# One Designer + AI. Hundreds of Deliverables. — Vincent Wendy, AI Engineer

## Executive summary

This talk details how one designer managed the massive scale of deliverables (signage, stickers, landing pages, etc.) for a large conference (7,000 attendees, 140+ sponsors, 300+ speakers). The solution involves implementing a structured design system and automating workflows using AI agents (like Devin) and tools like Figma. The core methodology emphasizes shifting from manual, linear processes to highly automated, validated pipelines to solve the 'scale problem.'

## Key takeaways

- The Five Pillars of Scaling Design: To manage massive deliverables, the process must focus on: 1) Building a solid foundation (design system, typography, components); 2) Making designs reusable; 3) Automating workflows; 4) Validating output; and 5) Removing friction. (4:45)
- AI Agents for Automation: AI agents (e.g., Devin) are used to automate complex tasks, such as generating speaker announcement graphics and trading cards for 300+ speakers, or pulling live schedule data and exporting it as PNGs. (9:16)
- Systemic QA and Validation: AI can be used for visual quality assurance (QA), such as checking 140+ sponsor logos on a banner for missing assets or detecting visual inconsistencies on merchandise. (13:15)
- Thinking as a User: The most critical shift is to think like an end-user (attendee) rather than a designer, focusing on handling exceptions and ensuring all elements (wayfinding, schedules) are interconnected. (14:21)

## Technical details

- Design System Foundation: Establishing a tightly defined design system (typography, color palettes, components) ensures consistency and allows non-design teams (like marketing) to build deliverables (emails, flyers) without direct designer involvement. (6:54)
- Automated Data Pipelines: Schedule signage, once manually laid out in Figma, can now pull fresh data from live sources, export it, and be displayed on physical screens. (6:54)
- AI-Assisted Content Generation: A generator can automatically produce pixel-perfect speaker announcement graphics and trading cards, pulling in headshots and details for hundreds of speakers. (9:16)
- Developer-Designer Collaboration: The process is streamlined by connecting tools like Slack and Figma, allowing AI agents to annotate PDFs (spec sheets) and define spacing, font sizes, and colors, enabling pixel-perfect development. (11:50)

## Practical implications

- Implement structured design systems (atomic design) early in the product lifecycle to ensure consistency across all marketing and physical assets.
- Treat design deliverables as automated pipelines, connecting live data sources (e.g., scheduling databases) directly to output formats (PNG, signage).
- Utilize AI agents for high-volume, repetitive tasks (e.g., generating hundreds of similar graphics) to drastically reduce manual labor and human error.
- Shift QA processes to include AI-driven visual checks (e.g., logo gap detection) to ensure comprehensive coverage.

## Topics

AI Automation, Design Systems, Workflow Optimization, Build Engineering, Product Design, Large-Scale Event Management, Devin, GPT, Figma, Spec Sheet (Plugin)

Source: https://www.youtube.com/watch?v=O1FN4awNEtM