A practical guide to connecting Claude Opus 5.5 as an external tool to ChatGPT's Dots system, using it selectively for deep research, strict reviews, visual analysis, and long-running tasks while keeping Dots as the orchestrator. The article walks through 10 specific upgrades to make the combined system cheaper and more capable.

• Opus 5.5 connects as a private backend tool called only when tasks need deeper context, stricter review, visual analysis, or patience — not as a model replacement inside Dots itself.
• The four weakest points in Dots (shallow reading, uniform effort levels, weak self-review, poor visual work) map directly to where Opus adds value, and each has a specific upgrade to fix it.
• Caching the unchanging prompt prefix (standing brief, house rules, schemas) with a one-hour TTL cuts costs dramatically for teams running multiple tasks per day, and compacting the context window before it fills prevents mid-task cutoffs.
• Sorting work by whether anyone is waiting lets you move patient tasks (weekly digests, backlog triage, doc sweeps) to off-hours at lower cost, and moving house rules into the repo eliminates contradictions across four separate places.

The author tests Anthropic’s Mythos-class model, Claude 5 Fable, on tasks from epic poems to complex isochrone maps and research calibration software. Fable autonomously delegates work to cheaper agents, executes multi‐hour workflows, and produces sophisticated outputs, but its decision process remains a black box, shifting the user’s role from hands‐on builder to outcome judge.

• Claude 5 Fable autonomously delegated research to dozens of Sonnet agents (and spun up adversarial agents for edge cases like Pitcairn Island and Grise Fjord) to build a polished isochrone map in hours.
• It ran a nine-and-a-half-hour autonomous build of "Concord," a research calibration tool, complete with a 19-page design spec and production-ready code.
• The user's role shrank to prompting and light feedback while the model made hundreds of unseen micro-decisions, turning oversight into outcome judging rather than hands-on building.