AI Prompt Encoding: From Brief to Validated Job
Turn natural-language media briefs into constrained, reviewable configuration without giving a model unrestricted execution.
Read the guide · 6 minAI Prompt Encode API / A brief is just the beginning
Translate natural-language media requests into constrained configuration, with a visible boundary between proposal and permission.
Use a prompt-planning layer to propose a small set of approved choices. A valid object is only the start: the application must still confirm source access, compatible profiles, timing bounds, and publication review.
Identify the source, intended outcome, allowed profiles, and decisions that require editorial review before proposing a job.
Reject unknown properties and unsupported values. Validate relationships such as interval bounds against real asset data.
Translate an approved configuration through a controlled adapter. Do not execute arbitrary model-generated shell instructions.
MAKE SUCCESS OBSERVABLE
Use these as planning prompts. Adapt the acceptance conditions to your actual source and destination.
Technical background: JSON Schema validation reference ↗. The workflow suggestions here are editorial design patterns, not service guarantees.
GO DEEPER
Turn natural-language media briefs into constrained, reviewable configuration without giving a model unrestricted execution.
Read the guide · 6 minTurn long recordings into reviewed clips with explicit timing, framing, caption, and synchronization decisions.
Read the guide · 6 minDesign text preparation around the chosen tokenizer, context budget, Unicode handling, and explicit truncation rules.
Read the guide · 6 minMAKE THE NEXT STEP A CLEAR ONE
Bring a question, share a correction, or talk about an encoding idea.