Unlocking AI Memory: A Journey at Emotion Machine
At Emotion Machine, we explored the complexities of AI memory, evolving through three versions tailored for agent workflows:
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V1: pgvector Memory
- Leveraged importance scoring for facts.
- Competently remembered user details but faced retrieval limitations.
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V2: Scratchpad Model
- Transitioned to full context visibility.
- Promoted simplified relationship management (user & companion).
- Perfect for conversational use cases, offering intuitive LLM-managed memory operations.
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V3: Filesystem Approach
- Redesigned for agent mode tasks, using a file structure to manage context.
- Enabled on-demand navigation and curation for real-time chat.
- Adapted to encompass complex workflows and tool usage.
Key insights reveal that understanding what to remember is crucial for building meaningful AI companions. As the landscape evolves, we aim to refine how AI “remembers” and assists.
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