dvcrn Demo Precacher
The golden rule of AI demos: never rely on live API calls during a presentation. This skill provides a systematic approach to pre-generating and verifying all demo content before you go live.
Why This Exists
In a 48-hour hackathon, we had 18 stories across 10 languages with audio narration, sound effects, and background music. During the demo, the Mistral API had a 3-second latency spike. Because everything was pre-cached, the demo played flawlessly from cache while the audience assumed it was generating in real-time.
The Pattern
async def precache_demo():
scenarios = [
{"name": "Sophie", "language": "fr", "prompt": "A story about cloud whales..."},
{"name": "Kai", "language": "ja", "prompt": "A story about bamboo forests..."},
]
for s in scenarios:
# Step 1: Generate content (hits the real API)
story = await generate_story(s["prompt"], s["name"], s["language"])
# Step 2: Cache the result
await cache.set(s, story)
# Step 3: Generate all derived content (audio, images)
for scene in story["scenes"]:
audio = await generate_tts(scene["text"], voice_id)
await cache.set(f"audio_{scene['id']}", audio)
# Step 4: Verify playback
cached = await cache.get(s)
assert cached is not None, f"Cache miss for {s['name']}"
# Step 5: Report coverage
print(f"Cached {len(scenarios)} scenarios, all verified ✅")
Checklist
Before any live demo, verify:
- All primary scenarios cached and verified
- Audio files playable (correct format, no corruption)
- Fallback content available if cache miss occurs
- Demo account credentials working
- Network not required for cached playback
- Cache TTL won't expire during the presentation
Files
scripts/precache_demo.py— Example precacher with verification and coverage reporting