Portrait of Corey Alejandro, looking directly at the camera against a dark background
Corey Alejandro. The person behind the point.

Understanding
is a form of
Power.

AI Engineer · Instructional Systems Designer · Researcher · Maker

I design learning experiences, governed AI workflows, research tools, adaptive fashion and public performances. Come see how I think. Then see what I'm building.


A bearing chart. The highlighted point travels between published stories, newest first, and rests on each one for a full sweep of the beam.

One point. My own course. The point is me, moving through my work, newest first.

The highlighted dot

That point is me.

All my life, I've been a highlighted dot navigating life, trying to see the forest for the trees.

On the radar nowReflexiveResearch practice

Who gets understood?
Whose knowledge counts?
Who keeps the authority?

The through-line

Instructional systems design is an established strength in my practice. I bring that practice into AI Engineering, safety and governance research, dramaturgy, adaptive fashion and public making. These practices meet in questions about understanding, participation, evidence and human agency.


Don't just read.
Try a decision.

Learner's Ledger

Show how feedback changes a product through an interactive example. Compare Agile and Waterfall, and watch a simple booking flow change with learner input.

A process becomes something you can see.

Choose a delivery model
  1. Version 1
  2. Revise
  3. Try again
  4. Review
Book a visitYour next visit.
Thursday10:30 AM
Confirm booking

Step 1 of 4. A first usable booking version makes the initial idea inspectable.

Fig. 1 — A booking flow under two delivery models. Illustrative scenario.


Inside the Practice

One person. Several projects. A shared way of working.

An illustrative research table at a window: printed evidence in archival sleeves, handwritten index cards revised in pencil, and a researcher’s brown-skinned hands holding one card apart
Source preserved. Evidence stays sealed on the left; interpretation stays open on the right. AI-generated illustrative photograph.
Research practiceOn the radar

Reflexive

Keep the source. Contest the interpretation. Let the researcher decide what leaves.

Read the story →

A process across the projects

Find the problem.
Make it understandable.
Build. Check. Revise.

My working loop is identify a problem → investigate → write → build → test → revise. A paper, a learning experience, a governed AI workflow and a garment take different forms. Each asks what people need to understand, what the evidence supports and who keeps the authority.

CRGSLab is one project in that practice. Its research and governance methods may become part of how every project works, even if the lab name eventually disappears.