Configured Is Not Complete: Auditing My AI Automations by Outcome
I recently reviewed six improvements that my AI assistant had marked complete. Only two were actually complete. The other four were not imaginary or abandoned. Code existed. Tests passed. Prompts had been deployed. Scheduled jobs were enabled. Several parts had already worked in production. But each task still had at least one promised live outcome that had never been observed. One was waiting for its first scheduled weekly run. Another had delivered its news path but not the reading-feedback loop included in the same specification. A third had a longer observation period written into its own acceptance criteria. ...