A prescient post on knowledge economy written in 1996. https://hbr.org/1996/07/increasing-returns-and-the-new-world-of-business

Thought experiment in designing a great meeting room experience. https://abhyrama.com/2019/07/04/designing-a-great-meeting-room-experience/

Refreshing read from the co-founder of Dribble. http://simplebits.com/2019/06/25/dribbble.html

• Knowledge economy depends on someone’s ability to go deep into something and connect the dots. Quick street smart on the feet thinking is not of too much value. Interviews as they are conducted today are geared towards latter.
• I have been thinking of an interview format where you give questions well before the interview so that the candidate has ample time to think and organize her thoughts for a productive discussion. This would reflect the true skill needed to thrive in knowledge economy.

Space would probably be the best frontier to expand the pie for humans in an automated robots do everything world.

When someone gives you feedback, irrespective of whether you agree with it or not, shut up and listen. Feedback is a great way for you to understand how the world perceives you and your actions.

One should keep narrative fallacy in mind while reading success stories, especially stories that try to figure out the reasons for success.

Simple hack for being accountable; if someone asks for a favor, tell them you will do it by a certain date and ask them to remind you on that date if they do not see you fulfilling the ask.

Seeing tweets on 10x, 20x, foox engineers. One thing you for sure want in your engineers is the ability to distinguish between micro and macro solutions. https://abhyrama.com/2018/09/23/micro-versus-macro-solutions/

Attempts to archetype productive people in the form of 10x engineers, Steve Jobs type CEO make it sound like one has to be an anti social jerk to be successful. I believe “Being Nice” is the most overlooked super power to a fulfilling and successful life.

• In software, it is difficult to correlate specific input (architecture, coding guidelines, tech choices, product features) with specific output (product adoption, user growth, revenue).
• This creates a view where complexity of the input gets conflated with the efficacy of the output leading to an environment where simplicity is shunned and unnecessary complexity is celebrated.

The problem with personality tests is that the questions are deviod of context. I believe human nature/behavior is highly contextual which the personality tests completely miss. Irrespective of that, it is always fun to answer one and see the assessment.

• Whenever someone writes a blogpost on using a particular technology, there are a lot of comments saying why the said tech is not the best for the use case.
• Tech choices are usually not made in absolute terms. The current context of the organisation, existing stack, talent, team structure, last but not the least - personal proclivity to the said tech play a much bigger role in the choice than we like to think.