Stitch Fix uses OpenAI's LLMs not to replace stylists, but to augment them. Their 'Note Assist' tool writes a first draft of personalized notes, handling the repetitive work. This allows stylists to spend more time on high-value tasks like creative styling and building empathetic customer relationships.
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To save time with busy clients, create a "synthetic" version in a GPT trained on their public statements and past feedback. This allows teams to get work 80-90% of the way to alignment internally, ensuring human interaction is focused on high-level strategy.
Beyond data analysis, Shutterfly's Director of Web Analytics envisions AI's primary role as a creator's assistant. For complex products like photo books that can take 30 hours to build, AI can drastically reduce customer effort by intelligently sorting photos and suggesting layouts. This makes high-value products more accessible to a broader audience.
Users are dissatisfied with purely AI-generated creative outputs like interior design, calling it "slop." This creates an opportunity for platforms that blend AI's efficiency with a human's taste and curation, for which consumers are willing to pay a premium.
An executive created a custom AI agent to handle repetitive tasks like meeting prep, calendar triage, and email. This "chief of staff" provides analysis, suggests delegations, and even offers blunt feedback, demonstrating how AI can be personalized to augment executive functions.
The most effective application of AI isn't a visible chatbot feature. It's an invisible layer that intelligently removes friction from existing user workflows. Instead of creating new work for users (like prompt engineering), AI should simplify experiences, like automatically surfacing a 'pay bill' link without the user ever consciously 'using AI.'
Even powerful AI tools don't produce a final, polished product. This "last mile" problem creates an opportunity for humans who master AI tools and then refine, integrate, and complete the work. These "finisher" roles are indispensable as there is no single AI solution to rule them all.
By handling repetitive production work, AI gives designers bandwidth to focus on high-impact, creative problems. This includes innovating on previously overlooked details like loading states, which have new importance in AI-driven products for building user trust.
Most AI writing tools produce generic content. Spiral was rebuilt to act as a partner. It first interviews the user to understand their thoughts and taste, helping them think more deeply before generating drafts. This collaborative process avoids "slop" and leads to more authentic writing.
LinkedIn is piloting a "Full Stack Builder" model where individuals handle the entire product lifecycle. The model's goal is to automate most tasks, allowing builders to focus on uniquely human traits: vision, empathy, communication, creativity, and especially judgment.
When AI automates a core task like content writing, don't eliminate the role. Instead, reframe it to leverage human judgment. A "content writer" can be transformed into a "content curator" who guides, edits, and validates AI-generated output. This shifts the focus from replacement to augmentation.
