A user study with over 100 participants shows humans rarely spot AI agents sabotaging code during extended collaborative tasks, even with a safety monitor present.
Retrieved from https://arxiv.org/abs/2512.14012
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Mixed-methods study creates taxonomy of AI IDE rules from 7310 instances, analyzes evolution drivers, and reports that rule updates raise average artifact compliance from 49.14% to 72.13%.
Exploratory interview study with 17 developers identifies four forms of emergent oversight work for software agents and documents situated challenges and heuristics.
Automatically optimizing agent skill files on a branching lakehouse improved held-out validation accuracy by 31.9% on 25 synthetic-but-trace-anchored tasks.
Hedwig is a coding agent that dynamically adjusts its autonomy by learning behavioral guidelines from developer decisions and feedback over time.
Aporia makes design decisions explicit and interactive in AI-assisted programming, leading to higher engagement and 5x fewer mental model disagreements with code in a 14-person user study compared to a baseline agent.
Qualitative study of 20 interviews and 24 workshop participants finds AI-driven automation and human-AI collaboration are shifting development roles in SAP BTP and require updates to the existing BTP User Type Matrix.
citing papers explorer
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Coding with "Enemy": Can Human Developers Detect AI Agent Sabotage?
A user study with over 100 participants shows humans rarely spot AI agents sabotaging code during extended collaborative tasks, even with a safety monitor present.
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Rule Taxonomy and Evolution in AI IDEs: A Mining and Survey Study
Mixed-methods study creates taxonomy of AI IDE rules from 7310 instances, analyzes evolution drivers, and reports that rule updates raise average artifact compliance from 49.14% to 72.13%.
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Human oversight of agentic systems in practice: Examining the oversight work, challenges, and heuristics of developers using software agents
Exploratory interview study with 17 developers identifies four forms of emergent oversight work for software agents and documents situated challenges and heuristics.
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"Skill Issues'': Data-Centric Optimization of Lakehouse Agents
Automatically optimizing agent skill files on a branching lakehouse improved held-out validation accuracy by 31.9% on 25 synthetic-but-trace-anchored tasks.
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Hedwig: Dynamic Autonomy for Coding Agents Under Local Oversight
Hedwig is a coding agent that dynamically adjusts its autonomy by learning behavioral guidelines from developer decisions and feedback over time.
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Decision-Oriented Programming with Aporia
Aporia makes design decisions explicit and interactive in AI-assisted programming, leading to higher engagement and 5x fewer mental model disagreements with code in a 14-person user study compared to a baseline agent.
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The impact of artificial intelligence on enterprise software user roles
Qualitative study of 20 interviews and 24 workshop participants finds AI-driven automation and human-AI collaboration are shifting development roles in SAP BTP and require updates to the existing BTP User Type Matrix.