Declarative vs. Imperative: Why Agentic Workflows are a Superior Model

In the world of software development, we constantly grapple with complexity. We build abstractions, create frameworks, and adopt new paradigms—all in the service of managing that complexity. One of the most fundamental distinctions in how we instruct our machines is the difference between imperative and declarative programming.

For years, automating business operations has been stuck in the imperative world: brittle, hard-to-maintain scripts that detail every single step. But a new paradigm is emerging. By embracing a declarative model through Agentic Workflows, we can build more robust, scalable, and understandable systems.

This isn't just a theoretical shift; it's a practical evolution that platforms like devs.do are turning into a reality for developers.

The Old Way: The Chains of Imperative Automation

Think about the last time you had to automate a multi-step business process. Maybe it was a user onboarding sequence, a data processing pipeline, or a code quality check. Your first instinct was likely to write a script—in Python, Bash, or Node.js.

This is the imperative approach: you provide explicit, step-by-step instructions.

1. Call API A, get a token.
2. If the token is valid, use it to call API B.
3. Parse the JSON from API B.
4. Loop through the results array.
5. For each item, perform a transformation.
6. Handle potential TypeError if a field is missing.
7. Post the transformed data to API C.
8. Log the result of each step to a file.
9. Implement a retry mechanism if API C is down.

While this works, it's fraught with peril. This imperative code defines how to do the task, and the business logic—the what—is lost in a sea of boilerplate, error handling, and low-level commands. This model is:

• Brittle: A small change in an API response can break your entire script.
• Hard to Read: New developers have to decipher hundreds of lines of code just to understand the workflow's intent.
• Difficult to Scale: Orchestrating, logging, and managing the state of many such scripts is an operational nightmare.

A Paradigm Shift: The Power of Declarative Thinking

Now, consider the declarative approach. Instead of detailing the how, you simply describe the what—the desired end state. The underlying system is responsible for figuring out the most effective way to achieve it.

You already use this model every day:

• SQL: SELECT name FROM users WHERE status = 'active'; You declare what data you want, not how the database engine should scan indexes and retrieve it.
• React: <h1>Hello, {name}</h1> You declare what the UI should look like for a given state, and React handles the complex DOM manipulations.
• Infrastructure-as-Code (IaC): You declare the desired state of your cloud infrastructure, and tools like Terraform make it so.

The declarative model is powerful because it abstracts away implementation details, leading to code that is more readable, maintainable, and less prone to bugs.

Enter Agentic Workflows: Declarative Business Logic on devs.do

So, how do we apply this powerful declarative model to complex business operations? The answer lies in Agentic Workflows, the core concept behind the devs.do platform.

An Agentic Workflow is a sequence of tasks executed by specialized, autonomous AI agents. Instead of writing imperative code for each step, you simply declare which agents to use and what data to pass between them. The platform handles the orchestration, error handling, and execution. It's Business-as-Code in its purest form.

Your Business Logic, Codified and Declarative

Let's look at a concrete example using the devs.do SDK. Imagine you want to create a service that analyzes a git repository for code quality.

Here's the declarative definition of that service, which we call a "Doer":

import { Doer, Client } from '@do-inc/sdk';

// Configure your client with an API key
const client = new Client({ apiKey: 'YOUR_API_KEY' });

// Define a new service (a "Doer")
const codeAnalysisService: Doer = {
  name: 'code-analyzer.devs.do',
  description: 'Analyzes a git repository for code quality.',
  input: {
    type: 'object',
    properties: {
      repoUrl: { type: 'string', description: 'The URL of the git repository.' },
    },
  },
  // Define the agentic workflow
  workflow: [
    { agent: 'git.clone', params: { url: '{{input.repoUrl}}' } },
    { agent: 'linter.run', params: { path: './cloned-repo' } },
    { agent: 'security.scan', params: { path: './cloned-repo' } },
  ],
};

// Deploy your new service to the .do platform
async function deployService() {
  const deployedDoer = await client.create(codeAnalysisService);
  console.log(`Service deployed successfully at: ${deployedDoer.url}`);
}

deployService();

Look closely at the workflow array. It’s a masterclass in declarative thinking:

1. You state the what, not the how: You don't write the logic for git clone, handle credentials, run a linter process, or parse security tool output. You simply declare that you want the git.clone agent to run, followed by the linter.run agent, and finally the security.scan agent.
2. The intent is obvious: Anyone can read this workflow and understand the business goal: "Clone a repo, lint it, and scan it for security issues."
3. The platform handles complexity: The devs.do platform is the intelligent engine that interprets this declaration. It provisions the agents, orchestrates the data flow, handles transient failures, and manages logging. The imperative mess is gone.

Once deployed, this complex workflow becomes a simple, callable API endpoint—a true Service-as-Software.

Why Agentic Workflows are the Future

Treating your operational logic as declarative code isn't just a neat trick; it's a fundamental improvement in how we build and manage software. This approach, central to devs.do, offers massive advantages:

• Focus on Business Value: Stop wrestling with boilerplate code for API authentication, retries, and state management. Focus on the high-level workflow that delivers value to your users.
• Radical Simplicity & Readability: Your business processes become self-documenting artifacts that can be version-controlled, reviewed, and understood by the entire team.
• Built-in Resilience and Scalability: The platform manages the execution environment. If one step in your workflow fails, the platform can handle retries intelligently. As your service grows, the platform scales the underlying agents for you.
• Composability: Each Doer is a building block. You can chain them together, creating incredibly sophisticated systems from simple, single-purpose services.

The era of brittle, thousand-line automation scripts is coming to an end. The future belongs to clear, concise, and powerful declarations. By shifting from an imperative mindset to a declarative one with agentic workflows, you're not just writing better code—you're building a better business.

Ready to stop scripting the how and start declaring the what? Get started with devs.do and transform your operations into scalable, manageable code today.