Your design team, working agentically.
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AI in design gets used for the wrong half of the job.
Teams reach for image generation and get output nobody needed. The gains are in research synthesis, iteration speed, and designing the states an agentic product actually has: slow, unsure, partly right, wrong. We set up the first and we teach the second.
Your designers have the tools too. What they do not have is a process built around them, or patterns for the products your engineers are now shipping.
Every pattern in your design system assumes determinism. Press the button, get the result. Agentic products break that, and the interface has to carry it honestly or people stop trusting the product.
Where research, iteration and handover lose time, and what your team still does by hand that it should not. Output: a ranked list of where AI belongs in your design process, and where it does not.
Research synthesis, rapid prototyping, and variant and content generation, wired into the tools your team already uses. Output: a working process, not a list of tool recommendations.
Your first real surfaces where output varies. Trust, streaming, sources, confidence, correction and undo, tested against live model output rather than perfect placeholder text. Output: patterns proven with real users.
Agent states and correction flows as components your designers and engineers share. Output: an AI pattern library your team owns and maintains.
What our clients say.
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Any Questions?
