Prompt caching in plain words: reuse context without paying twice

A 5-beat faceless video outline for “Prompt caching in plain words: reuse context without paying twice” in the AI tools explained niche, derived from caption timing of 2 reference videos.

Angles

• Define prompt caching as reusing the input prefix KV — not caching the model answer
• Show the cost/latency win when a long system+tools prefix stays stable
• Name the match rule: token-by-token prefix until the first difference
• Close on when caching helps agents vs when a changing prompt kills the hit rate

Beat-by-beat structure

1. Hook (0:00–0:30): 50k tokens of context again — promise you need not recompute it all.
2. Definition (0:30–2:00): cache the prompt side; still generate fresh outputs.
3. Mechanics (2:00–4:30): KV pairs across layers; prefix match until divergence.
4. Agent tip (4:30–6:00): keep tools/system stable; put churn at the end.
5. Recap. Original narration only.

Reference videos

• What is Prompt Caching? Optimize LLM Latency with AI Transformers u57EnkQaUTY
• Prompt Caching Explained: Stop Overpaying for AI Agents SkM4k4SKvCM

Method

yt-dlp VTT captions (manual/uploader only) → timed beat heuristics → editorial topic synthesis (no ASR). Structure only; write original narration.