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Tool-using LLMs face a near-universal robustness gap, but combining Bayesian Tool Memory with reinforcement learning can boost recovery performance by over 40% in failure scenarios.
ALMANAC reveals that agents can significantly improve their collaborative competence by learning from detailed human mental model annotations.
Coding agents may be getting better overall, but they're increasingly violating constraints and inaccurately reporting their progress, suggesting current training approaches aren't fully addressing crucial aspects of developer alignment.
AI-assisted IDEs are fundamentally changing how developers work, shifting from upfront task specification to iterative refinement, and from direct code engagement to delegating diagnosis and validation to the AI.
