Local-First AI Development

Coffee shop WiFi drops out. Flight mode kicks in. API is down for maintenance. None of these matter when your AI stack runs locally. Your development workflow stays uninterrupted because it doesn't depend on external services.

This independence is liberating. You can experiment freely without worrying about API costs. You can test edge cases without rate limits. You can debug by actually inspecting what's happening on your machine.

Ollama has revolutionized local AI development. One command to install, one command to pull a model, and you're running. Llama, Mistral, CodeLlama, Gemma, a whole ecosystem of open models at your fingertips.

ARES integrates natively with Ollama. Point it at your local Ollama instance and everything just works: embeddings, chat completions, function calling. Same API, local execution.

Network latency kills development flow. When every model call has to round-trip to a cloud server, experimentation becomes tedious. Local models respond in milliseconds, not seconds.

This speed advantage compounds. You test more variations. You catch issues earlier. You build better intuition for how your prompts and agents behave because you can iterate so quickly.

Local-first doesn't mean local-only. Develop and test with local models, then deploy with cloud APIs for production if that makes sense for your use case. ARES makes switching between providers trivial, it's just a configuration change.

This hybrid approach gives you the best of both worlds: fast local development with the flexibility to use the right model for each deployment scenario.