This page shows the most relevant public items for Agentic AI, ranked by trend activity and review signal. Use weekly for fast changes, monthly for more stable patterns, and all-time for evergreen picks.
Blog • Feb 8, 2026 • Medium • Mark S. Davidson
The framework wars of 2025 have settled, leaving LangGraph and AutoGen as the dominant orchestration layers for enterprise AI Engineering. Davidson provides a brutal, battle-tested comparison of th...
Paper • Feb 28, 2026 • arXiv • Virginia Dignum, Frank Dignum
The rapid popularization of the term 'Agentic AI' has led to semantic confusion, often blurring the lines between simple generative loops and true software agency. This position paper critically ex...
Paper • Feb 28, 2026 • arXiv • Ziheng Geng, Jiachen Liu, Ran Cao
Predicting complex human economic behavior is notoriously difficult using traditional statistical models. InsurAgent leverages LLM-empowered agents to simulate thousands of distinct individual pers...
Paper • Feb 28, 2026 • arXiv • Jiangping Huang, Wenguang Ye, Weisong Sun, Jian Zhang, Mingyue Zhang, Yang Liu
While LLMs excel at generating initial code snippets, they struggle immensely with resolving complex runtime errors. TraceCoder introduces a multi-agent framework that utilizes actual execution tra...
Blog • Feb 20, 2026 • Medium • David T. Sterling
Scaling an autonomous workforce from a single instance to a thousand concurrent processes requires a completely new infrastructure paradigm. This post introduces the modern stack detailing the nece...
Blog • Jan 29, 2026 • Medium • Sarah Jenkins
Founders are discovering a painful truth in early 2026 regarding the hidden costs of autonomous reasoning loops. Jenkins explores how infinite loops and constant reflection cycles are driving cloud...
Paper • Feb 25, 2026 • arXiv • Ling Chen, Yonggan Fu, Song Han
The deployment of personal digital assistants is severely hindered by the privacy risks associated with uploading sensitive personal data to centralized cloud environments. We propose a federated f...
Paper • May 12, 2025 • arXiv • Ling Chen, David Wu, Samantha Harris, Yong Zhang
Single-agent code generation models frequently fail when confronted with repository-level refactoring and complex architectural planning. We propose SwarmCoder, an Agentic AI framework that deploys...
Paper • Aug 8, 2025 • arXiv • Jian Lu, Percy Liang, Chelsea Finn
While scaling laws for single-model LLMs are well established, the relationship between the number of collaborating agents and overall system performance remains poorly understood. This paper inves...
Blog • Mar 11, 2026 • OpenAI • Thomas Shadwell, Adrian Spânu
OpenAI frames prompt injection not as simple string-matching but as an evolving social-engineering-like threat that targets tool-using agents. The post defines the problem of malicious external con...
Paper • Feb 28, 2026 • arXiv • Qiang Wang, Xinyuan Gao, SongLin Dong, Jizhou Han, Jiangyang Li, Yuhang He, Yihong Gong
Generating highly detailed, temporally accurate video captions requires models to understand complex spatial and temporal dynamics. VDC-Agent introduces an autonomous framework where the captioning...
Other • Mar 31, 2026 • GitHub • instructkr
This project is a complete architectural overhaul of the Claude Code CLI, rewritten from the ground up in Rust following the high-profile source leak on March 31, 2026. It aims to solve the severe ...
Paper • Mar 11, 2026 • arXiv • Zhiwei Liu, Kay Liu, Jingdi Chen, Carlee Joe-Wong
This paper presents the first systematic and comprehensive survey of AI agent security, analyzing the design space, attack landscape, and defense mechanisms for autonomous systems. The researchers ...
Paper • Mar 10, 2026 • arXiv • Md Nasir Uddin Shuvo, Md Aidul Islam, Md Mahade Hasan, Muhammad Waseem, Pekka Abrahamsson
This paper presents one of the first real-world experience reports of applying vibe coding in production environments. The authors analyze how LLM-based coding accelerates development while introdu...
Paper • Mar 6, 2026 • arXiv • Unknown
This paper proposes a schema-gated architecture that separates natural language reasoning from strict execution constraints in agentic AI systems. The framework allows large language models to gene...
Blog • Mar 5, 2026 • Medium • Marcus Sterling
For the past year, web automation agents have relied heavily on parsing HTML DOM structures, making them notoriously brittle whenever a website updates its layout. The release of OpenClaw 3.0 this ...
Paper • Mar 4, 2026 • arXiv • Minjune Hwang, Yigit Korkmaz, Daniel Seita, Erdem Bıyık
Reward learning from human preferences often suffers from spurious correlations, leading agents to develop brittle and misaligned behaviors. The authors present a framework that integrates causal i...
Paper • Feb 28, 2026 • arXiv • Ling Chen, David Wu, Yong Zhang
The migration of legacy codebases to modern architectures is a notoriously slow error prone and expensive human endeavor. We introduce a persistent multiagent system designed to operate continuousl...
Book • Jan 15, 2026 • O'Reilly • Michael Albada
This book provides a practical guide to designing and implementing AI agent systems using foundation models and modern orchestration techniques. It focuses heavily on multi-agent architectures, inc...
Paper • Feb 5, 2026 • arXiv • Minghao Du, Yifan Sun, Zeyu Li
A-RAG proposes an agentic retrieval framework that exposes retrieval tools directly to large language models. Rather than treating retrieval as a static preprocessing step, the architecture allows ...
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Use weekly for fast-moving updates, monthly for stable trend confirmation, and all-time for evergreen references. This guidance is specific to Agentic AI topic page on Attendemia and is written so it still makes sense without reading other sections on the page.
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