Question 1

What is the difference between an Agent and a Chatbot?

Accepted Answer

A chatbot waits for your prompt, replies with text, and stops. An Agent receives a goal, creates a plan, uses tools (like browsing the web or querying a database), evaluates its own progress, and takes multiple independent actions to achieve the goal before returning to you.

Question 2

Can the agent perform dangerous actions by mistake?

Accepted Answer

Safety is our priority. We design agents with strict RBAC (Role-Based Access Control) and Read-Only permissions where possible. For actions that change state (e.g., sending an email to a client, deleting a file, making a purchase), we enforce a hard 'Human-in-the-Loop' pause where the agent drafts the action and waits for your explicit approval.

Question 3

What are Multi-Agent Systems?

Accepted Answer

Instead of one 'super' agent trying to do everything, Multi-Agent systems use a team of specialized agents. For example, a 'Researcher Agent' gathers data, hands it to an 'Analyst Agent' who processes it, who then gives it to a 'Writer Agent' to draft the report. This greatly improves accuracy and reduces hallucinations.

Question 4

What tools can the AI use?

Accepted Answer

We can build tools for almost anything with an API. Common tools include Web Browsers (Playwright), Search Engines (Tavily/Google), Code Interpreters (Python sandboxes for data analysis), CRM platforms (Salesforce), and your own internal databases.

Question 5

Do agents hallucinate more than normal LLMs?

Accepted Answer

Agents can get confused or stuck in loops, but their tool use actually reduces factual hallucinations. Instead of guessing a fact, an agent is instructed to use its 'Search Web' tool to find the exact truth before answering.

Question 6

How do you handle an agent getting stuck in an infinite loop?

Accepted Answer

We use state-graph frameworks like LangGraph, which allow us to set strict boundaries. We implement 'Max Iteration' limits and timeout protocols. If an agent tries the same tool 3 times and fails, the system forces it to stop and ask a human for help.

Question 7

Are these agents expensive to run?

Accepted Answer

Agents consume more API tokens than standard chatbots because they 'think' and make multiple tool calls behind the scenes. We optimize costs by using cheaper models (like GPT-4o-mini or Llama 3) for basic tool routing, and only calling expensive models for complex reasoning tasks.

Question 8

How long does it take to build a custom agent?

Accepted Answer

A simple agent with access to 2-3 basic tools (like web search and a simple API) takes about 3-4 weeks. Complex multi-agent workflows with memory, secure sandboxes, and custom integrations typically take 8-12 weeks.

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