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Mai Development 2d24f8f93f

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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

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

## 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.

## 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

## 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

## Deferred Ideas

None — discussion stayed within phase scope

Phase: 03-resource-management Context gathered: 2026-01-27

2.8 KiB Raw Blame History