One Agent Is a Cook. Five Agents Are a Restaurant.

A single cook can make momo.

A wedding needs a kitchen team.

Same with AI.

The wedding kitchen

Have you ever seen the kitchen at a Nepali wedding?

One group is folding momo.

Another is frying sel roti.

Someone is managing the giant pot of tea.

Someone else is checking what goes out and when.

Nobody is doing everything.

That's why 500 guests get fed.

If one cook tried to do it alone, the guests would still be waiting for tea next Tuesday.

Multi-agent flows work the same way

One AI agent trying to do a big job can lose focus.

It researches, writes, reviews, and tests in one long session, and quality slips as the context grows.

A multi-agent flow splits the work:

• One agent gathers information
• One agent builds
• One agent reviews
• One agent tests

Each one has a single job.

Each one does it better.

Tools like Cursor and Grok Bot both support working with several agents in parallel in their own way.

How to brief the kitchen

Bad:
Build the new checkout feature.
 
Good:
Agent 1: Find how existing payment flows are
structured in the codebase and summarise the pattern.
Agent 2: Using that summary, implement checkout.
Agent 3: Review the changes for edge cases
and security issues.
I'll review the final result.

Notice the last line.

There's still a head chef.

You.

When not to bother

A team is overkill for a cup of tea.

For small, clear tasks, one agent is perfect.

Multi-agent flows shine when:

• The job has clear stages
• Research and building are separate
• A second opinion matters

Final thoughts

One cook can make momo.

But when 500 guests are coming, you don't hire a faster cook.

You organise a kitchen.

That's what multi-agent flows really are.

Not smarter AI.

Better organisation.