Practical learning, designed to be used.
Learning Experience Designer & Learning and Development Specialist
I design practical, interactive learning systems that turn complex workflows into clear, engaging training experiences.
I combine live facilitation, instructional design, process improvement, AI-assisted development, and front-end classroom tools to build learning resources that are easier to use, easier to scale, and easier to remember. The work below is a set of original sample projects and classroom-ready templates — built to show how I think and what I can produce.
Start from the problem
I don't build training to check a box. I find where learners actually get stuck, then design the smallest resource that fixes it.
Make it usable
Job aids, classroom tools, and trackers a facilitator can open and run immediately — clean, low-friction, easy to trust.
Measure and tighten
I track readiness, scores, and follow-up so training keeps getting sharper instead of staying static.
About me
I came into Learning & Development the long way around. I started out teaching martial arts — up to a dozen classes a day, every age and every skill level — and that's where I learned the thing that still runs my work: people don't learn from what you tell them, they learn from what they practice. From there it was retail, mobile sales, and call centers, and in every one of those rooms I ended up being the person who trained everyone else.
What I actually bring to a team is an analytical mindset. The first thing I do with any document or process is look for how to make it better — but I won't propose a single change until I understand it completely. That order is the whole point: learn it inside and out, then improve it. It's why the things I build tend to hold up.
Across my career I've developed more than 4,000 people. At NYU Langone Health I've put that mindset to work across the entire program — I've revamped roughly 60% of it so far. And it's not just training material: I build walkthroughs, tip sheets, job aids, and process guides, plus countless trackers that tie multiple systems into one smooth workflow — Microsoft 365 apps, Power Automate, and Excel working together instead of sitting in silos.
I also just love to build. I've made my own AI assistant, Zareli, and it grows a little more every day — because I love learning, and building it is how I learn fastest. I bring that same curiosity to the AI I use at work: as a tool, with a human keeping it honest.
Underneath all of it, my approach is simple: solve the real problem. I don't build training to check a box. I find where people actually get stuck, design the smallest thing that fixes it, and keep everything clean enough that the next person can pick it up and trust it.
Sample projects & learning-design case studies
Original portfolio prototypes and classroom-ready templates — honest sample work, not employer or production deployments. Tap any project for the full case study, the file to open or download, and how to make it your own.
Handing these to another trainer? The maintenance walkthrough explains how to keep them updated.
Using AI to build better training, faster
How I use AI in a learning-design workflow — with judgment and accuracy kept in human hands.
Zareli
An AI assistant and agent platform I'm designing and building from scratch.
Zareli (earlier working-named WAYLON) is a personal project where I'm building a full-stack AI assistant the same way I build training: solve the real problem, keep it clean, and keep a human in control. It pairs a Python/FastAPI backend with a React interface, and it's built around an approval-first model — the assistant proposes actions and a person confirms them, rather than acting on its own. It's the same "human in the loop" principle I apply to AI in learning design, turned into software.
- Full-stack build — Python / FastAPI, React, local data store
- Approval-first automation — actions are proposed, a human confirms
- Two surfaces — an admin console and a user workspace
- Designed for safety and traceability from the ground up
Where it fits in the workflow
Content development
First drafts of explanations, job aids, and outlines I then edit and verify.
Prompt libraries
Saved prompts so any trainer gets consistent output without prompt skills.
Scenario generation
Variations of realistic situations so learners practice more than one example.
Knowledge checks
Draft questions and distractors from a workflow, reviewed for accuracy.
Plain-language explanations
Readable rewrites of dense policy or system steps.
Coaching feedback drafts
Specific, constructive starters a coach can tailor.
Workflow simplification
Long procedures compressed to the fewest steps that still work.
Human review
Nothing ships without a person checking it against the source of truth.
Sample trainer prompts
Starting points, not magic. Copy one, add your topic, then review the output.
Create a plain-language explanation
Generate roleplay scenarios
Turn a workflow into a knowledge check
Draft coaching feedback
Build a facilitator guide
Simplify a policy into training language
Working with AI
A practical page on getting real value from AI — how I pick a tool, prompts worth stealing, and the one habit that keeps AI useful instead of risky.
