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This tutorial walks through a scheduled AI agent built with the OpenRouter Agent SDK, using step and cost caps per run, a spend limit on the API key, and approval gates before consequential tool calls. The reported costs ($0.0003 to $0.0012 per check with Claude Haiku 5.5) come from the author's own runs, so they're useful as a rough benchmark rather than a guarantee. For readers building agents, the main takeaways are the bounding and human-in-the-loop patterns, and the file-based memory that keeps per-check cost flat over time.
How to Build Your Own Always-On AI Agent
An always-on AI agent wakes up on a schedule, checks something with tools, and reports or acts without you asking. This tutorial builds one in TypeScript with the OpenRouter Agent SDK that watches Hacker News, remembers what it has seen across restarts, stops any run at five cents, and waits for your approval before it posts.
An always-on AI agent is a program that wakes up on a schedule, uses tools to check on something, decides what matters, and acts or reports without you asking each time. At DevDay 2026, OpenAI announced Dots, its version of always-on agents. You can also build your own, choosing the model, tools, and how much each run can spend. In this tutorial, we build one in TypeScript with the OpenRouter Agent SDK that watches Hacker News for topics you choose, writes a digest of what’s worth reading, remembers what it has already seen across restarts, and stops any run that reaches five cents. Each check costs us between $0.0003 and $0.0012. This same structure works for any agent that should keep running, such as one that watches a repository or a status page, and then takes an action. An always-on AI agent wakes on a schedule, checks something with tools, and reports or acts without being asked each time. This tutorial builds one in TypeScript with our Agent SDK, @openrouter/agent 0.11.0. Each check cost $0.0003 to $0.0012 with Claude Haiku 5.5 in our runs on October 13, 2026, or roughly $0.86 to $3.46 a month at one check every 15…
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