Building a Knowledge Graph of Your Codebase

P icture a vast, interconnected web of code—functions calling functions, data flowing through pipelines, classes inheriting from other classes.

Now imagine you could navigate this web with ease, understanding not just the structure, but the very essence of your software.

As software systems grow, so does the challenge of understanding them. Traditional code search tools often fall short, leaving developers lost in a sea of syntax. But what if we could map the entire ecosystem of our code, capturing not just its structure, but its meaning?

For the last few months I have been playing with various SOTA embedding models and LLMs, experimenting with how they can transform the landscape of code comprehension. We have supported interns to play with various concepts as part of our Daytona Experiments programme.

A code knowledge graph is more than just a fancy diagram. It's a living, breathing representation of your codebase that captures:

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