World's Fair 2025
Build Dynamic Products, and Stop the AI Sideshow — Eliza Cabrera (Workday) + Jeremy Silva (Freeplay)
Overview
This talk argues for building dynamic, deeply integrated AI products rather than AI "sideshows" that are bolted onto existing systems. The core thesis is that companies should move beyond using AI primarily to demonstrate technological capability and instead focus on solving customer problems by integrating AI strategically into their core product development. This approach requires aligning AI and product strategies, teams, and roadmaps, and embracing a crawl, walk, run methodology for iterative development.
Who should watch
- Product Managers and Product Engineers looking to build differentiated AI-powered products.
- AI Engineers seeking to understand how to integrate AI capabilities beyond basic chatbots or co-pilots.
- Builders aiming to avoid common pitfalls in AI product development, such as focusing on technology over customer needs.
- Teams struggling with AI initiatives that feel like add-ons rather than core product features.
Key takeaways
- The initial phase of AI product development often involves using AI to explore technological boundaries, leading to undifferentiated "AI slideshows" or bolt-on features.
- Common causes for these AI sideshows include mitigating risk by quarantining AI, prioritizing technology over customer problems, and top-down solution pushing.
- To avoid the AI sideshow, integrate AI risk into product planning, start with customer problems, and enable bottom-up discovery processes.
- Successful AI integration results in products that solve customer problems more effectively without necessarily announcing themselves as AI.
- A crawl, walk, run approach allows organizations to iteratively build AI capabilities, starting with embedded experiences that enhance existing functionality, moving to more contextual and personalized features, and finally to dynamic, interoperable AI experiences.
- In the crawl phase, AI can be used on the backend to accelerate existing functionality, such as generating FAQs from policy documents or providing translations.
- The walk phase involves building new product surfaces with contextual AI, like a co-pilot that suggests actions based on the user's current task.
- The run phase entails fundamentally rethinking UI, UX, and architecture to create autonomous, proactive AI agents that operate across the product suite.
Notable quotes
Eliza Cabrera and Jeremy Silva advocate for stopping the AI slideshow and building dynamic products.
*The hallmark of good successful AI integration are AI products that need not announce themselves as AI but rather just solve the customer problem better than what came before.*
The crawl, walk, run approach helps teams iteratively build AI capabilities while laying the foundation throughout their product suite.
Unofficial community note. Prefer the recording for nuance.