Guides & Resources

In-depth guides on code review, git workflows, and specific productivity tips to help you build better software faster.

AI & Machine Learning Engineering

Agentic Workflows: Building Self-Correcting Loops with LangGraph and CrewAI State Machines

Build production-ready AI agents that iteratively improve their outputs through automated feedback loops, combining LangGraph's state machine architecture with CrewAI's multi-agent orchestration for robust, self-correcting workflows.

14 min read

Production LLM Deployment Guide: Quantization, vLLM Serving & GPU Memory Optimization

Master production LLM deployment with quantization techniques, vLLM serving architecture, and GPU memory optimization strategies for maximum throughput and minimum latency.

18 min read

Mojo Python Acceleration: SIMD Optimization and Parallel Processing for AI Workloads

Learn how to leverage Mojo's native SIMD vectorization and parallel processing capabilities to achieve 10-50x speedup over scalar Python loops for AI workloads while maintaining Python's development velocity.

9 min read

RAG Evaluation Pipeline: Implementing Ragas and TruLens for LLM Output Quality Metrics

A practical guide to evaluating RAG systems using Ragas for batch evaluation and TruLens for real-time observability, covering the RAG triad metrics, implementation patterns, and production-ready feedback functions.

12 min read

Master HNSW Parameter Tuning for Billion-Scale Vector Search in Milvus and Pinecone

Learn how to optimize HNSW index parameters for billion-scale vector search deployments, with practical configurations for Milvus and Pinecone that balance recall, latency, and memory.

12 min read

Mastering AI Model Deployment: Blue-Green, Canary, and A/B Testing Strategies

Learn three essential deployment patterns for ML models—Blue-Green, Canary, and A/B Testing—with practical examples on traffic routing, rollback mechanisms, and infrastructure requirements.

3 min read

Building Memory Systems for LLM Applications: Context Management Best Practices

Learn architectural patterns for implementing robust memory systems in LLM-based applications. Master context window management, vector databases, and RAG techniques for coherent long-term AI conversations.

10 min read

Scale Vector Search with FAISS and Milvus: Production Implementation Guide

Learn to implement production-grade vector similarity search using FAISS for in-memory indexing and Milvus for distributed database capabilities. Covers index selection, GPU acceleration, and scaling strategies for RAG and semantic search applications.

7 min read

LangChain vs LlamaIndex: Which LLM Framework Should You Choose?

Compare LangChain's action-centric orchestration for multi-tool agents with LlamaIndex's data-centric RAG capabilities to choose the right framework for your AI project.

7 min read

Multi-Modal AI Integration: A Complete Guide to Text, Image, and Audio Systems

Master the architecture and implementation of multi-modal AI systems that integrate text, images, and audio into unified models. Learn joint embedding spaces, cross-modal attention, fusion strategies, and deployment techniques for building robust applications.

6 min read
Microservices & Distributed Systems

Gleam on BEAM: Building Type-Safe, Fault-Tolerant Distributed Systems

Learn how Gleam combines Hindley-Milner type inference with Erlang's actor-based concurrency model to build systems that are both compile-time safe and runtime fault-tolerant. Covers OTP integration, supervision trees, and seamless interoperability with the BEAM ecosystem.

5 min read

eBPF Networking: High-Performance Policy Enforcement, Traffic Mirroring, and Load Balancing

Master kernel-level networking with eBPF: implement XDP firewalls, traffic mirroring for observability, and Maglev load balancing with Direct Server Return for production-grade infrastructure.

18 min read

Java Performance Mastery: Complete JVM Tuning Guide for Production Systems

Master Java performance optimization with comprehensive JVM tuning, garbage collection algorithms, and memory management strategies for production microservices and distributed systems.

14 min read

Building Resilient Distributed Systems: Circuit Breakers, Bulkheads, and Retry Patterns Explained

Master three essential patterns to prevent cascading failures and maintain system stability. Learn how to implement circuit breakers, bulkheads, and retry strategies with practical JavaScript examples.

5 min read

Redis vs Memcached vs Hazelcast: The Ultimate Distributed Caching Guide

Compare Redis, Memcached, and Hazelcast architectures, features, and use cases to choose the right distributed caching solution for your application's performance and scalability needs.

4 min read

Event Sourcing vs CQRS: A Practical Guide to Choosing the Right Architecture Pattern

Learn when to use Event Sourcing, CQRS, or both in your distributed systems. This guide breaks down the trade-offs, use cases, and implementation strategies for these powerful architectural patterns.

3 min read

Master Microservices Architecture: Service Boundaries, Data Ownership, and Communication Patterns

Learn the three critical design decisions that determine microservices success: defining service boundaries using DDD, managing distributed data ownership, and selecting the right communication patterns for scalable systems.

6 min read

API Gateway Showdown: Kong vs Ambassador vs AWS API Gateway for Microservices

Compare Kong, Ambassador, and AWS API Gateway across architecture, performance, security, and cost to choose the right gateway for your microservices.

12 min read

Serverless Architecture Patterns: Lambda vs Cloud Functions vs Vercel Edge Performance Comparison

Compare AWS Lambda, Google Cloud Functions, and Vercel Edge across architecture, cold starts, runtime constraints, and performance benchmarks to choose the right serverless platform for your use case.

5 min read

Istio vs Linkerd: Complete Service Mesh Comparison for Kubernetes Microservices

Compare Istio and Linkerd service mesh implementations across architecture, security, observability, and performance to choose the right solution for your microservices.

10 min read