AI Agent vs Workflow Builder: Talk to It or Draw It?
Manus and Burrak take a goal in plain English; Lindy and n8n run a workflow you can see. What each is good at, where each breaks, and how to choose.
There are two ways to build an AI agent today, and they are less interchangeable than the marketing suggests.
You talk to it. You describe the job in plain English — "every morning, research the new leads in my sheet and draft a first message for each" — and the agent works out the steps, the tools and the order. Manus works this way. So does Burrak.
You draw it. You build the workflow on a canvas: trigger → node → condition → action. Every step is spelled out, and the run follows the drawing. Lindy and n8n work this way.
We build Burrak, so we are biased. This is the honest scorecard anyway, including the parts where the other camp is simply the better tool.
The line moved in 2026 — but not where you would think
A year ago the difference was obvious from the first screen: a chat box or a canvas. That is no longer a reliable tell.
- The builders added a chat box. n8n's AI Workflow Builder takes a plain-English description and drafts the node graph for you. Lindy's Agent Builder does the same, then opens the result in its Flow Editor to refine.
- The agents added schedules. Manus shipped recurring scheduled tasks in May 2026 and event triggers from email, Slack and Notion with Manus 2.0. Burrak agents have run on schedules from the start.
So "do I have to drag boxes?" is the wrong question now. The right one is what actually runs when the job fires: a fixed diagram that a model helped you draw, or an agent that decides the next step at run time, every time.
Conversational agents: what you get, and what it costs
✅ Set up in minutes, with no technical knowledge. The setup is a paragraph. If you can explain the job to a new colleague, you can explain it to the agent. There are no triggers to configure, no field mappings, no branches to anticipate.
✅ Good at messy, open-ended work. Research, writing and judgement calls are exactly the jobs where you cannot draw every branch. "Find out what this company does and whether they are worth a message" has a hundred paths depending on what the website says. An agent takes whichever one the evidence points to.
✅ You change it by saying so. "Also skip companies under ten people" is one sentence. In a flow builder it is a new condition node, a data field you may not have, and a re-test of everything downstream.
⚠️ Less predictable. The same task can take a slightly different path on each run. Most of the time that is the point — it adapted — but it also means you cannot promise that run 300 behaves exactly like run 1.
⚠️ Harder to check at a glance. You review outputs and run logs, not a diagram. That is a real cost when something looks wrong and you need to know why. It is why every Burrak run keeps a transcript of what the agent did, and why scheduled tasks can be set to check their own result against the brief before they report success — the subject of our piece on what breaks when nobody is watching.
⚠️ Cost varies with the thinking. An agent pays for its reasoning. A five-minute research task costs more than a two-step lookup, and the same brief can cost more on a day the inputs are messy. Manus, Lindy and Burrak all bill in credits for this reason; the honest ones show you what each run used.
Visual flow builders: what you get, and what it costs
✅ Does exactly what the diagram says, every time. For a process that must not vary — routing an invoice, copying a form submission to the CRM — that is the whole requirement, and nothing beats it.
✅ Easy to audit, hand over and debug. A teammate can read the canvas. When step four fails, you open step four. Compliance teams like workflows for the same reason engineers like tests: the behaviour is written down.
✅ Great for high-volume, rule-based plumbing. Form → CRM → Slack, ten thousand times a month, at a predictable cost per execution. n8n's self-hosted edition will do that on your own server for the price of the server.
⚠️ Setup takes longer. Even with an AI drafting the first version, someone has to read the graph, fix the field mappings and think in triggers and branches. That person is usually the bottleneck.
⚠️ Breaks on the edge cases nobody drew. The lead with no website. The email in Portuguese. The invoice with two currencies. A diagram handles what its author imagined; everything else is an error branch or, worse, a silent pass-through.
⚠️ The "AI" is often one node. Many "AI workflows" are a fixed pipeline with a model call in the middle — summarise this, classify that. That is useful, but it is not an agent: the model is filling in a blank, not deciding what to do next.
Where the four products actually sit
| Burrak | Manus | Lindy | n8n | |
|---|---|---|---|---|
| How you set it up | Describe the job | Describe the job | Describe it, then edit a flow | Draw a graph (AI can draft it on Cloud) |
| What runs | An agent that plans each run | An agent that plans each run | A flow with agent steps inside | A fixed workflow with AI nodes |
| Recurring work | Scheduled tasks | Scheduled tasks and event triggers | Triggers on email, chat, forms and more | Triggers on almost anything |
| Where it runs | Cloud, or an agent on your own machine | Cloud VM | Cloud | Cloud, or your own server |
| Integrations | 90 connectors, plus Zapier | MCP and native connectors | Thousands | Hundreds of nodes |
| Billing | Credits for work performed | Credits per task | Credits per task | Per execution, or self-hosted |
Two rows here are wins for the other side, and they matter. Lindy and n8n reach far more apps than we do. And n8n is the only one of the four you can read, modify and run entirely on your own hardware. The full, sourced breakdowns are on our comparison pages for Manus, Lindy and n8n.
The rule of thumb
If you can draw the process on a whiteboard and it never changes, use a flow builder. You will get something cheaper, more predictable and easier to hand over than any agent.
If the hard part is judgement — what to research, what to write, what to do when something unexpected shows up — describe it to an agent. Drawing it would mean drawing every exception, and you will not think of them all.
Five questions settle most cases:
- Could you write the steps down today, in order, without "it depends"? Yes → flow builder.
- Does the input vary in shape — free text, websites, documents, people? Yes → agent.
- Does a wrong path cost more than a slow one? Money moving, records being deleted → flow builder, or an agent that only drafts.
- Will this run thousands of times a month? Volume favours a flow's flat cost per execution.
- Who maintains it? No one technical → agent. An operations engineer → either.
Most teams end up needing both
The useful split is not between products but inside the job. The plumbing — the form submission landing in the CRM — is a flow. The judgement step — researching that lead and writing the first message — is agent work.
You can wire the two together. A Burrak agent can call actions you have already set up in Zapier through the Zapier connector, so the fixed, audited part stays in the tool built for it and the agent does the part that needed a person.
A few limits on our side, so this stays an honest scorecard. Burrak's remote agents have a time budget per run, so a job that needs an hour of continuous work has to be split into steps. They have no shell in the cloud — code runs on a local agent on your own machine, not in a hosted VM the way Manus's do. And with fewer connectors than Lindy or n8n, a long-tail app may only be reachable through Zapier.
The real question is not which camp is better. It is which one handles the work that keeps you up at night. If that work is a pipeline, draw it. If it is a judgement call you make fifty times a week, describe it once and let an agent make it.