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September 12, 2025Why Rust Was Not the Right Choice for an AI Gateway
A development team spent nearly three months building an AI gateway using the Rust programming language. The initial launch thread received over two hundred thousand views, creating an expectation of high demand. However, actual traffic was slow, revealing critical missteps in the development approach.
The team realized several key issues had contributed to the project not meeting expectations. Building with Rust had taken so long that the developers became disconnected from their customers actual needs. The development speed required by Rust was unsustainable in the fast-paced AI industry. The team already had a functional gateway built with JavaScript, making feature parity achievable in days rather than weeks. Clients overwhelmingly preferred a simple, no-brainer solution over a highly customizable one.
- Building with Rust created a long development cycle
- The team lost touch with customer needs during the extended build
- JavaScript offered a faster path to feature parity
- Clients preferred simplicity over customizability
The Pivot to a New Open-Source Solution
Observing the success of platforms like OpenRouter, the team decided to build an open-source alternative. This new solution integrated built-in observability features and charged zero percent markup fees. The implementation is straightforward, requiring only a single API key for the Helicone service to function as a gateway to over one hundred different AI models.
The newly launched AI gateway offers significant advantages including zero percent markup fees, automatic fallbacks between providers, built-in observability with logs and metrics, cost optimization that routes to the cheapest reliable provider, and support for passthrough billing or bring your own keys. The key lesson was that high view counts do not equate to actual demand; real engagement and clear benefits are what drive product adoption.
