Agentic Engineering Manifesto — Practical Principles for AI-Driven Development
A short note on why I wrote the Agentic Engineering Manifesto and what I think changes when teams build software with AI agents.
The full manifesto is available here: Agentic Engineering Manifesto.
AI agents are changing how we build software, but I do not think the important change is only that code gets written faster.
The bigger change is where engineering judgment moves.
When working with agents, the human role becomes less about typing every line of code and more about shaping the problem, giving useful context, choosing the direction, reviewing the approach, and making sure there is a good feedback loop.
That is why I wrote the Agentic Engineering Manifesto.
The main idea is simple: agents are useful, but they need to be guided in the right way. A good prompt is not just a task description. It should tell the agent where to look, what matters, how to think about the change, and how to verify the result.
I also think codebases now need to be easier for agents to navigate. Names, structure, examples, tests, and discoverable patterns matter more when another participant in the development process is searching and reasoning through the codebase.
Another important shift is refactoring. Since agents can make broad changes more cheaply, we should be more willing to ask whether a feature is hard because the feature is actually hard, or because the current architecture is resisting it.
The manifesto is my attempt to write down these ideas in a small and clear form.
It is not about trusting AI blindly. It is almost the opposite. Agentic engineering needs planning, verification, tests, build output, logs, and review. The better the feedback loop, the more useful the agent becomes.
I see this as an early version of how software teams will work with agents: humans leading design and direction, agents taking more ownership during implementation, and both depending on codebases that are easy to understand, change, and verify.