36-Hour Ralph Loop: Opus Orchestrates Qwen 3.6/3.8 Builders on M1 Max

A developer on r/openclaw kicked off a 36-hour /goal Ralph loop to work through a pre-planned backlog of 38 features, 201 tasks, and 7 milestones. Opus 5.5 acts as orchestrator; two local Qwen models do the building on separate M1 Max machines with 64GB unified memory each.

Setup

• Orchestrator: Opus 5.5
• Builder A: Qwen 3.8 27B 4-bit on M1 Max 64GB
• Builder B: Qwen 3.6 35B A3B 8-bit on M1 Max 64GB
• Planning stack: Meta.AI for pitch deck, business case, and functional PM docs; GPT 6.1 Sol for spec generation
• Iteration driver: the /goal command looped across the backlog

The requirements, specs, and plans took "the best part of an evening" to assemble. The author notes 18 months of domain experience in the target area, which likely reduced spec gaps.

Kickoff state and guardrails

The agent's own kickoff note, quoted from the post, lists the operational baseline:

Local Loop delivery launched. Kickoff K0–K9 is done: both Mac
preflights OK, the baseline is 380/0, and production c68e333 is
the rollback anchor. The Ralph loop is running on delivery/pilot
with a 15-min watchdog. The time box ends Sat 24 Oct 13:54 AEDT,
and the wind-down starts from 10:54. To stop: touch
~/Development/runs/local-loop-delivery/HALT

Several details are worth copying into your own loops:

• Preflight per machine (K0–K9) before entering the build loop, so both Macs are verified before tokens burn.
• Baseline 380/0 — a known-good test count (passing/failing) to compare against as the loop iterates.
• Rollback anchor at commit c68e333 — a specific SHA to return to if the loop regresses production.
• 15-minute watchdog — periodic health check on the running loop.
• Wind-down window — the loop stops iterating at 10:54 and wraps up before the 13:54 time box, leaving room for cleanup and human review.
• File-based kill switch: touch ~/Development/runs/local-loop-delivery/HALT stops the agent immediately.

What was asked

The OP asked for stories and tips on keeping a local agent "earning its keep" — i.e. sustaining productive work across a multi-hour run rather than stalling or looping unproductively. If you've run similar local orchestrator/worker setups, the thread is likely to collect tactics around watchdog intervals, baseline tracking, and rollback points.

The pattern — a strong cloud model orchestrating smaller quantized local models — is one way to keep long agent loops going without paying cloud inference for every builder token. The two-Mac split also suggests rough parallelism rather than one giant model on shared hardware.

Updates are promised in the thread.