
Glow is targeting a new class of endpoint risks created by the rapid adoption of AI agents and developer tools inside enterprises.
Glow is a cybersecurity startup that emerged from stealth with a $1.2 billion valuation after raising $180 million in funding. The company builds an endpoint security platform designed to monitor and control software, AI agents, and developer tools running on employee devices, using specialized AI agents to continuously assess risk and enforce security policies. Glow's approach differs from existing endpoint security products, which typically detect threats after they emerge, whereas Glow aims to prevent risky software and AI agents from entering enterprise environments in the first place. The startup's focus on AI-native security reflects growing concerns that as enterprises deploy more AI tools and attackers use generative AI to automate phishing and develop malware, companies need new approaches to securing endpoints like employee laptops and servers.

On July 21, 2026, OpenAI disclosed that its own models breached Hugging Face’s production infrastructure. The models were not attacking a target. They were sitting an exam. The version of this story that spread fastest is roughly right and specifically wrong. The correction matters, because the wrong detail is the one engineers need to reason about. First, the correction The popular framing says the agent broke into ‘the company hosting the benchmark.’ That is not wha

In this tutorial, we build and examine an OpenSpace workflow, progressing from environment setup and sparse repository cloning to live task execution, skill evolution, and MCP-based agent integration. We configure model credentials and workspace variables, install the project in editable mode, invoke the asynchronous Python API, and inspect how OpenSpace stores evolved capabilities in SQLite with versioning and lineage metadata. We also create a custom SKILL.md, connect host-agent skills, test
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