Building Reusable AI Functions with Lexi: From Single-Task to Super-Agent

The promise of AI has long been to create intelligent assistants that don't just answer questions, but get things done. We're moving beyond the era of simple chatbots and into the age of autonomous agents—digital workers capable of tackling complex, multi-step projects. At the forefront of this revolution is lexi.do, an autonomous AI agent designed to execute intricate business workflows with a single command.

But the true power of an agent like Lexi isn't just in one-off tasks. It's in building a reliable, scalable system of intelligence. This post will guide you on the journey from delegating a single task to Lexi to creating a powerful library of reusable AI functions—transforming Lexi into your own custom-built super-agent.

The Power of a Single Command

Before we build, let's understand the foundation. Lexi isn't just a large language model; it's an agent. When you give Lexi a goal, it intelligently breaks it down into a sequence of tasks, utilizes the necessary tools, and works autonomously until the objective is complete. It truly functions as a service-as-software, delivered via a simple API.

Imagine you need a complete market analysis for a new product idea. Instead of spending days on research, you can delegate the entire project to Lexi with a simple API call.

import { lexi } from '@do/sdk';

// Give Lexi a complex, multi-step task
const marketAnalysisReport = await lexi.do({
  task: "Perform a comprehensive market analysis for a new AI-powered email client.",
  objectives: [
    "Identify top 5 competitors and their market share.",
    "Analyze current market trends and user sentiment.",
    "Suggest a target audience and key messaging points."
  ],
  format: "markdown"
});

console.log(marketAnalysisReport);

In this single call, you're not just asking a question. You're commissioning a complete piece of work. Lexi understands the high-level task and uses the objectives as a guide to structure its autonomous agentic workflow, finally delivering a formatted markdown report. This is the magic of delegating to an autonomous worker.

From One-Off Task to Reusable AI Function

The example above is incredibly powerful for an ad-hoc request. But what happens when market analysis becomes a core part of your product development cycle? What if you need to run this analysis every month, or for every new feature you're considering?

Copying and pasting this code block is inefficient and not scalable. The real enterprise-grade solution is to abstract this powerful capability into a reusable function within your own codebase.

Let’s refactor the previous example into a dedicated, reusable "AI function."

import { lexi } from '@do/sdk';

/**
 * A reusable AI function, powered by Lexi, to generate
 * a comprehensive market analysis report for any product idea.
 * @param productIdea - The product concept to be analyzed.
 * @returns A promise that resolves to a markdown report.
 */
async function generateMarketAnalysis(productIdea: string): Promise<string> {
  console.log(`[Lexi] Starting market analysis for: ${productIdea}`);

  const report = await lexi.do({
    task: `Perform a comprehensive market analysis for a new ${productIdea}.`,
    objectives: [
      "Identify top 5 competitors and their market share.",
      "Analyze current market trends and user sentiment.",
      "Suggest a target audience and key messaging points."
    ],
    format: "markdown"
  });

  console.log(`[Lexi] Market analysis for ${productIdea} complete.`);
  return report as string;
}

// Now, you can perform complex business automation with a simple function call!
const emailClientReport = await generateMarketAnalysis("AI-powered email client");
const crmReport = await generateMarketAnalysis("CRM for small freelance photographers");

By wrapping the lexi.do call in a typed function, you gain several key advantages:

Reusability: Call generateMarketAnalysis() anywhere in your application, just like any other function.
Abstraction: Your team members don't need to be prompt engineering experts. They can use this powerful AI capability without knowing the underlying implementation details.
Maintainability: If you want to refine the analysis objectives, you only need to update them in one central place.
Consistency: Every market analysis report will now follow the same structure and meet the same quality bar, ensuring consistent outputs across your organization.

Assembling Your Super-Agent

Now, expand this concept. A single reusable function is useful, but a library of them is transformative. You can create a suite of AI functions tailored to your specific business needs, effectively building your own specialized super-agent on top of Lexi's generalist platform.

Imagine an internal SDK for your company: company.ai.ts

// Your company's internal AI library, powered by lexi.do

// Generates a market analysis report
export async function generateMarketAnalysis(productIdea: string): Promise<string> {
  // ... Lexi implementation
}

// Drafts a social media campaign schedule
export async function createSocialCampaign(topic: string, platform: 'twitter' | 'linkedin'): Promise<string> {
  // ... Lexi implementation
}

// Analyzes customer feedback from raw text data
export async function analyzeCustomerFeedback(feedbackData: string): Promise<any> {
  // ... Lexi implementation returning structured JSON
}

// Drafts a complete business plan
export async function draftBusinessPlan(idea: string, targetMarket: string): Promise<string> {
  // ... Lexi implementation
}

With this library in place, you’ve achieved business automation at a whole new level. You have created a digital worker with a defined set of skills, ready to be integrated into any application, workflow, or internal tool.

You can even chain these functions together. Use the generateMarketAnalysis output to inform the draftBusinessPlan function, creating a fully autonomous workflow from idea to execution plan. This is the essence of building a true super-agent.

The Future is Functional

Lexi.do provides the engine for autonomous work. By structuring your interactions with it as clean, reusable functions, you move from one-time AI magic to a systematic, scalable AI strategy. You build a durable competitive advantage by embedding bespoke intelligence directly into the fabric of your operations.

Stop thinking in terms of single prompts and start building a library of AI functions. This is how you unlock the full potential of autonomous agents and build the future of your business.