docs: Add continuous learning and documentation framework

[glandua]

Summary

Documents the continuous learning system that enables both agents and human contributors to build on accumulated knowledge, leveraging the Regen Heartbeat digest system and KOI knowledge infrastructure.

Key Additions

• docs/learning/continuous-learning-architecture.md

  • Temporal hierarchy (daily → weekly → monthly → yearly)
  • Knowledge sources and data flow
  • Agent memory architecture (short-term, working, long-term, semantic)
  • Regen Heartbeat digest system integration

• docs/learning/contributor-learning-paths.md

  • Ecosystem Newcomer (1-2 weeks)
  • Technical Contributor (4-6 weeks)
  • Governance Participant (4 weeks)
  • Agentic Contributor (6-8 weeks)

Temporal Scale Benefits

Scale	Focus	Value
Daily	Immediate activity	Stay current
Weekly	Short-term patterns	Spot trends
Monthly	Medium-term themes	Strategic view
Yearly	Long-term evolution	Historical context

Related PRs

• PR-01: Contributor Guide ✅
• PR-02: Agentic Governance ✅
• PR-03: Claims Engine ✅
• PR-04: Token Economics ✅
• PR-05: Continuous Learning (this PR)
• PR-06: Regen Commons (coming)

References

• Regen Heartbeat
• KOI Research

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[gemini-code-assist]

Summary of Changes

Hello @glandua, I'm Gemini Code Assist¹! I'm currently reviewing this pull request and will post my feedback shortly. In the meantime, here's a summary to help you and other reviewers quickly get up to speed!

This pull request introduces comprehensive documentation for the Regen Network's continuous learning framework. It establishes a clear architecture for how knowledge is aggregated and disseminated across different temporal scales, benefiting both AI agents and human participants. Additionally, it provides structured learning paths to guide new and existing contributors in developing expertise across various domains, from understanding the ecosystem to contributing technically, participating in governance, or working with AI agents.

Highlights

• Continuous Learning Architecture Documentation: A new document docs/learning/continuous-learning-architecture.md has been added, detailing the Regen Network's continuous learning system. This includes its multi-scale temporal architecture (daily to yearly digests), knowledge sources (Forum, GitHub, Ledger, Notion, Discord/Telegram, YouTube), and an agent memory architecture (short-term, working, long-term, semantic memory using various storage solutions like Redis, PostgreSQL pgvector, Apache Jena).
• Contributor Learning Paths Documentation: A new document docs/learning/contributor-learning-paths.md has been added, outlining structured learning paths for different types of contributors. These paths include "Ecosystem Newcomer," "Technical Contributor," "Governance Participant," and "Agentic Contributor," each with specific goals, durations, phases, and completion criteria.

Changelog

• docs/learning/continuous-learning-architecture.md
  • Added a new document outlining the architecture of the Regen Network's continuous learning system.
  • Details the temporal hierarchy for knowledge outputs (daily digests, weekly summaries, monthly reports, yearly reviews).
  • Specifies primary knowledge sources and their update frequencies.
  • Describes the agent learning integration, including how agents query KOI and Ledger MCPs, consume digests, and persist memory.
  • Defines a four-tiered agent memory architecture: short-term, working, long-term, and semantic memory.
  • Lists access points like Regen Heartbeat and KOI Search capabilities.
• docs/learning/contributor-learning-paths.md
  • Added a new document defining structured learning paths for contributors.
  • Introduces four distinct learning paths: Ecosystem Newcomer, Technical Contributor, Governance Participant, and Agentic Contributor.
  • Each path includes a goal, duration, phased learning content, and clear completion criteria.
  • Provides resources relevant to each learning path.

Activity

• No activity has been recorded for this pull request yet.

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[gemini-code-assist]

Code Review

This pull request introduces comprehensive documentation for the continuous learning architecture and contributor learning paths. The new documents are well-structured and provide clear information. My review focuses on ensuring the long-term maintainability and accuracy of the documentation, and I've found a few issues with external links. Specifically, there is a broken link and a couple of links pointing to a personal GitHub fork, which should ideally be updated to point to official repositories. Please see the specific comments for details.

[gemini-code-assist]

The link for 'HTTP Config Architecture v2' points to a personal fork (DarrenZal/koi-research). For official documentation, it is best practice to link to resources within the organization's main repositories to ensure long-term availability and maintenance. Please consider moving this document to the gaiaaiagent organization and updating the link.

[gemini-code-assist]

The link for 'HTTP Config Architecture v2' points to a personal fork (DarrenZal/koi-research). For official documentation, it is best practice to link to resources within the organization's main repositories to ensure long-term availability and maintenance. Please consider moving this document to the gaiaaiagent organization and updating the link.

[glandua]

@DarrenZal please generate a plan to migrate these important repos over into the regen-network org github, and/or to the gaiaaiagent org. I'd prefer we centralize everything onto regen-network so that we can more easily manage permissions and coordinate multi-agent development. but it can be phased, and start with a migration over to gaia ai agent repo then from there to regen-network repo.