The biggest issue, when learning about systems, networked thought, accelerated learning, etc, is handling how to implement it all in a practical, realistic, and time-efficient manner.
At first, your systems will slow you down and reduce your output, until you improve them and get past the learning curve.
Staying in that theoretical loop was my biggest weakness for the past few years, in all areas of life (=action-faking).
This forced them to quickly pass through selection tests (because outputs are required), discard inefficient tools fast, and iterate on their process regularly.
How do you bridge the gap between theory and reality with all these "knowledge-work enhancement" practices?
What are the workflows, processes, and systems that you use, that stood the harsh test of reality?
I love Twitter though, and I feel like it's one of the best platforms to express my thoughts. More tweetstorms coming in the future!