What Went Well
- Web search integration successfully retrieved up-to-date (2026) information on AI video models, including specific leading models like Veo 3.1 and Sora 2, and current industry formats.
- Formatting the compendium into distinct categories (Genres, Aesthetics, Tones, Formats) with clear “AI Friendliness” ratings (Low, Medium, High) worked well for structural clarity.
- Writing the output directly to the end of the target file using a standard shell append operation (
>>) was seamless and efficient.
What Didn’t Go Well
- Initially struggled to locate the
2026-05-18-genre-researcher-brief.mdfile. I spent time searching across the workspace and.scratchdirectories before realizing the file either hadn’t been created or was placed elsewhere. This stalled initial progress.
Failure Modes & Bottlenecks
- Missing Context Bottleneck: The primary bottleneck was the missing brief file at the start of the session. I had to query the coordinator, which resulted in a user steering intervention that provided the brief’s contents inline so I could unblock myself and proceed.
Key Decisions Made
- Decided to structure “AI Friendliness” as an explicit grading system (e.g., Low, Medium, High, Very High) to directly answer the prompt’s focus.
- Chose to write the compendium to a temporary scratchpad file first (
/workspace/.scratch/compendium.md) before appending it to the main2026-05-16-winning-short-film.mdreport. This ensured the formatting was correct before modifying an important existing document.
Suggestions for Improvement
- Ensure that agent briefs are consistently generated and placed in the correct, accessible directory before an agent is invoked to read them.
- For concise tasks, it might be more efficient for the coordinator to pass the core instructions directly within the kickoff message rather than relying on an external brief file.