Honcho and Medicine-Wheel Memory Integration Schema 260903
By the Miadi-Chronicle and Medicine-Wheel development team https://youtu.be/oXR0dO8cNc0
Intent
Would lead to implementing inside the repo jgwill/medicine-wheel an integration to 'honcho' and if whatever is needed on the repo miadisabelle/mia-honcho as well
STATUS:
- 2026-09-19: I worked on creating
@medicine-wheel/honchoand it is being tested on host side Eury.
Discussion
001
You’re describing a very clear and sensible architecture: keep medicine-wheel focused on capturing notes and data from sessions and ceremonies, then delegate the organizing and sense‑making over time to a dedicated memory system like Honcho that already has its own agent inside it. That division of labor makes a lot of sense, and it’s exactly the kind of pattern this type of memory was designed for.
Medicine-wheel acts as the ritual and data layer. It captures structured or semi‑structured entries: session notes, ceremony logs, reflections, maybe some tags or simple metadata. It stays relatively simple and stable, with a schema for entries, basic queries, and perhaps some views or timelines. It doesn’t need to know how memories get clustered, summarized, or re‑interpreted over time.
Honcho acts as the memory and meaning layer. It ingests events from medicine-wheel, for example when a session is closed, a ceremony is completed, or a note is added. Its internal agent then summarizes sessions, extracts themes, insights, and action items, clusters related sessions over time, and maintains longer‑term narratives or arcs. It then exposes that organized memory back to you, and potentially back into medicine-wheel as higher‑level nodes.
This matches the earlier idea where Honcho becomes a conversational and episodic memory service that feeds ImportanceUnit‑style events into your graph, instead of you re‑implementing all that agent logic inside medicine-wheel.
A practical integration pattern looks like this. In medicine-wheel, on session close or ceremony end, you emit an event to Honcho with a type like session_closed, a session ID, user ID, timestamp, and a payload containing notes, tags, and location. On the Honcho side, it receives the event and its internal agent reads recent related sessions for that user, then produces derived memories such as summaries, themes, and insights, storing these as its own memory units. Optionally, you can write back into medicine-wheel: Honcho or a small adapter posts back to medicine-wheel’s API to create new nodes like memory_summary, theme_cluster, or arc_segment. Medicine-wheel just stores them as another kind of entry; it doesn’t need to understand the agent logic.
This keeps the complex agent work isolated in Honcho, while medicine-wheel remains a clean event and note store plus a place to display whatever Honcho sends back.
Your earlier notes already pointed in this direction: Honcho as a conversational memory layer that feeds session interactions and conclusions into the medicine-wheel graph as ImportanceUnit events, with awareness that multiple medicine-wheel instances in different locations might appear as different users or spaces in memory, which Honcho can handle via metadata.
What you’re articulating now is essentially: don’t rebuild Honcho’s brain inside medicine-wheel. Let Honcho be the brain; medicine-wheel is the body and ritual interface. That’s coherent and aligned with how you were already thinking.
Academics
Cognitive Neuroscience
Studies memory integration, consolidation, and how related experiences form overlapping representations. Useful for designing how session notes in medicine-wheel can be linked into longer-term themes and arcs.
Artificial Intelligence
Covers memory-augmented agents, episodic memory, and retrieval-based reasoning. Relevant to Honcho acting as the organizing “memory brain” while medicine-wheel remains the capture layer.
Knowledge Representation and Reasoning
Focuses on structuring events, entities, and relationships so systems can infer higher-level meaning. This fits schema design for notes, summaries, themes, and cross-session links.
Human-Computer Interaction
Explores how people record, revisit, and make sense of personal experience through interfaces. Important for shaping the ritual, note-taking, and review experience in medicine-wheel.
Information Systems
Examines how data capture systems connect to downstream processing, workflows, and organizational memory. Relevant to integration patterns between repository services and memory services.
Software Architecture
Addresses separation of concerns, event-driven integration, and service boundaries. This field supports the idea of keeping medicine-wheel simple while delegating memory synthesis to Honcho.
Citations:
[1] Memory integration: neural mechanisms and implications ... - https://www.sciencedirect.com/science/article/abs/pii/S2352154614000072
[2] Extending cognitive architecture with episodic memory | Proceedings of the 22nd national conference on Artificial intelligence - Volume 2 - https://dl.acm.org/doi/10.5555/1619797.1619895
[3] Episodic Memory in Agentic Frameworks: Suggesting Next ... - https://arxiv.org/abs/2511.17775
[4] AN EPISODIC MEMORY-BASED FRAMEWORK FOR ... - https://openreview.net/pdf/00c84232cbfd93e6038adcc398d3fd1e6d664e4a.pdf
[5] Enhancing intelligent agents with episodic memory - https://www.sciencedirect.com/science/article/abs/pii/S1389041711000428
[6] 1 - https://arxiv.org/pdf/2511.10652
[7] Episodic memory for autonomous agents - https://www.academia.edu/3268279/Episodic_memory_for_autonomous_agents
[8] On the risks and benefits of episodic memory in agents On - https://www.cs.columbia.edu/~dechant/safeaiworkshop2023.pdf
[9] Editorial: Synthesizing memory: integrating across fields and levels of scale - https://www.frontiersin.org/journals/cognition/articles/10.3389/fcogn.2025.1637173/pdf
[10] Elements of episodic memory: insights from artificial agents - https://pmc.ncbi.nlm.nih.gov/articles/PMC11449156/
[11] Memory integration: neural mechanisms and implications for ... - https://pmc.ncbi.nlm.nih.gov/articles/PMC4346341/
[12] Episodic-Semantic Memory Architecture for Long-Horizon Scientific Agents - https://arxiv.org/html/2605.17625
[13] A Structured Approach for Embedded Memory Integration of Emerging Memory Technologies - https://ieeexplore.ieee.org/document/10506121/
[14] Contextual Memory Intelligence: A Foundational Paradigm ... - https://arxiv.org/html/2506.05370v1
[15] A Proposal for Intelligent Agents - https://arxiv.org/pdf/2005.03182
LINKS and metadata
https://www.perplexity.ai/search/608ccaa0-c597-46c0-a235-5f8ec9d9c278