Podcast: The Future of Web Apps: Will AI Agents Generate UIs on the Fly?
Rachel Lee Nabors, former React core team member, dives into the architecture and philosophy behind local-first applications, exploring how small language models (SLMs) running directly on-device can deliver privacy-focused, low-latency, and cost-effective alternatives to cloud-hosted LLM wrappers. By Rachel Lee Nabors
Rachel Lee Nabors is a former React core team member who now works on building Mima, a client-first social and news aggregator. She wanted to create a privacy-focused, local-first application that could aggregate content from various social networks and provide a unified experience. Mima leverages client-side AI and native web APIs to operate without relying on external servers or large language models (LLMs).
Instead, it uses smaller language models (SLMs) that run directly on the user's device, allowing for faster processing, lower latency, and less reliance on cloud-based services. Rachel believes this approach offers a more secure and cost-effective alternative to cloud-hosted LLM wrappers.
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