Helping learners choose a career goal and find a useful next step with Coach, CareerVillage.org’s AI career coach.
Production screenshot: Pathways in the live Coach product.
At a glance
Company: CareerVillage.org
Product: Coach
Role: Primary Product Designer, Pathways
Timeline: Late 2025 to early 2026
Collaborators: Product management, engineering, UX research, and design
Overview
Coach helps learners explore careers and prepare for opportunities. I designed Pathways to connect that guidance to a goal and a small set of activities they could act on.
The most important thing we learned was that learners wanted AI to help them work toward a goal, not choose the goal for them.
That shaped three decisions: let learners choose their goal, gather context without making setup a chore, and show how the next activity connects to what they want to achieve.
The Problem
Coach had career guidance and activities, but the connection between them wasn’t always clear. Learners needed to know what they were working toward and where to start.
My Role
I was the primary product designer for Pathways. I explored the structure, designed the goal-setting and recommendation flows, worked through usability feedback, and prepared the designs for engineering.
I worked with product management, engineering, research, and design. Xavier Garcia primarily designed the streaks and gamification work that developed alongside Pathways.
Starting with a goal and three activities
My first explorations put a current goal, three recommended activities, and progress in one place. I wanted learners to see a connection between what they wanted to achieve and what they could do next.
Figma design exploration: An early Pathways concept showing how a career goal could be broken into a sequence of three recommended activities.
Designing for flexibility
I also explored editing a goal and generating new recommendations. Those controls gave learners flexibility, but testing showed that the difference between them wasn’t clear.
Looking beyond the interface
I raised a separate concern early on: could the activity library support the recommendations we wanted to make? An interview goal, for example, needed relevant practice and feedback, not just a convincing-looking roadmap.
01. Let learners choose their goal
Michelle’s usability research showed that learners could recognize the individual parts of Pathways without understanding how they fit together. Some weren’t sure who controlled the goal or whether editing it would change the activities.
The early concept pre-filled a Coach-suggested goal. Learners could change it, but many wanted to define their own starting point. The production flow instead asks them to choose a suggestion or write their own.
Before: Coach-suggested, pre-filled goal
Figma design exploration: Pre-filled, Coach-suggested goal.
After: Learners choose a suggestion or write their own
Production screenshot: Learner-directed goal selection.
Research led us away from a pre-filled goal and toward an explicit choice.
The learner chooses the destination. Coach helps with the next steps.
Suggested goals still give people a starting point if they’re unsure what to write. The difference is that a suggestion is something they choose, not something already chosen for them.
Some learners came in with a clear goal. Others wanted a job change but weren’t sure where to start. We explored ways Coach could help them define a goal, but the interviews surfaced a wide range of situations that were difficult to capture in one flow.
02. Ask for context without making setup a chore
The homepage needed a clearer place to start. Testing showed that extra activities could pull attention away from goal setting, so the team gave that entry point more emphasis.
The production homepage starts with an invitation to set a goal rather than presenting goal suggestions and regeneration controls all at once.
Before: Goal suggestions and regeneration on the homepage
Figma design exploration: Early first-time homepage.
After: A focused invitation to set a career goal
Production screenshot: Goal-setting entry point.
The early concept put more decisions on the homepage. Production gives goal setting its own entry point.
Collecting context without making the experience overwhelming
Recommendations depend on knowing what someone needs help with. The flow starts with a career need, such as exploring options or preparing for interviews, then asks relevant follow-up questions.
Learners can add a résumé, a Google Docs link, or their experience manually. They can also skip that step. The aim was to collect useful context without making a complete profile a condition of getting started.
Production screenshot: Learners identify their career needs before answering follow-up questions and optionally adding relevant experience.
03. Make the next activity make sense
Once a learner chooses a goal, Coach recommends three activities. I started small in parts of the project and built on that foundation as we learned more.
Testing showed that people didn’t always recognize the recommended activities as part of their pathway. Putting the current goal beside “Up next” made that relationship more explicit.
The homepage now keeps the objective visible while pointing to one activity to start. Additional recommendations are still available, but they don’t all carry the same weight.
Loading and confirmation messages explain what Coach is doing and let learners know when their recommendations are ready.
Production screenshot: The production homepage makes the relationship between a learner’s goal and their next recommended activity more explicit.
Keeping progress and streaks distinct
Progress and streaks sat alongside each other, but they meant different things. Pathway progress was about completing recommended activities. Streaks were about coming back and working on an activity.
Figma design exploration: A progress design exploration combines career advancement and engagement indicators. Streaks and gamification were primarily designed by Xavier Garcia.
Some participants thought they had to finish an entire career goal to maintain a streak. The team revised the explanations to make the distinction clearer.
That was a useful reminder for me. A progress indicator doesn’t help much if people aren’t sure what it measures.
Small changes that helped
The team changed the activity button from “Continue” to “Start.” Later testing showed that participants found it easier to identify where to begin.
We also refined the language around career goals. Broad ambitions like financial independence were hard to turn into immediate activities, so the wording needed to set clearer expectations.
A separate suggested-goal interaction duplicated other goal controls. The team removed it rather than adding another explanation.
What shipped and what we learned
Pathways moved from exploration and usability testing through engineering handoff into production. The shipped flow connects a learner’s career need to a chosen goal and three recommended activities.
The interviews showed that learners needed different kinds of support, from taking action on a clear goal to figuring out what that goal should be. Changes to button copy and visual hierarchy also helped participants identify where to begin.
These findings show improved usability in testing. They don’t establish an impact on production adoption, completion, or retention.
Reflection
Personalization is only useful if people understand it.
I started this project thinking about how to organize recommendations. The harder question turned out to be who was making the decisions and whether learners understood the connection between their goal and the activities.
The work also pushed me to look beyond the interface. A clear flow can’t make up for activities that don’t fit someone’s needs.
Next time, I’d test the match between learner goals and the available activities earlier, before spending as much time on the pathway structure.
Research source: CareerVillage.org, “Testing: Gamification and Pathways Designs, Findings,” September 2025. Images are labeled as Figma explorations or production screenshots.