Selecting the right work samples for a portfolio requires understanding what specific evidence the target role needs to see — not defaulting to your personal favorites or most impressive projects. AI can help map your existing work samples to the competency requirements of a target role and identify the best selection. This concept covers portfolio selection as an alignment exercise rather than a showcase.
Portfolio and work sample selection is the strategic process of choosing which examples of your past work to present to a specific employer based on alignment with their industry, role requirements, and likely evaluation criteria. Submitting the wrong samples — even excellent ones — can signal poor judgment or misalignment.
Creative, technical, and knowledge workers increasingly need to submit portfolios or work samples as part of applications, yet most people default to their personal favorites rather than their most strategically relevant pieces. AI can help you audit your existing work samples, map them to a specific job description's priorities, and identify gaps where you might need to create new demonstration pieces before applying.
List five to ten work samples you have available — with one-line descriptions of each — and paste them alongside a target job description into ChatGPT. Prompt: 'Given these work samples and this job description, rank my samples by relevance to this role, explain your reasoning, and identify any type of sample I am missing that would strengthen my application.'
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