Autonomous AI Agents

AI Agent Developer Building Custom AI Agents That Take Action

A chatbot answers questions. An AI agent does something with the answer — looks up a record, qualifies a lead, sends a follow-up, updates a system — without a human driving every step. As an AI agent developer, I build custom AI agents for business using LLM function calling and tool use, so the agent can take real, multi-step action inside your existing systems, not just hold a conversation.

This is autonomous AI agent development grounded in production use: agents that read context, make a decision, and act on it — the same architecture behind the calling agent case study below.

Case Study

AI Calling Agent — Agent Architecture in Production

Problem

A simple scripted phone bot can't qualify a lead — it can only follow a fixed decision tree and hand off anything unexpected.

Solution

Built an AI agent using OpenAI function calling that holds a real conversation, autonomously looks up and updates caller records, decides whether a lead qualifies, and triggers an SMS follow-up — all without a human in the loop for the standard case.

29,600+ records processed autonomously356 leads qualified without manual reviewAutomatic SMS follow-up triggered by agent decisions
OpenAI Function CallingDjango REST FrameworkTwilioElevenLabs

Who This Is For

Built for Businesses Like Yours

Law Firms

Agents that qualify intake calls and route or escalate cases based on what the caller actually says.

Roofing & Home Services

Agents that capture a lead, check availability, and trigger the next step without manual handling.

Real Estate

Agents that qualify buyer/renter inquiries and update your CRM automatically.

Restaurants

Agents that manage reservation logic end-to-end — check, confirm, and follow up.

Common Questions

Frequently Asked Questions

What is an AI agent and how is it different from a chatbot?

A chatbot's job is conversation — answering questions in a chat window. An AI agent can take action: querying a database, updating a record, triggering a message, or deciding what to do next, using tool/function calling rather than just generating text.

Can an AI agent take actions, not just answer questions?

Yes — that's the defining feature. The calling agent case study above autonomously looks up records, qualifies leads, and triggers SMS follow-up as part of the conversation, not as a separate manual step afterward.

What tools or systems can an AI agent connect to?

In production, I've connected agents to telephony (Twilio), SMS, CRMs, and internal databases via REST APIs. Generally, if a system has an API, an agent can be built to use it.

Is agent development more expensive than a simple chatbot?

Usually yes, since it involves more backend logic, integrations, and testing around the actions the agent can take — but it also replaces more manual work. I'll scope it against what you're trying to automate.

How do you prevent an AI agent from making mistakes?

By scoping what the agent is allowed to do tightly, adding fallback/escalation paths for anything outside that scope, and logging every action so decisions are traceable — the same approach used in the production calling agent above.

Have a project like this?

Tell me what you're trying to build or automate — I typically reply within a day.