Which workflows are worth a team of agents.
Every post starts from a workflow: what goes in, which agent handles which part, and where the approach stops paying for itself.
One workflow, start to finish.
A scenario walked through end to end, with a runnable example you can open alongside the article.
Support Tickets: A Fixed Pipeline and a Routed Agent Team
Keep the high-volume path on a typed classify → draft → QA graph, let escalations get a coordinator-built team, and put the refund behind a confirmation gate the runtime enforces per call.
Competitive Monitoring: Isolate Each Source Before Comparing Them
One agent per source, structured claims out of each, and an aggregator that reads validated records instead of prose — so contradictions between a vendor post, a community thread, and a news article survive to the report.
Incident Postmortems: Parallel Investigation, Serial Judgment
Logs, deployments, and blast radius are independent evidence streams. A runTasks() DAG starts them together, keeps each result unmerged in taskResults, and hands the analyst validated structured payloads instead of prose.
Translation Drift: Route the Back-Translation to Another Model
Translate with one provider, back-translate with another through a model-routing rule, and let a reviewer return structured drift findings — then measure the reviewer itself with a versioned EvalSet.
From Transcript to Typed Action Items: Three Parallel Agents in TypeScript
Most meeting summarizers cram summary, action items, and sentiment into one LLM prompt. Here's a cleaner TypeScript shape: three specialist agents run in parallel, two return typed Zod output, and an aggregator merges them into one report.
Give Your TypeScript AI Agents Long-Term Memory with TencentDB-Agent-Memory
Wiring open-multi-agent's MemoryStore to TencentDB-Agent-Memory through its Hermes Gateway: a measured cross-run memory loop, and two upstream gotchas that decide whether anything gets stored.
Adding Multi-Agent Orchestration to a Vercel AI SDK App
A multi-agent orchestration layer for the Vercel AI SDK: open-multi-agent's runTeam() plans and runs the agents, the AI SDK streams the result to the browser.
What it looks like once it runs.
What the tokens cost, where it slowed down, what got in the way — and the boundaries that only surface after enough runs.
Five Seams That Decide Whether a Workflow Needs a Team
Across OMA's runnable recipes the same five boundaries keep reappearing — and each one turns out to have a specific runtime mechanism behind it, from structured dependency payloads to an execution routing decision you can read back.
A 100% Local Multi-Agent Team in TypeScript (Ollama + Gemma, $0 API Cost)
Run a multi-agent team fully on your laptop in TypeScript — even the coordinator is a 5B Gemma over Ollama, at $0 API cost. With a real per-agent ledger, honest friction, and a hybrid cloud+local variant.
5 walls multi-agent frameworks hit: receipts from Mastra's year of .network() to Supervisor migration
Mastra spent a year migrating .network() to the Supervisor pattern. 5 engineering walls hit (context, routing, observability, nesting, performance), 18 GitHub issues as receipts. What it means for TypeScript multi-agent framework development.
How to Run a Mixed-Model AI Agent Team in TypeScript?
A practical walkthrough from a single-model team baseline to a mixed-provider production setup with live cost and latency monitoring, using open-multi-agent, the TypeScript-ecosystem answer to CrewAI.
Which framework fits which workflow.
Comparisons that cite their sources and say who each option suits, including the workflows where open-multi-agent is the wrong tool.
6 Best TypeScript Multi-Agent Frameworks 2026 (Trade-offs)
LangGraph, Mastra, Vercel AI SDK, OpenAI Agents, AgentKit, Open Multi-Agent: which TypeScript multi-agent framework fits the workflow you own?
Multi-Agent AI in a TypeScript Service, No Python Sidecar
Three agents behind one Express route, in the Node process you deploy: per-agent model tiers, validated JSON handoffs, a token ceiling, and an egress policy.
Goal-Driven Agent Orchestration vs Explicit Graphs: A TypeScript Framework Taxonomy
Most multi-agent framework reviews compare features. This post compares a different axis: where the framework places the decomposition cost. Goal-first frameworks pay it at runtime in tokens; graph-first frameworks pay it at design time in code.
How the runtime works, and what changed.
Mechanism walkthroughs and what shipped in each version.
Open Multi-Agent v1.14: Repair the Plan, Keep the Record
ReleaseOpen Multi-Agent v1.13: Route, Govern, Schedule, and Prove the Run
ReleaseOpen Multi-Agent v1.12.1: Evaluation, Offline Inspection, and a No-Key First Run
EngineeringGoal In, DAG Out: How Open-Multi-Agent Turns a Goal into a Task DAG
Taking this to production?
open-multi-agent is MIT-licensed and free to run yourself. When you need it delivered, integrated, or supported on a deadline, 元定义科技 (YuanASI) offers commercial delivery and support.