AI Training
Your team knows AI exists. They don't know how to use it yet.
RBX Labs runs practical AI training for teams that need more than inspiration. The format depends on how fast you need adoption to show up in the work.
Sessions are workflow-specific and built around what your team needs to do next, not generic AI trends.
Credential
Practical training backed by institutional delivery
Three ways to train the team
Pick the format based on how much change the team needs, how cross-functional the work is, and whether you need momentum or habit formation.
01
Workshop
Half-day session for one team
Best for a specific workflow focus such as prompting, evaluation, product discovery, or AI-assisted execution.
Leaves the team with a shared mental model, a concrete workflow map, and immediate next actions.
02
Sprint
2-3 days for cross-functional teams
Best when product, operations, and leadership need alignment plus something tangible by the end.
Leaves the team with a working prototype, decision framework, and a clearer path to pilot or rollout.
03
Program
4-8 weeks for adoption and habit formation
Best when the goal is not just exposure to AI, but making it part of how the team actually operates.
Leaves the team with repeatable routines, coaching touchpoints, and usage patterns that stick.
Featured curriculum
Stanford Code in Place 2026
A banner-style showcase for the Stanford Code in Place learning track, adapted into a clean Week 1 to Week 6 training flow.
The page now gives this program a dedicated training feature instead of a single embed. Learners can jump into Weeks 1 through 4 immediately, while the remaining weeks stay visible as the upcoming path.
Next Step
Plan the session around the team and the workflow
Use a short planning call to decide whether a workshop, sprint, or longer program makes sense for your team.
If there is a real training need, the session should end with the right format, audience, and outcome.