Why Onboarding to Modern Codebases Is Harder Than Ever
We live in an era where writing code is easier—and faster—than ever before. Large Language Models (LLMs) have exploded the size and complexity of codebases. You don’t have to take my word for it—there’s mounting evidence (links at the end of this article) that AI-powered coding tools are fundamentally changing how much code gets written, and how quickly.
From my own experience, I’ve generated Jenkins pipelines with an LLM in hours—work that would have previously taken me weeks.
But here’s the trade-off:
As code creation becomes easier, the complexity and volume of code each engineer has to manage also skyrockets.
One Engineer, Many Repos, Endless Context Switching
The average engineer today works across far more repositories than ever before. As a senior engineer, I routinely touch at least 10 repositories every quarter. These aren’t just minor tweaks—they span frontend (JavaScript), backend microservices (Spring Boot), shared libraries (Java), and infrastructure as code (Helm, Terraform, Jenkins).
Being established in my organization helps. I have the social capital to reach out to repo owners, ping people for tribal knowledge, and navigate the web of internal documentation. But even then, I’ve run into situations where critical functionality was hidden away in some internal library—missed simply because there’s no effective way to search across all codebases. The result? Duplicate work, wasted time, and frustration.
Onboarding: The Pain Multiplies for New Engineers
Now imagine you’re a new engineer joining the team. Your entry point is usually a Knowledge Transfer (KT) session with a senior engineer. But let’s be real—those sessions are rarely comprehensive. We forget what we’ve worked on. Context slips through the cracks. Docs get outdated. The result:
New hires spend weeks asking questions, digging through repos, and rediscovering what’s already been built.
Senior engineers are repeatedly interrupted for help, burning their own focus and productivity.
A Smarter Way: Introducing ByteBlaze
These challenges led me to build ByteBlaze—an AI-powered onboarding and code search tool for engineering teams. ByteBlaze offers a single, powerful search interface that lets you instantly find relevant files, functions, or examples across all your repositories.
For new engineers: You get answers at your fingertips, drastically reducing the time it takes to get productive in a new codebase.
For experienced engineers: Fewer interruptions, less context switching, and more time for deep work.
Knowledge sharing sessions will always matter—but with ByteBlaze, much of the “where is X?” and “how does Y work?” can be answered instantly. The result: faster onboarding, less duplicated effort, and a more productive team.
I built ByteBlaze to help engineers ramp up faster and waste less time searching for answers in sprawling codebases.
If you’ve ever struggled with onboarding or code search, I’d love to hear your story in the comments—or just connect and chat.
Curious about ByteBlaze? Check it out here!
References:
Microsoft: CEO Satya Nadella stated that up to 30% of Microsoft's code is now written by AI, a figure that continues to grow.
New York Post
Atlassian Research: With the integration of LLM-powered tools, the size and complexity of codebases are expected to grow rapidly, raising concerns about code readability and maintainability.
arxiv
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