A deep-dive into the shell injection vulnerability found in MCP server implementations, what it reveals about securing agent environments, and how Neumar approaches safe MCP server management.
Research on CoAct and hierarchical agent systems demonstrates consistent capability gains over single-model approaches. Here is what the architecture looks like in practice.
A Fortune 500 manufacturing company achieved a 300% velocity increase in software maintenance by deploying AI agents across their development workflow. A detailed look at what they built and how it actually works.
A timeline of Anthropic's product releases and how the Claude Agent SDK became the foundation for production-grade AI agent development. What changed, what stayed the same, and what it means for teams building on Claude.
A practical, no-hype comparison of the leading AI coding tools in 2026 — what each does well, where each falls short, and how desktop agents like Neumar complement rather than compete with IDE integrations.
AI companies are trading at revenue multiples that would have seemed absurd in the SaaS era. Understanding what drives these premiums — and what can deflate them — is essential for anyone thinking seriously about the AI market.
METR research shows AI agents can autonomously handle tasks of double the duration every 7 months. We break down what that trajectory means for desktop agent applications like Neumar.
