Agents

AI agents are LLM-driven systems that pursue a goal over multiple steps — planning, calling tools, observing the results, and deciding what to do next — instead of producing a single response. The model runs inside a loop rather than answering once.

What separates an agent from a chatbot is autonomy over control flow: it chooses which Tool Use action to take and when the task is done. This unlocks work like research, multi-step coding, and workflow automation that no single prompt can complete.

For builders the hard problem is reliability, not capability: small per-step error rates compound over a long loop, so production agents lean on Context Engineering, Agent Memory, guardrails, and verification far more than on a smarter base model.

Related: Agent Memory Tool Use Context Engineering Code Agents

This is the Agents concept page (definitions and fundamentals). For dated developments, see the Agents Topic hub.

Recent Updates

• 2026-09-09: DAREBench: Deployment-Aware and Reliable Evaluation of Models as Agents (breakingnewsofficial) · arxiv.org
• 2026-09-09: Memory in Deep Time-Series Models: A Unified Framework for Retention and Access (breakingnewsofficial) · arxiv.org
• 2026-09-09: AgentBrew: Offline Tool-Use Agent Learning from Raw Real-World Trajectories (breakingnewsofficial) · arxiv.org — Qwen3-32B · Qwen3-235B
• 2026-09-09: Beyond Prompts: Measuring and Optimizing LLM Tool-Agent Harnesses (breakingnewsofficial) · arxiv.org
• 2026-09-09: SurveyAgent-HKA: Multi-agent framework for scientific survey generation with LLM and human knowledge (breakingnewsofficial) · arxiv.org
• 2026-09-09: AtomCite: Verification and Correction of Supplied Page-Level Citations in Multi-Page Documents (breakingnewsofficial) · arxiv.org — Anthropic · OpenAI · Google · Claude · Gemini · GPT
• 2026-09-09: AutoFyn: Expert Iteration for Long-Horizon Agents via Persistent State Adaptation (breakingnewsofficial) · arxiv.org — AutoFyn Next.js MetaMask · pnpm · Warp · LiteLLM · Langflow · Open WebUI
• 2026-09-09: MERIT: Cost-Aware Evaluation of Memory in Tool-Using LLM Agents (breakingnewsofficial) · arxiv.org — OpenAI · Anthropic · GPT-4.1-mini · GPT-4.1 · Claude Haiku 4.5 · Claude Sonnet 5
• 2026-09-09: XunFei Spark X2.5: End-to-End Agentic Task Delivery from Creative Prompts to Production Code (breakingnewsofficial) · qbitai.com — XunFei OpenAI · Anthropic · NVIDIA · Hugging Face · DeepSeek Spark X2.5 · Claude
• 2026-09-09: Geiger – See every AI agent on your machine and what it can touch (breakingnewsofficial) · github.com — Anthropic 21st-dev
• 2026-09-09: OtoDock: Self-hosted agent platform with persistent memory and team coordination (breakingnewsofficial) · github.com — Anthropic · OpenAI · Twilio
• 2026-09-10: Separating Agent Storage from Usage: RD-Forget Framework for Persistent Memory Management (breakingnewsofficial) · arxiv.org
• 2026-09-10: Kernel-Managed Shared Memory for Multi-Agent System Personalization (breakingnewsofficial) · arxiv.org — OpenAI · Meta · Alibaba · Mem0 · GPT-4o · Llama-3.1:8B · Qwen 2.5 7B
• 2026-09-10: VLX-VR: An Agentic-Aware Video Reasoning Model (breakingnewsofficial) · arxiv.org — VLX-VR
• 2026-09-10: AgentAudit: An Open, Extensible Framework for Full-Lifecycle Trust Evaluation of AI Agents (breakingnewsofficial) · arxiv.org — OpenAI · Anthropic · Google · Meta Sarvam AI · GPT-5 · Claude Sonnet 5 Sarvam 105B · Llama-3.3-70b · Gemini 2.5 Flash
• 2026-09-10: Procedural Memory Under Change: Reuse and Interference in Controlled Web Tasks (breakingnewsofficial) · arxiv.org — Qwen3-8B
• 2026-09-10: ROAM: Robust Organization of Atomic Memories for Agents through Semantic Relations (breakingnewsofficial) · arxiv.org
• 2026-09-10: ContractEval: Diagnostic Framework for Procedural Instruction Conformance in LLM Agents (breakingnewsofficial) · arxiv.org
• 2026-09-10: State-Path Tool Menus: Learning Execution Routes to Improve Agent Tool Selection (breakingnewsofficial) · arxiv.org
• 2026-09-10: Subagents vs Agent Skills: Executing Reusable Knowledge for Long-Horizon Agentic Tasks (breakingnewsofficial) · arxiv.org
• 2026-09-10: HybridDeepResearch Benchmark Reveals AI Agents Struggle With Web and Database Reasoning (breakingnewsofficial) · arxiv.org — Snowflake · OpenAI · Anthropic · Hugging Face · GLM-5.2 · Claude Sonnet 4.6 · GPT-5
• 2026-09-10: How AI agents now compress multi-day prototyping into minutes with Codex and tool orchestration (breakingnewsofficial) · t.me
• 2026-09-11: Auto-RecSys: Harnessing Autonomous Research Agents for Industry-Scale Recommender Systems (breakingnewsofficial) · arxiv.org
• 2026-09-11: SearchAtlas: Analyzing LLM Search Agent Behavior Through Evidence Graphs (breakingnewsofficial) · arxiv.org
• 2026-09-11: Benchmarking RTK terminal compression: claimed 60% token savings don’t materialize in practice (breakingnewsofficial) · quesma.com — Anthropic · JetBrains · OpenRouter · Fable 5 · DeepSeek V4

FAQ

What is Agents?

AI agents are LLM-driven systems that can plan, call tools, inspect results, and iterate toward a goal. GROUNDING tracks agent architectures, benchmarks, tool use, browser agents, coding agents, and reliability patterns.

Which concepts are related to Agents?

Related concepts tracked by the radar include Agent Memory, Tool Use, Context Engineering, Code Agents.

What does this Agents page track?

Dated updates, papers, and mentions of Agents collected by the GROUNDING radar, most recently on 2026-09-11.