A recipe for your campus
One real workflow.
Something everyone can try.
People to learn with.
Bring students, faculty, and staff together to experiment with AI. Start with a borrowed room, a useful question, and a small team ready to help.
Plan your first sessionThis guide draws on AI Kitchen at Santa Clara University. It offers a starting recipe to adapt to your people, space, and budget.
01 / Gather your ingredients
No application and no coding prerequisite. Invite people across majors and job roles around a useful question: planning a trip, exploring feedback, making a game, or preparing a learning activity. State what people will try and what they need to bring.
Invite someone willing to show their work, including the choices and wrong turns. Industry guests, faculty, staff, and students bring different perspectives. Where useful, show AI using tools to create, inspect, and revise a file or small app. Participants can try a smaller step with the access they have. Choose one task and one reusable lesson; share our guest chef guide to prepare.
Students help choose the exercise, test it beforehand, and get participants unstuck. Budget for paid preparation and hosting, with clear hours, supervision, and someone to turn to for help. Begin with a session small enough for your hosts to support.
Find a campus partner who can help with the room, tools, and continuity. Invite advisers, teachers, researchers, and artists to bring their expertise and questions. Everyone can contribute knowledge while learning alongside others.
An invitation you can adapt
“Curious about AI? Come watch someone use it for a real task, then try one small step with help nearby. Students, faculty, and staff from every field are welcome. No coding experience needed.”
Add your task, date, room, tool-access plan, and contact for questions or access needs.
02 / Your first Taste Test
Adaptable sample
90 minutes
A compact first session could look like this. Adjust the pace for your audience, exercise, and available support. SCU’s Friday format leaves more time for the demonstration and open projects.
Explain the task in plain language. Help people open the tool and practice material. Invite them to work with a partner if that helps.
The guest works through a specific problem on screen. Ask them to explain what they give the AI, what they inspect, and how they decide what to change.
Participants repeat a manageable part using their own example or shared practice material. Hosts circulate. Offer one optional extension for people ready to go further.
Invite a few people to show a result or a sticking point. Ask: What did you notice? What would you check? What would you change next?
Invite brief project questions and introductions. Name the next opportunity to meet, and share the exercise and useful links afterward.
A small exercise to borrow
Pair up, or use two fictional profiles. Open a browser AI tool your campus provides. The goal: three movies both people would enjoy tonight.
“Interview us one person at a time about our preferences, constraints, films we’ve seen, time available, and where we can watch. Ask one question and wait for the answer. Then suggest three films we might both enjoy, explain the fit for each person, and flag assumptions to check.”
Leave with: a three-film shortlist, reasons each fits both people, and one refinement. Check availability yourself; verify any streaming claims before choosing.
A little practice that travels
Three examples from our sessions. Pick one habit for your first exercise.
Gather context
Have AI ask about the purpose, preferences, and constraints before producing an answer.
Explore the movie recommender sessionInspect the evidence
Ask for the data behind a summary. Check how examples were grouped and whether the interpretation follows.
Explore reviews into research insightsTry & revise
Use what AI makes. Describe a specific change, then check the next version.
Explore the game-building session03 / Before you cook
Adapt these steps to your campus. Check them off as you plan, or print the guide for your team.
04 / Stock the kitchen
A dedicated space can come later. Build your local budget around the work required to make a modest first session welcoming and workable.
| Resource | What to plan for |
|---|---|
| People & preparation | Student host pay for preparation, the session, and follow-up; staff or faculty coordination; guest preparation and any agreed honorarium or travel. |
| Tool access | Start with tools your institution already provides, or a free option that supports the whole exercise. Budget for temporary access or credits when needed. Test limits before the session and explain any participant costs in advance. |
| Room & equipment | A borrowed classroom or meeting room, reliable Wi-Fi, a projector or shared screen, power, and a plan for participants who need a device. |
| Participation support | Accessible materials, captions, accommodations, clear directions, and optional refreshments. Include recording or editing time if you choose to share a recording with permission. |
| Continuity | A page for the schedule and materials, reminders, host debriefs, and time for introductions and project follow-up. |
Match the exercise to the access. A guest can show an advanced workflow while participants try a smaller step in a browser tool. See our tools guide for examples, and check what your campus supports.
Download the one-page color ATXpo handout (US Letter PDF)
Print in color, single-sided on US Letter paper in portrait orientation, at actual size (100%). One sheet makes one handout.
05 / Keep cooking
Run another small session and improve one thing. Invite a different field into the room. Teaching, art, research, advising, and everyday life can all offer useful questions.
Make space for people with ongoing projects to ask for guidance. Introduce a student builder to a faculty or staff member who knows the subject, or connect people with complementary skills. Agree on a manageable next step and who will follow up.
When there is interest and enough support, add longer projects, mentoring, or a showcase. Our joint Demo Night with CSEN 174 is one example of a later opportunity to share work.
Notice who comes, who gets a chance to try, and what gets in the way. Use that feedback to improve the experience; attendance alone does not tell you what people learned.
Everyone brings an ingredient
Borrow the recipe. Adapt it to your campus. Tell us what you try.