---
title: "Slides: GTM Is You - Victoria Melnikova, Evil Martians"
category: "slides"
video_id: "G6IlDzj8OjA"
sourceLabels: ["Public YouTube video frames", "Public YouTube metadata"]
---

# Slides: GTM Is You - Victoria Melnikova, Evil Martians

## Source Video
[GTM Is You - Victoria Melnikova, Evil Martians](https://www.youtube.com/watch?v=G6IlDzj8OjA)

## Relationship To World's Fair 2026
These slides are extracted from a public AI Engineer YouTube video connected to World's Fair 2026. Speaker-matched clips are supporting context unless later confirmed as exact session recordings; official livestream recordings are day-level/event-level source material.

## Related Scheduled Sessions
- No individual scheduled session mapping has been assigned yet; treat this as an event livestream deck.

## Extracted Slides
![[assets/slides/G6IlDzj8OjA/slide-003.jpg]]

- Recreated text/layout view: [open HTML recreation](/assets/slide-recreations/slides/G6IlDzj8OjA/slide-003.html)
- AI slide classifier: `content_slide` confidence `0.98`
- Text source: agent_vision.

Slide text:

> The PMF compass We analyzed 37 successful devtools: Cursor, Vercel, Supabase, Linear and others

![[assets/slides/G6IlDzj8OjA/slide-004.jpg]]

- Recreated text/layout view: [open HTML recreation](/assets/slide-recreations/slides/G6IlDzj8OjA/slide-004.html)
- AI slide classifier: `content_slide` confidence `0.98`
- Text source: agent_vision.

Slide text:

> For early-stage devtools 9 out of 10 startups Signal > Revenue

![[assets/slides/G6IlDzj8OjA/slide-005.jpg]]

- Recreated text/layout view: [open HTML recreation](/assets/slide-recreations/slides/G6IlDzj8OjA/slide-005.html)
- AI slide classifier: `content_slide` confidence `0.97`
- Text source: agent_vision.

Slide text:

> Come to SF

![[assets/slides/G6IlDzj8OjA/slide-008.jpg]]

- Recreated text/layout view: [open HTML recreation](/assets/slide-recreations/slides/G6IlDzj8OjA/slide-008.html)
- AI slide classifier: `content_slide` confidence `0.97`
- Text source: agent_vision.

Slide text:

> Do events in SF


### Hidden Non-Slide Evidence
- [`slide-001.jpg`](/assets/slides/G6IlDzj8OjA/slide-001.jpg) — `speaker_stage` confidence `0.99`; speaker camera shot, not a slide
- [`slide-002.jpg`](/assets/slides/G6IlDzj8OjA/slide-002.jpg) — `speaker_stage` confidence `0.99`; speaker camera shot, not a slide
- [`slide-006.jpg`](/assets/slides/G6IlDzj8OjA/slide-006.jpg) — `demo_video` confidence `0.96`; embedded video player, not a readable slide
- [`slide-007.jpg`](/assets/slides/G6IlDzj8OjA/slide-007.jpg) — `speaker_stage` confidence `0.99`; speaker camera shot, not a slide
- [`slide-009.jpg`](/assets/slides/G6IlDzj8OjA/slide-009.jpg) — `demo_video` confidence `0.97`; YouTube/demo-video frame with people on camera, not a presentation slide.

Classification audit: `raw/sources/slide-ai-classification/slides/G6IlDzj8OjA/audit.json`

## Slide-Derived Subjects To Review
Subject extraction uses video title, related session titles/descriptions, transcript context, and OCR text when available. OCR is best-effort and should be reviewed against the embedded slide images.