Spec-Driven Development#
Spec-driven development is a way of working where the requirements are described before the solution is built. Instead of starting with code right away, you first write down what the application should be able to do, how the user should move through it, and what should happen in important situations.
I think this becomes especially relevant when working with code agents. A code agent can help build and change a project, but it still needs direction. If the task is only described in a very short or unclear prompt, the agent may create something that works technically, but does not match the real purpose of the application.
Why specs matter#
A specification works like a map for the project. It can describe the features, the user flow, the expected behavior and the limits of the system. For example, if I am building a quiz application, the spec should explain what happens when a user answers correctly, what happens when the answer is wrong, and whether the user should be able to continue later.
This is useful because it makes the task more concrete. Instead of writing “make a quiz”, it is better to describe the experience the user should have. That gives both the developer and the code agent a clearer understanding of what needs to be built.
My experience with Codex#
In this course, I worked with Codex as a code agent. This gave me a better understanding of the difference between using AI as a normal chatbot and using AI as part of the development process.
When I use an assistant, I usually ask questions, get explanations or ask for suggestions. A code agent feels different because it can work more directly with a project. It can help edit files, suggest structure, fix errors and follow a task through several steps.
Because of that, the way I communicate with the agent becomes very important. I learned that a good prompt should not only say what I want, but also include the context, the goal and the important rules. If the prompt is too open, the result can become too random. If the prompt tries to include too many things at once, the agent can lose focus.
Example: a meditation quiz#
One example I worked with was a meditation quiz website. The idea was to create a calm and simple quiz experience, where the user could answer questions and continue through the quiz without feeling blocked.
For this type of project, a spec could include requirements such as:
- The quiz should use multiple choice questions
- The user should be able to continue after a wrong answer
- The user should be able to restart the quiz
- Progress should be saved locally
- The design should feel simple and calm
These requirements are small, but they make a big difference. They describe not only the code that needs to exist, but also the experience the application should create. That is one of the things I have learned from working with specs: they help connect technical work with user needs.
Specs, logs and debugging#
I can also see how specs and logs can work together with code agents. The spec explains what the application is supposed to do. Logs and browser errors show what actually happens when the application runs.
When something goes wrong, it is much easier to get help from an agent if I can provide a specific error message from the browser console. Instead of saying “it does not work”, I can share the actual error and explain what I expected to happen. The agent can then compare the problem with the intended behavior and suggest a more useful fix.
This makes debugging more structured. The spec gives the goal, and the logs give evidence about the problem.
Reflection#
My main takeaway is that code agents are powerful, but they are not magic. They work best when the task is described clearly and when the developer still checks the result. Spec-driven development can help with this because it forces me to think about the application before asking the agent to build it.
I also learned that AI-supported development is not only about getting code generated quickly. It is also about communication, structure and testing. A clear spec can make the work more reliable, and logs can help improve the solution when the first version does not behave as expected.
Overall, I see spec-driven development as a useful method when working with code agents. It gives the agent better context, makes the project easier to debug, and helps keep the focus on what the user actually needs.