Local development keeps you in control of dependencies, latency, configs and costs—and the bragging rights that “it works on my machine!” But with AI-driven tools, pure offline workflows get messy. This session by Carratalá and Dubois shows how to keep your dev environment network-optional: spin up AI models locally, pick the right code assistants, and inject AI power into your own codebase.
Along the way, you’ll run benchmarks on models of different sizes, weigh performance versus accuracy, and debate the pros and cons of local versus remote inference. Come learn how to supercharge your dev flow with AI without ever leaving your machine.
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