Building with Multiple AI Providers

One of the interesting challenges I’ve been working on is integrating multiple AI providers into a single application. Here’s what I’ve learned so far.

The problem

Different AI models are good at different things. Claude excels at reasoning and code, GPT is solid for general tasks, and local models via Ollama give you privacy and offline capability. Why pick one when you can use them all?

The approach

The key insight is building a provider abstraction layer. Instead of coupling your app to one API, you define a common interface:

interface AIProvider {
  chat(messages: Message[]): Promise<Response>;
  stream(messages: Message[]): AsyncIterable<Chunk>;
}

Each provider implements this interface, and the rest of your app doesn’t need to know which model it’s talking to.

Lessons learned

Error handling differs wildly between providers. Normalize errors early.
Streaming formats aren’t standard. Each provider has its own chunking behavior.
Rate limits and pricing vary so much that you need per-provider config.

More details on the architecture in future posts.