As somebody from outside academia, what's the worst that can happen by not reading every paper related to your research, you accidentally end up replicating (part of) somebody else's results? That sounds useful in itself.
Given how low the reproduction rate in science is, I'm not sure that time would be wasted.
For example, suppose you discover the structure of DNA, you try to publish but find someone already published it last year. You've just wasted a lot of time.
I don't know what the solution is.
In the fields of computer science where you actually implement something, it's the design and implementation of that new artifact that takes up most of your time. The experiments are not nothing, but they tend to be the sort of thing you can script: run a bunch of programs, accumulate results, do data analysis. Even the data analysis tends to be scripted. If, at the last moment you discover a small tweak that could improve your implementation, it can be trivial (in effort, not necessarily time) to re-run your experiments.
Now, the experimental evaluation is still important, and it is also easy to do wrong. But I also claim it's more deterministic. If an author is honest in describing their experiment, it's easier for reviewers to cry foul in computer science systems research than in, say, psychology. There are ways in computer science to design poor experiments that show bogus results, but it tends to be more obvious.
If, upon trying to publish, you discover that someone else had a similar idea and implemented something similar, you have replicated the hardest part. You spent a lot of time and effort designing this new thing that overcomes all of these challenges. If someone else already did that, you could have just skipped all of that, and started on improving it right away. In computer science systems research, replicating someone's research may actually be must faster. Sometimes you can view their code directly, or you can implement their idea in another system. Re-implementing an idea in a new context can take a lot of engineering effort, but it can still be a lot less work than doing it the first time.
Now, what happens if that was a bogus technique, and you can't replicate the results? That's a publishable result, but it tends not to be the whole paper. You figure out a better way, and explicitly compare your new way to that old published way. Again, that's because in computer science systems research, you're not discovering fundamental properties of things. Instead, you're discovering better ways of doing things.
I do sometimes read computer science systems papers and think "Eh, I don't buy this result". That's usually not because they did anything wrong (although sometimes it is), but because I just think that what they are investigating does not matter. "Sure, I believe you figured out a reliable way to optimize a three wheeled car, but four wheels is still better."
Theoretical computer science is not impacted by this at all, as there usually are not experiments in such papers. Their "results" tends to be a proof.