AI Coding

The Python ecosystem this month is dominated by Claude Skills and AI agent tooling. This overview analyzes the top trending Python repositories on GitHub.

The Rust ecosystem is exploding with innovative projects, particularly in AI coding tools and terminal applications. This overview analyzes the top trending Rust repositories on GitHub this month.

The Go ecosystem continues to thrive with innovative projects spanning AI tooling, self-hosted applications, and developer infrastructure. This overview analyzes the top trending Go repositories on GitHub this month.

The NVIDIA DGX Spark (GB10 Grace Blackwell) is now available in Australia at major PC retailers with local stock. If you’ve been following the global DGX Spark pricing and availability, you’ll be interested to know that Australian pricing ranges from $6,249 to $7,999 AUD depending on storage configuration and retailer.

Token optimization is the critical skill separating cost-effective LLM applications from budget-draining experiments.

The Model Context Protocol (MCP) is revolutionizing how AI assistants interact with external data sources and tools. In this guide, we’ll explore how to build MCP servers in Python, with examples focused on web search and scraping capabilities.

NVIDIA DGX Spark is real, on sale Oct 15, 2025, and targeted at CUDA developers needing local LLM work with an integrated NVIDIA AI stack. US MSRP $3,999; UK/DE/JP retail is higher due to VAT and channel. AUD/KRW public sticker prices are not yet widely posted.

This guide provides a comprehensive overview of available Go SDKs for Ollama and compares their feature sets.

Here is a comparison between Qwen3:30b and GPT-OSS:20b focusing on instruction following and performance parameters, specs and speed:

In this post, we’ll explore two ways to connect your Python application to Ollama: 1. Via HTTP REST API; 2. Via the official Ollama Python library.

Ollama’s GPT-OSS models have recurring issues handling structured output, especially when used with frameworks like LangChain, OpenAI SDK, vllm, and others.

Here’s a side-by-side support comparison of structured output (getting reliable JSON back) across popular LLM providers, plus minimal Python examples

Large Language Models (LLMs) are powerful, but in production we rarely want free-form paragraphs. Instead, we want predictable data: attributes, facts, or structured objects you can feed into an app. That’s LLM Structured Output.

Here is an up-to-date GitHub Copilot cheat sheet, covering essential shortcuts, commands, usage tips, and context features for Visual Studio Code and Copilot Chat

Here we have a description of The Model Context Protocol (MCP), short notes on how to implement an MCP server in Go, including message structure, protocol specifications.

Since standard Ollama doesn’t have a direct rerank API, you’ll need to implement reranking using Qwen3 Reranker in GO by generating embeddings for query-document pairs and scoring them.