LSTM - How many times should I look back to predict next six hours -Multivariate Time-Series I am still finding confusing on look back topic when using LSTM for time-series analysis.
If I have hourly data and I want to predict next 6 hours with multiple predictors, should I look back up to 6 hours when I prepare my training set? 

OR

Should I look back one hour (shift 1) and then predict next hour and take that predicted value and feed it back to predict the value after until next 6 hours? 

This concept is still a little fuzzy for me in LSTM. Any thoughts would be appreciated.
The second option sounds fun but better don't do it: errors will sum up and it's much harder to track where errors come from. Like you have some error for the 1st hour, feed it back in the net, predict the 2nd hour get an error there and can't really tell how much of that is caused by the error of the first hour.

Besides that, I haven't seen any application which works with this feedback mechanism.