Deft

Agent Deck is an open-source terminal dashboard for running and monitoring multiple AI coding agents in parallel. It displays each session’s status, active tool, working directory, and last prompt in real time, with Vim-style keyboard navigation for creating, focusing, closing, and renaming panes. It supports Claude Code and OpenCode through automatically installed hooks and runs as the single-binary `dot-agent-deck`, with native embedded terminal panes and no external terminal multiplexer required. The dashboard runs inside terminals including Ghostty, iTerm2, Alacritty, Kitty, and WezTerm, while preserving the agent clients’ existing shortcuts, skills, and configurations. Per-project TOML configuration can pair an agent with side panes for test runs, log tails, or `kubectl` watches. macOS and Linux installation is available through Homebrew, Nix, prebuilt binaries, or source builds; Windows use is currently through WSL. The project is distributed under the MIT license.

DeerFlow is an open-source long-horizon super-agent harness developed in the ByteDance repository. Built on LangGraph and LangChain, it orchestrates a lead agent with sub-agents, progressively loaded skills, memory, tools, and sandboxed execution environments for research, coding, file work, report generation, slide creation, web-page creation, and other multi-step tasks. The runtime provides a filesystem for uploads, workspaces, and outputs; configurable web search, web fetching, browser control, Bash and file tools; MCP servers; reusable Markdown-based skills; long-term memory; scheduled tasks; and messaging-app channels. Sub-agents receive scoped context, tools, and termination conditions, and can run bounded parallel work before returning structured results to the lead agent. Sandbox modes include local execution, isolated Docker containers, Kubernetes-backed execution, and E2B-based environments, depending on configuration. DeerFlow can run locally or with Docker Compose and exposes a Web UI and Gateway at the documented local address. Its setup wizard generates configuration for model providers, search, sandbox, Bash, and file-writing options; the project also documents integrations for LangSmith, Langfuse, and Monocle tracing, personal access tokens, custom agents, MCP background tasks, and extensible Python packages. Version 2.0 is a ground-up rewrite of the earlier 1.x Deep Research framework; active development is on the 2.0 line.

PI-Desktop is a local-first desktop workspace for AI coding agents, built with Electron, a Rust host core, and the pi Agent Harness. It lets users open local projects, connect cloud or local models through providers such as OpenAI-compatible APIs, manage projects and long-running sessions, and review file changes and command output. Its architecture separates the React renderer, Electron desktop orchestration, Rust-managed permissions, filesystem access, SQLite persistence and secrets, and a pi Agent sidecar responsible for the agent loop, model interaction, and streaming. Agent, Plan, and Goal modes provide different approval boundaries; agents can read and edit files, run commands, and delegate exploration, implementation, research, testing, or review to background Subagents. The workspace supports MCP servers, Skills, installable Plugins, model and provider switching, session imports, notifications, context checkpoints, and a plugin marketplace. Conversations are stored locally as JSONL with a SQLite index, settings and logs remain on the machine, credentials use the operating-system keychain, and model requests go directly to the configured provider or endpoint. Plugin processes are permission-gated and isolated from the renderer, but plugins remain user-trusted code rather than a complete operating-system sandbox. It is an early-preview cross-platform application distributed for macOS, Windows, and Linux under the GNU Lesser General Public License v3.0.

CowAgent is an open-source AI assistant and agent harness developed by LinkAI. It plans complex tasks step by step, runs tools and skills, controls computers and external services, maintains long-term memory and a personal knowledge base, and supports multi-agent teams with separate roles, models, skills, knowledge, and workspaces. Its architecture routes messages from web and messaging channels through an agent core that reasons over available models, tools, skills, memory, and knowledge before returning a response. Memory uses a three-tier structure of conversation context, daily memory, and long-term MEMORY.md, with a nightly Deep Dream process that distills memories; the knowledge base is an automatically curated Markdown wiki with cross-references and a browsable knowledge graph. Built-in tools include file and terminal operations, web fetching and search, scheduling, memory retrieval, vision, and browser automation, while MCP servers can be added through configuration. Skills can be installed from the Skill Hub, GitHub, ClawHub, or URLs, or authored through conversation. CowAgent supports multiple LLM providers and routes chat, vision, image generation, speech, and embedding workloads separately. It can run locally, in Docker, on a server, or through its macOS and Windows desktop client, with a web console for configuration and a command-line interface for service and skill management. The project is licensed under the MIT License and was formerly named chatgpt-on-wechat.

An AI software engineering agent developed by Cognition that runs isolated cloud coding sessions, writes and modifies code, and can test applications through a browser. Devin is designed as an end-to-end software-development environment for planning and implementing coding tasks. Vals evaluated it internally and increased its adoption after finding it to be token-efficient.