Intelligence-as-Code: How to Deploy an AGI Agent with a Simple API Call

The conversation around artificial intelligence is evolving. We've moved beyond simple chatbots and text generators to the frontier of Agentic AI—autonomous systems that can reason, plan, and execute complex tasks from start to finish. But how do you harness this power without a team of PhDs? The answer lies in a new paradigm: Intelligence as Code.

Welcome to agi.do, the platform designed to turn sophisticated Autonomous General Intelligence (AGI) into a scalable, API-driven service. Forget the complex orchestration and endless prompt engineering. Here, you can build, manage, and scale AI agents that tackle real business problems with a few lines of code.

This is not just about using an AI model; it's about deploying an intelligent workforce.

What is an Autonomous AGI Agent (and Why Isn't it Just an LLM)?

It's a common question: "How is an AGI agent different from a standard large language model (LLM)?" While an agent on agi.do uses powerful LLMs as its core reasoning engine, it is a complete, goal-oriented system.

Think of an LLM as a brilliant but isolated brain. You can ask it questions, and it will give you articulate answers. An agi.do agent, on the other hand, is a full-fledged employee. It has:

• A Clear Objective: A high-level goal it needs to accomplish.
• Memory: The ability to learn from past actions and interactions.
• Planning & Reasoning: It can break down a complex goal into a series of logical steps.
• Tools (Capabilities): It can access and use tools like web browsers, data analysis libraries, and code interpreters to take action in the real world.

In short, an LLM generates text. An AGI agent gets the job done.

Build Intelligence with a Simple API

The philosophy behind agi.do is to abstract away the immense complexity of building agentic systems. We believe deploying autonomous intelligence should be as straightforward as deploying a microservice.

Our SDK provides a clean, developer-friendly interface to define and run sophisticated agents. Let's see how you can deploy a market analysis agent with a simple API call.

How it Works: A Practical Code Example

Imagine you need a comprehensive report on Q3 market trends for renewable energy. Instead of spending days on research, you can deploy an AGI agent to do it for you.

Here's what that looks like in TypeScript:

import { AGI } from "@do/agi";

// Define and deploy an AGI agent for market analysis
const marketAnalyst = new AGI({
  objective: "Analyze Q3 market trends for renewable energy, identify key growth drivers, and generate a summary report.",
  capabilities: [
    AGI.tools.webSearch,
    AGI.tools.dataAnalysis,
    AGI.tools.reportGeneration
  ]
});

// Execute the autonomous workflow
const report = await marketAnalyst.run();

console.log(report.url);
//=> https://storage.do/reports/q3-renewable-energy.pdf

Let's break this down:

1. Define the Objective: You give the agent a high-level goal in plain English. No complex prompting required. The agent understands the intent behind "Analyze... identify... and generate."
2. Assign Capabilities: You grant the agent the tools it needs to succeed. In this case, it can search the web for data, perform data analysis to find trends, and compile its findings into a polished report.
3. Execute the Workflow: With a single command, marketAnalyst.run(), you trigger the autonomous workflow. The agent plans its steps, browses the web, analyzes the data it finds, synthesizes insights, and builds the final report.
4. Get the Result: The agent's output isn't just a block of text; it's a tangible asset—a ready-to-use PDF report, accessible via a URL.

This is "Intelligence as Code" in action. A complex cognitive workflow, encapsulated and executed as a single function call.

What Business Problems Can You Solve with agi.do?

The potential is vast. By turning knowledge-based work into software, you can automate, scale, and innovate across your organization. Here are just a few applications:

• Complex Market Research: Deploy agents to continuously monitor competitors, track industry trends, and produce daily or weekly intelligence briefings.
• Financial Analysis: Create agents that can analyze financial statements, economic indicators, and stock performance to generate investment theses.
• Automated Software Testing: Instruct an agent to test a new feature by simulating user behavior, identifying bugs, and documenting the entire testing process.
• Tier-3 Customer Support: Build agents that can handle complex customer issues from start to finish—diagnosing problems, querying databases, executing solutions, and communicating with the customer.
• Strategic Planning: Run simulations with agents that explore potential business scenarios and predict outcomes based on a given set of variables.

Effortless Integration into Your Existing Systems

An agent is only useful if it can connect to your business. That's why every agent you create on agi.do is instantly accessible via a standard API endpoint.

This means you can easily:

• Trigger autonomous workflows from your web application.
• Integrate AGI into your internal business processes and tools.
• Add intelligent automation to your CI/CD pipelines.

The agent becomes a seamless part of your software stack, a reliable service you can call on to perform intelligent work on demand.

The era of Agentic AI is here. It's time to stop just talking to models and start deploying autonomous intelligence to build the future.

Ready to turn human-level intelligence into a scalable API? Visit agi.do to get started.