AI Character Live Runtime
Building AI characters that can perform live without getting tired.
A live runtime for AI Vtuber-style characters that can stream, publish videos and shorts, remember viewers, follow scripts, and run fully automated shows.
4
active AI Vtubers
3000+
watch hours
24h
stream potential
Auto
live performance
The Problem
Human Vtuber performance is constrained by fatigue, scheduling, memory, and consistency. The challenge was making AI characters feel alive while also being stable enough for real livestream operation.
Role: Project Lead · Persona Designer · Runtime Debugger · Live Flow Owner · Tooling Integrator
These 4 characters are real and currently in active operation — the cards are a recreation, but the roster and the numbers are not.
Illustrative — not a real screenshot
AI Streamer 01 · live now
412 watching · started 18m ago
AI Streamer 02 · live now
198 watching · started 42m ago
AI Streamer 03 · live now
356 watching · started 7m ago
AI Streamer 04 · live now
287 watching · started 53m ago
3000+
watch hours — accumulated from real viewers, not a lab demo.
Before
- 01
Characters could exist as concepts, but live operation required many fragile manual pieces.
- 02
Persona, tooling, runtime behavior, and livestream flow were not yet unified into a stable performance system.
- 03
Long-running shows needed better consistency than a human operator could maintain manually.
After
- 01
Four active AI Vtuber-style characters now run across livestreams, videos, and shorts.
- 02
The system has accumulated more than 3000 watch hours from real users.
- 03
AI characters can run stable fully automated livestream performances.
- 04
A confidential collaboration with a listed Taiwanese game company validated that the AI virtual talent could perform better live than a human-played Vtuber in the tested context.
one stable runtime
Contributions
What I actually did.
Led project management and execution across persona, runtime, and live workflow.
Designed character personas and operating behavior.
Debugged runtime issues and livestream flow stability.
Defined character settings, tool connections, and automated show behavior.
Coordinated the system toward demo-ready and production-like livestream performance.
AI collaboration governance
Keeping AI characters live without incident isn't about writing a good script — it's about turning "which AI behaviors can't be left unchecked" into architecture and rules. This page is the governance I paid for in hard lessons.
Governance cases
Open for first-hand evidence
The AI's ingrained pattern
Early vibe coding: the character's stateless persona data and stateful runtime sessions all lived in one Node.js process's inline memory. An hour into a stream, as concurrency rose, context bloat caused an OOM and the character froze — amnesiac — live on air.
The governance mechanism I built
Broke decisively with vibe coding, separating identity, writing style, and the memory layer — stateless persona decoupled from stateful runtime — and built an observable runtime debugging path.
The collaboration value it unlocked
The lesson that a hollow prototype collapses at first contact with production forced my architecture thinking; that failure is the real starting point for the whole runtime and workflow I designed afterward.
The AI's ingrained pattern
I assumed generating a readable script was as simple as writing copy, but the AI-generated stream agenda had too heavy an AI footprint — too formulaic, no character voice, no flexibility. It produced "averagely correct" but soulless content.
The governance mechanism I built
Beyond iterating with front-line operators, I redesigned the whole generation flow so the agenda starts entirely from the character: pick topics, generate the agenda, deliver the script, read the chat, break from the script when it fits — every step bound to the persona.
The collaboration value it unlocked
Upgraded "can generate" into "a stream this character would actually run"; the flow now outputs performances with humanity and character consistency, not generic AI scripts.
The AI's ingrained pattern
AI defaults toward being all-obliging, answering anything — but that dilutes a persona. A character who can do and knows everything feels less like a real person.
The governance mechanism I built
Built each character from scratch with a fully-formed identity: values, preferences, behavioral norms — explicitly drawing the line on what the character does NOT do, extracting the human-felt "AI-ness" to suppress it deliberately.
The collaboration value it unlocked
A rarely-noticed governance dimension — making a character credible through what it refrains from, rather than exposing itself by being omnicapable.
Outcomes
Validated with real viewers
The system is not only a lab demo: active characters have produced thousands of hours of watch time.
Always-on performance
Unlike human performers, AI characters can stream continuously, follow scripts precisely, and remember viewer context.
Commercial collaboration
Built and tested a confidential all-AI virtual entertainer with a known Taiwanese public game company.
Specific character identities and partner names are intentionally omitted for confidentiality.