Question 1

What is the difference between an LLM and an AI Agent?

Accepted Answer

An LLM generates text. An AI agent can take actions. An agent uses an LLM as its 'brain' to decide which software tools to use to accomplish a goal.

Question 2

Is it safe to let AI take actions in our systems?

Accepted Answer

Yes, because we enforce strict permissions. We never give agents destructive access (like 'drop table') unless explicitly required, and we use human-in-the-loop approval for sensitive actions.

Question 3

How does a supervisor agent work?

Accepted Answer

A supervisor agent acts like a manager. You give it a massive goal (e.g. 'Write a research report'). It breaks the goal down and delegates pieces to a researcher agent, a writer agent, and an editor agent.

Question 4

What happens if the agent gets stuck in a loop?

Accepted Answer

We hardcode maximum iteration limits (e.g. max 5 tool calls). If an agent cannot solve a problem within the limit, it gracefully fails and escalates to a human.

Question 5

Do we need a custom interface to interact with the agent?

Accepted Answer

We typically deploy agents directly where you already work — as Slack bots, GitHub apps, or background jobs triggered by webhooks.

Question 6

How long does it take to build a custom agent?

Accepted Answer

A single-task specialized agent can be built in 2-3 weeks. A multi-agent supervisor framework takes 4-8 weeks depending on the complexity of the tools.

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AgentArchitecture.

DeploymentResults.

What WeDeliver.

// FAQ

Let's buildyour autonomousworkflow.

Agent
Architecture.

Deployment
Results.

What We
Deliver.

Let's build
your autonomous
workflow.