I turn open questions into functional solutions through user research,
product definition, and full‑stack AI engineering.
Working on a national data platform for the U.S. Department of Education. I am responsible for the technical core: a REST API, an MCP server deployed as a live pilot so that any AI assistant can reliably get the numbers with their uncertainty and citations attached, and a data-crosswalking capability to overlay assessment data with external data sources.
I built a LangGraph-based multi-agent system for consulting sales experts, solo in 6 weeks. I owned it end to end, from product definition through evaluation and development, and drew the line between what the agents automate and what stays deterministic and human.
An AI diagnostic tool for thyroid pathology that had never been tested outside the team that built it. I reframed the work from feature validation to trust validation. Does this earn a place in the experts' existing workflow?
A 300-person consultancy whose expertise lived in people, not systems. I designed and ran the workshop that decided what got built, and surfaced organizational change opportunities.
JavaScript
Python
React
D3.js
SQL
LangGraph
Gemini API
Claude Code
Cursor
GitHub
Vercel
ngrok
Supabase
Hugging Face
Ollama
Next.js
The fastest way to understand a new technology is to make it do something useful. Independent tools and experiments I built on my own, to answer questions no off-the-shelf product would.
A live experiment testing whether different interfaces over identical data actually improve decision quality.
A 30+ column dataset (telemetry, surveys, coded responses) consolidated into one view: distributions, correlations, t-tests, and more.
| Comparison | Δ accuracy | t | p |
|---|---|---|---|
| Sandbox vs table | +0.42 | 2.31 | .025* |
| AI chat vs table | +0.31 | 1.94 | .058 |
| Scrollytelling vs table | +0.48 | 2.67 | .010* |
Hear how a stakeholder group would answer, grounded in real interviews, fully local.
A Chrome extension that turns ten minutes of copy-pasting into a one-click fit score.
I grew up in Italy, and later moved to the United State. Since then, I have earned a Bachelor of Science in Computer Science and Philosophy, and I am graduating with a Master of Science in Human-Computer Interaction from the Institute of Design at Illinois Tech in December 2026. Every problem I care about sits somewhere between people and the technologies that serve them.
Before I was anything else, I spent seventeen years as a classical pianist, which taught me the importance of the "unglamorous" daily work — and how to perform under pressure. When I'm not sitting in front of a piano, I like to read fiction, lose my voice at R&B concerts, chase a ball around a squash court, and build small utilities. That last habit turns out to be quite useful.
I spent the last few years TA'ing computer science, documenting workflows, running research studies, building MVPs, and working across product strategy, design research, and engineering.
Say helloThe philosophy half of my education never wore off: I still think an argument you can't articulate is at best a vibe. These essays take a position and take their chances.
Intelligence never lived only in our skull. It evolved with our tools, and it has just crossed a threshold no individual could have ever crossed alone. On what machines contribute, what judgment (should) refuse to cede, and why work will soon be measured by it.
By Angela Petrone · 14 min readSynthetic users promise research insights minus people. But what happens to knowledge when the data we use becomes a copy of a copy of a copy...?
By Angela Petrone · 9 min readWhy surfacing every detail backfires, and how we earned trust with the right feedback at the right moment in their workflow.
By Angela Petrone · 7 min readWhen one person can ship custom infrastructure in a weekend, the old reasons to buy off-the-shelf stop holding.
By Angela Petrone · 5 min readEngagement and comprehension metrics miss what matters most: whether someone can act on what they saw. Evaluating data products on the quality of the decisions they enable.
By Angela Petrone · 6 min readdef translate(team):
# clinicians, engineers,
# executives, agencies
shared = find_common_terms()
aligned = agree(team, shared)
return ship(aligned)Facilitating the conversations that find shared language, so everyone is heard and the team works towards the same thing.
def build(question):
tool = find_tool(question)
if tool is None:
# nothing fits? make it
tool = build_my_own()
return tool.answer(question)When no tool fits the question, I make one, so I can test it and talk to engineers with context.
def scope(problem):
ideas = run_workshop()
vital = prioritize(ideas)
cut(everything_else)
# smaller, but shippable
return tractable(vital)Run the workshop, hear stakeholders' voices, so time and resources go where they matter.
I’m open to full-time roles starting January 2027,
and I’m always free for a coffee.
I'm Angela Petrone's AI assistant. Ask me anything about her work, her thinking, or how she builds. Everything here runs in your browser; nothing you type leaves the page.
Angela is a product builder working on AI systems and data products: she takes open questions into functional solutions through user research, product definition, and AI engineering.
Right now she's at Education First Consulting, building a public data service for the U.S. Department of Education. Before that she shipped a multi-agent sales system solo in 6 weeks at GlobalLogic, validated clinical AI at UChicago Medicine, and shipped AI knowledge management at Method.
Between projects she builds her own tools: live experiments, local RAG pipelines, Chrome extensions.
Reach her at apetronedesign@gmail.com, LinkedIn ↗.