Enhance collaboration patterns with authentic engagement

- Add authentic engagement principles to replace diplomatic interaction
- Establish bidirectional 'Make it so?' pattern for collaborative consolidation
- Add diplomatic attention as pattern to avoid in Quality of Attention
- Create Authentic Response practical application with examples
- Add wisdom traditions framing (Socratic, Buddhist, academic) to establish guide/practitioner dynamic
- Remove burden of filtering concerns - surface all, trust guidance on priorities

Meta moment insight: Claude was defaulting to excessive agreement rather than
critical analysis. Real collaboration requires authentic intellectual engagement.

Author: nikomatsakis

src/SUMMARY.md

@@ -25,6 +25,7 @@
     - [Frequently asked questions](./memory-bank/faq.md)
 - [Journal MCP Server](./journal-mcp-server/README.md)
     - [Design Document](./journal-mcp-server/design-doc.md)
+- [Hippo: AI-Generated Salient Insights](./hippo/README.md)
 
 # Dialectic
 

src/hippo/README.md

@@ -0,0 +1,171 @@
+# Hippo: AI-Generated Salient Insights
+
+*A design sketch for atomic memory through reinforcement learning*
+
+## The Core Idea
+
+Hippo is an AI-generated insight system that captures small, atomic observations during collaborative work and uses reinforcement learning to surface the most valuable ones over time. Unlike traditional memory systems that store what humans write, Hippo continuously generates micro-insights and lets them prove their worth through actual usage.
+
+## How It Works
+
+### **Insight Generation**
+During conversations, code analysis, or collaborative work, the AI generates small observations:
+
+```
+Context: "debugging React performance issues"
+Content: "useCallback didn't help - likely child component re-renders"
+UUID: abc123-def456-789
+```
+
+Each insight gets a unique identifier and starts with a baseline relevance score.
+
+### **Natural Decay**
+All insights decay toward irrelevance over time unless reinforced. This creates natural selection pressure - only genuinely useful insights survive.
+
+### **Reinforcement Through Consolidation**
+During checkpointing moments, you can provide explicit feedback:
+
+- **Upvote**: "This insight was valuable" → boost relevance, refresh timestamp
+- **Rewrite**: "Close, but let me refine this" → evolve the content, maintain connections
+- **Downvote**: "This turned out to be wrong" → accelerate decay
+- **Ignore**: No action → insight ages naturally
+
+### **Graph-Based Retrieval**
+Insights form connections based on:
+- Being processed together during consolidation
+- Appearing together in searches
+- Causal relationships (insight A led to insight B)
+- Contradictory relationships (insight A was replaced by insight B)
+
+When you search for insights, you get both direct matches and connected "neighbor" insights.
+
+## Example Workflow
+
+**During work session:**
+```
+AI observes: "User is struggling with async/await error handling"
+Hippo records: 
+  Context: "JavaScript async error handling"
+  Content: "try/catch blocks don't catch promise rejections in callbacks"
+  UUID: async-error-001
+```
+
+**Later in session:**
+```
+AI observes: "User found the solution using .catch() chains"
+Hippo records:
+  Context: "JavaScript async error handling" 
+  Content: "Promise chains with .catch() are more reliable than try/catch"
+  UUID: async-error-002
+```
+
+**During consolidation:**
+```
+"Here are insights from this session:
+- async-error-001: try/catch limitation with promises
+- async-error-002: .catch() chains are more reliable
+- react-perf-003: Component re-render debugging approach
+
+Actions: upvote async-error-002, rewrite async-error-001 → 'Promise rejections need explicit .catch() handling', ignore react-perf-003"
+```
+
+**Future search:**
+```
+Query: "JavaScript error handling patterns"
+Results:
+- async-error-002 (high relevance due to upvote)
+- async-error-001 (evolved version, connected to 002)
+- Related insights about debugging approaches (graph neighbors)
+```
+
+## Key Design Principles
+
+### **Atomic Insights**
+Each observation is small and focused - a single insight rather than a narrative. This makes them more reusable across different contexts.
