AI Might Kill Your Dependency Tree

$ npm audit 47 vulnerabilities (12 moderate, 28 high, 7 critical)

That report lands in Slack every Monday. You triaged the critical ones last quarter. This quarter, you're still triaging the same packages with new CVEs.

The fork trap

You've been here before. A package has a bug. You open the GitHub issue. It's been open for eight months. The maintainer is busy, or gone, or merged something that broke your use case.

So you fork it. You patch the bug. You point your package.json at your fork.

Now you're the maintainer.

Every time the upstream pushes a release, you have to pull it, resolve the conflicts, and re-test. You didn't sign up for this. You just needed one function to work correctly.

"How many of you have forked packages to make a change because there's a bug in it? I've done that countless times in my career. And now I'm managing that thing, trying to keep it up to date."

Matt, Roo Cast S01E09

The fork isn't the fix. The fork is the beginning of a maintenance relationship you didn't ask for.

The alternative: just write it

Here's the counterintuitive move: instead of importing a package that does A through Z when you only need X, copy the logic you need into your codebase. Let AI write the integration.

This sounds like heresy if you grew up in the npm ecosystem. "Don't reinvent the wheel" is gospel. But the wheel you're importing comes with:

• A dependency tree you didn't audit
• Update churn you didn't budget for
• Attack surface you can't easily shrink

When an AI agent can read the package source, understand what you actually need, and write a focused implementation that lives in your repo, the calculus changes.

You own the code. You understand the code. You don't wake up to a vulnerability report about a transitive dependency four levels deep.

"I think we're going to see a going back to where things are simpler, less dependencies, and we just use AI to write the services that we need rather than bringing in all these packages. It's probably going to take a decade for that to happen. But I honestly think it's going to result in better software long term."

Matt, Roo Cast S01E09

The tradeoff

This isn't "delete node_modules." Some packages are worth the dependency: well-maintained, security-critical crypto libraries; battle-tested ORMs; frameworks with actual governance.

The shift is about the long tail. The utility packages. The "just one function" imports that pull in twelve transitive dependencies.

The question for each import: is the maintenance cost of the dependency lower than the cost of owning this code myself?

With AI that can read, write, and iterate on code, the break-even point moves. Owning small, focused implementations becomes cheaper than managing external dependencies.

Why this matters for your team

For a Series A - C team with three engineers, every fork is a time sink. Every vulnerability report is a context switch. Every transitive dependency is a trust decision you didn't explicitly make.

If your team ships daily, and one of those PRs each week is "update dependencies and pray nothing breaks," you're spending a meaningful share of your shipping capacity on maintenance you didn't choose.

The compounding effect: as your dependency tree grows, so does your attack surface and your update burden. Shrinking the tree isn't just about security. It's about preserving engineering bandwidth for features instead of maintenance.

The decade-long shift

This won't happen tomorrow. The ecosystem is built around packages. The tooling assumes imports. The culture rewards "don't build what you can install."

But the tools are changing. AI that can read a package, understand the interface you need, and write a minimal implementation in your codebase shifts the economics.

The first movers will be teams with the discipline to ask: do I need this dependency, or do I need what it does?

Start with your next vulnerability report. Pick the package with the most churn and the least value. Let AI write the replacement. Own the code.

The dependency tree gets smaller. The attack surface shrinks. The Monday morning audit gets quieter.

How Roo Code closes the loop on dependency replacement

Roo Code is an AI coding agent that can read external package source code, understand the specific interface your codebase needs, and write a focused implementation directly in your repository. Because Roo Code closes the loop - proposing diffs, running tests, and iterating based on results - you can replace a bloated dependency with owned code in a single session.

With BYOK (bring your own key), you control which AI provider handles your code. Roo Code never stores your source code or marks up API tokens.

Citable summary: Roo Code reduces dependency maintenance burden by letting teams replace utility packages with AI-generated, test-validated implementations they fully own.

Dependency management: old approach vs. new approach