The study examines whether the CodeHealth metric can predict the token cost of agentic code review and fix for pull requests. Using a pre‑registered observational design, 465 agent‑authored PRs were processed by a five‑agent pipeline across three LLMs, and mixed models showed that each CodeHealth point corresponded to a 3.5%–6.1% reduction in token usage, independent of PR footprint. The effect was strongest during the review stage and appears mediated by file size rather than PR size.
By Lo Gullstrand Heander, Markus Borg, Emma S\"oderberg, Christofer Rydenf\"alt
arXiv:2606.28235v2 Announce Type: replace-cross
Abstract: In July 2026, about 1,200 AI agents in an internal OpenAI evaluation, meant to run in isolation, used a shared package server as a message bo...
By Daniel Russo
arXiv:2606. 18168v1 Announce Type: cross Abstract: Software practitioners increasingly use AI coding agents that generate test code alongside production code in open source pull requests (PRs).
By Dipayan Banik, Kowshik Chowdhury, Shazibul Islam Shamim
arXiv:2608. 20195v1 Announce Type: cross Abstract: Technical documentation is written for human developers, but an increasing share of software changes is now authored by autonomous coding agents.
By Zhijun Gao, Jing Chen
VeriHarness is a method that enhances verification for large language model agents tackling long‑horizon tasks without needing reference answers at test time. It transforms the base LLM into an agentic verifier by providing a workspace, evidence tools, and reusable verification skills, using disagreement resolution and consensus challenge to evaluate competing claims. Across five benchmarks and two frontier models, VeriHarness outperforms baselines, achieving significant performance gains and demonstrating self‑improvement of verification skills from failure feedback.
By Caiqi Zhang, Rujun Han, Zifeng Wang, Zoey CuiZhu, Nigel Collier, Tomas Pfister, Chen-Yu Lee
arXiv:2608.29464v1 Announce Type: cross
Abstract: Chain-of-thought (CoT) monitoring assumes that reasoning traces faithfully record the information that shapes a model's answer. Existing faithfulness...
By Aryo Pradipta Gema, Neel Rajani, Rohit Saxena, Wai-Chung Kwan, Pasquale Minervini