A morning intelligence run is an automated daily briefing where an orchestrator agent coordinates specialist agents to pull data from multiple sources into one consolidated report.
AI can predict your highest dropout risk points before a cohort launches by identifying difficulty spikes, low-progress stretches, and unclear transitions where students typically disengage.
Paste course content into Claude and ask it to flag language that is too complex, too technical, or too simplistic for your specific audience — reading level calibrated in two minutes.
Ask AI to score your curriculum across defined quality dimensions — sequencing, outcome alignment, depth, completeness — and get a structured rating with reasoning for each.
Ask AI to describe what a best-in-class course on your topic includes, then compare your curriculum to that benchmark to find gaps and confirm your strengths.
AI evaluates whether your curriculum logically delivers on your outcome promise by checking each module against the stated goal and flagging what is missing or misaligned.
AI reliably catches structural problems — sequencing, missing steps, outcome mismatches, pacing — but not subject matter accuracy. Use it for structure; use your expertise for content.
Run adversarial prompts before launch — ask AI to find the holes, challenge the logic, and predict where students will fail. Three prompts, fifteen minutes, expensive problems avoided.
Share your lesson outlines with AI and ask it to flag lessons that are too long, too short, or too shallow — it catches pacing problems you can no longer see yourself.
Give AI a detailed student profile, then ask it to review your course as that student. You get student-perspective feedback before a single real student enrols.