HN knlsn 3/18/2026

Your terminal, finally has memory!

Terminal tool with local AI memory using Ollama. Save/recall commands, notes, URLs via natural language. Runs locally, no cloud.

HN MaysonL 3/18/2026

Gas Town by Kilo

Gas Town is Steve Yegge's agent orchestrator coordinating multiple AI coding agents simultaneously, hosted on Kilo Cloud infrastructure.

Ax Zeyu Zhang, Rui Li, Xiaoyan Zhao, Yang Zhang, Wenjie Wang, Xu Chen, Tat-Seng Chua 3/18/2026

NextMem: Towards Latent Factual Memory for LLM-based Agents

NextMem proposes a latent factual memory framework for LLM-based agents to address limitations of existing textual and parametric memory approaches.

Ax Yibo Yang, Fei Lei, Yixuan Sun, Yantao Zeng, Chengguang Lv, Jiancao Hong, Jiaojiao Tian, Tianyu Qiu, Xin Wang, Yanbing Chen, Yanjie Li, Zheng Pan, Xiaochen Zhou, Guanzhou Chen, Haoran Lv, Yuning Xu, Yue Ou, Haodong Liu, Shiqi He, Anya Jia, Yulei Xin, Huan Wu, Liang Liu, Jiaye Ge, Jianxin Dong, Dahua Lin, Wenxiu Sun 3/18/2026

AIDABench: AI Data Analytics Benchmark

AIDABench: Comprehensive benchmark for AI data analytics and document understanding. Evaluates end-to-end task effectiveness in practical document processing scenarios.

Ax Alexandre Lacoste, Nicolas Gontier, Oleh Shliazhko, Aman Jaiswal, Kusha Sareen, Shailesh Nanisetty, Joan Cabezas, Manuel Del Verme, Omar G. Younis, Simone Baratta, Matteo Avalle, Imene Kerboua, Xing Han L\`u, Elron Bandel, Michal Shmueli-Scheuer, Asaf Yehudai, Leshem Choshen, Jonathan Lebensold, Sean Hughes, Massimo Caccia, Alexandre Drouin, Siva Reddy, Tao Yu, Yu Su, Graham Neubig, Dawn Song 3/18/2026

CUBE: A Standard for Unifying Agent Benchmarks

CUBE: Universal benchmark standard for AI agents built on MCP and Gym. Addresses fragmentation by allowing benchmarks to be wrapped once and used everywhere.

Ax Rushil Thareja, Gautam Gupta, Francesco Pinto, Nils Lukas 3/18/2026

MAC: Multi-Agent Constitution Learning

MAC automatically learns constitutional AI rules from training data using multi-agent approaches, improving upon existing LLM-based prompt optimizers through structured learning.

Ax Hong Zhang, Barry Smith, Satish Balay, Le Chen, Murat Keceli, Lois Curfman McInnes, Junchao Zhang 3/18/2026

An Agentic Evaluation Framework for AI-Generated Scientific Code in PETSc

petscagent-bench evaluates AI-generated scientific code for HPC libraries beyond test-case matching, assessing solver selection, API conventions, memory management, and performance.

Ax Sarthak Ahuja, Neda Kordjazi, Evren Yortucboylu, Vishaal Kapoor, Mariam Dundua, Yiming Li, Derek Ho, Vaibhavi Padala, Jennifer Whitted, Rebecca Steinert 3/18/2026

VIGIL: Towards Edge-Extended Agentic AI for Enterprise IT Support

VIGIL deploys edge-resident AI agents for enterprise IT support, performing diagnosis, knowledge retrieval, and policy-governed remediation on user devices with consent and observability.

Ax Chunjiang Mu, Ya Zeng, Qiaosheng Zhang, Kun Shao, Chen Chu, Hao Guo, Danyang Jia, Zhen Wang, Shuyue Hu 3/18/2026

Adaptive Theory of Mind for LLM-based Multi-Agent Coordination

Adaptive theory of mind framework for LLM-based multi-agent coordination, aligning agents' reasoning depth about others' mental states.