Transcripts become an index
Time-aligned transcripts make long programs searchable. Preserve raw recognition, corrected text, timestamps, confidence, and verified speaker labels. Search and ranking can then operate on an accountable record instead of an unstructured media file.
A transcript is not the whole edit. Picture, tone, gesture, music, reaction, and the surrounding conversation can change the meaning of a quote.
Ask for structured candidates
Request source ID, start and end times, handles, proposed title, one-sentence summary, transcript excerpt, hook, context dependency, risk flags, and a boundary rationale. Require the system to mark uncertainty and avoid inventing speaker names.
Rank with explicit components such as completeness, relevance, technical quality, timeliness, audience fit, and risk. A reasoned candidate is easier to review than a mysterious virality score.
Keep a human in the meaning loop
Review the full source around every candidate. Check qualifiers, pronouns, off-screen references, overlapping speakers, claims, privacy, and rights. Listen and watch the exact render plan before approval.
Record rejection reasons. Duplicate, incomplete context, weak payoff, technical damage, rights concern, unsafe content, or wrong audience are useful labels for improving the system.
Publish provenance, not internal clutter
Internal records can preserve model version, prompt, candidate scores, reviewer, and decision history. Public feed items should present clean approved media and accurate metadata. Suggested copy should not masquerade as verified description.
The goal is a reproducible edit decision list that can be rendered in Premiere, Resolve, or another system and published as one stable Clip RSS item.
