03 — Writing Samples

Featured Artifacts

Both artifacts were produced in ENGW 3304: Advanced Writing in Business Administration at Northeastern University. They represent two distinct genres — public opinion writing and formal research reporting — and together demonstrate my range as a writer who can adapt voice, structure, and evidence to serve very different audiences and purposes.

Artifact 01

The Atlantic · Guest Essay
March 31, 2026

Op-Ed WritingPublic ArgumentationAudience AdaptationSource IntegrationVoice & Tone

~8 min read

The Great AI Heist

How Machines Are Learning From Your Life's Work

Tech companies are building the future on the backs of human creativity — without asking for permission or offering a dime.

Written for ENGW 3304 (Advanced Writing in Business Administration) at Northeastern University, this Op-Ed was formatted for publication in The Atlantic and directed at a general educated readership. The assignment required students to take a clear, defensible position on a contested public issue, adapt their voice and style to a specific publication's audience, and support their argument with credible sources while maintaining the accessible, urgent tone that defines quality opinion journalism.

Central Argument: To argue that AI companies are training their systems on copyrighted creative work without consent or compensation — and to call for three concrete policy changes that would protect creators.

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Artifact 02

ENGW 3304 Research Report
February 28, 2026

Research SynthesisAcademic WritingAPA CitationBusiness Report FormatCritical Analysis

~2,500 words

AI Agents and Managerial Decision Making

in Business Organizations

AI does not replace managerial responsibility — it redefines it.

This formal research report was produced for ENGW 3304 (Advanced Writing in Business Administration) under Dr. Tabitha Clark at Northeastern University. The assignment required students to synthesize peer-reviewed scholarship and industry data into a structured report with a clear executive argument, supported findings, and actionable recommendations. The target reader is a professional or academic audience with a stake in organizational management and technology governance.

Central Argument: To evaluate how AI agents influence managerial decision-making, accountability, and control in business organizations, and to provide evidence-based recommendations for effective governance.

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