Building Production-Ready RAG Systems: A Practical Guide
A comprehensive guide to building robust Retrieval-Augmented Generation (RAG) systems. Covers chunking strategies, hybrid search, embedding models, and production pitfalls.
Full-stack developer, AI/ML Engineer, and open-source maintainer building developer-first tools, software, and AI applications.
A comprehensive guide to building robust Retrieval-Augmented Generation (RAG) systems. Covers chunking strategies, hybrid search, embedding models, and production pitfalls.
A guide to transitioning machine learning models from Jupyter notebooks to scalable production services using FastAPI, Docker, and Kubernetes.
A technical overview of fine-tuning methodology, focusing on Parameter-Efficient Fine-Tuning (PEFT), LoRA, and dataset preparation strategies.
An analysis of current autonomous agent frameworks, exploring planning capabilities, tool use, and the shift from chat interfaces to goal-directed behavior.
A comprehensive guide to running Large Language Models locally. We analyze hardware requirements, quantization techniques, and inference engines.
A technical overview of Logly v0.1.0, a thread-safe, modular logging library for the Zig ecosystem focusing on performance and developer ergonomics.
A comparative analysis of memory safety strategies. We contrast Rust's compile-time formal verification with Zig's approach of explicit memory management and runtime defenses.
A technical guide to Prompt Engineering strategies, including Chain-of-Thought, Few-Shot prompting, and structural constraints for reliable LLM integration.
Leveraging Rust and WebAssembly (Wasm) to offload compute-intensive tasks from the JavaScript main thread. Includes benchmarks and implementation patterns.
An introduction to the themes of this blog: AI Engineering, Systems Programming, and High-Performance Computing.
An analysis of the transition from efficient scripting (Python) to high-performance systems programming (Zig). Includes performance benchmarks and a comparison with Rust.