In the world of software development, automation is king. We write scripts to deploy code, configure pipelines for CI/CD, and build services to handle routine tasks. But as our systems grow in complexity, traditional automation often hits a wall. Rigid scripts become brittle, orchestrating multiple microservices turns into a tangled mess, and scaling on-demand can feel like a feat of black magic.
What if there was a better way? A more intelligent, flexible, and scalable approach to automation.
Enter agentic workflows. This paradigm is revolutionizing how we think about everything from complex data pipelines to intricate business logic. In this guide, we'll dive into what agentic workflows are, why they're so powerful, and how you can build your first one using a simple API.
Before we look forward, let's glance back. Traditional workflow automation often involves:
These approaches lack the resilience and scalability needed for modern, high-throughput applications.
An agentic workflow reframes automation by breaking processes down into independent, intelligent "agents" that are managed by a central "orchestrator".
This is the core of what we've built at processing.services.do. You define your business logic as containerized agents, and our platform acts as the powerful, scalable orchestrator.
The beauty of the agentic model is that it transforms incredibly complex back-end processes into simple, scalable API calls. Instead of building and maintaining a fragile web of services and scripts, you simply tell the orchestrator what you want to achieve.
Let's look at a practical example. Say you want to enrich a new user profile with data from multiple sources. With processing.services.do, you can trigger this complex, multi-step workflow with a few lines of code.
import { Do } from '@do-sdk/core';
const processing = new Do('processing.services.do', {
apiKey: 'your-api-key',
});
// Define and run a data enrichment workflow
const job = await processing.run({
workflow: 'enrich-user-profile',
payload: {
userId: 'usr_12345',
sources: ['clearbit', 'linkedin', 'internal_db'],
},
config: {
priority: 'high',
onComplete: 'https://myservice.com/webhook/job-done',
}
});
console.log(`Job started with ID: ${job.id}`);
Let's break down what’s happening here:
Behind this simple API call, the platform is automatically scaling compute resources, running agents in parallel where possible, handling transient errors, and managing the entire lifecycle of the job.
This approach offers several game-changing benefits for developers:
Agentic workflows are more than just a new buzzword; they represent a fundamental shift toward more resilient, scalable, and intelligent system design. By separating the "what" from the "how," they empower developers to focus on creating value, not on managing infrastructure.
Ready to transform your complex data and workflow processing? Sign up at processing.services.do and build your first agentic workflow in minutes.
You can run virtually any custom logic. Common use cases include data transformation (ETL), batch processing, image/video rendering, financial calculations, and orchestrating sequences of microservice calls. If you can code it, we can process it.
You define your business logic as containerized agents. processing.services.do acts as the orchestrator, invoking your agents with the provided payload and managing the execution state, scalability, and error handling for you.
Yes. Our platform is engineered for high-throughput, parallel processing. It automatically scales compute resources based on your workload, ensuring your jobs are completed efficiently, whether you're running one task or a million.
Absolutely. The platform is designed for both synchronous (quick) and asynchronous (long-running) jobs. For long jobs, you can provide a webhook URL to be notified upon completion, allowing you to build robust, event-driven systems.