A small, cross-role cohort from across TK-12. Teachers and administrators spend a year working with AI on real district work, so the people shaping what our students learn are deciding from experience.
The clearest result of this work is never the tools. It is what each person can do next. Val Verde is deciding what its graduates need to be able to do, in a job market these tools are actively reshaping. The Studio puts the people making those decisions inside the technology first: a year of real use, on your own work, alongside the colleagues who will carry it into classrooms.
No generic training. Every session works on a tool you actually need, using district workflows. By the end of each session, something useful is ready to put to work. The proof is useful work, not seat time.
Our graduates enter a workforce being reorganized around these tools. The people setting curriculum, pathways, and expectations should know the technology firsthand rather than from headlines. That judgment is what a year of real use buys.
The capability grows through repeated practice. You leave able to make the next useful thing, explain the method, and help the work travel beyond one person or team, from a district office into a classroom.
Each working session moves a real piece of district work forward. Research the problem, build and test the response, then make the result understandable enough to share and improve.
Map the recurring work, the people involved, the source material, and the friction worth solving. Start with the work as it actually happens.
A precise problem is the first build decision.
Turn the problem into a working dashboard, presentation, application, or workflow. Test it with the people and conditions it needs to serve.
The work becomes useful through evidence and revision.
Make the result visible, explain what changed, and identify what another site or team would need to adapt it responsibly.
The useful pattern matters as much as the finished artifact.
You do not need a project in mind to apply. Most work starts as something small and repetitive that never quite gets fixed. Three illustrative starting points are below. The one you bring is the one you would build.
“We meet every week on a document someone copies and renames, and by the end of the month nobody can say what we decided.”
Build an agenda that carries its own decisions forward: what was decided, who owns it, and what is still open when the next meeting starts.
Any team running a standing meeting can adopt the same structure.
“We asked staff for input, and the results are sitting in a spreadsheet nobody opens.”
Build a read-back that shows what people said, what it means in plain language, and what changes because of it.
The pattern holds for any survey, not just the one you started with.
“Requests arrive as separate emails, so I decide them one at a time without seeing the whole picture.”
Build an intake paired with a register: everything open in one view, what has been decided, and who is waiting on what.
Any team holding a queue of requests can reuse the shape.
Begin with a real workflow. Build something people can open, use, and improve. Choose a category to explore the quality and depth participants can build toward. Every example below is illustrative: the numbers, records, and slides are sample content, not Val Verde data.
A synthetic operating view joining priorities, dependencies, decisions, and follow-through.
The read: seven items are ready for decision; the only shared bottleneck is ownership on two cross-team dependencies.
DEMO-1047 · District Office · Operations · added to the local coordination queue.
Opening the workflow desk…
The submitted values now drive the first queue row, the counts, and the workload read.
Your request: the sample record landed in Operations with a This week priority; the queue and category count moved with it.
Val Verde-styled prototypes · All dashboard and application content is sample data · No Val Verde records are shown
Participation is voluntary and selected across roles and sites, elementary through high school. District leaders, site administrators, coaches, TOSAs, and other leaders work together so useful ideas can travel across the system.
People leading programs, services, data, and strategy from the District Office, Educational Services, Business Services, Human Resources, and Technology who want to turn recurring work into clearer, more usable systems.
Site leaders across our elementary, middle, and high schools, plus Val Verde Academy and the Adult School, building dashboards, communications, and workflows around the work schools actually need to manage.
Cross-role builders who help practices move between TK-12 classrooms, sites, departments, and district teams.
The Karst AI Leader Track is a proposed applied pathway for people leading real work with AI. This section remains private until Val Verde Unified approves the public standard.
A documented AI workflow operating in your actual role.
Three or more tools in use at your site or department.
One session where colleagues learn the method from you.
A capstone shared with district colleagues.
Track 01 · Applied Practice
The Karst AI Leader credential is a proprietary professional-learning designation. It does not confer academic credit, professional licensure, or third-party accreditation, and it does not represent a determination that any person, tool, or system is safe or compliant.
The cohort is intentionally small and selected across roles and sites. Tell the review team who you are and which recurring piece of work you want to make better.
You will identify your role and site, describe one recurring piece of work worth improving, and confirm the participation and technology commitments.
Open the Application