Local Micro-Agents That Observe, Log and React. Build powerful micro-agents that observe your digital world, remember what matters, and react intelligently—all while keeping your data 100% private and secure.
A roundup of four lightweight Python utilities that automate common annoyances—sorting your Downloads folder, quickly logging timestamped notes, cleaning tracking parameters from copied URLs, and logging intermittent internet outages—each presented with source code and usage tips.
Plural is bringing AI into the DevOps lifecycle with a new release that leverages a unified GitOps platform as a RAG engine. This provides AI-powered troubleshooting, natural language infrastructure querying, autonomous upgrade assistance, and agentic workflows for infrastructure modification, all with enterprise-grade guardrails.
Jules Tools has quietly joined Gemini CLI and GitHub Actions in Google's lineup. This article details how these command-line agents differ and provides examples of their use.
An article detailing the author's experience replacing bash scripts with Python, outlining the improvements in readability, error handling, and testability, as well as the challenges encountered during the migration.
Agentic AI is beginning to reshape malware detection and broader security operations. These systems are being used not to replace humans, but to take on the lower value jobs that have historically tied up analysts — from triaging alerts to reverse-engineering suspicious files.
TraceRoot.AI is an AI-native observability platform that helps developers fix production bugs faster by analyzing structured logs and traces. It offers SDK integration, AI agents for root cause analysis, and a platform for comprehensive visualizations.
The article discusses 5 self-hosted services (NetBox, Harvester, Terraform, Ansible, and Kubernetes) that the author finds useful in their home lab despite being potentially overkill for typical setups. It details the benefits and use cases for each service, highlighting how they enhance the author's tinkering and learning experience.
This article discusses the potential shift away from traditional graphical user interfaces (GUIs) towards interaction with computers through AI agents and natural language processing. It argues that AI is eliminating the need for windows, menus, and clicks, allowing users to simply tell computers what they need.
This article details how to set up an email triage system using Home Assistant and a local Large Language Model (LLM) to summarize and categorize incoming emails, reducing inbox clutter and improving email management. It covers the setup of a REST command to interface with Ollama, the automation process, and the benefits of using a local LLM for privacy.
