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THYNKQ PRIVATE BRIEF

Local AI Architecture

One operator. Two machines. Router intelligence. Token-efficient delivery at production speed.

Rack Topology

i5

Orchestrator + fast local assist

deepseek-coder-v2:16b

Direct lane: 10.0.0.1

k8

Heavy code worker + dashboard fleet node

qwen3-coder:30b

Direct lane: 10.0.0.2 / 10.0.0.3

Unified Router

Task Intake
Classifier
Route Score
Dispatch + Fallback
  • Probe ethernet targets first, then WiFi fallback.
  • Attach i5 preflight context before high-scope k8 code runs.
  • Fallback to secondary node on timeout, unreachable, or no-change.

End-to-End Task Flow

1Rodolf defines objective
2Claude or Codex frames execution prompt
3thynkq-router selects best local node
4run-task creates branch and executes
5Commit and push branch to GitHub
6Rodolf reviews and merges

Weekly Benchmark Control Loop

  • Weekly model benchmark job runs on k8
  • Measure quality, t/s, wall time, and stability
  • Update routing defaults from measured results
  • Keep primary and backup model choices evidence-based

Token Saving Strategy

Local deterministic edits
95%
Local bounded implementation tasks
84%
Cross-file tasks with fallback
68%
Cloud escalation for edge cases
22%