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The Notion team was frustrated by their AI assistant repeatedly hallucinating icon names. They built a custom "skill" that, when prompted to add an icon, runs a script to programmatically search their icon library for the correct filename using synonyms (e.g., searching for "magnifying glass" when asked for "search").

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For niche tasks, leverage an AI model with deep domain knowledge (like Claude for its own 'Skills' feature) to create highly specific prompts. Then, feed these optimized prompts into a powerful, generalist coding assistant (like Google's) to achieve a more accurate and robust final product.

Instead of complex SDKs or custom code, users can extend tools like Cowork by writing simple Markdown files called "Skills." These files guide the AI's behavior, making customization accessible to a broader audience and proving highly effective with powerful models.

Atlassian found users struggled with prompting, using vague language like 'change logo to JIRA' which caused the AI to pull old assets. They embedded pre-written, copyable commands into their prototyping templates. This guides users to interact with the underlying code correctly, reducing hallucinations and boosting confidence.

Users can now upload instructional files to teach Claude AI specific abilities. This allows the AI to perform complex, branded tasks like creating presentations or designing posters according to a company's unique style guide, effectively turning it into a personalized expert assistant.

Instead of iterating on prompts for single assets, focus on building reusable systems. This approach ensures brand consistency, saves time, and empowers non-designers to create on-brand assets efficiently by turning complex workflows into simple interfaces.

The process of building AI tools is becoming automated. Claude features a 'Skill Creator,' a skill that builds other skills from natural language prompts. This meta-capability allows users to generate custom AI workflows without writing code, essentially asking the AI to build the exact tool they need for a task.

A key aspect of Claude's new feature is its ability to intelligently choose the right tool for the job. When a user makes a request, the AI automatically scans its library of uploaded skills and selects the most appropriate one without needing to be explicitly told, creating a seamless user experience.

Instead of uploading brand guides for every new AI task, use Claude's "Skills" feature to create a persistent knowledge base. This allows the AI to access core business information like brand voice or design kits across all projects, saving time and ensuring consistency.

Instead of generating UIs from scratch, Atlassian provides AI tools with a pre-coded template containing complex elements like navigation. The AI is much better at modifying existing code than creating complex layouts from nothing, reducing the error rate for navigation elements from 50% to nearly zero.

Treat AI skills not just as prompts, but as instruction manuals embodying deep domain expertise. An expert can 'download their brain' into a skill, providing the final 10-20% of nuance that generic AI outputs lack, leading to superior results.

Combat AI Asset Hallucination by Building a Synonym-Searching "Find Icon" Skill | RiffOn