October 17, 2026
“Zapier alternatives” is one of the most-typed questions in this category, and the answer depends on which half of the problem you have. Zapier and Make ask: how do I connect app A to app B without writing code? LiveGraph asks: how do I operate agents that are already running? The tools overlap on the word “automation” and diverge almost everywhere else — including the one place this post is about: what each of them lets you change while a run is in flight.
Both are connector catalogs with a pipeline builder on top. A Zap is a trigger followed by actions; a Make scenario is modules wired on a canvas. The value is breadth: thousands of pre-built app connectors, so “new Typeform response → Sheets row → Slack ping” is configuration, not code. Scheduling, filters, and branching paths cover the long tail of commodity automation, and both platforms have earned their reputation on exactly that.
Both now offer AI-assisted building and agent-shaped features too — describe the automation and the platform drafts it. What those modes don't give you is the graph. Once a run starts, the pipeline you published is the pipeline that executes:
For the workloads these tools are built for, that's a fine trade — a form-to- sheet pipeline doesn't need steering. It becomes the whole question when the “pipeline” is a chain of agents working against systems you're responsible for.
LiveGraph is an agent orchestrator whose canvas stays live mid-run. The topology is data — nodes and edges are rows, not a compiled scenario — and the engine dispatches one hop at a time, re-reading the graph fresh after every model call to decide where the run goes next. While a run executes, you can drag an edge to a different agent, wire in a new node, or reroute around a hop that's clearly off-course — and the next hop follows it.
That changes what “editing” means. On the trigger platforms, an edit is a deploy: it takes effect on the next run. In LiveGraph, an edit on a run you're watching is an ops action on this run — as routine as canceling it. Approvals park mid-run instead of aborting it, so a human gate doesn't cost the work already done. And unattended runs (schedules, webhooks, API launches) start pinned — they snapshot the graph at launch and ignore mid-run drags, because a reproducible rerun is what you want when nobody's watching. Steering is the opt-in, not the surprise.
The honest costs, same as the LangGraph comparison: a topology-as-data engine can't validate the whole run up front (there is no whole run yet), and it can't tell you a run's remaining path because the route exists one hop at a time. And LiveGraph is deliberately not a connector catalog — if the job is a library of pre-built SaaS integrations, that's the other tools' home turf.
Pick Zapier or Make when the automation is between apps, not agents. If the job is commodity plumbing — syncing forms to sheets, posting to Slack, updating a CRM field — the connector catalog is the product, and thousands of ready-made integrations beat anything you'd wire by hand. These tools have also made non-technical teams genuinely self-sufficient, which matters more than any feature list.
Pick LiveGraph when you're operating agents, not plumbing. The audience we build for is the founder or small agency already running agents against real systems — a repo, an inbox, a client's stack — who is on the hook when a hop goes to the wrong place. In that world a routing change isn't a republish; it's something you do while watching the canvas, mid-run, because watching is the first half of steering.
Zapier and Make make the next run better. LiveGraph lets you change where this run goes — while the model is still thinking. If that capability is the one you keep reaching for, watch it work — the demo reroutes a live run with a scripted model, no account and no API key.