ZCode
ZCode is an Agentic Development Environment built to bring GLM-5.2 into real coding workflows, combining the best AI agents with existing tools so developers can plan, code, review, and deploy without friction. It is designed for long-context, long-horizon, and agentic coding tasks, helping users move from requirement understanding to implementation, verification, and review inside one stable desktop workspace. ZCode Agent is the default self-developed agent framework, deeply integrated with tasks, models, permissions, file references, execution modes, Git branch state, and commit flow, making it a strong fit for everyday development, task breakdown, multi-file edits, debugging, testing, project preview, and continuous project work. Built around GLM-5.2, ZCode keeps goals, files, terminal results, browser context, execution modes, and Git state in the same task, so complex work can continue without losing continuity.
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Laguna S 2.1
Laguna S 2.1 is an open weight agentic coding model designed to pursue longer-horizon work and make effective use of reasoning. It uses a 118-billion-parameter Mixture-of-Experts architecture with 8 billion active parameters per token and supports a context window of up to one million tokens in both thinking and no-thinking modes. Its compact active size makes it suitable for complex work on local machines while remaining competitive with models many times larger on terminal, software-engineering, codebase-question-answering, and tool-use benchmarks. Laguna S 2.1 is built to keep working through difficult tasks with greater persistence, verification, and willingness to backtrack instead of declaring success too early. In demonstrated runs, it built and validated a browser rendering engine from an empty folder, optimized an agent harness for faster execution and substantially lower memory allocation, and completed extended mathematical research using the tools in its environment.
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Muse Code
Muse Code is Meta’s terminal coding agent, powered by Muse Spark 1.2, for handling complex software engineering tasks across large repositories. The agent can plan changes, write code, validate results, and coordinate multiple persistent subagents during development sessions. Muse Code uses async background agents that stay active throughout a session to reduce repeated information gathering and help complete multi-step tasks with less steering. Its runtime uses a local event log that records model calls, tool runs, approvals, and edits so sessions can be replayed and resumed after failures. Muse Code includes bundled skills such as /plan for approval-gated planning, /grill for stress-testing plans, and /goal for working toward completion. Built for AI developers and software teams, Muse Code helps automate coding workflows, long-running engineering tasks, debugging, and repository-level development.
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iFlow
iFlow is an AI-powered development and productivity platform centered around its terminal-based assistant, iFlow CLI, which enables users to interact with advanced AI models directly within their command-line environment to automate coding, analysis, and workflow execution. It is designed to understand entire codebases, interpret contextual requirements, and execute tasks ranging from simple file operations to complex multi-step automation, all driven through natural language rather than traditional commands. It integrates multiple state-of-the-art AI models, allowing users to access capabilities such as code generation, debugging, documentation, and optimization within a single interface, while maintaining compatibility with existing tools and environments like Visual Studio Code, JetBrains IDEs, and CI/CD pipelines. A key feature of the platform is its multi-agent architecture, where specialized “SubAgents” collaborate to break down and handle complex tasks in parallel.
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