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Model-lane validation: GLM + deepseek-aider on real company tasks — quality report + token-ROI evidence (Gate 0b) #1067

Description

@kokevidaurre

Founder direction 2026-07-10 (launch Gate 0b — launch-founding spec §6): no provider is claimed in public copy until its lane runs real company work with good results.

What

  1. Run real squad tasks (not toys — actual company work items) through the GLM lane and the deepseek-aider lane.
  2. Per lane, produce a quality/problem report: output quality vs the Claude lane, failure modes (tool gaps, format drift, silent losses — see reference: deepseek/aider = code-only no-web; web-scanners need claude-haiku+), retry/salvage behavior, wall-clock.
  3. Token-ROI evidence in the same runs: cost per LANDED outcome per lane vs Claude-direct. Token ROI is the business wedge — "this really makes good use of tokens" is what makes a business buy squads instead of spending on CC tokens directly.
  4. Output: a lane scorecard (green/yellow/red per task class) → green lanes may be claimed publicly; yellow/red get issues.

Depends on honest outcomes data — cli#1060 (outcomes hardcoded zero) should land first or the ROI numbers will be garbage.

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