Essential Work Sample Exercises for Hiring AI Documentation Specialists

Creating effective product documentation for AI systems requires a unique blend of technical understanding, communication skills, and organizational ability. Documentation specialists in this field must translate complex AI concepts into clear, accessible information for various audiences while maintaining technical accuracy. They serve as the critical bridge between sophisticated AI technology and the users who need to understand it.

The challenge in hiring for this specialized role lies in evaluating candidates' ability to not only understand AI concepts but also communicate them effectively through documentation. Traditional interviews often fail to reveal a candidate's actual documentation capabilities, their process for organizing information, or their skill in maintaining documentation as AI products evolve.

Work sample exercises provide a realistic preview of how candidates approach documentation tasks in an AI context. They demonstrate a candidate's ability to plan documentation architecture, create clear explanations of complex concepts, improve existing materials, and collaborate with technical stakeholders. These practical demonstrations reveal skills that might otherwise remain theoretical in a standard interview.

The following work samples are designed to evaluate candidates' abilities across the full spectrum of AI documentation responsibilities. Each exercise simulates real-world scenarios that documentation specialists encounter when working with AI products, from initial planning to ongoing maintenance. By observing candidates complete these tasks, hiring managers can make more informed decisions about which candidates possess the right combination of AI knowledge and documentation expertise.

Activity #1: Documentation Planning for a New AI Feature

This exercise evaluates a candidate's ability to strategically plan documentation for a new AI feature. Effective documentation begins with thoughtful planning that considers user needs, technical complexity, and organizational structure. This activity reveals how candidates approach the architecture of documentation and their understanding of different user personas interacting with AI systems.

Directions for the Company:

• Provide the candidate with a brief description of a new AI feature being added to your product (e.g., a new sentiment analysis capability, an image recognition feature, or an automated recommendation system).
• Include information about the target audience (e.g., developers integrating the API, data scientists fine-tuning the model, and end-users interacting with the feature).
• Supply any existing documentation structure or templates your company uses.
• Allow 45-60 minutes for this exercise.
• Prepare to evaluate the candidate's understanding of documentation needs for different user types and their ability to create a logical structure.

Directions for the Candidate:

• Review the AI feature description and audience information provided.
• Create a documentation plan that includes:
• An outline of documentation sections needed for this feature
• Identification of different documentation types required (e.g., API reference, tutorials, conceptual guides)
• A list of key concepts that will need explanation
• Suggestions for visual aids or examples that would enhance understanding
• A brief description of how you would approach gathering the necessary technical information
• Be prepared to explain your rationale for the documentation structure and priorities.

Feedback Mechanism:

• After reviewing the candidate's plan, provide feedback on one strength (e.g., "Your consideration of different user personas was thorough") and one area for improvement (e.g., "The technical reference section could benefit from more structure").
• Ask the candidate to spend 10 minutes revising one section of their plan based on your feedback.
• Observe how receptive they are to feedback and how effectively they incorporate it into their revision.

Activity #2: Explaining an AI Concept for Different Audiences

This exercise tests a candidate's ability to translate complex AI concepts into clear, accessible documentation for different audience types. A key skill for AI documentation specialists is adapting technical information to the knowledge level of various readers while maintaining accuracy. This activity reveals how candidates balance technical precision with clarity and audience awareness.

Directions for the Company:

• Select a moderately complex AI concept relevant to your product (e.g., embeddings, attention mechanisms, transfer learning, or model drift).
• Prepare a technical description of this concept that might come from a data scientist or ML engineer.
• Identify two distinct audience types that would need to understand this concept (e.g., non-technical business users and technical developers).
• Provide any style guides or tone guidelines your documentation typically follows.
• Allow 45-60 minutes for this exercise.

Directions for the Candidate:

• Review the technical description of the AI concept provided.
• Create two different explanations of the same concept:

1. An explanation for a technical audience (e.g., developers or data analysts) that maintains technical accuracy while being clear and practical
2. An explanation for a non-technical audience (e.g., business users or executives) that conveys the essential understanding without unnecessary complexity

• Include at least one analogy or visual description that helps illustrate the concept.
• Keep each explanation under 500 words.
• Consider what questions each audience might have and address them proactively.

Feedback Mechanism:

• Provide feedback on one strength (e.g., "Your analogy effectively simplified the concept") and one area for improvement (e.g., "The technical explanation assumes knowledge that some developers might not have").
• Ask the candidate to revise a specific paragraph based on your feedback.
• Evaluate how well they maintain the balance between accessibility and technical accuracy in their revision.

Activity #3: Documentation Review and Improvement

This exercise evaluates a candidate's ability to identify and fix problems in existing documentation. Maintenance is a critical aspect of documentation work, especially for AI products that evolve rapidly. This activity demonstrates the candidate's editorial skills, attention to detail, and ability to improve clarity while maintaining technical accuracy.

