~/work

Built, shipping,
and brewing.

Every project here answers the same question: what makes people better together than alone?

01 / projects

Study Together FOUNDER · IN PROGRESS ▸ validating on campus

The problem: studying is solitary by default, and motivation is treated as a personal failing instead of a design flaw. People don't lack tools — they lack someone expecting them to show up.

The product: book a study session the way you'd book a court — a real time, a real place, matched with people who share your course or your goal. The booked commitment is the engine: a person is waiting for you.

  • Social accountability is research-backed — booked co-working measurably lifts follow-through.
  • Existing tools match or book. The gap is doing both, in person.
  • Starting where density is unbeatable: thousands of students within a ten-minute walk.
  • Validating by hand before writing serious code — if humans won't show up, software won't fix it.
Hestia CO-FOUNDER ▸ shipped & tested

The insight: community volunteering had been reduced to hours and signatures — something to finish rather than value. The first version solved logistics: matching volunteers to opportunities. It worked. It also missed the point.

The pivot: mentors pushed us to see that access wasn't the real problem — volunteers didn't feel connected to the people they served. So we redesigned Hestia around listening: volunteering begins with the community's own voices — their needs, in their words — before anyone signs up.

  • Taught me the most valuable product lesson I own: listen before you build.
  • Tested the redesign in the field with real volunteers and real institutions.
MEET ALUM → CS TEACHING ASSISTANT ▸ three years + taught

Three years in MEET — an MIT-affiliated program combining a serious computer science curriculum with entrepreneurship, taught in English by MIT-affiliated instructors.

Then I went back on the other side of the room: as a CS teaching assistant — running labs, explaining concepts, and debugging the next cohort's first real code. Teaching something is the fastest way to find out whether you actually understand it.

Yazan assisting students during a MEET computer science lab
drop teaching.jpg into /assets
to render this frame
meet — cs lab, other side of the room[TEACHING]

02 / operating theses

What I think about.

T-01

AI will reshape how people learn before it reshapes anything else — and the builders who understand learning will build the layer everyone else uses.

T-02

Accountability is a product surface. People don't lack information or tools; they lack someone expecting them to show up. Software can be that someone's scheduler.

T-03

Technology should start with listening. The best products I've worked on began by understanding people — not by shipping features at them.

03 / in the lab

Always running.

▸ ONGOINGai-ml-mastery

AI & ML Mastery

A self-designed program to go deep on machine learning alongside coursework — because staying ahead of this field is not optional for what I want to build.

▸ QUEUEnext-experiments

The idea queue

A running pipeline of captured ideas, each one stress-tested before it earns code. The bar for building is high; the bar for writing an idea down is zero.

▸ OPENcollaboration

Your project here?

If you're building something in learning, accountability, or community — and want a collaborator who ships — the network is open.