Blog
Articles from the Replai team on expertise, AI, and enterprise workflows.
When should you fine-tune a video model?
A decision framework for knowing when inference-time control is no longer enough for video generation.
Video generation is a planning problem
Controllable AI video looks more like compilation than prompting: explicit shot plans, visual anchors, selective continuity state and local repair.
The first frame is a contract, not a thumbnail
Controllable AI video starts with a clear opening frame. Define what must remain true, add compatible motion controls, and evaluate fidelity, movement and creative validity.
The Goal Is Not Maximum Autonomy
Bounded autonomy assigns authority to each decision based on reversibility, blast radius, evaluator reliability and frequency. Human attention goes where it changes the outcome.
AI video evals should behave like a test suite, not a critic
AI video evaluation needs explicit tests, deterministic checks, specialist judges and selective expert review. Each decision needs evidence, and each evaluator needs validation.
Stop calling everything agent memory
Facts, procedures, current work and past experience need different rules. Separate knowledge, skills, working context and memory by scope, ownership and update policy.
From expert judgement to executable creative workflows
How Replai is building a system that increases creative experimentation without throwing away the expertise that made the original work good.