Developer builds persistent memory system for Mac AI coding app Deiko

A developer building Deiko, a Mac app that captures screen context and voice input for AI coding agents, grew frustrated that agents had no memory of previous debugging sessions on the same issue. After noticing repeated explanations of identical bugs across days, he spent a week engineering a memory layer to let Deiko recognize when new briefs relate to past tasks. He evaluated Jev, a probability-focused model from TypeSafe AI priced at $0.042 per million input tokens, which returns a confidence score on whether two items are related rather than a verbose response. When TypeSafe paused signups, he rerouted through gateways including Vercel AI Gateway, OpenRouter, and Cloudflare to access the same model. Drawing on how tools like Claude Code, Mem0, and Sentry handle memory and issue grouping, he built a small filing algorithm that combines exact contextual clues with model-based classification to cluster related briefs automatically.
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