TACT: Mitigating Overthinking and Overacting in Coding Agents via Activation Steering

📰 ArXiv cs.AI

Learn how TACT mitigates overthinking and overacting in coding agents, improving their performance on complex software engineering tasks

advanced Published 9 May 2026

Action Steps

Implement TACT to calibrate think-act cycles in coding agents
Use activation steering to mitigate overthinking and overacting
Evaluate agent performance on complex software engineering tasks
Compare results with and without TACT to measure its effectiveness
Refine TACT parameters to optimize agent performance

Who Needs to Know This

AI engineers and researchers working on coding agents can benefit from this knowledge to improve their agents' performance and reduce agent drift

Key Insight

💡 TACT helps mitigate agent drift by calibrating think-act cycles, reducing overthinking and overacting in coding agents

Key Takeaways

Learn how TACT mitigates overthinking and overacting in coding agents, improving their performance on complex software engineering tasks

Full Article

Title: TACT: Mitigating Overthinking and Overacting in Coding Agents via Activation Steering

Abstract:
arXiv:2605.05980v1 Announce Type: new Abstract: When language model agents tackle complex software engineering tasks, they often degrade over long trajectories, which we define as *agent drift*. We focus on two recurring failure modes *overthinking* and *overacting*, i.e., where the agent repeatedly reasons over information it already has, and where it issues tool calls without integrating recent observations or acquiring new evidence. In this paper, we introduce TACT (Think-Act Calibration via

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