We are making it easier than ever to build and deploy AI agents. But reliable agents are not built on prompts alone — they require a robust, coordinated infrastructure of underlying primitives.
The Architecture of Modern Agents
At the core of every AI agent is a reasoning loop. The agent receives a task, breaks it down into steps, selects the appropriate tools, executes them, and iterates until the task is complete. This loop is deceptively simple in concept but extraordinarily complex in practice.
The key primitives that power this loop include:
- State persistence for maintaining context across interactions
- Workflow orchestration for managing long-running tasks
- Sandboxed execution for running untrusted code safely
- Tool calling for interacting with external APIs and services
Why Edge Deployment Matters
When you deploy agents at the edge, you get several critical advantages. First, latency drops dramatically — your agent can respond in milliseconds rather than seconds. Second, you gain data locality, keeping sensitive information closer to where it is processed.
import { Agent } from '@framework/agents';
const agent = new Agent({
model: 'kimi-k2.5',
tools: [searchTool, calculatorTool, codeTool],
maxSteps: 10,
temperature: 0.7,
});
const result = await agent.run('Analyze the performance metrics for Q1 2026');
console.log(result.output);The Cost Equation
As AI adoption increases, we are seeing a fundamental shift in how engineering teams operate. It is becoming increasingly common for people to have a personal agent running 24/7. The volume of inference is skyrocketing.
This new rise in personal and coding agents means that cost is no longer a secondary concern — it is the primary blocker to scaling. When every employee has multiple agents processing hundreds of thousands of tokens per hour, the math for proprietary models stops working.
Enterprises will look to transition to open-source models that offer frontier-level reasoning without the proprietary price tag.
Getting Started
To start building your own AI agent, you need three things: a capable model, a set of well-defined tools, and an orchestration framework that ties everything together. The good news is that all of these components are now available as open-source software.
Check out our documentation for a step-by-step guide to building your first agent.