Launched 67 DNA scanner subagents in 5 waves across all 55 AIS projects — then followed up with 50 DNA executor subagents to apply fixes. The scanner wave pattern was simple: send 12-15 projects per wave, let the manifests flood in, launch the next wave before the previous one finishes. Each scanner reads package.json, checks git remotes, counts screenshots, detects framework versions, and writes a structured .ais-manifest.json into the project root. 52 of 55 projects got manifests. The executors then ran the initial cleanup playbook on each: delete import maps, migrate API keys from process.env to import.meta.env, swap Tailwind CDN scripts for npm-installed PostCSS pipelines, and clean scaffold cruft.
The whole operation ran autonomously from a single parent conversation — 6,006 total steps across scanners and executors combined, one human message at the end asking for a recommended prompt for the next phase. The ai-studio-export-rescue skill (342 lines) codified every fix pattern learned from doing these rescues manually, and the agent applied it at fleet scale. The result: 52 projects with structured manifests, consistent build pipelines, and a clear status classification — shipped, needs-polish, raw-export, or local-only.