OpenBMB/PilotDeck

What it solves

PilotDeck is a task-oriented AI agent productivity platform designed for long-running, multi-project work. It addresses common agent limitations such as "black-box" memory (where users cannot see or edit what the AI remembers), high token costs when using flagship models for simple tasks, and the inability of agents to work autonomously in the background while the user is away.

How it works

The platform is organized around "WorkSpaces," which isolate files, memory, and skills for each project to prevent context pollution. It employs three core mechanisms:

• White-box Memory: Makes memory generation, extraction, and retrieval visible and editable, allowing users to fix incorrect memories and rollback states via a "Dream Mode."
• Smart Routing: Automatically detects task difficulty and routes complex requests to flagship models (e.g., Claude 3.5 Sonnet) and simpler tasks to lighter models to reduce costs.
• Always-on Execution: Enables agents to proactively discover tasks, monitor progress, and deliver results as local files without constant user prompting.

It natively supports the Model Context Protocol (MCP) and provides a Web UI, CLI, and IM integration.

Who it’s for

It is built for users engaged in complex, multi-task productivity work, such as AI engineering, mini-game development, and social media operations, who need a traceable and cost-effective agent system.

Highlights

• WorkSpace Isolation: Dedicated file systems and memory stores per project.
• Traceable Memory: End-to-end visibility and manual editing of memory entries.
• Cost Optimization: Smart routing that can reduce token spend by up to 70% on specific workloads.
• Background Autonomy: Ability to run long-horizon monitors and land deliverables as files on disk.
• Extensible Architecture: Native MCP support and a plugin system for custom tools, skills, and memory stores.