Published on August 5, 2025
AI agents are rapidly becoming the new building blocks of software — digital teammates that can reason, act, and execute business tasks autonomously. But to scale agents across real-world use cases, you need more than just prompts.
You need modularity.
At Vortex IQ, we’ve built a framework that allows anyone to create modular, reusable AI agents by combining APIs with logic, memory, and context. In this post, we’ll show you exactly how to design and build modular agents using APIs — and why this architecture is key to long-term flexibility, governance, and scalability.
A modular AI agent is a composable unit that:
Unlike monolithic workflows or prompt chains, modular agents are:
Composable across business functions (e.g. pricing, SEO, merchandising)
Here’s our approach to modularity using APIs, structured into four core layers:
1. Intent Layer
This is where the user’s natural language input is parsed into structured intent.
Example:
“Increase the price of all jackets by 10% and update SEO description.”
Becomes:
json
CopyEdit
{
“task”: “bulk_update”,
“target”: “product”,
“filters”: { “category”: “jackets” },
“operations”: {
“price”: { “action”: “increase”, “value”: “10%” },
“seo_description”: “Updated for winter collection”
}
This layer is LLM-powered but bounded by schemas and business rules
2. Schema Layer (via MCP Server)
This connects the agent’s logic to real API definitions. Using our Model Context Protocol (MCP), agents can:
For example, the BigCommerce Products API might expose:
“name”: “price”,
“type”: “number”,
“required”: true
Now the agent knows how to validate and execute the intent.
3. Skill Layer
Each “skill” is a modular function — a unit of logic that maps to an API action. Think of skills as reusable functions with awareness of schema + auth + error handling.
Example skill: update_price_by_category
yaml
name: update_price_by_category
inputs:
– category
– percentage
steps:
– GET /products?category={{category}}
– FOR each product:
– PATCH /products/{{id}}
body: { price: old_price * (1 + percentage) }
Skills are:
4. Execution Layer
The agent execution engine handles:
It also enables sandbox execution to preview changes before pushing to production.
Modular agents can call other agents or skills in a flow like this:
Agent: Inventory Optimiser
Each skill can be reused by other agents — e.g. the pricing skill could also be used by a Promotions Agent or Revenue Recovery Agent.
Reusability Skills can be shared across agents and adapted for different brands or stores.
Governance & Security Each skill has bounded permissions and field-level controls.
Faster Iteration Update one skill without rebuilding the entire agent.
Easier Debugging Logs and test environments isolate failures to individual components.
Marketplace Ready Modular agents can be bundled and published in an agent marketplace for others to use and build on.
Agent Marketplace (coming soon): Share and monetise your custom agents
The future of automation is not in prompt chains — it’s in modular, reasoning-driven agents that can adapt, scale, and evolve.
By leveraging existing APIs and structuring logic into composable skills, you can build an intelligent system that grows with your business — securely, transparently, and at scale.
If you’re building agentic infrastructure or want to plug into ours, let’s talk.
Reach out: [email protected] Visit: vortexiq.ai
The future of e-commerce optimisation—and beyond—is bright with Vortex IQ. As we continue to develop our Agentic Framework and expand into new sectors, we’re excited to bring the power of AI-powered insights and automation to businesses around the world. Join us on this journey as we build a future where data not only informs decisions but drives them, making businesses smarter, more efficient, and ready for whatever comes next.