The Problem
In many organizations, performance issues trigger an immediate reaction:
“We need training.”
In reality, this is often the wrong solution.
Through my work in Learning & Development, I repeatedly saw:
vague business problems with no clear success metrics
desired behaviour described too broadly to be actionable
root causes assumed instead of diagnosed
training used to solve problems caused by environment, incentives, or processes
The result: time-consuming solutions that fail to change behavior or business outcomes.
My Approach
I designed and built an AI-powered Action Mapping Assistant that guides users through a structured performance diagnosis process—based on Kathy Moore’s Action Mapping principles.
The goal was not to create another learning tool, but to: help people think clearly about performance before jumping to solutions
Explore
You may explore the solutions below.
What the Tool Does
The application guides users step-by-step to:
Clarify the performance problem
→ What is actually happening vs. what should happen?
Define a measurable business goal
→ What metric should change, by how much, and by when?
Identify observable on-the-job actions
→ What should people do differently in real situations?
Diagnose barriers across 4 dimensions
Environment (tools, time, culture, incentives)
Knowledge
Skill
Motivation
Generate targeted solutions using AI
→ Including both training and non-training interventions
Visualize the system in an Action Map
→ Goal → Actions → Barriers → Solutions
What Makes This Different
This is not a form or chatbot.
It is a guided thinking system that:
prevents users from jumping to training too early
forces focus on observable behavior
structures complex thinking into a clear, defensible model
distinguishes between training problems and system problems
supports both managers and L&D professionals, adapting to their mindset
Key Design Decisions
One-question-at-a-time flow
→ reduces cognitive overload and improves thinking quality
AI used as a thinking partner, not an answer machine
→ asks better questions, challenges vague inputs, refines outputs
Barrier diagnosis structured across Environment / Skill / Knowledge / Motivation
→ ensures root causes are not oversimplified
Solution generation aligned with barrier type
→ e.g. environment problems → system fixes, not training
Visual Action Map output
→ transforms messy analysis into a clear, shareable artifact
Innovation
This project reflects a shift in my work:
from designing courses → to designing performance systems
I used no-code / AI-assisted development (Lovable) to rapidly prototype:
interactive workflows
AI-driven decision support
dynamic visual outputs
This allowed me to:
test ideas quickly
iterate based on real usage
focus on problem-solving logic instead of just production
What This Project Demonstrates About Me
I design for real business impact, not just learning outputs
I apply performance consulting principles in practice
I build tools that change how people think and make decisions
I am comfortable experimenting with AI and no-code tools to solve real problems
I focus on behavior change and systems, not just knowledge transfer