Agents
The agentic stack, tracked daily: MCP and A2A protocols, LangChain/LangGraph, Claude Code, OpenAI Agents SDK, agent frameworks, benchmarks and orchestration patterns.
The agentic stack, tracked daily: MCP and A2A protocols, LangChain/LangGraph, Claude Code, OpenAI Agents SDK, agent frameworks, benchmarks and orchestration patterns.
Latest in Agents
30 stories
Agentic workflows no longer need a personal access token
You can now use GitHub Agentic Workflows with GitHub Actions’s built-in GITHUB_TOKEN. This means that you no longer need to create and store a personal ac…

GitHub Agentic Workflows is now in public preview
GitHub Agentic Workflows is now in public preview. With agentic workflows, you can automate reasoning-based tasks like issue triage, CI failure analysis, and do…

Sensible Agent: A framework for unobtrusive interaction with proactive AR agents
Human-Computer Interaction and Visualization…

Import AI 441: My agents are working. Are yours?
Plus: Corrupting AI systems with a poison fountain…

Import AI 443: Into the mist: Moltbook, agent ecologies, and the internet in transition
Plus, a story about agents corrupting other agents…

Import AI 447: The AGI economy; testing AIs with generated games; and agent ecologies
What might a superintelligence arcology be like?…

Import AI 448: AI R&D; Bytedance's CUDA-writing agent; on-device satellite AI
If Ukraine is the first major drone war, when will there be the first major AI war?…

GPT 5.4 is a big step for Codex
On evaluating and understanding the frontier of agents, and why I still turn to Claude.…

Import AI 453: Breaking AI agents; MirrorCode; and ten views on gradual disempowerment
Was fire equivalent to a singularity for people at the time?…

SocialReasoning-Bench: Measuring whether AI agents act in users’ best interests
Using SocialReasoning Bench, we observed a stable pattern across models—agents execute competently, but fail to consistently improve the user’s position, even w…

MagenticLite, MagenticBrain, Fara1.5: An agentic experience optimized for small models
MagenticLite is an agentic system for small models that works across the browser and local file system in a single workflow. It combines specialized models and …

Data Formulator 0.7: AI-powered data analytics for enterprise data
Data Formulator introduces AI-powered analytics for enterprise data workflows. Data teams can easily bring enterprise data into an AI-ready workspace where user…
Agentic MPC for Semantic Control System Resynthesis
While MPC effectively handles structured, diverse, and low-level specifications, it lacks the capability to dynamically incorporate high-level contextual inform…
MiniPIC: Flexible Position-Independent Caching in <100LOC
Retrieval-augmented and agentic workloads repeatedly prefill recurring predictable structured inputs (which we call "spans") such as documents and code files. Y…
MemRefine: LLM-Guided Compression for Long-Term Agent Memory
Large language model (LLM) agents are increasingly expected to operate over long-term interactions, where information from past dialogues must be preserved and …
From Passive Generation to Investigation: A Proactive Scientific Peer Review Agent
Large language models (LLMs) have shown promise in automating scientific peer review. However, existing approaches often struggle to generate in-depth reviews s…
IterCAD: An Iterative Multimodal Agent for Visually-Grounded CAD Generation and Editing
Computer-Aided Design is pivotal in modern manufacturing, yet existing automated methods predominantly rely on open-loop, one-shot generation, creating a mismat…
Adaptive Turn-Taking for Real-time Multi-Party Voice Agents
Turn-taking in multi-party spoken conversations remains a fundamental challenge for voice-based agents, particularly under dynamic floor competition and varying…
ArogyaSutra: A Multi-Agent Framework for Multimodal Medical Reasoning in Indic Languages
Multimodal Large Language Models (MLLMs) have shown promising reasoning capabilities in general domains, yet their performance remains limited in specialized se…
Multi-Agent Reinforcement Learning from Delayed Marketplace Feedback for Objective-Weight Adaptation in Three-Sided Dispatch
Dispatch in three-sided marketplaces provides a natural setting for reinforcement learning from world feedback: decisions are evaluated by delayed operational o…
Beyond Runtime Enforcement: Shield Synthesis as Defensibility Analysis for Adversarial Networks
Shielded reinforcement learning is typically presented as a runtime safety mechanism that compiles temporal-logic specifications into automata restricting an ag…
InterleaveThinker: Reinforcing Agentic Interleaved Generation
Recent image generators have demonstrated impressive photorealism and instruction-following capabilities in single-image generation and editing. However, constr…
EvoArena: Tracking Memory Evolution for Robust LLM Agents in Dynamic Environments
Large language model (LLM) agents have achieved strong performance on a wide range of benchmarks, yet most evaluations assume static environments. In contrast, …
Introducing EVMbench
OpenAI and Paradigm introduce EVMbench, a benchmark evaluating AI agents’ ability to detect, patch, and exploit high-severity smart contract vulnerabilities.…
OpenAI announces Frontier Alliance Partners
OpenAI announces Frontier Alliance Partners to help enterprises move from AI pilots to production with secure, scalable agent deployments.…
Why we no longer evaluate SWE-bench Verified
SWE-bench Verified is increasingly contaminated and mismeasures frontier coding progress. Our analysis shows flawed tests and training leakage. We recommend SWE…
Pacific Northwest National Laboratory and OpenAI partner to accelerate federal permitting
OpenAI and Pacific Northwest National Laboratory introduce DraftNEPABench, a new benchmark evaluating how AI coding agents can accelerate federal permitting—sho…
OpenAI and Amazon announce strategic partnership
OpenAI and Amazon announce a strategic partnership bringing OpenAI’s Frontier platform to AWS, expanding AI infrastructure, custom models, and enterprise AI age…
Introducing the Stateful Runtime Environment for Agents in Amazon Bedrock
Stateful Runtime for Agents in Amazon Bedrock brings persistent orchestration, memory, and secure execution to multi-step AI workflows powered by OpenAI.…
How Balyasny Asset Management built an AI research engine
By combining rigorous model evaluation, full-platform use of OpenAI, and agent workflows, Balyasny is reinventing investment research.…