How to Document Decision Records and Design Choices

Why Decision Records Matter

Code tells you what a system does. Tests tell you what it should do. Decision records tell you why it was built that way. Without decision records, every architectural question requires finding the original developer and asking them to recall their reasoning. When that developer leaves the company, the reasoning is lost permanently.

The most expensive consequence of missing decision records is relitigating settled decisions. A new team member encounters a technical choice that seems suboptimal, proposes changing it, and the team spends hours discussing it before someone remembers that the current approach was chosen for specific reasons that are not obvious from the code. If a decision record existed, the new team member could read the reasoning, understand the constraints that led to the choice, and either accept it or propose a change that addresses the original constraints.

Decision records also prevent the gradual erosion of architectural coherence. Without documented decisions, developers make individual choices that seem reasonable in isolation but conflict with the original architectural vision. Each small deviation compounds until the system's architecture no longer follows a coherent design.

What a Good Decision Record Contains

The Context

What was the situation when the decision was made? What problem needed solving? What constraints existed? The context section captures the circumstances that made the decision necessary. It helps future readers understand whether the original constraints still apply.

The Decision

What was decided? This section states the decision clearly and specifically. "We will use PostgreSQL for the user service" is a decision. "We should think about our database strategy" is not.

The Alternatives Considered

What other options were evaluated? For each alternative, what were its strengths and weaknesses? Why was it ultimately rejected? This section is the most valuable part of a decision record because it prevents future developers from proposing alternatives that were already evaluated and rejected for good reasons.

The Consequences

What are the known trade-offs of this decision? What becomes easier and what becomes harder? What new constraints does this decision create? The consequences section helps future developers understand the implications of the decision and plan accordingly.

How AI Helps Create Decision Records

The challenge with decision records is that nobody wants to write them. The decision is made in a meeting, a Slack thread, or a code review, and then everyone moves on to implementation. The reasoning exists in scattered messages, comments, and memories, but nobody consolidates it into a structured record.

AI agents can help by drafting decision records from the artifacts that already exist. They can read pull request descriptions and discussions, extract the reasoning behind architectural choices, identify the alternatives that were mentioned, and produce a structured decision record that a developer can review and refine. The AI does the tedious work of consolidation, and the developer provides the final validation.

AI agents can also analyze code and identify implicit decisions that were never documented. When the agent sees that the entire application uses a specific error handling pattern, it can ask whether this was a deliberate decision and, if so, generate a decision record that captures the reasoning before it is forgotten.

Keeping Decision Records Useful

Decision records are only useful if people can find them when they need them. Storing decision records alongside the code they affect makes them discoverable. A developer working on the database layer finds the database-related decision records in the same directory. A developer modifying the authentication system finds the authentication decisions nearby.

Decision records should also be linked from code comments. When a piece of code exists because of a specific decision, a brief comment pointing to the decision record helps developers understand why the code looks the way it does. AI agents can identify these connection points and suggest where to add links.

Finally, decision records should be revisited periodically. The constraints that drove a decision two years ago may no longer apply. AI agents can flag decision records whose context has changed, prompting the team to evaluate whether the decision still makes sense or should be reconsidered.