Enterprise Case Study: Oracle Application Modernisation

Background

A mission-critical Oracle application operates in a high-security, near-airgapped environment with extensive system interfaces. The application faces:

• Planned migration to Oracle Cloud Infrastructure

• Numerous integration points with other systems via PL/SQL-based file generation and consumption

• An aging workforce with specialized knowledge approaching retirement

• A significant knowledge gap between experienced engineers and newer team members

• Industry-wide shortage of PL/SQL expertise (only 0.15% of developers per TIOBE index)

The modernization effort requires deep understanding of existing PL/SQL code, system integrations, and custom modifications beyond the core application.

Challenges

Knowledge Preservation

• Critical system knowledge concentrated in retirement-eligible workforce

• Limited documentation of system customizations and integration points

• Risk of knowledge loss during transition to OCI

Technical Complexity

• Extensive PL/SQL codebase requiring analysis and possible refactoring

• Multiple system interfaces to maintain during migration

• Security constraints limiting access to external resources

Skill Shortage

• Extreme scarcity of PL/SQL developers in the market

• Learning curve for newer team members to understand legacy system

• Difficulty recruiting replacement expertise

AI-Assisted Modernization Approach

The organization explored AI-based solutions to accelerate understanding of the legacy system and support the modernization effort, including:

1. Oracle Code Assist for legacy code analysis and new code generation using the Vibe Coding Framework

2. Air-gapped AI deployment using LM Studio or Ollama with specialized LLMs for PL/SQL analysis

3. Hardware options including NVIDIA DGX GB10 or dual NVIDIA 4090 GPU configurations to support approximately 20 users

4. AI interface considerations such as Open WebUI with Active Directory integration

Implementation Plan

Phase 1: Secure AI Environment Setup

The organization implemented an air-gapped AI solution with the following components:

Hardware Configuration

After careful evaluation, the team selected the NVIDIA DGX GB10 platform for its:

• Enterprise-grade security features aligning with the high-security environment

• Optimized performance for large language models

• Support for multiple concurrent users

• Pre-configured AI software stack reducing deployment time

Software Implementation

• Deployed Ollama for model hosting

• Configured Text Generation WebUI with Active Directory integration

• Implemented strict access controls aligned with existing security policies

LLM Selection and Configuration

• Primary: CodeLlama 34B with GGUF quantization for code understanding

• Secondary: WizardCoder for specialized PL/SQL analysis

• Models were validated with sample PL/SQL code before full deployment

Phase 2: Framework-Guided Knowledge Capture

The team applied the Vibe Coding Framework's Documentation Standards to systematically capture knowledge from retiring engineers:

D.O.C.S. Methodology Implementation

• Design Decisions: Documented architectural choices in PL/SQL implementations

• Operational Context: Mapped integration points and system dependencies

• Code Understanding: Created explanations of complex PL/SQL procedures

• Support Information: Developed troubleshooting guides and known issue documentation

Interface Documentation

• Created comprehensive interface catalog using the framework's Documentation Generator

• Applied S.C.A.F.F. prompt structure to generate detailed interface specifications

• Verified documentation accuracy through the V.E.R.I.F.Y. protocol

Phase 3: AI-Augmented Training Program

The team developed a structured knowledge transfer program leveraging framework components:

Curriculum Development

• Created modular training based on the captured knowledge

• Developed progression path from basic PL/SQL to advanced system concepts

Mentorship Program

• Implemented the C.O.D.E.S. collaboration model for knowledge transfer

• Paired experienced engineers with junior staff in structured sessions

• Used AI tools to enhance and document collaboration

Phase 4: Oracle Code Assist Integration

Custom Extensions

• Developed PL/SQL-specific prompt templates using the S.C.A.F.F. methodology

• Created verification checklists aligned with the framework's Security Toolkit

• Implemented prompt libraries following framework standards

Security Enhancement

• Applied S.H.I.E.L.D. security methodology to all generated code

• Implemented Oracle-specific security scanning

Results

The implementation of the Vibe Coding Framework for this Oracle modernization project yielded significant benefits:

• Knowledge Preservation: 95% of critical system functionality documented

• Training Effectiveness: Junior team members achieved competency in 80% of system functions within 6 months

• Development Efficiency: 40% reduction in code analysis time

• Risk Reduction: Successfully mitigated knowledge loss risk from retiring engineers

Key Learnings

• AI-assisted knowledge capture proved most effective when structured using the framework's documentation standards

• The S.C.A.F.F. prompt structure required adaptation for PL/SQL-specific contexts

• The framework's verification protocols were essential for ensuring reliability in the security-sensitive environment

• The collaborative approach outlined in the C.O.D.E.S. model effectively bridged the knowledge gap between experienced and junior engineers

Conclusion

This case study demonstrates how the Vibe Coding Framework can be effectively applied to enterprise modernization initiatives, even in highly specialized and security-sensitive environments. The structured approach to AI-assisted development provided by the framework was instrumental in preserving critical knowledge, accelerating training, and reducing modernization risks.