What is exploratory AI prototyping?

Exploratory AI prototyping is a discovery-first approach to prototyping that uses AI tools to expose unknowns, reveal possibilities, and inform strategy before building. It transforms prototypes into instruments for discovery and credible proofs of concept, not just validation.

What are branching techniques in prototyping?

Branching techniques allow you to explore multiple design directions simultaneously, creating parallel prototypes to test different approaches. This enables safe, rapid learning by comparing alternatives without committing to a single path early in the design process.

What is context priming in AI prototyping?

Context priming involves providing AI tools with structured background information, design system constraints, and project context before generating prototypes. This helps AI understand the problem space and generate more relevant, useful prototypes.

What is a structured prompting framework?

A structured prompting framework is a systematic approach to writing prompts for AI tools that turns ambiguity into actionable plans. It involves breaking down complex problems into clear, sequential steps and providing the right context at each stage.

How does discovery-first prototyping reduce risk?

Discovery-first prototyping uncovers complexity and uncertainties before you begin building, allowing teams to identify potential issues early and make informed decisions. This reduces the risk of derailing projects or locking teams into bad decisions later in the development process.

Who should attend this session on prototyping for the unknown?

This session is for design system practitioners, design technologists, engineers, product designers, and design leaders who are tackling complexity at scale and want to learn how to use AI prototyping to expose unknowns and inform strategy.

What is the difference between exploratory prototyping and traditional prototyping?

Traditional prototyping validates existing ideas, while exploratory prototyping discovers new possibilities and exposes unknowns before building. Exploratory prototyping uses branching techniques, context priming, and structured prompting to transform prototypes into discovery instruments.

Conference Agenda March 2026

Complete schedule for Into Design Systems Conference 2026. March 19-20 online. 14+ sessions on AI Design Systems, Vibe Coding, MCP integrations. Speakers from WhatsApp, Miro, Indeed, Adobe, GitHub, Figma.

Day 1 - March 19, 2026

Prototyping for the unknown by Nate Baldwin (5:00 PM - 6:00 PM)
WhatsApp Web: Reclaiming UI Excellence through Vibe Coding by Sebastian Rousseau (6:00 PM - 7:00 PM)
Product Primitives: The New Material of Design System by Yesenia Perez-Cruz (7:00 PM - 8:00 PM)
The path to an AI enabled design system: Our approach and lessons learned by Andressa Lombardo & Eddie Machado (8:00 PM - 9:00 PM)
Agentic Design Systems by Romina Kavcic (9:30 PM - 10:30 PM)
I'm not an engineer but I ship code: How designers can ship production code and work like an engineer by Freya Stockman (10:30 PM - 11:30 PM)
Context > Probability: Design systems as AI infrastructure by Jesse Gardner (11:30 PM - 12:30 AM)
Encoding governance on agentic design systems by Cristian Morales Achiardi (12:30 AM - 1:30 AM)

Day 2 - March 20, 2026

Building real design systems with agents by Jan Six (5:00 PM - 6:00 PM)
Vibe coding with zero drift: from Figma to Storybook to Production by Shuaiqi (Mr.Biscuit) Sun (6:00 PM - 7:00 PM)
Machine-Readable Design Systems for MCP and LLMs by Diana Wolosin (7:00 PM - 8:00 PM)
From falling for markdown to solving real problems with scripts by Laura Fehre (8:00 PM - 9:00 PM)
Ship It! Vibe Coding Your First Figma Plugin by Davy Fung (9:30 PM - 10:30 PM)
Designers Who Ship: Building a Real Plugin in 48 Hours with AI by Casandra Sandu, Christoph Hellmuth & Raquel Pereira (10:30 PM - 11:30 PM)
AI Without the Chaos: Context-Based Design Systems to the Rescue by Brad Frost, Ian Frost & TJ Pitre (11:30 PM - 12:30 AM)

Prototyping for the unknown

Complex systems hide uncertainties that can derail projects or lock teams into bad decisions. Too often, these challenges only surface once you're deep into building. What if you could uncover complexity before you begin building?

This talk shows how exploratory AI prototyping can expose unknowns, reveal possibilities, and inform strategy for large-scale systems. We'll go beyond novelty tools and demonstrate the sophisticated potential of vibe coding through real-world examples. You will learn practical methods for branching, context priming, and structured prompting. These techniques transform prototypes into instruments for discovery and credible proofs of concept, not just validation.

Key Learnings

Why discovery-first prototyping accelerates complex projects and reduces risk
How to use branching techniques for safe, rapid learning
A structured prompting framework that turns ambiguity into actionable plans

Who is this for

Design system practitioners, design technologists, engineers, product designers, and design leaders tackling complexity at scale.

Speaker

Nate Baldwin, Sr Staff Experience Designer at Adobe's Spectrum Design System. Nate is a designer driven by a passion for elevating enterprise-level design quality through systems and processes. His deep curiosity about visual perception and science fuels his work in creating flexible, adaptive, and accessible design systems. Nate has worked on design systems for over 10 years, with a specialty in generative and accessible color. Originally starting his journey in Fine Art, Nate discovered a passion for UX design and now brings his expertise to Adobe's Spectrum as a Senior Staff Designer. He's the creator of free online tools and resources for design such as ColorAndContrast.com, LeonardoColor.io, and Proportio.app.

Tags: Design Systems, Vibe Coding

Prototyping for the unknown

About this Session

From my session, you will learn:

Who is this for?

Presented by:

Nate Baldwin

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