🚨 Claude Code costs $200/month. GitHub Copilot costs $19/month. Jack Dorsey's company built a free alternative. 35,000 GitHub stars. It's called Goose. An open source AI agent built by Block that goes beyond code suggestions. It installs, executes, edits, and tests. With any LLM you choose. Not autocomplete. Not suggestions. A full autonomous agent that takes actions on your computer. No vendor lock-in. No monthly subscription. Bring your own model. Here's what Goose does: → Works with ANY LLM. Claude, GPT, Gemini, Llama, DeepSeek, Ollama. Your choice. → Reads and understands your entire codebase → Writes, edits, and refactors code across multiple files → Runs shell commands and installs dependencies → Executes and debugs your code automatically → Extensible through MCP. Connect it to any external tool. → Desktop app, CLI, and web interface. Pick your workflow. → Written in Rust. Fast. Lightweight. No bloat. Here's the wildest part: Block is a $40 billion company. They built Cash App, Square, and TIDAL. They use Goose internally. Then they open sourced the entire thing. This isn't a side project from a random developer. This is production-grade tooling from a company that processes billions in payments. Built for their own engineers. Given to everyone. Claude Code: $200/month. Locked to Claude. GitHub Copilot: $19/month. Locked to GitHub. Cursor: $20/month. Locked to their editor. Goose: Free. Any LLM. Any editor. Any workflow. Forever. 35.3K GitHub stars. 3.3K forks. 4,078 commits. Built by Block. 100% Open Source. Apache 2.0 License.

🚨 ByteDance (the company behind TikTok) just open sourced an AI SuperAgent that can research, code, build websites, create slide decks, and generate videos. All by itself. It's called DeerFlow. Give it a task that would take you hours. It breaks it down, spawns sub-agents, and delivers the finished result. Not a chatbot. Not a copilot. An AI employee with its own computer, filesystem, and memory. Here's why this is different from every other AI agent: It has its own sandbox. A real isolated Docker container with a full filesystem. It reads files, writes files, executes code, runs bash commands. It doesn't just suggest things. It actually does them. No other agent framework gives the AI its own actual computer. Here's what it can do out of the box: → Deep research across the entire web with cited sources → Generate full reports with charts and analysis → Build complete websites and web apps → Create slide decks from scratch → Generate images and videos → Run Python scripts in its sandbox → Spawn sub-agents that work in parallel on different parts of a task → Remember your preferences, writing style, and workflows across sessions Here's how it handles complex tasks: You say "Research the top 10 AI startups in 2026 and build me a presentation." DeerFlow's lead agent breaks that into sub-tasks. One sub-agent researches each company. Another collects funding data. Another finds competitor analysis. They all run in parallel. Results converge. A final agent builds the slide deck with generated visuals. One prompt. Multiple agents. Complete deliverable. Here's the wildest part: It started as a simple deep research tool. Then the community started using it to build data pipelines, automate content workflows, spin up dashboards, and create full applications. ByteDance realized it wasn't a research tool anymore. It was a SuperAgent harness. So they rewrote it from scratch. DeerFlow 2.0 hit #1 on GitHub Trending on launch day. Works with GPT-4, Claude, Gemini, DeepSeek, Ollama, or any OpenAI-compatible API. Skills load progressively. Only what the task needs, when it needs it. No context window bloat. 22.7K GitHub stars. 2.7K forks. 1,531 commits. Hit #1 on GitHub Trending. 100% Open Source. MIT License.