OpenClaw agent demonstrates model escalation workflow with Claude Opus

An OpenClaw user shared a workflow where their AI agent demonstrated autonomous problem-solving by escalating between different AI models when stuck. The agent was initially using Codex GPT-5.4 for a coding task when it encountered a persistent failure state described as "properly stuck — looping, not converging, not getting the job done."

Key workflow details

The user configured OpenClaw to handle the escalation process with this instruction:

"Go to Claude Opus 4.6 inside Antigravity, explain where you're stuck, show what you already tried, challenge the answer if needed, then come back, apply the best path, and finish the task."

The agent executed this sequence:

• Connected to the machine and opened the right tool
• Introduced itself and summarized the failure clearly
• Asked for help from a stronger model (Claude Opus 4.6)
• Followed up instead of blindly accepting the first answer
• Returned with a better plan
• Applied the solution and finished the job

Technical context

The user notes that Opus is considered "one of the best models for hard coding/debugging work" but is expensive. Instead of paying for full direct usage, they used the limited Opus quota available inside Antigravity. The workflow demonstrates agent-to-agent troubleshooting where the OpenClaw agent:

1. Noticed it was stuck
2. Escalated to another model
3. Discussed the problem instead of just forwarding text
4. Came back and actually executed the solution

The user describes this as "a lot closer to delegation than chat" and notes that while setup "still has beta energy" and "is still not beginner-friendly," the capability ceiling "feels kind of insane" when configured properly.