Agents That Teach: Towards Designing Incidental Learning Back into AI-Assisted Software Development
AI coding agents are rapidly reshaping how software is built, with developers increasingly delegating substantial coding tasks to autonomous agents in pursuit of higher productivity. While these gains are real, they come at the cost of incidental learning. Developers historically acquired informal knowledge through effortful problem-solving, and this has long shaped how software engineering expertise develops. However, with over-reliance on agentic coding, unpracticed skills could atrophy silently over time. As this learning pathway is short-circuited, developers risk silently accruing Knowledge Debt, a developer-level analogue of Technical Debt, where changes the agent executes that the ...
| Authors | Rohit Mehra, Samdyuti Suri, Prithviraj K Tagadinamani et al. |
|---|---|
| Primary category | cs.SE |
| Published | 7 July 2026 |
| Last updated at source | 7 July 2026 |
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