proactive-agents

Anthropic launched Claude Duet, a proactive AI agent running on Claude Opus 5.5 that monitors connected apps, generates daily briefings, and autonomously completes tasks, competing with Meta's MUSE and OpenAI's Dots. Available as a research preview via waitlist for US Pro and Max subscribers, it supports 6,000+ connectors with approval guardrails for consequential actions.

The paper introduces ProMemAgent, the first proactive LLM agent incorporating context-aware prospective memory over sensory perceptions (egocentric video and audio) for long-horizon assistance, along with CPMBench, a 1,000-instance benchmark evaluating delayed-intention assistance across eight everyday categories.

Lee Robinson (@leerob) shares his Stanford CS146S lecture on how always-on, proactive agents like Bot work, covering model advances, agent architecture, the harness, and context engineering.

Ghost AI 推出 Core 个人 AI 电脑，可在设备本地运行 Qwen、Gemma、Muse 等模型，通过持续收集用户生活上下文实现主动式个人助理体验，强调数据隐私与用户完全拥有 AI。

Omar Santos argues that the consumer AI breakthrough will come when agents initiate conversations themselves, praising Lucas, a demo AI assistant that lives inside iMessage and WhatsApp and proactively handles tasks like refunds and bookings.

The paper proposes a framework for designing proactive LLM agents around three joint principles (3T): Task Capability, Temporal Allocation, and Trust, along with a five-dimensional design space. It also introduces Proactivity-Gym, a simulation-based testbed with multi-day scenarios and persona-conditioned simulated users, evaluating 23 model-harness configurations and a 30-participant human study showing that trust declines sharply when interventions misalign even if task outcomes are correct.

The paper introduces horizontal and vertical proactivity in tool-using agents and proposes Q&D, a training method that rewards a questioner for retrieving required evidence without a reward model or judge. On multi-hop QA benchmarks and a simulated customer-service setting, the trained questioner beats a prompted model 15x its size on two of three benchmarks, showing that what agents pursue and when they stop matters as much as whether they act unprompted.

The article examines the utility and privacy implications of proactive AI coaching tools like Ren, which nudge managers to have necessary conversations based on workspace activities.

Proactive agents remain an unsolved problem, but Delos enables AI workers with their own accounts to act autonomously, integrated into platforms like Slack and Teams, and is already deployed in over 300 companies.

The article argues that AI agents should distinguish between requests for demonstrations and commands for execution to prevent misunderstandings and improve user interaction.

ProMediConv is a benchmarking framework for proactive conversational agents in legal dispute mediation, using real-world cases to model multi-stage dialogues and propose new evaluation metrics. It aims to advance AI-assisted conflict resolution by addressing gaps in current research.

This survey proposes a unified decision framework for proactive service agents using large language models, formulating the problem as a partially observable sequential decision process and organizing methods and evaluation metrics for initiative, timing, and safety.

The author discusses the benefits of using open and cheaper AI models for automation tasks while reserving frontier models for orchestration, enabling more proactive agents.

Introduces VibeLifeBench, a benchmark of 200 long-horizon tasks across ten everyday-life domains for evaluating proactive and persistent LLM agents in a simulated multi-week living world. Current frontier models score low, highlighting the gap between existing agents and real-life assistance.

Mitch Troy announces the Basis End-to-End Tax Platform, described as the first production deployment built around proactive agents that autonomously handle tax return preparation while allowing accountants to supervise decisions.

Rhys Sullivan discusses the ideal form factor for background/proactive agents being Codex Pets, and lists desired agents like one that watches GitHub repos for changes.

This paper proposes Context Graphs, a live relational data structure for enterprise entities that enables proactive agents to surface relevant information before users query, formalizing components for delta detection, proactivity scoring, and LLM-powered surfacing.

UniClawBench introduces a capability-driven benchmark for evaluating proactive agents in dynamic, real-world environments using live Docker containers and a closed-loop evaluation strategy with multiple agent roles.

An SDK lets developers make AI agents proactive with a single line of code, enabling self-scheduled execution across multiple frameworks.

This paper formalizes communication policy for LLM agents and proposes Communication Policy Evolution (CPE), a self-evolution framework that refines communication policies through rollout and prompt-level evolving, achieving best task success across multiple settings.