Engineering Essays

Long-form technical writing on AI systems, distributed backend architecture, cloud-native infrastructure, and modern frontend engineering.

Featured · AI Systems

Designing Deterministic AI Systems for Production: Engineering Reliability into ML

Build production-grade AI systems that don't fail. Learn how to wrap probabilistic models in deterministic architecture, implement validation layers, and achieve 99.9% uptime with LLM guardrails and fallback mechanisms.

2026-01-1516 min read

Backend Engineering18 min read

Scaling FastAPI to 100k Requests/Second: Production Architecture for High-Performance APIs

Master the architecture patterns for scaling FastAPI: async/await optimization, connection pooling, caching strategies, load balancing, and monitoring. Real-world patterns for handling 100k+ concurrent connections.

2025-12-10

MLOps17 min read

Production ML Monitoring: Detecting Model Drift, Data Skew, and Performance Degradation

Learn to detect when ML models fail in production. Master drift detection strategies, implement continuous monitoring, set up automated retraining pipelines, and maintain model performance over time.

2025-11-12

Frontend Architecture15 min read

Next.js 15 Architecture Patterns: Building Scalable Web Applications with App Router and Server Components

Master advanced Next.js patterns: App Router, server components, streaming, incremental static regeneration, and data fetching strategies. Build fast, scalable web applications that outrank competitors.

2025-10-08

Cloud Infrastructure16 min read

Cloud-Native AI Infrastructure: Designing Scalable Systems for ML Workloads on GCP, AWS, and Azure

Build production ML infrastructure: containerization, orchestration, model serving, cost optimization, and monitoring. Handle training pipelines, batch inference, and real-time serving at scale.

2025-09-05