Introduction :

Here at Panoply Media our culture of continuous communication and mentorship towards employee growth, recognizes the importance and developing a performance check/learning goals and manage them for employee growth. This document can aid in preparing a process checklist with your employee/mentor/management.

Documentation : Ava writes clearly and keeps organized notes. She’ll learn to document the Claude skills she builds and the research behind them, so the workflows are reusable and others can run and improve them.

Archivage des données : She’ll learn to build and structure a points-of-interest (POI) database — naming, tagging, and organizing entries (and their source documents) so the data is easy to find, trust, and reuse across the planning team.

Conception de la recherche : Ava is learning to design and iteratively refine repeatable research workflows — building Claude « skills » that automate parts of our media research, testing the outputs against her own manual research, and re-running until results meet a high-quality bar. She’ll develop a strong sense of how to structure a research process, define success criteria, and improve a workflow through testing.

Recherche appliquée : She’ll do practical, applied research on Canadian media outlets — gathering real information that directly feeds the POI database and our internal tools — combining structured and unstructured data into usable records.

Agrégation de données : A throughline of her work is combining structured and unstructured data. She’ll learn to consolidate sources — geographic boundaries, station and coverage information, census figures — into consistent, structured datasets the planning team can rely on.

Recherche d’informations : She’s comfortable researching online across multiple sources. She’ll deepen this by researching Canadian regions and radio stations — identifying authoritative sources, verifying details, and judging which sources are reliable for media-planning data.

AI Skill Development & Prompt Engineering : Ava’s core project is teaching Claude to collect both structured and unstructured data. She’ll develop and refine reusable AI « skills, » write and iterate on prompts, evaluate output quality against her own research, and learn when AI can be trusted versus when human verification is essential.

Commentaires supplémentaires de l’employeur :

This placement gives Ava hands-on experience building AI-assisted research workflows inside an early-stage tech environment. Success looks like growing independence, designing automated « skills » that produce reliable structured and unstructured data, validating outputs against her own research, and developing sound judgment about when AI accelerates the work versus when human review is essential. We’ll check in regularly to set short goals and review progress.

Commentaires supplémentaires des étudiants :

Ceci est pour confirmer que les commentaires ci-dessus ont été discutés et sont clairs pour toutes les parties concernées.