What is Agentic Engineering?

Introduction

Agentic engineering is an emerging discipline focused on the design, construction, and operation of autonomous artificial intelligence agents. Unlike traditional AI systems that simply respond to prompts, agents are capable of planning, executing actions, and adapting to results autonomously.

What makes an agent different?

An AI agent is distinguished by three fundamental capabilities:

1. Perception: Ability to observe and understand its environment
2. Reasoning: Ability to plan and make decisions
3. Action: Power to execute tasks that modify its environment

class Agent:
    def __init__(self, tools, memory, llm):
        self.tools = tools
        self.memory = memory
        self.llm = llm
 
    async def run(self, task: str):
        plan = await self.llm.plan(task, self.memory)
        for step in plan:
            result = await self.execute(step)
            self.memory.store(result)
        return self.memory.summarize()

The agentic loop

The fundamental cycle of an agent consists of:

Observe

The agent gathers information from its environment through tools and APIs.

Think

Using an LLM as a reasoning engine, the agent analyzes information and plans its next steps.

Act

The agent executes concrete actions using available tools.

Reflect

After each action, the agent evaluates results and adjusts its strategy.

Practical applications

Agentic engineering has applications in:

• Software development: Agents that write, review, and deploy code
• Research: Agents that search, synthesize, and generate reports
• Enterprise automation: Intelligent workflows that adapt
• Education: Personalized tutors that adapt to the student

Conclusion

Agentic engineering represents a paradigm shift in how we build AI systems. It's no longer just about models that generate text, but about complete systems that can reason, plan, and act autonomously.