$150 to close 18+ PRs with Fable
Theo spent roughly $150–$200 of Fable API usage to review, close, rebase, or land over 30 pull requests in a 5-hour agentic loop.
Where this was said
Fable Is Back: First Impressions & What Actually Changed
At 42:32 · chapter starts 39:50
With Fable back in their hands, both hosts have been running it hard. Ben's first major use case was rebuilding the brittle CLI that spun up his Hermes agent container — a task involving Hermes, Codex, Claude Code, and an Executor, all needing to live in a single deployable box. What Opus had built barely worked; Fable rebuilt the entire architecture in about an hour of back-and-forth. [1] — Theo "Theo gave Fable his entire backlog of stale, conflicted, and draft PRs and told it to figure out which ones to keep, merge, rebase, or kill…" 41:40 Theo's story is more cinematic: he had 18-plus stale pull requests sitting in his Lakebed project, some finished but unrebased, others superseded by later merges, a few just outright slop. Rather than manually triaging them, he asked Fable to read all the PRs, figure out what they were for, identify overlaps, write plans for anything worth salvaging, and then execute. He read the plans briefly, said 'YOLO — slash goal, complete all the work we talked about,' and watched the model close a dozen PRs and land 14 more in one loop. The thing that makes this work, Theo emphasizes, is that Fable can pull intent from incomplete context — it doesn't need you to re-explain what you were trying to do; it can figure it out.
Fable Closes 30+ PRs in One 5-Hour Session
Theo gave Fable his entire backlog of stale, conflicted, and draft PRs and told it to figure out which ones to keep, merge, rebase, or kill. Without needing step-by-step instructions, the model categorized overlapping work, wrote plans for missing features, and landed or closed over 30 PRs in a single 5-hour loop — for about $150–$200.
Theo's Conspiracy: 7 Days Was Always the Plan
The 7-day Fable window at half rate limits wasn't a consolation prize — it was a calculated GPU provisioning experiment. Anthropic needed exactly one full week of data to see usage rates across every day of the week so they can plan how to allocate compute between enterprises and subscribers. The FOMO from the export ban was also a feature, not a bug.
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