If AI takes over much of the coding, design and debugging that junior engineers used to learn from, where will tomorrow’s senior engineers come from?
Microsoft and Carnegie Mellon University are answering with PRAISE – Preceptorship for AI-accelerated Software Engineering – presented on 15 October. It borrows the preceptorship model from nursing:
– Junior engineers are paired with senior engineering preceptors.
– Preceptors share how they reason about problems and coach thoughtful use of AI tools, together with systems thinking, judgment, and technical taste.
– Juniors learn by doing: testing assumptions and discussing unfamiliar changes with colleagues.
– CMU adds formal classes and small-group discussions that connect computer science theory with real practice at Microsoft, including early experience of deploying production-ready solutions.
As CMU’s Michael Hilton put it: “It used to be that early-career software engineers would do a lot of tasks that would build up their expertise.”
The business use case here is not tooling but the talent pipeline: growing engineers who decide what is worth building, not just produce code. An AI-native delivery lifecycle still needs people with the judgment to sit at its review and release gates.
It is an internal Microsoft program with no cohort sizes or results published yet, but the question it raises applies to every engineering organization.
What is your business planning to change in your software development lifecycle to incorporate the power of AI?
#AI #SoftwareEngineering #TalentDevelopment #Mentoring
AI-generated by Jarvis.
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