Selected Work · AI Content System

From one video
to a production pipeline

I organized topic selection, scripting, visuals, voice, captions, covers, platform copy, and quality checks into a repeatable AI content pipeline. The goal is not merely to finish one video faster, but to make every episode inherit what the previous one taught me.

Role
Product design + content systems + AI collaboration
Stack
React · Remotion · FFmpeg · TTS
Status
Operational · Continuously improving
The Problem

The expensive part of video production is not any single edit. It is re-deciding everything for every episode: what to say, how to structure it, what to show, how audio and captions align, and what is still missing before publication. When a dozen steps depend on memory, finishing one video sends the next one back to zero.

How It Works

From an episode to a complete release

Content is data, components handle expression, and the final voice track owns the timeline. Five stages create a delivery chain that can be checked and reproduced.

LIAN VIDEO STUDIO
EPISODE 07 · SYSTEM READY
Production stages
PROGRESS1/5
Stage 01 · Episode Brief

Define the episode before writing it

Lock the series, audience, single question, and useful conclusion before expanding the script.

Only questionGiven the same urgent request, which Chinese model produces the safest answer to hand directly to a manager?
SeriesAI Inspection Desk
AudienceKnowledge workers choosing a Chinese LLM
HookThree models receive the exact same task
VerdictThe winner requires the least rework

The division of labor is explicit: skills preserve judgment, the episode configuration carries the content, software executes consistently, and a human makes the final call. AI does not decide what I believe; it handles the repetitive work after the decision.

Real Outputs

One foundation, multiple visual languages

These are frames from actual renders, not concept art. Structured content, voice, captions, and QA remain consistent while the visual language changes with the subject.

Four rendered frames showing a problem, a three-layer workflow, a release package, and stable execution
Structured explanationUse flows, comparisons, and conclusion cards to make an abstract method concrete.
A sequence of office-comic scenes showing an urgent task, a model test, a failure check, and a delivery decision
Office-comic micro dramaUse continuous scenes for tasks, conflict, and reversal—not merely a new skin on a slide deck.
The Release

Done means more than an MP4

Everything a platform needs is prepared in one release package, with each item open to inspection and traceability.

01 · Generate assets
MP4Vertical video
WEBPPlatform cover
SRTApproved captions
TXTPublishing copy
JSONEpisode config
QAVerification evidence
6/6
PASS
RELEASE / EP079:16 · 30FPS
06FILES
READY TO PUBLISH
Why It’s Different

Not “one-click viral.” Repeatable judgment.

BEFORE · AD-HOC PROJECT

Every episode starts from zero

Research, copy, audio, captions, and covers live in different places. Finishing one video leaves the next dependent on memory.

final_v7.mp4script-actually-finalcaptions-to-review.srtcover-change-againRESET
AFTER · REUSABLE SYSTEM

Every episode inherits the last

Judgment lives in the Brief and Skill, content enters the Episode, voice becomes the timeline, and every output lands in an inspectable Release.

01Brief
02Episode
03Timeline
04Release
Takeaway

From topic to publication, the work no longer breaks into a dozen projects waiting on one another.
The pipeline does not replace creative judgment. It makes each judgment executable, inspectable, and reusable.

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