You’ve felt it. That sinking feeling when you add one more npm package to your LLM routing stack and suddenly your node_modules folder weighs more than a small planet. You tell yourself it’s fine—everyone else is doing it. But deep down, you know the truth: your AI infrastructure is a house of cards held together by quilts of dependencies, each one a potential security breach, each one a maintenance headache.
I’ve been there. I spent weeks trying to make litellm work for a production system. It’s powerful, sure. But it’s also a monster. Thousands of dependencies, a Node.js runtime that feels like a paperweight, and a codebase so abstracted that debugging a single routing error turns into a archaeology expedition. I was exhausted. So I did what any frustrated developer would do: I wrote my own thing.
“Less code is not a limitation—it’s the only path to security and scalability.”
Meet eek—a tiny Rust LLM proxy in roughly 1,000 lines of code. No npm. No Python virtualenv. No dependency tree that looks like a fractal. Just a lean, auditable binary that routes your requests to open models without the bloat. And it’s not just a toy. It’s a statement.
The AI industry has been sold a lie: that more features mean more value. Every vendor wants you to believe you need their all-in-one solution. But the truth is, most of those features are dead weight. You don’t need a dozen model routers, eight caching layers, and a dashboard that shows you the same metrics three different ways. You need a proxy that handles 80% of the use cases with 1% of the complexity.
“If your AI infrastructure requires a security audit of 10,000 npm packages, you don’t have infrastructure—you have a liability.”
This isn’t about being nostalgic for “simpler times.” It’s about recognizing that the modern AI tooling ecosystem is suffocating under its own weight. The vulnerability surface of a typical LLM stack is terrifying. Every dependency is a potential CVE waiting to be exploited. And with AI moving into production—healthcare, finance, legal—the cost of bloat isn’t just developer time. It’s security breaches, compliance failures, and lost trust.
What makes eek revolutionary isn’t its feature set. It’s what it doesn’t have. No unnecessary abstractions. No “enterprise” features that nobody asked for. Just a clean, Rust-powered proxy that you can fully understand in a single sitting. The GitHub comment that started it all says it best: “I wrote this while looking for a lightweight version of litellm, and, after much frustration at all the npm projects with huge blankets (quilts, even) of dependencies.”
“We built a 1,000-line proxy because we were tired of shipping quilts of dependencies.”
This is the moment the industry needs to pause. The race to build the most comprehensive AI platform has become a race to the bottom—a competition of who can wrap the most libraries, who can add the most integrations, who can claim the most “seamless” experience. But seamless doesn’t mean secure. And comprehensive doesn’t mean reliable.
Here’s the twist: the most scalable, enterprise-ready AI infrastructure might actually be the one with the least code. The one that forces you to think about what you actually need rather than accepting everything a vendor hands you. The one that is so small and simple that you can audit it in an afternoon, deploy it in a minute, and trust it because you know every line.
“The best AI infrastructure is the one you can read, understand, and sleep soundly at night knowing it won’t break.”
So next time you’re about to pull in that 50,000-line Python library, ask yourself: do I really need this? Or is there a 1,000-line Rust alternative that does the job better? The answer might surprise you. And if you’re still not convinced, go ahead and try eek. It’s free, it’s open, and it might just be the wake-up call the AI industry needs.
Less code. More trust. That’s the future.
FAQ
Q: Is a 1,000-line Rust proxy really production-ready for complex AI workloads?
A: It depends on your needs. For 80% of use cases—routing to open models, handling basic rate limiting, and simple load balancing—it's more than enough. If you need advanced caching, multi-model orchestration, or custom metrics, you might need to supplement it. But the point is: most teams don't need those features. The proxy is auditable, fast, and doesn't introduce the security risk of a massive dependency tree.
Q: Should I drop my current stack and switch to eek immediately?
A: Not blindly. Evaluate your actual requirements. If you're using litellm or similar and your team is constantly fighting dependency issues, performance bottlenecks, or security bloat, then yes—consider a migration. Start with a non-critical path, test the proxy's limits, and measure the operational simplicity. The real win is not just the proxy itself, but the mindset shift: ask 'what do I actually need?' instead of 'what can I add?'
Q: Isn't more features always better? Why would I want a less capable tool?
A: Because 'more features' often means 'more attack surface', 'more maintenance burden', and 'more cognitive load'. Every feature you don't use is a liability. The contrarian truth is that the best tools are those that force you to be deliberate about what you include. A 1,000-line proxy that you fully understand will outperform a 100,000-line framework that you only half-know, especially in production where reliability and security matter most.