Directions for the Company:

• Prepare a sample of documentation about an AI feature that contains several issues:
• Technical inaccuracies or outdated information
• Unclear explanations or jargon without definition
• Poor structure or organization
• Missing information that would be necessary for user understanding
• The sample should be 2-3 pages in length and relate to a realistic AI feature.
• Provide any style guides or documentation standards your company follows.
• Allow 45-60 minutes for this exercise.

Directions for the Candidate:

• Review the provided documentation sample.
• Identify and list all issues you find, categorizing them as:
• Technical accuracy issues
• Clarity/readability issues
• Structural/organizational issues
• Missing information
• Create a revised version that addresses these issues.
• Write a brief explanation of the most significant changes you made and why.
• If you make assumptions about technical details, note these explicitly.

Feedback Mechanism:

• After reviewing their work, highlight one improvement they made effectively and one issue they either missed or didn't address optimally.
• Ask the candidate to explain how they would approach verifying the technical accuracy of their revisions in a real work environment.
• Have them make one additional improvement based on your feedback.
• Evaluate their process for verification and their receptiveness to feedback.

Activity #4: Technical Interview Simulation for Documentation Requirements

This exercise simulates the process of interviewing subject matter experts to gather information for documentation. Documentation specialists must effectively collaborate with AI engineers and data scientists to extract and clarify technical information. This activity reveals the candidate's ability to ask insightful questions, understand technical responses, and identify what information is most relevant for documentation.

Directions for the Company:

• Assign a technical team member (ideally an AI engineer or data scientist) to play the role of a subject matter expert (SME).
• Brief this person on a fictional AI feature they've "developed" and provide them with technical details they should know.
• Prepare the SME to initially provide incomplete or overly technical explanations that would need clarification.
• Schedule 30 minutes for the interview simulation.
• Provide the candidate with a basic feature description and the documentation deliverable they need to create.

Directions for the Candidate:

• Review the basic feature description provided.
• Prepare a list of questions to ask the subject matter expert to gather the information needed for comprehensive documentation.
• During the interview:
• Ask clarifying questions about technical aspects
• Request examples or use cases
• Confirm your understanding by restating complex concepts
• Identify areas where users might need additional explanation
• After the interview, create a brief outline of how you would document this feature based on the information gathered.
• Note any follow-up questions you would ask in a real scenario.

Feedback Mechanism:

• Have the SME provide feedback on the candidate's questioning technique and their ability to understand technical concepts.
• Provide feedback on one effective strategy they used (e.g., "Your follow-up questions effectively uncovered the user impact") and one area for improvement (e.g., "Consider asking more about edge cases").
• Ask the candidate to revise their documentation outline based on this feedback.
• Evaluate how well they incorporated the feedback and identified the most important information for users.

Frequently Asked Questions

How long should we allow for these work sample exercises?

Each exercise is designed to take 45-60 minutes, with additional time for feedback and revision. For remote candidates, consider sending the first two exercises as take-home assignments with a reasonable time limit. The interview simulation should be conducted live, either in-person or via video conference.

Should we provide all four exercises to every candidate?

We recommend selecting 2-3 exercises most relevant to your specific documentation needs. Activity #2 (Explaining an AI Concept) and Activity #3 (Documentation Review) provide the most comprehensive view of core skills and are recommended for all candidates.

How should we evaluate candidates who have strong technical AI knowledge but less documentation experience?

Focus on their ability to translate complex concepts into clear explanations and their receptiveness to feedback about documentation best practices. Technical knowledge can be valuable, but look for evidence they can adopt the user's perspective rather than remaining in the technical expert mindset.

Can these exercises be adapted for candidates with different levels of AI expertise?

Yes, adjust the technical complexity of the AI concepts based on the role requirements. For roles requiring deep AI expertise, use more advanced concepts like model architecture or training methodologies. For roles focused more on user-facing documentation, use concepts like basic model capabilities or feature interactions.

How do we ensure these exercises don't take too much of the candidate's time?

Be transparent about time expectations upfront. Consider compensating candidates for take-home exercises that require significant time investment. You can also scale the scope of each exercise—for example, requesting an outline rather than a complete document.

Should we share our evaluation criteria with candidates?

Providing basic evaluation criteria helps candidates understand what you value and allows them to showcase relevant skills. However, keep some aspects of your evaluation private to observe how candidates naturally approach documentation tasks.

AI documentation is a specialized field that requires both technical understanding and exceptional communication skills. By using these work sample exercises, you can identify candidates who not only understand AI concepts but can effectively translate that knowledge into clear, useful documentation that serves your users' needs.

Yardstick's suite of AI-powered hiring tools can help you further refine your hiring process for AI documentation specialists. Our Interview Intelligence tool can analyze candidate responses during technical interviews, while our Predictive Talent Analytics can help identify which traits lead to success in documentation roles at your company. To create comprehensive job descriptions for AI documentation roles, visit our AI Job Descriptions tool. For generating targeted interview questions, try our AI Interview Question Generator. And to build complete interview guides for AI documentation specialists, check out our AI Interview Guide Generator.

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