variet_llm/.planning/.continue-here.md

phase, task, total_tasks, status, last_updated

phase	task	total_tasks	status	last_updated
00-initialization	0	0	paused	2026-04-05T00:51:15+09:00

<current_state> Completed project initialization and architecture planning. GSD project state (.planning/PROJECT.md and config.json) corresponds to the 'Dual-Orchestration AI Assistant' structure using a 2+0 GPU division. Right before starting Phase 1 planning. </current_state>

<completed_work>

• Configured git repository, remote (Variet/variet_llm), and Vikunja
• Cleaned up previous agent_guide config
• Wrote .planning/PROJECT.md outlining the 3-Tier model strategy and the requirements
• Written .planning/config.json
• Committed everything to git </completed_work>

<remaining_work>

• Plan Phase 1: Machine A LLM inference server setup and Hot-swap scripts (Fast/Balanced/Deep)
• Plan Phase 2: Machine B VS Code Extension
• Plan Phase 3: Machine B Discord Bot
• Plan Phase 4: MCP Tool integration </remaining_work>

<decisions_made>

• Decided to use 2+0 GPU architecture because it gives single-user coding requests maximum throughput (50-80 t/s) while keeping orchestration neatly on Machine B.
• Picked a 3-tier model strategy: Gemma4 26B (Fast), Qwen 35B (Balanced), Qwen 122B (Deep). </decisions_made>

- None. We transitioned from pure Llama.cpp tuning to architectural layout. The logic for how tools are routed has been clarified (LLM thinks on Machine A, tools are executed locally on Machine B). Next logical step is to execute Phase 1 (infrastructure and hot swap on Machine A).

<next_action> Start with: /gsd-plan-phase 1 to design the Machine A startup and hot swap mechanism. </next_action>