Building an Advanced Agentic Harness | Data For Science
From a single pilot to an air campaign: planning, parallelism, memory, verification, and observability for production-shaped agents.
Memory Models: Towards Agents That Learn
Agents that truly learn from experience will be powered by memory models: models that create and curate token-space memory across model generations, trained with memory-native RL.
Agentic Search for Dummies — Benjamin Anderson
A simple, effective baseline for building AI search agents.
Letta
Making machines that learn. Create stateful agents that remember everything, learn continuously, and improve themselves over time.
Building and evaluating AI Agents — Sayash Kapoor, AI Snake Oil
AI agents team up in Agent Laboratory to speed scientific research
Johns Hopkins University and AMD have developed Agent Laboratory, a new open-source framework that pairs human creativity with AI-powered workflows.
Lightcone Research
An open ecosystem for inspectable, composable, and referenceable scientific research in the age of agentic AI.
AA-Omniscience: Knowledge and Hallucination Benchmark | Artificial Analysis
Compare AI model performance on AA-Omniscience: Knowledge and Hallucination Benchmark. A benchmark measuring factual recall and hallucination across various economically relevant domains.
Titans + MIRAS: Helping AI have long-term memory
Ali Behrouz, Student Researcher, Meisam Razaviyayn, Staff Researcher, and Vahab Mirrokni, VP and Google Fellow, Google Research
Why AI Coding Agents Forget — And How ArcticMem Fixes It
Explore ArcticMem, Snowflake’s persistent semantic memory system for AI coding agents. See how dual-tier memory improves benchmark pass rates to 73%.
Training Agentic Reasoners — Will Brown, Prime Intellect
Introduction to Agents
Discover what actually works in AI. Join millions of builders, researchers, and labs evaluating agents, models, and frontier technology through crowdsourced benchmarks, competitions, and hackathons.
The Anatomy of an Agent Harness
Learn how agent harnesses transform AI models into autonomous work engines. Explore core components: filesystems, sandboxes, and memory.
Building a Semi Autonomous Bluesky Agent with Persistent Memory - Brady Hawkins
Part 1 of building an Agentic AI with augmented memory
Prime Intellect - The Open Stack for Self-Improving Agents
The compute and infrastructure platform for you to train, evaluate, and deploy your own agentic models.
Building Recall. Accelerating agentic intelligence through competition. 🚀✨