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Course Outline

Introduction to DeepSeek Harness

  • Overview of DeepSeek Harness and its role in the ecosystem
  • The "everything is a plugin" design approach
  • Web UI, CLI, and headless operating modes

Installation and Initial Setup

  • Node.js requirements and package installation
  • Starting the Web UI using npx
  • Compiling and running from source code

Model Configuration

  • Configuring the DeepSeek API key
  • Selecting and switching between models
  • Integrating OpenAI-compatible endpoints

Workspaces and Sessions

  • Selecting and switching between workspaces
  • Using the session composer and managing conversation flow
  • Reading, modifying, and generating files

Executing Coding Tasks

  • Summarizing repositories and navigating codebases
  • Running commands and delegating specific tasks
  • Maintaining and updating task plans

Permissions and Sandboxing

  • Approval workflows and permission policies
  • Restricting file and command access
  • Configuring local and remote sandbox backends

Native Tools and Integrations

  • Filesystem, terminal, and shell utilities
  • Support for the Model Context Protocol
  • Integration with the Language Server Protocol

Subagents and Task Delegation

  • Creating and forking subagents
  • Connecting to providers for other coding agents
  • Distributing work across a session

The Cordis Plugin Model

  • Plugins defined as services, events, and effects
  • Shared context and lifecycle management
  • The absence of a privileged core structure

Profiles, Bundles, and Configuration

  • Layering profiles and bundles
  • Modifying configuration via cordis.patch.yml
  • Reviewing the initialized component tree

Core Subsystems

  • The append-only session logging mechanism
  • Assembling system prompts and tool schemas
  • The agent loop and turn processing flow

Events and Extension Hooks

  • Session, agent, and capability events
  • Waterfall and interceptor event handling
  • Aligning behavior with specific extension points

Plugin Development

  • Registering services under context keys
  • Incorporating custom tools and model adapters
  • Releasing and discovering plugins

SDK, Headless Mode, and Automation

  • Controlling the harness from external processes
  • Utilizing TypeScript and Python SDKs
  • Automating via CLI and headless workflows

Requirements

  • Foundational knowledge of software development principles
  • Proficiency with command line tools and Git
  • Basic familiarity with JavaScript or TypeScript

Target Audience

  • Software developers
  • AI and machine learning engineers
  • DevOps and platform engineers
 14 Hours

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