I built an open-source orchestration engine for multi-agent AI – Fulcrum

yasir — Sun, 22 Mar 2026 17:50:20 +0000

Been thinking about the same problem everyone building multi-agent systems runs into: you spend more time writing routing logic, retry handlers, and state management than actually building agents.

So I built Fulcrum — a TypeScript library that handles the plumbing:

Task decomposition via LLM (splits your task into parallel subtasks automatically)
Agent routing by capability type (researcher, writer, analyst, coder, etc.)
Parallel execution with dependency graphs (tasks that don't depend on each other run concurrently)
Automatic retry with exponential backoff
SQLite persistence so state survives process restarts

Works with Anthropic and OpenAI out of the box:

import { Fulcrum, createAnthropicAgents, createAnthropicDecomposer } from '@fulcrumhq/core'

const orchestrator = new Fulcrum({
  agents: createAnthropicAgents({ apiKey: process.env.ANTHROPIC_API_KEY }),
  decompose: createAnthropicDecomposer({ apiKey: process.env.ANTHROPIC_API_KEY }),
})

const result = await orchestrator.run(
  'Research our top 3 competitors and draft a positioning doc'
)

console.log(result.summary)

npm install @fulcrumhq/core

GitHub: https://github.com/hashegsethbeenfired-web/fulcrum

Would genuinely love feedback from anyone building multi-agent pipelines. What's the biggest pain point you hit that this doesn't solve?

DEV Community: yasir

I built an open-source orchestration engine for multi-agent AI – Fulcrum