The approach changes what happens inside each phase, but the phases stay the same.
01
ScopeDefine goals, audience, deliverables, and constraints with partners.
02
KickoffAlign the team on roles, schedule, and how we’ll work together.
03
ManageKeep development on track while the work takes shape.
04
DeliverLaunch, hand off, and capture what we learned.
05
EvaluateReview how the product is working and plan what comes next.
02 · Choosing an approach
Matching the approach to the project
I choose during scoping, based on how defined the work is and how often partners can review it.
AgileBest when
The product will change as we learn
Partners can give frequent feedback
Working versions matter more than a full spec
Example: AI Pilot
HybridBest when
The plan is set but details will evolve
Partners review work in batches
Some pieces need room to iterate
Example: Ethics, Equity, and Patient Safety in AI for Nursing Practice
TraditionalBest when
Requirements are clear from the start
Deadlines and approvals are fixed
Each phase builds on the one before
Example: Data Science with R
03 · Agile
Agile
Work is planned and delivered in short sprints, with a working version reviewed at the end of each one.
↻ Repeats each sprint
↻ Repeats each sprint
Step 1 of 5Product & backlog
Each product starts with a short definition: what it is, who it’s for, the problem it solves, and what success looks like for a first usable version (the MVP). The Product Owner then builds a backlog of cards sorted into Discovery, Build, Test, Refine, Deploy, and Icebox.
Output: a product definition and a prioritized backlog on our Monday.com board
Step 2 of 5Sprint planning
At the start of each one-week sprint, each person pulls two to four ready cards from their backlog and writes a one-sentence sprint goal. The goal stays fixed for the week. The cards underneath it can be swapped, split, or added to.
Output: a sprint goal, committed cards, and estimated hours
Step 3 of 5Build & check in
Midway through the sprint, everyone posts a short async update: progress toward their goal, any blocked cards, and what support they need. Blockers come up here instead of waiting for the review.
Output: an async update in Teams, with blocked cards flagged on the board
Step 4 of 5Review & demo
At the end of each sprint, each person shows what they built or learned and reflects on whether they met their goal. Work can be rough; the point is to make progress visible to the team.
Output: goal met, partial, or not met, plus cards carried into the next sprint
Step 5 of 5Retrospective
Right after the review, a 15-minute conversation about how we worked rather than what we built: what went well, what was hard, and what we’ll change next sprint.
Output: one or two adjustments for the next sprint, and blockers escalated to leadership
Hover or select a step to see what happens.
Example projectAI Pilot
✓Weekly goals stayed fixed while tasks changed.
✓Blockers came up every week.
✓Everyone saw each other’s work at show-and-tell.
TimelineJune to August 2026, in one-week sprints
My roleDesigned and facilitated the Agile process; Product Owner for two of the tools
Why AgileWe didn’t yet know what the tools could do.
Leadership asked our team to explore where AI could handle clearly defined steps in course development, giving designers more time for work that needs their judgment and expertise. We used that goal as a direction, not a checklist, and agreed on a few principles: a person stays responsible for every decision, bold experiments are welcome, and it’s okay to say, “This didn’t work.”
Coaching in addition to project management
Several teammates had never built software. Alongside running the pilot, I coached them as they built. I asked who each tool was for and pushed on questions like, “How will it avoid sounding like AI?” That question led one colleague to build a library of strong example scripts. I also explained API keys and hosting in plain language and shared my own prompts and Claude Skills so others could adapt them.
Adjusting as we went
The task cards we drafted with AI were too detailed and hard to act on. We simplified them and kept the weekly show-and-tell sessions at the center of the process. When most of the team was out for a week, we shared updates asynchronously rather than skipping the sprint.
Results
Three tools were working after the first one-week sprint. At the end of the pilot, I compiled a report for leadership showing each tool’s status and what it would need to be ready for regular use, including hosting and API costs. That gave leadership a basis for deciding what to invest in.
“I’m blown away, one, by all the work you guys are doing, but two, how much you have learned.”
A teammate at our first sprint review
04 · Hybrid
Hybrid
A fixed roadmap of phases and sign-offs, with scheduled cycles of review, feedback, and implementation inside it.
↻ Review, feedback, implement
↻ Review, feedback, implement
Step 1 of 5Kickoff & discovery
A project kickoff and onboarding for each faculty lead, followed by one-on-one walkthroughs with each member of the design team to discuss the course, its learning goals, and what it should include.
Milestone: onboarding and course walkthroughs complete, with faculty sign-off
Step 2 of 5Design & alignment
Faculty leads develop their course design with the design team through ongoing planning meetings. Full project team meetings bring every course together for alignment, and the gaps or open questions they surface shape the next co-design session.
Milestone: course design drafted, with faculty sign-off
Step 3 of 5Co-design
Practicing nurses respond to the questions and gaps identified during design. Faculty leads and the design team refine each course from that input before production begins.
Milestone: course and module maps finalized, and every learning asset identified
Step 4 of 5Production & build
Scripting, studio recording, video editing, and course build. Scripts and video edits each get a dedicated review round, and a second co-design session gathers feedback across all courses near completion.
Milestone: video edits approved and all courses built and ready for review
Step 5 of 5Review & launch
Continuing education review, stakeholder feedback, launch preparation, and submission to Coursera.
Milestone: courses launch-ready and the Specialization launched
Hover or select a step to see what happens.
Example project · In developmentEthics, Equity, and Patient Safety in AI for Nursing Practice
✓Sign-offs keep courses in step.
✓Co-design with practicing nurses.
✓Review rounds are built in.
TimelineSeptember 2026 to an August 2027 launch
My roleProject Manager and Senior Learning Experience Designer across all four courses
Why HybridA fixed launch date and four parallel courses, shaped by feedback from practicing nurses.
The four courses
Ethical Foundations of AI in Nursing PracticeBias, Fairness, and Health Equity in AI-Enabled CareUnderstanding AI Tools, Data, and Technical LimitsPatient Safety, Simulation, and Responsible Generative AI Use
05 · Traditional
Traditional (Waterfall)
Work moves through defined phases in order, with each phase reviewed and approved before the next begins.
Step 1 of 5Initiate
Meetings with faculty and leadership define the project’s scope, objectives, and success criteria, and identify everyone who has a stake in the outcome.
Milestone: project charter and stakeholder register approved
Step 2 of 5Plan
An integrated project plan sets the scope, schedule, and cost baselines, supported by a work breakdown structure, a communication plan, and a risk register.
Milestone: baselines approved, with milestones for drafts, media production, and launch
Step 3 of 5Develop
The team designs course materials, produces video, and builds assignments in sequence. Progress is tracked against the baselines, and any change goes through a formal change request.
Milestone: course materials, videos, and assignments complete
Step 4 of 5Review & QA
Courses are checked against accessibility and quality standards, then reviewed by stakeholders before launch.
Milestone: stakeholder acceptance of the courses
Step 5 of 5Launch & close
Courses launch, lessons learned are documented, project files are archived, and ownership moves to the team that maintains the courses.
Milestone: launch and handoff for ongoing maintenance
Hover or select a step to see what happens.
Example project · LaunchedData Science with R
✓Baselines set the path.
✓A pause, then a new baseline.
✓On budget with a clean handoff.
TimelineFebruary to December 2024
My roleProject Manager for a design team of three, working with two faculty instructors and four additional stakeholders
Why TraditionalThe scope was clear from the start: four courses with defined lessons and assessments. When our faculty lead paused the project, we set a new baseline for the restart.
The four courses
Data Visualization and Transformation with RData Tidying and Importing with RData Science Ethics with RData Modeling and Prediction with R