Build AI Agents that Never Sleep

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Build an incident-response agent that investigates a simulated service, takes action, waits for human approval, and resumes after failures. Learn how to put the harness in control with durable execution, events, safe retries, and observable state.

Build durable Node.js agents with Inngest, event-driven execution, human approvals, and reliable recovery.
Give an agent a goal, close the tab, and return when it needs you. In this hands-on workshop, you’ll build an incident-response agent that investigates a simulated service, chooses a remediation, waits for approval when required, verifies recovery, and produces an incident report.

Starting with a small agent loop in Node.js and TypeScript, you’ll put the harness in charge of state, action validation, and completion. Then you’ll use Inngest to make execution durable, pause for external events and human decisions, and recover safely from failures. You’ll deliberately restart the agent, duplicate events, and lose tool responses to see what durable execution handles and where application-level safeguards are still needed.

A prebuilt local UI and event simulator keep the focus on the agent and its harness. Each lesson includes live coding, Markdown notes with the exact code changes, and a catch-up break. Everything runs locally with your LLM API key; no deployment is required. By the end of the day, you’ll have a working reference architecture and a clear mental model for when background agents are useful, how they pause and resume, and how to inspect their behavior.

What You Will Master
The Senior Engineer Toolkit

Understand how background execution differs from a chat interface and when an agent needs a durable lifecycle.
Build a Node.js agent harness that observes current state, validates model-selected actions, and verifies completion.
Use Inngest to checkpoint model calls and tool execution so runs can resume after app restarts.
Suspend runs until events, timers, or human decisions arrive, then reassess the current state.
Require approval for disruptive actions and handle rejection, expiry, and changed conditions before execution.
Make retries safe with action idempotency, timeouts, run limits, and cancellation.
Use a local event simulator and Inngest traces to reproduce failures and explain what a run did.
Leave with a working incident-response agent and a reference architecture you can adapt for your own background workflows.
Table of Contents
1 Introduction & Setup
2 Goals and Loop
3 Durable Loop
4 Waiting for Input
5 Human in the Loop