We’re changing how people contribute to goose by moving design and discussion into issues before agents turn ready issues into code.

Benchmarks are most useful when they become bug reports. Here's how the goose team uses Terminal-bench failures, Harbor, and human judgment to improve real agent behavior.

goose now supports lifecycle hooks via the Open Plugins spec. Wire shell scripts into PreToolUse, PostToolUse, UserPromptSubmit, SessionStart, and more.

Use goose to coordinate multi-agent workflows — decompose complex tasks, delegate to specialized agents in parallel, and synthesize the results.

Using goose with MiniMax M2.5 on the Databricks OfficeQA benchmark

The Computer Controller extension was rebuilt with Peekaboo, giving goose the ability to see, click, type, and interact with any application on your Mac.

goose now ships with built-in local inference powered by llama.cpp — no server, no API key, no cost. Here's how it works and what to expect.

Mesh LLM is now available as a provider setting in goose.

We're shipping a new TUI, rewriting the desktop app in Tauri, and unifying everything under ACP.

ACP lets you keep your favorite editor but swap the AI agent, or keep your agent but use it from any editor. Here's what actually works today in Goose.

goose has moved to the Agentic AI Foundation (aaif) at the Linux Foundation

Introducing adversary mode — an independent agent reviewer that silently watches the main agent to keep it away from danger.

A quick update on using subscriptions for claude, gemini and codex

WebMCP lets websites expose structured actions that AI agents can call directly. This guide explains how it works, how it differs from MCP and browser automation, and how to build your own WebMCP-enabled site.

Use the Neighborhood extension in goose to discover nearby restaurants, browse interactive menus, and place a takeout order, all from a simple chat prompt.

Introducing a privacy-first, local AI home assistant powered by Goose on edge hardware.

goose v1.25.0 brings macOS sandboxing, a unified summon extension, rich MCP app UIs, agentic CLI upgrades, and SLSA build provenance.

Learn how Gas Town and Goosetown lead the industrial coding revolution by teaching AI agents to work together in a team. This beginner guide explains the infrastructure we're using to move from talking to one AI to coordinating many agents at once.

Practical steps and mental models for building context engineered workflows instead of clever prompts.

Discover how Code mode reduces context rot and token usage in AI agents making them more efficient for long running sessions.

A goose skill that measures the cognitive complexity of your AI collaboration using the Gas Town × DOK framework.