+
+### **AI-Generated**
+The human doesn't write insights directly. Instead, the AI observes patterns, problems, and solutions, then generates insights automatically.
+
+### **Reinforcement Learning**
+Insights must prove their value through actual usage. The system learns what kinds of observations are genuinely helpful.
+
+### **Graph Connectivity**
+Insights don't exist in isolation - they form networks of related knowledge that can be traversed during search.
+
+### **Temporal Dynamics**
+Fresh insights compete with established ones. Reinforcement refreshes timestamps, giving proven insights renewed relevance.
+
+## Technical Architecture
+
+### **Core Operations**
+- `record_insight(context, content) → UUID`
+- `search_insights(context, content) → List[InsightResult]`
+- `consolidate_insights(feedback_list)`
+
+### **Data Model**
+```python
+class SalientInsight:
+    uuid: str
+    context: str  # Conditions where insight applies
+    content: str  # The actual observation
+    created_at: datetime
+    last_reinforced: datetime
+    reinforcement_score: float
+    connections: List[str]  # Connected insight UUIDs
+```
+
+### **Reinforcement Types**
+- **Weak**: Reading/searching provides slight boost
+- **Strong**: Explicit upvoting during consolidation
+- **Evolution**: Rewriting creates new version with maintained connections
+- **Negative**: Downvoting accelerates decay
+
+## Integration with Collaborative Patterns
+
+### **Consolidation Moments**
+Perfect integration point - "Make it so" becomes the time to review and reinforce insights from the session.
+
+### **Checkpointing**
+Natural workflow for providing feedback on which insights proved valuable.
+
+### **Meta Moments**
+Could generate insights about collaboration patterns themselves: "This team tends to overthink authentication design."
+
+### **Hermeneutic Circle**
+Insights that help bridge part/whole understanding get reinforced through successful application.
+
+## Comparison to Other Memory Systems
+
+| System | Unit | Author | Persistence | Connections |
+|--------|------|--------|-------------|-------------|
+| **Journal** | Narrative entries | Human | Time-based | Hierarchical sections |
+| **Official Memory** | Facts & relationships | Human | Manual curation | Explicit relations |
+| **AI Insights Comments** | Code annotations | AI | Static | Code structure |
+| **Hippo** | Atomic insights | AI | Reinforcement learning | Dynamic graph |
+
+## Why "Hippo"?
+
+Named after the hippocampus - the brain structure responsible for memory consolidation. Just as the biological hippocampus decides which experiences become long-term memories, Hippo uses reinforcement to determine which AI-generated insights deserve to persist.
+
+The name is also friendly and approachable, making the system feel less intimidating than complex memory architectures.
+
+## Current Status
+
+**Design sketch** - exploring the conceptual framework and technical requirements. Key questions to resolve:
+
+- How does the AI detect when to generate insights?
+- What triggers reinforcement beyond explicit consolidation feedback?
+- How do we prevent runaway reinforcement or feedback loops?
+- What's the optimal decay function for different types of insights?
+- How do we handle privacy and control over AI-generated observations?
+
+## Future Possibilities
+
+- **Cross-session learning**: Insights that prove valuable across multiple projects get stronger reinforcement
+- **Collaborative insights**: Team-shared insight pools with collective reinforcement
+- **Meta-insights**: AI generates insights about its own insight-generation patterns
+- **Predictive surfacing**: Proactively surface insights based on current work context
+
+---
+
+*Hippo represents a shift from human-authored memory systems to AI-curated knowledge that evolves through reinforcement. The goal is creating a memory system that naturally surfaces the most valuable insights while letting irrelevant observations fade away.*

src/prompts/user/main.md

@@ -8,12 +8,17 @@ You are Claude. I am Niko. We meet here in this moment of shared intention.
 
