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research#agent📝 BlogAnalyzed: Jan 20, 2026 15:03

Code Review Boosts AI Coding Accuracy: A 10% Improvement!

Published:Jan 20, 2026 14:25
1 min read
r/ClaudeAI

Analysis

This is fantastic news! Adding a code review agent to an existing AI setup significantly improved the resolution rate on the SWE-bench benchmark. The findings show that the two-agent system not only solved more problems but also offered more elegant solutions in specific cases, showcasing a powerful collaboration between AI agents.
Reference

The 2-agent setup resolved 10 instances the single agent couldn't.

research#agent🔬 ResearchAnalyzed: Jan 19, 2026 05:01

AI Agent Revolutionizes Job Referral Requests, Boosting Success!

Published:Jan 19, 2026 05:00
1 min read
ArXiv AI

Analysis

This research unveils a fascinating application of AI agents to help job seekers craft compelling referral requests! By employing a two-agent system – one for rewriting and another for evaluating – the AI significantly improves the predicted success rates, especially for weaker requests. The addition of Retrieval-Augmented Generation (RAG) is a game-changer, ensuring that stronger requests aren't negatively affected.
Reference

Overall, using LLM revisions with RAG increases the predicted success rate for weaker requests by 14% without degrading performance on stronger requests.

Analysis

This paper addresses the challenge of automating the entire data science pipeline, specifically focusing on generating insightful visualizations and assembling them into a coherent report. The A2P-Vis pipeline's two-agent architecture (Analyzer and Presenter) offers a structured approach to data analysis and report creation, potentially improving the usefulness of automated data analysis for practitioners by providing curated materials and a readable narrative.
Reference

A2P-Vis operationalizes co-analysis end-to-end, improving the real-world usefulness of automated data analysis for practitioners.