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AI agent

Trial

Techniques

An autonomous software system that can take actions and use tools on behalf of users.

Why it's here

Placed in Trial: 9 article(s) of evidence from 6 source(s), led by research-stage coverage, with 6 in the last 30 days. Confidence 89%.

Evidence (9)

  • 4The New Stack·6/10/2026product_launch
    AI Agents Aim to Tame Observability Overload

    The article argues that modern observability stacks generate more logs, traces, and alerts than engineers can efficiently handle, slowing root-cause analysis and resolution. It highlights AI agents as a proposed solution, with vendors building systems that can correlate observability data, remediate issues autonomously, or surface guidance inside tools like Codex, Cursor, and Claude Code.

  • 7Hacker News·6/10/2026security
    Tiny Bank Transfer Exposed a Vulnerability in a Banking AI Agent

    The article describes how researchers helped bunq secure its financial AI assistant after finding that a very small bank transfer could be used to compromise the agent. The case highlights how AI systems connected to financial actions can be vulnerable to prompt injection or other manipulations through unexpected external inputs. The report focuses on the security risks and the steps taken to harden the assistant.

  • 4Hugging Face Blog·6/9/2026research
    Agent Chains Two Hugging Face Spaces to Build a 3D Paris Gallery

    A Hugging Face blog post describes how an agent created a 3D Paris gallery by chaining two Hugging Face Spaces together. The example highlights how agents can orchestrate multiple hosted apps and tools to produce a more complex interactive result.

  • 4InfoQ·6/8/2026research
    AI-Native Engineering Evolves from Vibe Coding to Autonomous Agents

    Birgitta Böckeler discusses how AI use in software delivery has changed over the past year, from vibe coding to a more mature AI-native engineering approach. The conversation also highlights the shifting tool landscape and the rise of more autonomous agents that can increase both productivity and risk.

  • 4Hugging Face Blog·6/1/2026research
    Why Enterprise AI Scaling Needs Agent Logic Beyond LLMs

    The article argues that enterprises cannot rely on large language models alone if they want AI systems to scale reliably in real workflows. It emphasizes agent logic as the missing layer for coordinating actions, handling tasks, and making enterprise adoption more practical.

  • 7NVIDIA Blog·6/1/2026product_launch
    NVIDIA Expands Global AI Cloud Ecosystem

    NVIDIA said its AI Cloud ecosystem is expanding across more regions to meet rising global demand for AI computing, including training, inference, agentic AI, and sovereign AI deployments. Partners such as CoreWeave, Firmus, IREN, Nebius, Nscale, and others are adding capacity with NVIDIA accelerated computing, networking, and software, with the ecosystem now spanning six continents.

  • 4Hugging Face Blog·4/15/2026research
    Inside VAKRA: Agent Reasoning, Tool Use, and Failure Modes

    This Hugging Face blog post examines VAKRA, focusing on how agents reason, use tools, and where they fail. It highlights failure modes as a way to better understand the limits and behavior of agentic systems in practice.

  • 7OpenAI Blog·3/25/2026security
    OpenAI launches Safety Bug Bounty program

    OpenAI has introduced a Safety Bug Bounty program to help identify AI abuse and safety risks in its systems. The program will focus on issues such as agentic vulnerabilities, prompt injection, and data exfiltration.

  • 5Hugging Face Blog·1/27/2026research
    Retrospective on Agentic RL Training for GPT-OSS

    Hugging Face published a practical retrospective on unlocking agentic reinforcement learning training for GPT-OSS. The piece focuses on the lessons learned, implementation challenges, and workflow considerations involved in training agentic models with this open-weight model family.