing them into predefined paths . (Enter "API KEY" in dashboard

High-quality scientific PDF translation using Claude Code Max - Transform scanned academic documents from English to French with precision

RAG implemented from scratch without using LangChain and LangGraph - designed specifically for processing and querying PDF documents with advanced support for visual content like tables, charts, and mathematical formulas.

AI-powered research assistant that combines intelligent web research, beautiful formatting, and automated email delivery. This full-stack application leverages n8n automation workflows to provide seamless research experiences with professional presentation.

🤖 Production-ready samples for building multi-modal AI agents that understand images, documents, videos, and text using Amazon Bedrock and Strands Agents. Features Claude integration, MCP tools, streaming responses, and enterprise-grade architecture.

Augmented Intelligence Framework: Create orchestrated multi-agent AI teams for software development, user research & content creation. Features 45+ specialized agents with structured workflows delivering the full benefits of human-AI collaboration

An interactive dashboard for exploring mathematical research trends on arXiv

AI-powered stock analysis and investment recommendation app using CrewAI agents, Gemini LLM, DuckDuckGo Search and real-time market data. Generates comprehensive reports, news summaries, and buy/hold/sell advice.

ScholarLens analyzes research papers using RAG with AI models from OpenAI, Anthropic, and Google. It identifies research gaps, assesses novelty, extracts key concepts, visualizes citations, and enables natural language queries of academic content. Features include PDF processing, arXiv/Semantic Scholar integration, batch processing, and intelligent

An enterprise-grade, full-stack AI travel planner which provides data-driven itineraries for Lucknow, India and showcases production-ready architecture, combining a FastAPI backend with a Streamlit frontend. It leverages an advanced agentic RAG system, context-aware responses by integrating a local knowledge base with live, external APIs.

⚙️ Automated LLM-based Prompt Engineering for Structured Data Processing

RAG enhances LLMs by retrieving relevant external knowledge before generating responses, improving accuracy and reducing hallucinations.

An open-source, reproducible framework for labelling maintenance logs from wind farms based on free-entry descriptors and benchmarking Large Language Models (LLMs) in this task. The repository is from a study evaluating proprietary and open-source models on performance, cost, and calibration to support data-driven O&M in the wind energy sector.

Local-first study cockpit for the Claude Certified Architect Foundations exam. Spaced-repetition flashcards, architect-tier MCQ trainer, corpus-grounded Ask Claude, and optional Skilljar autofill.

An experimental framework for building collaborative coding agents that design and implement software through structured debate and consensus.

Multi-agent fitness coaching without the framework bloat. Phase-based reasoning pipeline (Analyze → Think → Summarize → Decide) that actually improves training plans — not just chat.