I’ve just published the first portion of the slides about the NoSql introduction. Feedback is always welcome.

1. It’s designed to improve performance. “The essence of deliberate practice is continually stretching an individual just beyond his or her current abilities. That may sound obvious, but most of us don’t do it in the activities we think of as practice.”
2. It’s repeated a lot. “High repetition is the most important difference between deliberate practice of a task and performing the task for real, when it counts.”
3. Feedback on results is continuously available. “You may think that your rehearsal of a job interview was flawless, but your opinion isn’t what counts.”
4. It’s highly demanding mentally. “Deliberate practice is above all an effort of focus and concentration. That is what makes it ‘deliberate,’ as distinct from the mindless playing of scales or hitting of tennis balls that most people engage in.”
5. It’s hard. “Doing things we know how to do well is enjoyable, and that’s exactly the opposite of what deliberate practice demands.”
6. It requires (good) goals. “The best performers set goals that are not about the outcome but rather about the process of reaching the outcome.”

• Hard work is deliberate practice. It’s not fun while you’re doing it, but you don’t have to do too much of it in any one day (the elite players spent, on average, 3.5 hours per day engaged in deliberate practice, broken into two sessions). It also provides you measurable progress in a skill, which generates a strong sense of contentment and motivation. Therefore, although hard work is hard, it’s not draining and it can fit nicely into a relaxed and enjoyable day.
• Hard to do work, by contrast, is draining. It has you running around all day in a state of false busyness that leaves you, like the average players from the Berlin study, feeling tired and stressed. It also, as we just learned, has very little to do with real accomplishment.

• The solution is as simple as it is startling: Do less. But do what you do with complete and hard focus. Then when you’re done be done, and go enjoy the rest of the day.

Just recently watched Kevin Slavin [TED talk] on “How algorithms shape our world”. This made me realize why I’m intuitively trying to stay away from the open trading.

How can you continue to call yourself an investor and go against the algorithms? Your money can disappear in an instant like the 9% of the market Kevin was referring to. The market works like a lotto or a Russian roulette and very similar to the Wild Wild West – who pulls the gun first and pulls the trigger faster – wins.

• Dummy objects are passed around but never actually used. Usually they are just used to fill parameter lists.
• Fake objects actually have working implementations, but usually take some shortcut which makes them not suitable for production (an in memory database is a good example).
• Stubs provide canned answers to calls made during the test, usually not responding at all to anything outside what’s programmed in for the test. Stubs may also record information about calls, such as an email gateway stub that remembers the messages it ‘sent’, or maybe only how many messages it ‘sent’.
• Mocks are what we are talking about here: objects pre-programmed with expectations which form a specification of the calls they are expected to receive.

I’ve always felt that there was not enough time to consume and to learn in general. This was alway bugging me because I felt that my value was declining with each and every passing day and I was afraid that something new in the world will be born without me learning abou it.

I hope that this situation is going to improve going forward. Recently I got myself an iPad. This allows me to get more content consumption on the road and on a couch.

With this post I’m, in fact, testing a WordPress application for iPad.

If it works as expected, will try to start posting on my blog the links to noteworthy content and, as usual, you are welcome to comment.

Currently we have solutions like Script# and CofeeScript and others. The pros in cons of these systems have been discussed countless times (ex: Hanselminutes -  JavaScript is Assembly Language for the Web: Semantic Markup is Dead! Clean vs. Machine-coded HTML).

With the recently released project Roslyn (or alternatively Mono Compiler Services) it is possible to have a clean solution to the problem:  I write my data and data model in a language and an environment that allow solid validation and refactoring.

I’m ironing out some kinks in my implementation and, as soon as it’ll be in a stable state, I’m going to release a NWT (NeWT) project that will provide a similar to GWT (Google Web Toolkit) functionality.