Ai-Agents

Most tutorials about AI agents end with something that produces output. This one is about something different: an agent that produces income. Developer Eliott Reich documented how they built an AI agent that earns real money — not through speculation, not through selling the agent itself, but through autonomous task completion that generates actual revenue. Here’s a breakdown of how the system works and how you can build one. The Core Concept: Agents as Economic Actors The insight behind a money-earning agent is simple but consequential: if an agent can complete tasks that have economic value, and if those tasks can be reliably discovered and delivered, then the agent earns money as a byproduct of working. ...

A landmark empirical study from the UK’s AI Security Institute — co-authored with the Bank of England — has just published the most rigorous large-scale measurement of AI agent behavior to date. The paper, titled “How are AI agents used? Evidence from 177,000 MCP tools,” analyzed 177,436 Model Context Protocol (MCP) tools created between November 2024 and February 2026. The headline finding: AI agents have decisively crossed from observation to action, and the enterprise security community is not keeping pace. ...

Here’s a number worth sitting with: in any given business function at any given company, fewer than 10% of respondents say their organization is actually scaling AI agents. That’s the finding from McKinsey’s latest “Week in Charts” dataset — one of the more reliable pulse-checks on enterprise technology adoption because it pulls from real organizational survey data rather than vendor-funded enthusiasm. The conclusion is stark: the gap between the AI agent hype cycle and the ground truth of enterprise deployment is enormous. ...

When enterprise security vendors start building products specifically for your platform, you’ve crossed a threshold. OpenClaw has crossed it. Airia — an Atlanta-based enterprise AI management platform — announced on March 20th that its AI Gateway now provides enterprise-grade security capabilities specifically designed for OpenClaw deployments. The press release explicitly references OpenClaw’s heritage as “Clawdbot” and “Moltbot,” a hat-tip to the platform’s lineage that signals Airia has been watching this space closely. ...

Every AI agent pipeline eventually hits the same wall: documents. PDFs, Word files, scanned images, slide decks — agents need to read them all. Most solutions are either painfully slow, require an external API (and cloud costs), or demand a GPU just to process a 40-page report. LlamaIndex founder Jerry Liu announced LiteParse on X on March 19th, calling it “unglamorous but critical” infrastructure. He wasn’t wrong. LiteParse processes 500 pages in 2 seconds on CPU. No GPU. No API key. No cloud. ...

WordPress.com just crossed a significant line in the AI agent story: your AI agent can now not just read your site — it can run it. Automattic announced today that WordPress.com’s MCP (Model Context Protocol) integration now includes write capabilities, giving AI agents like Claude Desktop, ChatGPT, Cursor, and OpenClaw the ability to create posts, build pages, and manage site content through natural conversation. No new software to install — just enable the new tools in your MCP dashboard. ...

The infrastructure for autonomous AI agent commerce just got its first open standard. On March 18, 2026, Tempo — the payments blockchain incubated by Stripe and Paradigm — launched its mainnet alongside the Machine Payments Protocol (MPP): a co-authored open specification with Stripe that enables AI agents to transact independently, without human approval in the loop. This is a landmark moment for agentic AI. Until now, agents that needed to pay for services, buy compute, or execute purchases on your behalf faced a messy patchwork of workarounds — stored credentials, simulated user sessions, or blocking waits for human authorization. MPP is the industry’s first serious attempt at a unified, open standard for agent-to-agent and agent-to-service payments. ...

Alibaba dropped Wukong on Tuesday — and China’s enterprise AI agent race just got a lot more interesting. Named after the Monkey King from the classic Chinese novel Journey to the West, Wukong is Alibaba’s entry into the enterprise AI agent arena. It’s a Qwen-powered platform that lets businesses manage multiple AI agents through a single interface, with what Alibaba calls “enterprise-grade security infrastructure.” And it arrives at a pivotal moment: the company is mid-reorganization, competition from Tencent and Zhipu AI is heating up, and the broader OpenClaw wave is reshaping how China’s tech giants think about autonomous software. ...

While most of the world debates how to regulate AI, Hong Kong is moving to govern AI agents specifically — and doing so with a conceptual framework that doesn’t exist anywhere else yet. The Hong Kong Generative AI Research and Development Centre (HKGAI), a government-backed institute, announced plans Monday to launch what it’s calling the world’s first governed AI agent network. The defining concept: every AI agent operating within the network will be assigned a distinct “social identity” and bound by defined operational limits. ...

ServiceNow CEO Bill McDermott didn’t mince words on CNBC last week. Asked about the impact of AI agents on the workforce, he said graduate unemployment “could easily go into the mid-30s in the next couple of years.” That’s a striking statement from the head of a $200 billion enterprise software company that sells AI-powered automation to the same enterprises that hire those graduates. It’s also, increasingly, not a fringe view. ...