Learn how to build production-ready Claude Skills that extend AI capabilities through modular, filesystem-based components. This comprehensive guide covers architecture principles, implementation in Node.js, Python, and C#, API integration, and real-world enterprise use cases.
Author: Chandan
Vibe Coding in 2026: The Truth About AI-Powered Development and What the Data Really Shows
Examine the heated debate around vibe coding and AI-assisted development through hard data and real-world case studies. This analytical deep-dive separates marketing hype from measurable productivity gains.
Repository Intelligence: Microsoft’s AI Revolution That Understands Your Entire Codebase, Not Just Lines of Code
Explore how Microsoft’s repository intelligence transforms AI coding assistants from simple autocomplete tools into context-aware development partners that understand your entire codebase, relationships, and history.
Production Operations and Distributed Deployment: Monitoring, Versioning, and Maintaining Edge AI at Scale
Comprehensive production operations guide for distributed edge AI deployments. Covers Prometheus/Jaeger monitoring integration, data drift detection with statistical analysis, model versioning and registry management, canary deployment with automated rollback, OTA update orchestration, and fleet management patterns for 100+ edge devices.
Advanced Optimization Patterns: Concurrent Multi-Model Inference and Resource Management on Edge Hardware
Advanced optimization patterns for production edge AI deployments. Covers memory-aware multi-model scheduling, GPU resource pooling with priority queuing, adaptive batching for throughput optimization, KV cache management for transformers, and SLA enforcement achieving 50-70% latency reduction through intelligent resource coordination.
Multi-Language Edge Inference Servers: Building REST APIs for Real-Time Object Detection
Comprehensive guide to building production-ready multi-language inference servers for edge AI. Covers Node.js/Express and C#/ASP.NET Core implementations, camera integration for live streams, asynchronous request handling, error recovery mechanisms, and load testing achieving 15-22ms latency with 30+ concurrent requests on Jetson platforms.
Deploying to NVIDIA Jetson with TensorRT: Production-Grade Inference Optimization
Production deployment guide for YOLOv8 on NVIDIA Jetson platforms. Covers JetPack setup, TensorRT engine compilation with FP16/INT8 precision, calibration procedures, efficient inference implementation, performance tuning strategies, thermal management, and platform-specific benchmarks across Jetson Nano, Xavier NX, and Orin families.
YOLOv8 Implementation and Quantization: From Training to Edge Deployment
Comprehensive implementation guide for training and quantizing YOLOv8 models for edge deployment. Covers PTQ and QAT workflows, model export to ONNX/TensorRT/TFLite formats, rigorous validation methodologies, and performance benchmarking demonstrating 4x compression and 1.5-2.75x speedup with sub-2% accuracy degradation.
Real-Time Object Detection on Edge Devices: Building Production-Ready CNNs for On-Device Visual Analysis
Comprehensive guide to deploying production-ready CNNs on edge devices for real-time object detection. Covers architecture fundamentals, YOLOv8 vs YOLO26 comparison, quantization techniques achieving 4x compression, and hardware platform selection including NVIDIA Jetson, Raspberry Pi + Coral TPU, and Intel OpenVINO solutions.
Kafka Streams and ksqlDB: Building Real-Time Stream Processing Applications
Master real-time stream processing with Kafka Streams and ksqlDB. Comprehensive guide covering stateless and stateful operations, windowing, joins, aggregations, and production deployment patterns for building scalable streaming applications.
