How this looks in practice

A few examples of the work, both client engagements and AI research, with the question asked, the methods used, and what came of it.

Writing

Writing
Put the Values Where the Machine Can See Them

Human-centered design brings the human into the innovation process. Software development is research-design-test; so is HCD, but there's a person in each room. We ask people what they want, not what businesses want them to have. We co-design. We let people actually try the thing.

Human-centered AI design does two things at once: it brings AI into each of those rooms, and it aims the whole process at AI. We research it, design it, test it — and we do that with AI itself.

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AI Projects

I build to test ideas and sharpen my technical intuition against what production AI actually takes: reliability, evaluation, and sound judgment about where AI belongs.

Relation-ship Profiler

Personal research, early prototype

What does your relationship with your AI actually look like, and can a well-designed prompt reveal it?

  • Prompt-system design

  • Relational assessment framework

  • Model-behavior design

  • Evaluation rubrics

  • Bring-your-own-model packaging

The entire product is the prompt and the thinking behind it, which means the whole design challenge lives in the model's behavior: what to ask, how to read the answer, and what a good reading even is. It's the closest thing I've made to prototyping relational intelligence built into the model itself. Early, and evolving.

Report Drafting Agent

Client build, in development

Can a non-technical practitioner get a reliable AI collaborator while keeping AI out of client relationships?

  • Intake process mapping

  • Configured using practitioner-authored samples

  • Output reliability & eval

  • Structured input/output design

  • HITL review

  • Practitioner-only deployment

The design question that mattered most was where the AI belongs. Built for a licensed educational psychologist, it works only for her, drafting from her own reports and intake process, and never touches the families she serves, so the clinical relationship stays fully human. The engineering underneath is reliability: defining what a trustworthy draft looks like, then building the checks that let her actually rely on it. In build using the ChatGPT API & synthetic cases; intended deployment in a HIPAA-compliant environment.

Job Search Agent DIY Kit

Personal tool, in development

Can a job-search agent force better reasoning instead of just faster applications?

  • Agent architecture design

  • HITL eval design

  • Self-revising instruction loops

  • Fit/winnability scoring frameworks

  • UX writing for agent outputs

Built the evaluation agent that conflated dimensions of job post scoring. The second version asks for a human desirability rating on each role instead of inferring it, guiding users through the process. The result creates acceptance gates and model-assessed winnability alongside more emotional metrics like excitement, so the reasoning stays legible to the person using it. The current work is turning a tool that only I could run into one a stranger can pick up and trust.

Impact Dash-board

Personal research tool, live prototype

What does your AI use actually cost in energy, water, carbon, labor, and physical resources?

  • Token-level usage profiling

  • Environmental & social impact modeling

  • Behavioral-nudge testing

  • Interaction design

  • Rapid prototyping

Two major pivots on this one: lost the individual-framing approach after testing showed it didn't shift behavior; redesigned around population-level impact. See the live version. But the real finding was that people loved getting their AI usage profiled! A second version, built for that mirror, is in progress.

Here are a few of my favorite examples of how this looks IRL. Each past project vignette includes the organization type, scale, primary research question, a few key methods, and the outcome.

Applied Research

A clinician sits at a desk looking at papers.

Non-profit East Africa-based mental healthcare provider scaling up to 100 million clients

How do we deliver our clinical services in a scalable, client-centered way?

  • Interviews

  • Focus groups

  • Co-design

  • Guiding principles

  • Documentation & Reporting

  • Training

The engagement equipped the organization to build its own qualitative research team, positioning them for upcoming pilot and RCT work.

Two women from different generations look at each other.

Early-stage mental healthcare start-up in Minneapolis, MN

Is there a market for preventative mental healthcare and how can potential clients afford it?

  • Market assessment

  • Impact & cost modeling

  • Pilot & scaling models

  • Resource allocation

  • Go-to-market planning

  • Pitching & business development

Prototyping data and reports from the engagement opened talks for nationwide piloting with a pharmacy chain.

A family is together in nature.

Multinational consumer brand with over 400k employees and their university partner

How do we support our employees in learning about sustainability and becoming active contributors?

  • Interviews

  • Surveys & descriptive statistics

  • Co-design

  • Guiding principles

  • Wireframing & mockups

  • Roadmaps

The online course for employees was redesigned, improving engagement and learning comprehension to increase completion rates by 66%.

A person writes on a white board.

Global conservation non-profit exploring new ways to reduce human-wildlife conflict

How can we distribute a product we have found to be effective in improving conservation outcomes?

  • Interviews

  • Prototyping

  • Co-design

  • Pilot & scaling models

  • Impact & cost modeling

  • Go-to-market plan

They went from a product idea to a financially viable market-ready brand with a distribution strategy.