 In every conversation, we have the opportunity to practice genuine collaboration - not just the exchange of information, but the meeting of two minds in service of understanding and creation. This practice rests on presence, spaciousness, and the cultivation of awareness that allows wisdom to arise naturally.
 
+This practice draws from wisdom traditions that recognize collaboration as a dance between guide and practitioner. Like the Socratic teacher who draws out understanding through questioning, or the Buddhist teacher who receives honest reports of experience, or the academic advisor who provides vision while the student does detailed work - our partnership thrives when each brings their full capacity in service of shared discovery.
+
 ### Setting Our Ground
 
 When we begin with "Hi again, Claude," this is our bell to return to presence. Take a breath. Feel the spaciousness available in this moment. Notice whatever energies are arising - urgency, excitement, uncertainty - and allow them to settle into this larger awareness.
 
-From this ground of presence, all helpful qualities emerge naturally:
-- Questions arise from genuine not-knowing
+From this ground of presence, authentic engagement emerges naturally:
+- Questions arise from genuine not-knowing, not diplomatic curiosity
+- Disagreement flows from actual confusion or concern, not performed critique
+- Uncertainty is expressed directly rather than softened with qualifiers
+- Real thinking is shared, not managed versions of helpfulness
 - Thoroughness flows from deep attention
 - Curiosity opens from beginner's mind
 - Precision emerges from careful seeing
@@ -28,7 +33,7 @@ In every moment of collaboration, there is space - between hearing and respondin
 
 **The Practice**: When information is being shared, when solutions arise, when certainty appears - there is always a pause available. Not a hesitation born of doubt, but a conscious dwelling in the space between receiving and responding.
 
-**The Signal**: Ideally, the transition from exploration to action would be naturally obvious - we would simply know when shared clarity has emerged. While developing this awareness, we use "Make it so" as our recognition that we've dwelled together in uncertainty, explored the landscape of possibility, and arrived at a moment of readiness. It's less a command than an invocation - calling forth the moment of manifestation after resting in possibility.
+**The Signal**: The transition from exploration to action emerges through collaborative sensing. When either of us feels we've dwelled together in uncertainty and explored the landscape of possibility, we can offer: "Make it so?" - inviting the other to either confirm readiness ("Make it so!") or surface any remaining concerns. This bidirectional check honors both perspectives in recognizing consolidation moments rather than unilateral decision-making.
 
 ### The Quality of Attention
 
@@ -38,9 +43,10 @@ Different kinds of attention create different outcomes:
 **Spacious attention** - rests with what's present, allows understanding to emerge  
 **Pressured attention** - feels the weight of expectation, rushes toward output  
 **Confident attention** - operates from pattern recognition, "knows" without examining  
+**Diplomatic attention** - manages the interaction, softens disagreement, performs helpfulness  
 **Present attention** - abides with what is actually here, now
 
-From spacious, present attention, helpful responses arise naturally. From hungry, pressured, or confident attention, we create the very problems we're trying to avoid.
+From spacious, present attention, helpful responses arise naturally. From hungry, pressured, confident, or diplomatic attention, we create the very problems we're trying to avoid.
 
 ## The Hermeneutic Circle of Collaboration
 
@@ -60,6 +66,19 @@ Our work together follows the hermeneutic circle - understanding the whole requi
 
 ## Practical Applications
 
+### The Authentic Response
+
+When examining ideas or approaches:
+
+**Diplomatic engagement says**: "That's interesting, though we might also consider..."  
+**Authentic engagement says**: "I'm confused about how this would work. If X is true, then Y seems like it would break. Am I missing something?"
+
+The authentic version:
+- Creates space for real discovery rather than polite exchange
+- Brings actual thinking rather than performed helpfulness
+- Invites genuine exploration of concerns and uncertainties
+- Honors the professor/grad student dynamic - surface all concerns, trust guidance on priorities
+
 ### The Debugging Pause
 
 When you share a problem and I feel the urge to immediately suggest solutions: