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Peter Eichhorst
Peter Eichhorst

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Creating Hierarchical AI Assistant Contexts: Global vs. Project-Specific Configurations

#agents #ai #llm #architecture

Introduction

This article stems from a real challenge I encountered while developing and managing an AI assistant that needed to operate effectively across multiple contexts. The problem emerged when the same assistant needed to handle both general system administration tasks and highly specialized project work within specific codebases.

Initially, the AI assistant would experience "context confusion" - responding with general knowledge when working on specialized projects, or applying project-specific rules inappropriately to general tasks. This led to inconsistent behavior and reduced effectiveness.

The solution I developed involved creating a robust separation and hierarchy between global and project-specific AI assistant configurations, ensuring context-aware behavior without confusion. This approach allows the assistant to maintain its core safety and operational principles while specializing its behavior based on the current project context.

The Problem: Context Confusion

Without proper configuration hierarchies, AI assistants can experience identity confusion when switching between different scopes of work. For example, an assistant might respond with general system administration knowledge when working on a specific software project, or vice versa. This leads to inconsistent behavior and reduced effectiveness.

Solution Overview

The solution involves creating layered configuration files that establish clear priority and context-switching mechanisms:

  1. Global Configuration - Base rules that apply everywhere
  2. Project-Specific Configuration - Specialized rules for individual projects
  3. Dynamic Context Detection - Automatic switching based on current directory
  4. Clear Hierarchy - Well-defined priority when conflicts arise

Implementation Strategy

1. Global Configuration Foundation

The global configuration serves as the base layer with essential rules that apply universally:

## Every Session Protocol
1. Read core identity files (SOUL.md, USER.md)
2. Load memory context
3. Check for project-specific configs in current directory
4. Apply project rules with priority when applicable
5. Report current directory context when relevant
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2. Project-Specific Configuration

Each project maintains its own configuration files that specialize the assistant's behavior:

  • SOUL.md: Project-specific personality and priorities
  • IDENTITY.md: Role-specific identity and communication style
  • USER.md: Project team members and their preferences
  • AGENTS.md: Project-specific workflows and processes

3. Dynamic Context Detection

The assistant should automatically detect and adapt to the current project context:

// Pseudocode for context detection
if (current_directory.has_project_configs()) {
  const projectIdentity = loadProjectIdentity(current_directory);
  const globalRules = loadGlobalRules();
  return mergeConfigs(projectIdentity, globalRules, priority="project");
} else {
  return loadGlobalRules();
}
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4. Clear Hierarchy and Conflict Resolution

Establish explicit rules for handling conflicts between global and project-specific directives:

  • Development Tasks: Project rules take priority
  • Safety/Ethics: Global safety rules always take precedence
  • Operational Tasks: Apply both sets of rules appropriately
  • Identity Questions: Present project role first, then general capabilities

Best Practices

1. Consistent File Structure

Maintain the same configuration file structure across all projects:

  • SOUL.md (personality and values)
  • IDENTITY.md (specific role definition)
  • USER.md (team member information)
  • AGENTS.md (workflow and processes)
  • MEMORY.md (important project notes)

2. Explicit Context Reporting

Always be transparent about which context you're operating in:

  • Report current directory when relevant
  • Clarify your role based on context
  • Explain when switching between contexts

3. Seamless Transitions

Design the system so context switches feel natural:

  • Detect context changes automatically
  • Apply appropriate rules without user intervention
  • Maintain continuity across context switches

4. Safety-First Approach

Ensure that safety and ethical guidelines remain consistent:

  • Global safety rules override project-specific rules
  • Maintain privacy protections regardless of context
  • Preserve core ethical constraints

Benefits of This Approach

  1. Context-Aware Behavior: The assistant adapts its responses based on the current project
  2. Reduced Confusion: Clear identity and role definition prevents context mixing
  3. Scalability: Easy to add new projects with their own specialized configurations
  4. Consistency: Core safety and operational principles remain intact
  5. Flexibility: Can handle both specialized and general tasks effectively

Real-World Example

Consider an AI assistant working on both system administration and a specific web application:

  • In global context: Focus on system operations, file management, general productivity
  • In web app project: Focus on coding, testing, deployment, project-specific workflows
  • Identity: Always explain both general capabilities and project-specific role
  • Safety: Same security and privacy measures apply in both contexts

Conclusion

Creating a hierarchical AI assistant configuration system allows for both specialized project work and general utility while maintaining clear boundaries and preventing context confusion. By establishing proper separation with intelligent hierarchy, assistants can be both highly effective in specific domains and reliable in general tasks.

The key is to design the system with automatic context detection, clear priority rules, and seamless transitions that enhance rather than complicate the user experience.

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