My AI Agent Isn't Allowed to Decide Anything

Description and use

Shot‑Delivery Guardian uses AI to analyze a post‑production pipeline and recommend a safe task to delay, while a fixed rule makes the final decision, ensuring client and director constraints are respected.

Problem

When a film or TV production nears a delivery deadline, a bottleneck in any post‑production step can cause a missed deadline unless a human manually delays another task. The manual process is slow and error‑prone.

Outcome

In live tests, the system correctly identified safe tasks 60% of the time (3 of 5), matching the fixed rule’s choice. It reported issues in 44 seconds on average and never violated any safety rules.

Workflow

• 1. Monitor pipeline stages via three monitoring tools (overall backlog, task metadata, and stage‑level timing).
• 2. AI queries each tool to gather current state.
• 3. AI applies the fixed rule to filter out client‑approved, director‑flagged, or dependent tasks and selects the one with the most slack.
• 4. AI writes the recommendation as a note on the existing dashboard.
• 5. Human on call reviews the note and confirms the delay.
• 6. System logs the decision and updates the pipeline state.

Evidence

Three out of five. That's how often Shot‑Delivery Guardian, the system I built for Google's Agentic Cinema hackathon, picks the right answer when it's the one making that call, in real tests against the actual running system, not just on my laptop.

Source

It never once picked a piece of work the client had already signed off on. It never once picked something other work was waiting on. It never once touched anything the director had flagged as important.

Source

About 44 seconds on average to look into a problem and respond, timed against the real live system.

Source