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Example projects using AI agents

Claude changelog generator

Automatically generate professional changelogs from git commits using Claude.

Claude GitHub wiki agent

Generate and maintain GitHub wiki documentation with Claude-powered analysis.

ClickHouse chat agent

Build a chat agent that answers questions about your ClickHouse data with charts, tables and maps using chat.agent() and generative UI.

Human-in-the-loop workflow

Create audio summaries of newspaper articles using a human-in-the-loop workflow built with ReactFlow and Trigger.dev waitpoint tokens.

Mastra agents with memory

Use Mastra to create a weather agent that can collect live weather data and generate clothing recommendations.

OpenAI Agent Python SDK guardrails

Use the OpenAI Agent SDK to create a guardrails system for your AI agents.

OpenAI Agent TypeScript SDK playground

A playground containing 7 AI agents using the OpenAI Agent SDK for TypeScript with Trigger.dev.

Vercel AI SDK deep research agent

Use the Vercel AI SDK to generate comprehensive PDF reports using a deep research agent.

Smart Spreadsheet

Enrich company data using Exa search and Claude with real-time streaming results.

Batch LLM Evaluator

Evaluate multiple LLM models in parallel with the Vercel AI SDK and stream the results to a Next.js frontend using Trigger.dev Realtime.

Claude thinking chatbot

Build a Next.js chatbot that streams Claude’s extended thinking to the frontend with the Vercel AI SDK and Trigger.dev Realtime.

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Chat agents

Build a durable, multi-turn chat agent with chat.agent(). A durable session per conversation, with streaming and resumability handled for you.

Chat agent

Create a durable, multi-turn chat agent with chat.agent(), then add tools to it.

ElevenLabs Voice agent

Build a spoken-conversation voice assistant on chat.agent(), with streaming speech-to-text and text-to-speech from ElevenLabs and server-side voice activity detection.

Ask Trigger chat agent

Build a chat agent that teaches Trigger.dev with interactive node-graphs, quizzes and cards, using chat.agent(), generative UI and live docs grounding through an MCP server.

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Agent fundamentals

These guides will show you how to set up different types of AI agent workflows with Trigger.dev. The examples take inspiration from Anthropic’s blog post on building effective agents.
prompt-chaining

Prompt chaining

Chain prompts together to generate and translate marketing copy automatically
routing

Routing

Send questions to different AI models based on complexity analysis
parallelization

Parallelization

Simultaneously check for inappropriate content while responding to customer inquiries
orchestrator-workers

Orchestrator

Coordinate multiple AI workers to verify news article accuracy
evaluator-optimizer

Evaluator-optimizer

Translate text and automatically improve quality through feedback loops