Rethinking Workflows: A 2-Day AI Experiment
Product Team and Workflow Goal
I’ve been working with a learning community of UX professionals to create career development opportunities. The biggest topic in recent discussions has been the power of AI and how it affects product teams’ day-to-day work.
This sparked an idea to launch an AI Hackathon. In partnership with the UX Wizards team, I led a 2-day AI Hackathon activity.
The goal was simple. Use AI across stages of the product development process from research to prototype and explore how teams can collaborate more effectively with these tools. Two teams worked in small groups to build functional prototypes in just two days. We embedded AI directly into our workflows and one thing became clear.
AI Accelerates, But Humans Guide
The biggest shift wasn’t just speed, it changed how we worked.
We moved faster and produced solutions rapidly, but the real challenge wasn’t execution or output. It was prioritizing where to focus and making the most impactful decisions. This is where humans in the loop with experience and disciplinary knowledge became an advantage. For example, an experienced marketer quickly identified viable market opportunities, while a developer made informed recommendations around system integrations.
AI accelerated the work but domain knowledge guided it.
Brainstorming - in minutes we organized all types of messy data ie. meeting recordings, post-its, drawings into consumable, structured ideas we aligned on using speech prompts.
What We Tested
- Synthesizing research and team discussions
- Structuring messy brainstorming inputs; notes, recordings, sketches
- Generating concepts, narratives, and presentation content
- Supporting cross-functional collaboration across roles
Research - identified market opportunities and problems in minutes building interactive knowledge bases that summarized industry studies.
Challenges
- Managing signal over noise in high-volume AI outputs
- Maintaining focus on the highest-impact problems
- Accelerated decision-making and judgement calls
- Increasing reliance on strong domain expertise
- Determining when and where to apply AI effectively
What Worked
AI technology proved to be an accelerator. It accelerated productivity and enabled teams to deliver with incredible speed but this came with more responsibility. It raised the bar for judgement calls and decision.
Keeping humans in the loop especially those with strong domain expertise was not just an advantage, it was essential for ensuring the right decisions were made and someone was accountable.
- Speed and alignment improved immediately
- Research: Opportunities and insights surfaced in minutes
- Brainstorming: Raw inputs became structured, actionable ideas quickly
- Collaboration: AI enabled teams to communicate ideas in new ways
Closing Thoughts
As a team, we produced deliverables we’re proud of, and some participants are already exploring ways to bring their solutions to market. More importantly, it was inspiring to discover new and powerful ways to collaborate and gain new skills along the way.
What are you doing to empower your teams and unlock the value of AI?
I’d love to hear about what you’re working on or explore how I can help your team optimize workflows and get the most out of emerging technology.