Prompt Configuration Feature

Overview

The AI Platform Engineering Helm chart now supports flexible prompt configuration, allowing users to choose between predefined orchestration behaviors or provide custom configurations.

Feature Components

1. Configuration Files

The chart includes two predefined prompt configurations:

• data/prompt_config.yaml - Default configuration

  • Standard multi-agent orchestrator
  • Balanced between flexibility and control
  • Maintains strict provenance and source attribution
  • Best for: Development, testing, general platform operations

• data/prompt_config.deep_agent.yaml - Deep Agent configuration

  • Strict zero-hallucination mode
  • Enhanced provenance tracking
  • Enforces tool-only responses
  • Best for: Production, compliance, mission-critical systems

2. Helm Values Configuration

Two new values control prompt behavior:

# Select predefined configuration
promptConfigType: "default"  # Options: "default" or "deep_agent"

# Or provide custom configuration (overrides promptConfigType)
promptConfig: ""

3. Template Logic

The templates/prompt-config.yaml template implements a three-tier configuration hierarchy:

1. Custom override (promptConfig) - Highest priority
2. Deep Agent (promptConfigType: "deep_agent") - Second priority
3. Default (promptConfigType: "default") - Fallback

Usage Examples

Example 1: Deploy with Default Configuration

helm install ai-platform charts/ai-platform-engineering/ \
  --set promptConfigType=default

Example 2: Deploy with Deep Agent Configuration

helm install ai-platform charts/ai-platform-engineering/ \
  --set promptConfigType=deep_agent

Example 3: Deploy with Custom Configuration

Create a custom values file:

# custom-prompt-values.yaml
promptConfig: |
  agent_name: "Custom Platform Agent"
  agent_description: |
    Specialized agent for custom workflows
  system_prompt_template: |
    Custom system prompt...
  agent_prompts:
    argocd:
      system_prompt: "Custom ArgoCD routing..."
    # ... additional configuration

Deploy:

helm install ai-platform charts/ai-platform-engineering/ \
  --values custom-prompt-values.yaml

Example 4: Switch Configuration on Upgrade

# Upgrade from default to deep_agent
helm upgrade ai-platform charts/ai-platform-engineering/ \
  --set promptConfigType=deep_agent

Configuration Comparison

Feature	Default	Deep Agent	Custom
Zero-hallucination	Enforced	Strictly enforced	User-defined
Provenance tracking	Standard	Enhanced	User-defined
Tool response handling	Verbatim forwarding	Verbatim + validation	User-defined
Complexity	Low	Low	High
Customizability	None	None	Full
Use case	General	Mission-critical	Specialized

Key Differences Between Default and Deep Agent

Default Configuration

• Agent Name: "AI Platform Engineer"
• Focus: Balanced orchestration with standard compliance
• Behavioral Model: Standards-compliant orchestrator
• Validation: ComplianceGuard and Aggregator meta-agents
• Response Style: Professional, markdown-formatted with provenance

Deep Agent Configuration

• Agent Name: "AI Platform Engineer — Deep Agent"
• Focus: Maximum adherence to zero-hallucination principles
• Behavioral Model: Deep Agent Orchestrator with strict tool-only mode
• Validation: Enhanced provenance validation and source verification
• Response Style: Structured, highly traceable with explicit source attribution
• Additional Features:
  • Explicit "Source-of-Truth Policy"
  • Stricter routing logic with RAG-first fallback
  • Enhanced tool-response handling rules
  • Explicit behavior model separation (tool-only vs RAG modes)

Implementation Details

Template Hierarchy

data:
  prompt_config.yaml: |
{{- if .Values.promptConfig }}
  # Use custom configuration (highest priority)
{{ .Values.promptConfig | nindent 4 }}
{{- else if eq .Values.promptConfigType "deep_agent" }}
  # Use deep agent configuration
{{ .Files.Get "data/prompt_config.deep_agent.yaml" | nindent 4 }}
{{- else }}
  # Use default configuration (fallback)
{{ .Files.Get "data/prompt_config.yaml" | nindent 4 }}
{{- end }}

Configuration Loading

1. Check if promptConfig is set → Use custom configuration
2. Check if promptConfigType equals "deep_agent" → Load prompt_config.deep_agent.yaml
3. Otherwise → Load default prompt_config.yaml

Testing

All three configuration modes have been tested:

# Test default
helm template test charts/ai-platform-engineering/ \
  --set promptConfigType=default | grep agent_name

# Test deep_agent
helm template test charts/ai-platform-engineering/ \
  --set promptConfigType=deep_agent | grep agent_name

# Test custom
helm template test charts/ai-platform-engineering/ \
  --set-string 'promptConfig=agent_name: "Custom"' | grep agent_name

Backward Compatibility

This feature is fully backward compatible:

• Existing deployments without promptConfigType will use "default"
• The original promptConfig override mechanism is preserved
• No breaking changes to existing chart functionality

Best Practices

Development and Testing

promptConfigType: "default"

Production Deployments

promptConfigType: "deep_agent"

Specialized Workflows

promptConfig: |
  # Custom configuration
  ...

Documentation

• Chart README: /charts/ai-platform-engineering/README.md
• Example Values: /charts/ai-platform-engineering/values-prompt-examples.yaml
• Default Config: /charts/ai-platform-engineering/data/prompt_config.yaml
• Deep Agent Config: /charts/ai-platform-engineering/data/prompt_config.deep_agent.yaml

Future Enhancements

Potential future additions:

• Additional predefined configurations for specific use cases
• Configuration validation and schema enforcement
• Dynamic configuration switching without pod restart
• Configuration metrics and observability