You seem to forget the way it learned to play every part of the game (not just micro fights). That is, not by having any developer code any rules, but simply by "looking" and "playing".
That's the great accomplishment and nothing like that could have been done 10 years ago.
What makes this interesting is if they can make a computer program better at Starcraft strategy then a human. How they did that is irrelevant. If having developers code rules makes a better AI then deep learning, then the former is the most impressive solution. What they did is a great accomplishment and the AI they created was amazing, but I feel like the faster-then-humanly-possible micro makes any accomplishment hollow, because that is really nothing new.
If they beat human performance in this (non-AI-building) field by humans painstakingly coding rules for specific situations, then that's cool I guess but not groundbreaking, because the solution doesn't generalise.
If they beat human performance in a field heretofore intractable by software by throwing the basic rules and a ton of compute at an algorithm and then waiting for six weeks while the algorithm figures the rest out by itself, then that absolutely is qualitatively different.
The reason being, of course, that if they can find an algorithm that works like this across a wide enough problem space then eventually they'll find an algorithm which will work on the question of "build a better algorithm." After which, as we know, all bets are off.
If you think the how is irrelevant you are completely missing the point of this exercise. Maybe to you only the result matters but for every other task and humanity the how matters.
Simply imagine next taking on a different Game like one version of the Anno series.
If developers did it by hand, you need 50 devs sitting there for probably a couple of months, figuring out the best, rules their sequence and putting them in. That is about $20 Million just to get a similar AI for the next game.
Compare that to download all available replays, requiring maybe 2-3 data scientist to get the data into shape, renting some compute in the google cloud and you get the same or a better result for probably half a million $.
Watch and learn from data alone is why modern machine learning is considered a revolution and novelty. Buying compute time in the cloud is in comparison (to devs and hand coding) dirt cheap and the results are often better.
Deepmind is not working on this problem for the benefit of gamers or the Starcraft community. Making the perfect bot is not the aim. Tackling the next hurdle, next hardest problem in machine learning is. On the way to become better at generalizing the learning algorithms.
That's the great accomplishment and nothing like that could have been done 10 years ago.