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Coordinating chaos: Preventing workflow fragmentation when everyone accelerates with AI

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Coordinating chaos: Preventing workflow fragmentation when everyone accelerates with AI

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Tuesday, June 9, 2026 • Designing with AI 2026
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Coordinating chaos: Preventing workflow fragmentation when everyone accelerates with AI
Speakers: Claire Dhoosche
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Summary

When Product, Design, and Tech all adopt AI in parallel, we instinctively think about tools. I discovered through my experience at Criteo that the real challenge is profoundly human: aligning teams with different visions, different fears, and different territories to protect, into a shared workflow that actually makes sense. This is the story of my transformation-building journey over the past year, within Product, for designers as a team. In a world where almost everyone can do almost everything thanks to AI – in a company like Criteo, with 4,000 employees, 900 devs, 80 PMs, and 35 designers – how do you operate this AI transformation without it becoming a mess?

Key Insights

  • Successful AI adoption depends more on collaboration and orchestration than on individual tools.

  • Mapping the actual end-to-end workflow reveals where information loss and slowdowns happen.

  • AI initiatives must be positioned clearly within the workflow to make their impact and dependencies visible.

  • Unaligned prototyping tools like Replit can accelerate one team but create confusion and rework for others.

  • Defining prototyping scope with clear ownership for vision (PM), design prototype (design), and code artifact (tech) resolves cross-function confusion.

  • Better collaboration between design and engineering can solve problems that no existing prototyping tool could handle alone.

  • Forming cross-functional working groups with regular check-ins sustains collaboration and alignment in large organizations.

  • The convergence of PM, design, and tech roles via AI tools blurs lines but increases the need for clear accountability.

  • Design ops acts as a UX designer for internal teams, crucial for shaping processes that accelerate AI adoption.

  • Measuring AI initiative success requires tracking adoption, quality, and productivity from multiple angles—individual tasks and overall projects.

Notable Quotes

"This talk is not about AI. It's about collaboration and orchestration."

"Acceleration without losing quality is a company-wide goal, not just a design, product, or tech goal."

"Tools alone guarantee nothing. What really changes the game is where they sit in your workflow and how teams work together around them."

"Unaligned prototyping creates confusion: is this a vision? A finished product? Who owns it? Who maintains it?"

"We had three different definitions of what a prototype was across PM, design, and tech."

"If the best AI prototyping tools can’t understand our complex design system, no other tool can."

"The answer wasn’t a better tool, it was better collaboration."

"Alignment isn’t a one-time event. You build it, and then you maintain it."

"Even with all our automation, we always need a human to judge the output."

"Don’t start with the tools, start with the people."

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