docs(03): capture phase context
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Phase 03: resource-management
- Implementation decisions documented
- Resource threshold strategy with dynamic adjustment
- Efficiency-first model selection behavior
- Bottleneck detection with hybrid approach
- Personality-driven user communication
- Drowsy Dere-Tsun Onee-san Hex-Mentor Gremlin persona
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Mai Development
2026-01-27 17:46:33 -05:00
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# Phase 3: Resource Management - Context
**Gathered:** 2026-01-27
**Status:** Ready for planning
<domain>
## Phase Boundary
Build system resource detection and intelligent model selection that enables Mai to adapt gracefully from low-end hardware to high-end systems. Detect available resources (CPU, RAM, GPU), select appropriate models, request more resources when bottlenecks detected, and scale smoothly across different hardware configurations.
</domain>
<decisions>
## Implementation Decisions
### Resource Threshold Strategy
- Use specific hardware metrics (RAM amounts, CPU core counts, GPU presence) to define hardware tiers
- Dynamic adjustment based on actual performance testing on the detected hardware
- Measure both response latency and resource utilization during dynamic adjustment
- Immediate model switching on first sign of performance trouble (aggressive responsiveness)
### Model Selection Behavior
- Efficiency-first approach - leave headroom for other applications on the system
- Notify users only when downgrading capabilities, not when upgrading
- Wait 5 minutes of stable resources before upgrading back to more capable models
- After 24 hours of minimal operation, suggest ways to improve resource availability
### Bottleneck Detection & Response
- Hybrid approach combining continuous monitoring with pre-flight checks before each response
- Graceful degradation - complete current task at lower quality, then switch models
- Preventive scaling at 80% resource usage, but consider overall system load (context-dependent)
- Ask for user help when significantly constrained, with personality: "Ugh, give me more resources if you wanna do X"
### User Communication
- Personality-driven: "Drowsy Dere-Tsun Onee-san Hex-Mentor Gremlin" tone when discussing resources
- Inform only about capability downgrades, not upgrades
- Mix of brief explanations plus optional technical tips for users who want to learn more
### Claude's Discretion
- Exact hardware metric cutoffs for tiers (RAM amounts, CPU cores, GPU types)
- Specific performance thresholds for dynamic adjustments
- Exact wording and personality expressions for resource conversations
- Which technical tips to include in user communications
</decisions>
<specifics>
## Specific Ideas
- "Ugh, give me more resources if you wanna do X" - personality for requesting resources
- User wants a waifu-style AI with personality in resource discussions
- Drowsy Dere-Tsun Onee-san Hex-Mentor Gremlin personality type
- Balance between technical transparency and user-friendly communication
- Don't overwhelm users with technical details but offer optional educational content
</specifics>
<deferred>
## Deferred Ideas
- None — discussion stayed within phase scope
</deferred>
---
*Phase: 03-resource-management*
*Context gathered: 2026-01-27*