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Slides: Using Spec-Driven Development for Production Workflows - Erik Hanchett, AWS

Source Video

Using Spec-Driven Development for Production Workflows - Erik Hanchett, AWS

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

• Recreated text/layout view: open HTML recreation
• AI slide classifier: title_card confidence 0.98
• Text source: agent_vision.

Slide text:

What is Spec-Driven Development?

And how can it make code faster?

• Recreated text/layout view: open HTML recreation
• AI slide classifier: content_slide confidence 0.99
• Text source: agent_vision.

Slide text:

Spec-Driven Development

Structured specifications are created before any code is written.

• Recreated text/layout view: open HTML recreation
• AI slide classifier: content_slide confidence 0.9
• Text source: agent_vision.
• OCR decision: ready — Multi-column diagram with smaller labels and embedded logos; OCR can recover the full on-slide text more efficiently than manual transcription.

Slide text:

A Solution to the Integrations Problem

• Recreated text/layout view: open HTML recreation
• AI slide classifier: content_slide confidence 0.97
• Text source: none.
• OCR decision: ready — Dense code/editor screenshot with small UI text and multiple panes is better handled by OCR.
• Slide text: not surfaced (none by AI classifier).

• Recreated text/layout view: open HTML recreation
• AI slide classifier: title_card confidence 0.98
• Text source: agent_vision.

Slide text:

Thanks!

LinkedIn: Erik Hanchett

X/Bluesky: Erikch

Classification audit: raw/sources/slide-ai-classification/slides/IddXPepIAS4/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.