The Agentic World: How Coding Has Changed and Why Software Principles Still Matter

The rise of AI agents has fundamentally changed how we write code, but here's the thing: the fundamental principles of good software engineering haven't changed. In fact, they've become more important than ever. Let me explain why the agentic revolution makes software principles more critical, not less.

Treat AI Like a Good Intern, Not a Micromanaged One

We're using AI wrong. We babysit it like a bad intern, telling it what to do every 2 minutes, yelling at its mistakes, getting frustrated when it doesn't understand our intent for 8 hours straight. This never worked offline and will never work with LLMs and agents.

Instead, treat AI like a good intern: provide clear todos, give it a clean space to work (like a clean repo/branch), and let it follow the todo list. You go back to your job and come back after lunch to see the outcome. That's far better than chatting all day long.

The Agentic Revolution: What's Actually Changed

From Manual to Orchestrated Development

Gone are the days when we wrote every line of code by hand. Now we orchestrate AI agents to write code, review it, test it, and even deploy it. But here's the catch: the better your software engineering principles, the better your agents perform.

The New Development Workflow

The modern development process looks more like:

Strategic Planning: Human defines the problem and architecture
Agent Orchestration: AI agents handle implementation details
Human Oversight: Continuous review and refinement
Collaborative Iteration: Human-AI partnership in problem-solving

What This Means for Developers

We're not becoming obsolete, we're becoming conductors. The role has shifted from writing code to orchestrating AI agents to write better code than we could alone.

Why Software Principles Matter More Than Ever

1. Clean Code Principles Amplify Agent Performance

I've noticed that AI agents perform significantly better when working with well-structured, clean code. The principles we've always followed (single responsibility, clear naming, modular design) make it easier for agents to understand, modify, and extend code.

Example: A function with a clear, single purpose is much easier for an AI agent to understand and modify than a 200-line function that does everything.

2. SOLID Principles Enable Better Agent Collaboration

The SOLID principles become even more critical in an agentic world:

Single Responsibility: Each agent can focus on one aspect without confusion
Open/Closed: Agents can extend functionality without modifying existing code
Liskov Substitution: Agents can work with different implementations seamlessly
Interface Segregation: Agents can interact with specific interfaces without unnecessary dependencies
Dependency Inversion: Agents can work with abstractions rather than concrete implementations

3. Design Patterns Guide Agent Behavior

Classic design patterns provide a common language between humans and AI agents. When we structure our code using established patterns, agents can more easily understand the intent and maintain consistency. For example, don't write custom scripts to start services. If you have a Docker Compose YAML, stick to it.

Conclusion

The agentic revolution hasn't made software engineering principles obsolete, it's made them more important than ever. The organizations and developers who thrive will be those who:

Maintain strong software engineering fundamentals
Learn to effectively orchestrate AI agents
Focus on strategic thinking and problem definition
Embrace the human-AI collaboration model

The future of software development isn't about humans vs. AI, it's about humans and AI working together to create better software than either could create alone. The principles that made us successful in the past will make us successful in the agentic future.

The question isn't whether AI will replace developers, it's whether developers will learn to work effectively with AI agents. Those who do will find themselves more productive and valuable than ever before.