Essential Readings for Pyragogy A link without context is just noise. These resources have context. Foundational Texts The Peeragogy Handbook Authors: Howard Rheingold et al. | Available at: peeragogy.org | License: CC BY-SA What it is: A community-written guide to peer-to-peer learning, first published in 2012 and continuously updated. Why it matters to Pyragogy: Pyragogy is a direct evolution of this work. Understanding Peeragogy gives you the vocabulary (patterns, roles, emergent structure) and the spirit (horizontal, collaborative, self-organized) that Pyragogy extends. What to read it for: The pattern language chapters. The “Wrapper” and “Heartbeat” roles are still relevant in human-AI contexts. A Pattern Language Author: Christopher Alexander | Published: 1977, Oxford University Press What it is: Alexander’s documentation of 253 recurring patterns in architecture and urban design. The methodology, not the content, is what matters for Pyragogy. Why it matters to Pyragogy: A pattern isn’t a recipe — it’s a context-sensitive solution with documented failure modes. This distinction is foundational. What to read it for: The introduction only is enough to understand the methodology. Connectivism: A Learning Theory for the Digital Age Author: George Siemens | Published: 2005 (paper, available online) What it is: Siemens’ argument that learning in networked environments can’t be fully explained by existing learning theories. Knowledge, in a connected world, resides in networks of connections. Why it matters to Pyragogy: The question “where is knowledge stored?” becomes more interesting when part of the answer is “in the LLM.” Thinking Fast and Slow Author: Daniel Kahneman | Published: 2011 What it is: Dual-process theory: System 1 (fast, intuitive) and System 2 (slow, deliberate). Why it matters to Pyragogy: Many problems in AI-assisted work — over-relying on confident AI outputs, anchoring on first responses — are System 1 failures. Pyragogy practice requires deliberate System 2 engagement. What to read it for: Part I (Two Systems) and Part III (Overconfidence). Add Your Own Post resources using this structure: ### [Title] **Author(s):** | **Available at:** | **License:** **What it is:** [2 sentences] **Why it matters to Pyragogy:** [2-3 sentences] **What to read it for:** [1 sentence] Resources without context get moved to a “raw links” section. That’s the deal. Human-AI Co-Creation

Official Pattern Documentation Template When a pattern has been tested and validated, archive it using this formal template. Before using this template, your pattern should have: Been posted in rough form in The Agora → Pattern Workshops Received community feedback and survived at least one round of critique Been tested by at least one person other than the original author The Template --- pattern-name: [2-5 words, memorable and descriptive] pattern-id: PTN-[XXX] # Assigned by maintainers version: 1.0 status: draft | community-review | validated authors: [names/handles] date-submitted: [YYYY-MM-DD] --- ## [Pattern Name] ### Summary [One sentence: what this pattern does and when to use it] ### Context Where and when does this pattern apply? ### Problem What tension or challenge does this address? ### Solution What do you do? [Clear, actionable. Numbered steps if sequence matters.] ### Rationale Why does this work? [The underlying mechanism.] ### Examples #### Example 1: [Brief label] [Context, action, result — concrete enough to be usable] #### Example 2: [Brief label] [A second example from a different domain] ### Known Failure Modes When does this pattern not work, or work badly? [Required section. At minimum one failure mode.] ### Related Patterns [Pairs well with / Can be confused with] ### Revision History [Version notes] Notes On Known Failure Modes: This section is not optional. A pattern without documented failure modes hasn’t been tested seriously. On examples: Real examples are better than hypotheticals. Anonymize if necessary, but don’t fabricate specificity. Submission Process Draft in The Laboratory → Pattern Workshops Request community review in the thread Incorporate feedback, update version Tag a maintainer when ready for The Archive Maintainer assigns PTN-ID, moves to Validated Patterns Human-AI Co-Creation