# FALSIFY — 30-second demo script

A tight, judge-ready narration. Total runtime ~30s of talking over one `python main.py --demo` run. Capture the terminal + the `output/graph.html` for the GIF.

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## Setup (before recording)
- Terminal with a dark theme, font large enough to read on playback.
- `.env` has a working `LLM_API_KEY` (so embeddings + recall are real).
- Run once beforehand to warm caches; record the second run.

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## Beat sheet

**[0:00–0:05] The hook**
> "Every AI memory demo fixes *forgetting*. FALSIFY fixes something worse — an AI that confidently remembers a fact that's been **proven false**."

*Run:* `python main.py --demo`

**[0:05–0:12] Session 1 — the belief graph**
> "We're investigating: *did Company X know about the defect before the recall?* Two hypotheses — a March QA report, and a January supplier email. A conclusion rests on that March report."

*On screen:* the **BEFORE** panel — every node tagged `ALIVE` in green.

**[0:12–0:20] Session 2 — one contradicting fact**
> "Now one line arrives: *a forensic audit found the March report was back-dated.* Watch."

*On screen:* the revision log —
```
✗ refuted: 1 evidence node
✗ invalidated: 1 conclusion
hypothesis A → ↓ superseded
hypothesis B → ↑ promoted (new frontier)
🗑 forgotten: Company X knew about the defect by March 2021
```

**[0:20–0:27] The AFTER + scoreboard**
> "The March evidence is red. The conclusion built on it collapsed and was **surgically deleted** — from the graph *and* the vector store. Hypothesis B ignites as the new answer."

*On screen:* the **SCOREBOARD** —
```
FALSIFY : X knew by Jan 2021 (supplier email)      ← revised
RAG     : X knew by Mar 2021 (QA report)  [STALE]  ← still cites the refuted fact
```

**[0:27–0:30] The close**
> "Same store, same query. FALSIFY revised its belief and the disbelief persists across sessions. Plain RAG can't. **AI revised, not forgot.**"

*On screen:* open `output/graph.html` — the red refuted node, the missing orphan, the green frontier.

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## The single most important line
> **"It's not that the AI forgot where the context was — the context was *wrong*, and FALSIFY revised it."**

That reframes the hackathon's "Where's My Context?" theme into FALSIFY's exact contribution.

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## If asked "why can't RAG do this?"
> "Refutation is graph traversal over typed edges — *this fact grounds that conclusion three hops away.* A vector index has no edges to walk and no truth-state to filter on. This needs a knowledge graph — which is exactly what Cognee gives us."