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Cloud & Infrastructure
Google Cloud Blog·Jun 16·5 min read
How Siemens "slices the elephant," advancing agentic workflows for industrial software development
TL;DR
Siemens faced the challenge of modernizing complex industrial software, which is hindered by legacy code and existing AI tools lacking contextual understanding. To address this, they developed Knowledge Fabric, an AI system utilizing knowledge graphs and various Google Cloud technologies to automate the software development lifecycle.
✦ Why It Matters
Engineers can leverage Knowledge Fabric to enhance productivity and focus on innovative problem-solving in complex software environments.
Key Takeaways
- Explore using Knowledge Fabric for automating software development tasks.
- Implement graph-based AI to manage complex code relationships.
- Break down large projects into smaller tasks for better efficiency.
- Focus on customer value by reducing time spent on repetitive coding.
How It Works
Knowledge Fabric employs knowledge graphs to model the structure of codebases, linking code snippets to design requirements. It uses Spanner Graph for efficient querying and generates embeddings for semantic understanding, allowing AI agents to answer complex queries about code dependencies.
By combining these methods, the system enables precise impact analysis and supports a workflow where specialized agents handle different aspects of software development.