Why this work matters
Useful digital products require more than isolated code: they need clear user flows, structured information, validation, persistence, accessible interfaces, and a realistic delivery path.
05
Applications · Data · AI-assisted development
Full-Stack & AI Development
A growing portfolio connecting interfaces, application logic, structured data, testing, generative AI, and controlled agentic workflows.
What I contributed
Translate user and business requirements into interface concepts, application logic, data models, evaluation workflows, and testable implementation plans.
What it demonstrates
Brings product, content, education, marketing, and technical perspectives together so applications remain understandable to both users and stakeholders.
Selected examples
Case studies you can open
Each example adds a distinct workflow, domain, or evaluation method.
Traceable Ticket Routing
Classifies feedback and ticket queries, creates six-digit tickets in SQLite, retrieves status, and records the selected route and action.
Runnable prototype · deterministic tools · audit logOpen case studyPlanning with Safety Gates
Coordinates synthetic records and appointment proposals while preserving emergency escalation, explicit confirmation, and human review.
Safety screen · confirmation gate · human controlOpen case studyInsightForge Verified Analytics
Routes business questions to reproducible statistics, category analysis, time trends, and charts calculated from 2,500 supplied sales records.
Verified metrics · CSV analysis · visual outputsOpen case studyLocal Retrieval Workflow
Retrieves approved context, assembles a grounded prompt, produces an evidence-bound answer, and maintains bounded conversation memory.
Runnable offline retrieval workflowOpen case studyOrchestrator-Worker Pattern
Makes multi-step work visible through state, routing, bounded parallel workers, and a defined path for combining results.
Distinct state · routing · worker coordinationOpen case studyGovernance Toolkit
Supports AI inventory, risk assessment, control selection, fairness review, incident handling, and governance ownership.
Runnable decision-support prototypeOpen case studyCoding project categories
Three focused project lanes
Full-Stack Development
Interfaces, APIs, validation, data models, persistence, testing, and accessible user workflows.
AI Response Quality Lab · MindGarden portal and booking architectureGenerative AI
Prompt design, response comparison, quality evaluation, content workflows, and human review.
Educational and marketing evaluation · Prompt-engineering iterationsAgentic AI
Multi-step AI workflow concepts with tool use, decision gates, monitoring, and human approval.
Agentic-framework study · Responsible workflow and orchestration conceptsTechnical skills
AI, development & creative technology
Completed study, work in progress, and documented tools are labeled clearly for an accurate view of current technical range.
01
Advanced AI
Program-based study: MIT Sloan completed August 30, 2026; Purdue and Michigan expected September 30, 2026.
Generative AI models & architectureLLM applicationsAgentic frameworks & multi-step workflowsImage generationChatbot conceptsPrompt engineering & AI evaluation
02
Programming & Development
Current and developing proficiency through coursework and portfolio projects.
PythonJavaReact front-end developmentHTML & CSSC++SQL databasesData structures & algorithmsGenerative AI design & code optimization
03
Platforms & Creative Tools
Applied tools and documented prior technical experience.
GitHubVisual StudioWordPressCanvaArticulate 360Adobe Creative toolsMacromedia software
Selected deliverables
Work products
- 01AI Response Quality Lab workflow and application concept
- 02Prompt, response, rubric, score, and evaluation-history data model
- 03MindGarden portal, booking, and customer-data architecture
- 04Campaign intelligence ingestion and analytics design
- 05Responsive web interfaces and content systems
Evidence
What supports the work
- Python, Java, React, HTML/CSS, SQL, and REST concepts
- GitHub, Visual Studio, data structures, and algorithms
- Validation, persistence, comparison, filtering, and report-export requirements
- AI-assisted development with human review and testing
Evidence status
Work in development and representative technical concepts are labeled clearly; no unsupported claims of production scale or coding ownership.
Methods & capabilities
Skills used in this work
ReactPythonJavaSQLRESTHTML & CSSGitHub