Codebase Graphs: Mapping Software Logic for AI-Powered Development

~60 min · 15 stations

Conductor

All aboard the express to the heart of the codebase; we’re mapping the hidden architecture of software to power the next generation of AI. Mind the gap as we connect the nodes of your logic.

What you will learn

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FOUNDATION

Establishes the core vocabulary and essential context you need before going further.

• Examine how software structures function as interconnected networks

Station 01: The Basics of Code Graphs▶

• Trace the role of context in modern AI coding assistants

Station 02: AI and Codebase Context▶

• Define the fundamental building blocks of graph data models

Station 03: Nodes and Edges Defined▶

CORE CONCEPTS

Unpacks the ideas and principles that the subject is built on.

• Analyze how software dependencies form complex directed graphs

Station 04: Dependency Mapping▶

• Explore how semantic meaning improves code graph accuracy

Station 05: Semantic Code Analysis▶

• Compare common methods for searching through code networks

Station 06: Graph Traversal Basics▶

• Examine how graph embeddings represent code in vector space

Station 07: Embedding Code Logic▶

MECHANICS

Examines how things actually work — the processes, rules, and systems in action.

• Investigate the integration of graph data into LLM workflows

Station 08: Integrating Graphs and AI▶

• Practice using specialized query languages for code analysis

Station 09: Querying Codebase Graphs▶

• Evaluate tools for visualizing complex software relationship maps

Station 10: Visualizing Software Networks▶

APPLICATION

Puts knowledge to use through real-world scenarios and practical problems.

• Assess strategies for scaling graph analysis to massive codebases

Station 11: Scaling Graph Analysis▶

• Demonstrate how graph data powers automated code refactoring

Station 12: Automating Code Refactoring▶

• Analyze how graph structures reveal hidden software vulnerabilities

Station 13: Security and Vulnerability▶

SYNTHESIS

Connects everything together and explores broader implications and open questions.

• Construct a prototype analyzer for specific project needs

Station 14: Building Custom Analyzers▶

• Discuss emerging trends in graph-based AI software engineering

Station 15: Future of AI Coding▶

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General Public / 9th GradeAI Generated · gemini-3.1-flash-lite

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