Picking the right AI for the job
No assistant wins at everything — anyone who says otherwise is selling something. Here's where Claude tends to lead for the work I do. The last row is where other tools have the edge, on purpose: leaving it out would undercut the whole point.
Confidence isn't accuracy.
Every AI — Claude included — can sound completely sure and still be wrong. For anything a learner or a patient-facing team will rely on, I treat AI output as a first draft and check it against the source of truth. Knowing that is the difference between using AI well and getting burned by it.
Switching to Claude without starting over
Coming from another assistant? You don't have to lose your context. Claude has a built-in import under Settings → Capabilities → Memory → Start Import: it hands you a ready-made prompt to run in ChatGPT, Gemini, or Copilot, that tool summarizes what it knows about you, and Claude pulls that profile in — so new chats start with your background already loaded. For a deeper transfer, export your full history from the other tool and have Claude work through the file.
Prompts worth stealing
Copy, paste into your AI of choice, and replace the [brackets]. The starred one is the one I use most.
Interview me to find my real need
Pressure-test it before I use it
Make it teachable
Turn rough notes into a clean draft
Show me my blind spots
Be my thinking partner, not a yes-man
Explain it three ways
Give me the 80/20
Steelman the other side
Rewrite it at three lengths
Grade it against a rubric
Reverse-outline what I wrote
Role-play a hard conversation
Turn this into a reusable template
Meet Zareli — Tyler Locke's AI assistant
An AI assistant I'm building from the ground up — an approval-first co-pilot that thinks with me, not for me.
What Zareli is
Zareli isn't a skin over someone else's chatbot — it's my own platform, built from scratch around one rule: it proposes, I approve. A place to think, draft, organize, and automate the busywork, with a human always in the loop. I'm building it because the best way I've ever found to truly understand a tool is to build it myself — and then keep making it better.
How it's helped me so far
A place to untangle messy problems
I talk a problem through and come out with structure instead of a tab graveyard.
Faster first drafts
Quick passes on content, outlines, and messages that I then sharpen — the blank page disappears.
One place, less switching
Fewer tools fighting for attention, more momentum on the work that matters.
It made me a better builder
Building Zareli is how I've learned FastAPI, React, and how AI systems actually fit together.
The plan
Here's where it is, and where it's going — honestly.
A working assistant
Approval-first controls and a two-surface design: an admin console for me, a clean workspace for getting things done.
Real, approved actions
Connecting the tools I use every day so Zareli can do things — once I sign off — not just talk about them.
A coordinated team of agents
Specialized agents that each do one thing well, working together toward a goal — with me conducting.
The “orchestra”
This is the part I'm most excited about — and I'll keep it in quotes, because it's where Zareli is headed, not where it is today. The goal is an “orchestra”: a set of specialized agents that each play one part well — research, drafting, checking, organizing, automating — coordinated so they work together instead of one model trying to do everything alone. I'm the conductor. Zareli keeps everyone in time, and keeps a human approving the big moves. I don't have the full orchestra yet. But I will.
Zareli is a personal project, in active development — a working example of how I think about building with AI: ambitious vision, human in control, and accuracy that's earned, not assumed.
Files, profiles, and notes
Resume, live portfolio links, and a few notes on how I work.
Resume (PDF)
Two-page resume — selectable text, ATS-readable. Opens in a new tab.
Learning-design notes
Solve the real problem, keep tools simple and trustworthy, design for recall, and measure readiness — not just attendance.
AI process notes
AI accelerates drafting and organizing. A human verifies accuracy against the source of truth before anything reaches a learner.
See the tools
Screenshots of the interactive training tools in this portfolio. Click any to open the live tool.
Supporting documents
Let's talk
- Name
- Tyler Locke
- lockeprocess@gmail.com
- Location
- Boynton Beach, FL
Available for Learning Experience Design, AI-integrated training, digital learning development, classroom tool design, facilitation support, and process-improvement opportunities.