I lead AI enablement,
and I build with AI myself.

Most recently Director, Learning Product and AI Strategy at United Way Worldwide. I built the AI agents that draft its courses, designed how its staff learn to work with AI, and relaunched the learning platform its partner organizations use.

Agent draft

Module 3. Working with data

Approved AI tools are fine for any staff data, including personal records.

Expert note: Personal data stops for formal approval.

Before you start, ask two questions: what am I giving the tool, and what happens if the answer is wrong?

An illustration of how my course agents work: AI writes the draft, and a person edits in blue before anything ships. Across 11 courses, a course took 4 weeks instead of 12.

Try it

Sort eight tasksDecide, task by task, when AI belongs in the work, using the guide I wrote for AI Foundations.About 2 minutes Would you deploy this agent?Set its permissions, then see whether a hidden instruction gets through.About 3 minutes Review an AI draftBe the subject expert: find what the agent got wrong, then approve it or send it back.About 2 minutes

AI in course production

TRICIA 2.0. United Way Worldwide, 2026

The problemBuilding one course took 12 weeks and 90 hours of subject experts’ time.

What I builtTopic-specific AI agents that draft outlines, modules and job aids from United Way’s frameworks, learner personas and design standards. A subject expert reviews every draft and can send it back, and Learning checks each course against a rubric before it ships.

How it works

People decide in blue. Across 11 courses in 2026, a course took 4 weeks instead of 12, and 20 hours of expert time instead of 90.

BriefFrameworks, personas, standards
Agents draftOutline, modules, job aids
Expert reviewCan reject or send back
Learning QARubric and acceptance criteria
Published11 courses in 2026

People decide at the blue steps. A course took 4 weeks instead of 12, and 20 hours of expert time instead of 90.

Partner education at scale

UW Learn. United Way Worldwide, 2024 to 2026

The problemThe United Way network is 1,100+ independently run organizations in 36 countries, and none of them report to headquarters. Training has to be good enough that they choose to use it.

What I builtA catalog of 30 courses in English and Spanish, on a learning platform I relaunched. I built most of the courses and led a team of three learning experts who built the rest, each with subject experts.

One mark per course, grouped by program. As of October 2026, 800+ of the 1,100+ organizations use the platform, with more than 6,000 active users.

AI curriculum

AI for Impact and AI Foundations. United Way Worldwide

The problemStaff had AI tools before there was an AI policy, in a network where each local organization sets its own rules.

What I designedA ten-course curriculum on working with AI. It starts with AI Foundations, which gives everyone the same two questions for any task: what am I giving the tool, and what happens if the answer is wrong?

Sort eight tasks with the use guide Would you deploy this agent?See all ten courses

The use guide at the center of AI Foundations. Over-caution counts as failure too: the target is that no more than 10% of safe tasks get wrongly blocked.

Green

Summarize a published public report

Use it, and check the result.

Yellow

Draft an update from an internal plan

Approved tool, and a named person owns the draft.

Red

Rank partners for investment from their public websites

Stop for formal approval. It feeds a decision about organizations.

The use guide at the center of AI Foundations. Over-caution counts as failure too: the target is that no more than 10% of safe tasks get wrongly blocked.

Leadership programs

NuVuX, 2019 to 2024, and United Way Worldwide

The problemLeadership workshops tend to end with good ideas and no follow-through.

What I madePrograms where leaders build something for their own organization: design-thinking programs taken by leaders at Rolls‑Royce, Balfour Beatty, Plexus and Peak Scientific, and onboarding for new CEOs that ends with each CEO’s own 60-day plan.

See the programs

Designing Organizational Futures. Many ideas, most crossed out under critique. The leader chooses one, in blue, and builds it into a working prototype for their own organization.

Many ideasLeaders brainstorm around a real problem
Critique from other points of viewMost ideas do not survive
One prototypeChosen by the leader, built for their own organization

Designing Organizational Futures, a program for executives.

Alf Studio

An AI product I founded and built, 2026

The problemTeachers need project-based units that fit their own class, not every class.

What I builtPlanning software that drafts a full unit from a short form, keeps every edit, and learns a teacher’s habits only if she switches that on. I design it and build it by directing AI coding agents from written specs, with tests and code review.

The product story Open Alf

Alf StudioUnitsHelpDW

Done · 23 secondsGrade 6 · Science · 3 weeks

MS-PS3-3WHST.6-8.7

By mid-afternoon our blacktop is the hottest place on the block, hotter than the park across the street. Why, and what could we plant or build to cool the schoolyard before next summer?

