I really resonated with your point about avoiding perfectionism and shipping good-enough solutions. However, I’ve found that defining "good enough" is tricky and depends on the project’s context. For instance, in personal projects, I’m fine skipping automated tests to move faster, but at work, I invest time in writing them to ensure stability. My rule of thumb is: if a solution can evolve into something scalable and robust later without massive refactoring, it’s good enough. What do you think about balancing speed now versus technical debt later?
I think you captured it perfectly — the definition of "good enough" really depends on the situation, and your rule of thumb is very smart. In my opinion, if a solution is purely experimental, the main focus should be on speed. This keeps the cost of experimentation low, and if it fails, you can quickly move on to the next idea. If the experiment succeeds, you can always iterate on it later, making it more robust and resilient over time so tech debt is good here.
I really resonated with your point about avoiding perfectionism and shipping good-enough solutions. However, I’ve found that defining "good enough" is tricky and depends on the project’s context. For instance, in personal projects, I’m fine skipping automated tests to move faster, but at work, I invest time in writing them to ensure stability. My rule of thumb is: if a solution can evolve into something scalable and robust later without massive refactoring, it’s good enough. What do you think about balancing speed now versus technical debt later?
I think you captured it perfectly — the definition of "good enough" really depends on the situation, and your rule of thumb is very smart. In my opinion, if a solution is purely experimental, the main focus should be on speed. This keeps the cost of experimentation low, and if it fails, you can quickly move on to the next idea. If the experiment succeeds, you can always iterate on it later, making it more robust and resilient over time so tech debt is good here.