You’re watching a shift in how universities prepare students for software development careers. OpenAI launched its Codex app on February 2, 2026, and within days, Australia became an early adopter through an education pilot that embeds the technology directly into undergraduate IT curriculum. Notably, this isn’t optional enrichment. It’s the core curriculum. Specifically, NextEd Group integrated Codex into its Bachelor of Information Technology delivered through the Academy of Interactive Technology. The positioning matters because it signals how institutions view AI-assisted development: not as a supplementary skill, but as a fundamental workflow students will encounter in industry.
What Codex Actually Does
The Codex app functions as a command centre for managing multiple AI coding agents. These agents work in parallel across projects, using built-in worktrees and cloud environments to complete tasks that traditionally took weeks. To illustrate its capabilities, OpenAI reports that a four-person engineering team built and shipped the Sora for Android app in 28 days using Codex. Moreover, over a million developers used Codex in the past month, including teams at startups like Harvey and Sierra, plus large enterprises like Cisco. Ultimately, the app reflects a fundamental change in developer workflow. You’re no longer interacting directly with a single AI assistant. Instead, you’re overseeing several agents running tasks simultaneously.
The Adoption Numbers Tell a Story
The education pilot arrives amid explosive growth in AI coding adoption. In fact, in 2025, 41% of all code was AI-generated or AI-assisted. Furthermore, among professional developers, 76% either use AI coding tools or plan to adopt them soon. Interestingly, university students are leading this charge. AI usage among university students rose from 66% in 2024 to 92% in 2025. More specifically, 88% of students now use generative AI for assessments in 2025, up from 53% in 2024.
These aren’t marginal increases. They represent a fundamental shift in how students approach technical work. Looking ahead, the Tech Council of Australia predicts AI could create up to 200,000 AI-related jobs in Australia by 2030. Consequently, universities that integrate these tools into the core curriculum are positioning students for the job market.
The Trust Gap Remains Wide
However, high adoption doesn’t mean high confidence. According to Stack Overflow’s 2025 survey, 84% of developers use AI tools, yet more developers actively distrust the accuracy of AI tools (46%) than trust it (33%). Only 3% report they “highly trust” the output. As a result, this creates a teaching challenge. You need to train students to use tools they shouldn’t fully trust.
Adding to this complexity, a July study by the nonprofit research organisation Model Evaluation & Threat Research (METR) found that experienced developers believed AI made them 20% faster, but objective tests showed they were actually 19% slower. Perception and reality don’t align yet. Clearly, this gap matters for curriculum design. If students learn to rely on AI tools that slow them down while believing they’re faster, you’re building false confidence into technical education.
What This Means for Australian IT Education
In practice, the NextEd pilot includes ChatGPT Edu licenses across higher education and vocational programs, covering both domestic and international student cohorts. This broader integration shows how institutions are thinking about AI literacy across multiple platforms and use cases. Essentially, you’re not just teaching students to use Codex. Rather, you’re teaching them to work in environments where AI agents handle routine tasks while humans manage strategy, quality control, and decision-making.
For context, UTS ranks 2nd in Australia and 36th worldwide for Data Science and Artificial Intelligence studies. As more institutions adopt AI tools in the core curriculum, competitive positioning will depend partly on how well programs prepare students for AI-assisted workflows. Meanwhile, the integration raises practical questions about assessment design, academic integrity, and skill verification. When 88% of students use generative AI for assessments, traditional evaluation methods need rethinking.
The Broader Pattern
Overall, Australia’s early adoption of Codex in undergraduate IT programs fits a pattern of institutions racing to prepare students for AI-saturated workplaces. The question isn’t whether to integrate these tools, but rather how to do it in ways that build genuine capability rather than dependency. Right now, you’re watching curriculum evolve in real time. The NextEd pilot will generate data about how students learn with AI agents, how their problem-solving approaches change, and whether these tools accelerate or complicate skill development. Ultimately, that data will shape how other institutions approach AI integration in technical education. For now, Australia is writing the early chapters of that story.
