Campus AI Development · Building software with AI in higher education
Vibe coding, AI pair programming, agentic coding, spec-driven development and governed multi-agent work aren’t rivals. This guide arranges them on one continuum of structure and governance, with autonomy and code reading as separate dials. It helps you decide where a project belongs, and shows how colleges and universities apply it under the governance higher education requires.
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Why this guide
Software on campus used to come from a few developers in IT. Now an advisor, a faculty member or a first-year student can build a working tool in an afternoon. Most guidance hasn’t caught up: it either reviews tools or sets policy, and rarely helps someone decide how to build the thing in front of them.
This guide was written to fill that gap. It gives higher education a shared way to look at AI development: what kind of work this is, who is doing it, what it touches, and how much structure and governance it needs.
“Our students are not asking permission to use AI.”
A higher education executive
Nor are our campus community members asking permission to develop with AI.
The question for institutions is no longer whether people will build, but how to help them build well.Where this fits
A companion to the Campus AI Framework
The Campus AI Framework sets the institutional operating model: eight pillars for strategy and governance, four application domains and the AI Strategic Compass for prioritization. Once an initiative is worth pursuing, this guide helps decide how to build it. It goes deeper on the homegrown, in-house pathway and on the Campus Readiness and Implementation & Operations pillars. Both are starting points to adapt locally, not mandates.