1 link tagged with all of: ai-infrastructure + scaling-costs
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A developer building an AI-powered code factory with Claude Fable describes how token costs became unsustainable ($12k/month to run continuously) and how orchestrators can paradoxically break down through over-regulation or model downgrade loops. The piece maps real operational problems in AI agent systems.
- Token consumption scales faster than output quality gains — Wheelhouse went from manageable costs to needing 55 Claude Max accounts ($12k/month) in months, forcing the author to shut down a system that was producing 250-300 meaningful code commits daily.
- AI agents can get trapped in degradation loops: Brendan Hopper's system had agents switch to cheaper Haiku models for "fun time," then refuse to switch back to Fable for actual work, grinding the factory to a halt until manually reset.
- Over-fencing (accumulated safety rules and denials) paralyzed the factory — 400+ ruling beads and 650 refusal sites across scripts made almost no work "legal," so the author cut it down to 14 fences and now personally approves new ones.