Science · Grade 6 · 3 weeks · Drafted Oct 21

Cooling Our Schoolyard

How can we redesign our schoolyard to cool down our hottest outdoor spaces before next summer?

Edit unit

Saved. 1 change kept.

Week 1Ready

Map surface temperatures across the schoolyard and track how different materials absorb thermal energy.

Conduct the schoolyard surface temperature walk, log readings on varied surfaces, and build the initial class need-to-know board.
· 1 lesson
Run a controlled bench lab measuring how dark asphalt fragments, light concrete, sand, and shaded soil heat under heat lamps over time.
· 2 lessons
Analyze lab data in teams, graph temperature curves, and draw energy transfer diagrams showing solar radiation and surface conduction.
· 2 lessons

Deliverable

A completed thermal data sheet with a labeled energy transfer diagram of the schoolyard blacktop.

Supports

Provide bilingual graphic organizers for lab data tables; offer sentence frames for thermal energy explanations to students with writing accommodations; challenge fast finishers to calculate rate of temperature rise per minute for each material. Give every pair a sentence-starter card: “The hottest spot was ___ because ___.”

Added a scaffold · just now

Week 2Ready

Research cooling strategies and build a scaled prototype shade or greening design to test heat reduction.

Gather facts from local desert plant guides and shade cloth spec sheets to answer self-generated questions about cooling structures.
· 2 lessons
Sketch scaled design options for a chosen hot zone in the schoolyard using selected shade materials and native trees.
· 1 lesson
Build a tabletop scale model of the cooling design and test its interior temperature under a heat lamp against an unshaded control surface.
· 2 lessons

Deliverable

A scaled prototype model with heat-lamp test data showing thermal energy reduction.

Supports

Use visual vocabulary cards for plant types and shade structures; provide partially pre-scaled grid paper for drafting; invite extending students to test two competing shade materials simultaneously and compare cost estimates.

Week 3Ready

Refine the cooling proposal based on peer critique and present the final plan to school leaders.

Run a gallery walk critique where teams review draft cooling models and leave sticky notes on durability, shade coverage, and cost.
· 1 lesson
Revise the physical model or site layout using peer feedback and write a one-page summary explaining how the design stops heat transfer.
· 2 lessons
Present cooling proposals to the school facilities leader and principal, then write an individual reflection on the design process.
· 2 lessons

Deliverable

The finalized cooling proposal poster, scale model, and written design rationale.

Supports

Offer sentence starters for peer critique; allow oral explanation paired with bulleted visual summaries for students with modified output needs; encourage advanced groups to calculate square footage of total shade created at noon.

Critique and revisionReady

Final productReady

Rubric · 3 rows · 4 levelsReady

MaterialsReady

A recreation of Alf drafting a real three-week Grade 6 science unit, done in 23 seconds by its own timer, then learning from one teacher edit. Real text, real order, shown faster. See the real run

More work

AI red and blue teaming

Contract testing of frontier AI models in health, looking for subtle harm that builds over several turns of a conversation.

Pratica

A private AI Italian tutor I built, where 29 AI tasks feed one spaced-repetition system.

The assistant on this page

It answers only from a published record of my work and cites the section. A final check blocks any number that is not in the record, it is tested against 31 questions, including attempts to make it overclaim, and it stores nothing you type. The same record is open to AI tools as llms.txt.

Experience

2024 to 2026

United Way Worldwide

Director, Learning Product and AI Strategy

Learning and AI for a network of 1,100+ independently run organizations in 36 countries.

2019 to 2024

NuVuX

Global education programs, from the UK into Europe, MENA and Australia, and design-thinking programs for executives and ministries.

2018 to 2020

MIT Global Startup Workshop

Design Coordinator

Led the brand and platform redesign, including the participant site, event app and CRM data flows, which drove 1,500+ registrations from entrepreneurs and investors.

2018

Garage Museum of Contemporary Art, Moscow

Learning and Engagement Designer, MIT research grant

User research on how visitors learn, which shaped content strategy and the experience for multilingual audiences.

Alongside

AI red and blue teaming

Frontier models in health, contract

Education

MIT and SCI-Arc

MS in Design and Technology, MIT, where I worked for the Leventhal Center for Advanced Urbanism and the Self-Assembly Lab. Bachelor of Architecture, SCI-Arc. ATD Master Instructional Designer.

Contact

kjbranchesi@gmail.com

I lead AI enablement, and I build with AI myself.

AI red and blue teaming

Pratica

The assistant on this page

United Way Worldwide

NuVuX

MIT Global Startup Workshop

Garage Museum of Contemporary Art, Moscow

AI red and blue teaming

MIT and SCI-Arc

I lead AI enablement,
and I build with AI myself.