Indie Dev Builds Universal Memory Layer Across Models: No Vendor Lock-in, Predictable Cost
Opening-Dream9276 · reddit · 2026-08-04
An indie developer showcased a universal memory layer product built to work across different models. The core logic is that the memory store holds the conversation itself rather than being written by any specific model, completely avoiding format reshaping or extraction biases between different models.
This design allows users to seamlessly switch underlying models mid-conversation (e.g., from Claude to GPT) while sharing the exact same context. Its advantages include:
- Predictable Cost: Regardless of the model used, each query only adds about 2,000 tokens of context overhead.
- Efficient Retrieval: The retrieval process completes in about 1.5 seconds before the model starts generating.
The developer wants to discuss whether this solves the pain point of heavy users who pay for multiple subscriptions, juggle multiple tabs, and manually carry context between them.
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