Deploying a Hugo static site to AWS S3 using the AWS CLI provides a robust, scalable solution for hosting your website. This guide covers the complete deployment process, from initial setup to advanced automation and cache management strategies.

Dependency injection (DI) is a fundamental design pattern that promotes clean, testable, and maintainable code in Go applications.

Jumpstart the Jupyter Notebook productivity with essential shortcuts, magic commands, and workflow tips that will transform your data science and development experience.

With this crazy RAM prices volatility, to form and have a better picture, let’s track the RAM price in Australia ourselves first.

Table-driven tests are the idiomatic Go approach for testing multiple scenarios efficiently. When combined with parallel execution using t.Parallel(), you can dramatically reduce test suite runtime, especially for I/O-bound operations.

Ollama’s Python library now includes native OLlama web search capabilities. With just a few lines of code, you can augment your local LLMs with real-time information from the web, reducing hallucinations and improving accuracy.

Choosing the right vector store can make or break your RAG application’s performance, cost, and scalability. This comprehensive comparison covers the most popular options in 2024-2025.

Ollama’s Web Search API lets you augment local LLMs with real-time web information. This guide shows you how to implement web search capabilities in Go, from simple API calls to full-featured search agents.

The memory market is experiencing unprecedented price volatility in late 2025, with RAM prices surging dramatically across all segments.

API documentation is crucial for any modern application, and for Go APIs Swagger (OpenAPI) has become the industry standard. For Go developers, swaggo provides an elegant solution to generate comprehensive API documentation directly from code annotations.

Local deployment of LLMs has become increasingly popular as developers and organizations seek enhanced privacy, reduced latency, and greater control over their AI infrastructure.

Modern Go development demands rigorous code quality standards. Linters for Go automate the detection of bugs, security vulnerabilities, and style inconsistencies before they reach production.

Python linters are essential tools that analyze your code for errors, style issues, and potential bugs without executing it. They enforce coding standards, improve readability, and help teams maintain high-quality codebases.

Line ending inconsistencies between Windows and Linux systems cause formatting issues, Git warnings, and script failures. This comprehensive guide covers detection, conversion, and prevention strategies.

Let’s compare prices for top-level consumer GPUs, that are suitable for LLMs in particular and AI in general. Specifically I’m looking at RTX-5080 and RTX-5090 prices.

As AI and ML workloads become increasingly complex, the need for robust orchestration systems has become greater. Go’s simplicity, performance, and concurrency makes it an ideal choice for building the orchestration layer of ML pipelines, even when the models themselves are written in Python.