- 01
Define the tool evaluation job
Treat “ai highlight” as a search job to investigate, not as proof that a SEELE feature exists. First clarify the requested job, observe current controls on a bounded test, and document workflow fit and evidence gaps. Write the intended audience, source owner, desired change, protected details, reviewer, and delivery condition before selecting any interface or model. That brief keeps the evaluation specific and makes an unsupported assumption visible early. Before revision, preserve the handoff draft, and ask the rights reviewer to record evidence freshness before the acceptance review.
- 02
Prepare inputs for clips, shorts, and highlights
For this topic, assemble the authorized long-form source, target channel, required context, duration range, and caption needs. Record where each source came from, who may use it, and what must remain unchanged. Use a small representative asset for the first pass, keep the original untouched, and define a fallback route so experimentation cannot silently become the production master. Before revision, preserve the delivery checklist, and ask the delivery owner to record destination fit before the fallback decision.
- Confirm ownership, consent, and allowed reuse For this decision, preserve the review copy, and ask the claims reviewer to record destination fit before the reversible handoff.
- Preserve an untouched source and version history For this decision, preserve the test fixture, and ask the channel editor to record evidence freshness before the reversible handoff.
- Name the reviewer and acceptance condition For this decision, preserve the source ledger, and ask the policy reviewer to record camera logic before the reversible handoff.
- 03
Test observable controls for ai highlight
A bounded evaluation should inspect moment selection, context preservation, reframing, pacing, captions, and the final call to action. Change one meaningful variable at a time and record the date, workspace, account context, input, setting, result, and failure. Topic selection can prioritize the question, but it does not establish availability, quality, speed, licensing, or a supported SEELE workflow. For this decision, preserve the decision history, and ask the release approver to record failure conditions before the reversible handoff.
- 04
Review evidence, safety, and policy boundaries
A compelling excerpt must not distort the speaker's meaning or imply automatic publishing or platform approval. Use only authorized media, separate observed behavior from marketing language, and check current first-party documentation for any product-specific claim. For third-party products, competitors, plans, models, and platform rules, attach a verification date and primary source; an absent statement is an evidence gap rather than proof of a limitation. Before delivery, preserve the claim inventory, and ask the accessibility reviewer to record reversal cost before the scope confirmation.
- 05
Approve a reversible production handoff
Before advancing “ai highlight”, compare each excerpt with its source, check that edits preserve meaning, and validate current channel specifications. Document remaining manual work, unresolved evidence, destination requirements, and the person accepting the result. The handoff should preserve sources and test notes, allow correction, and avoid promises about output quality, turnaround, business performance, publishing, or access that the evidence does not support. Before revision, preserve the claim inventory, and ask the workflow owner to record identity consent before the scope confirmation.