Coaching, Mentorship, and Sponsorship
These are often repeated words in today's leadership parlance, but they are often confused, and sometimes even the best practitioners are often unaware of what they really mean. This is a great article by Lara Hogan, an engineering leader and author of Resilient Management.
Coaching: Ask questions and guide the subject in the right direction. Often, these questions are open-ended
Mentorship: Give specific examples and sequence of steps that the other person should follow to get to results
Sponsorship: Help the subject grow by sourcing and allocating projects that will challenge them and help them grow into the next phase of their career
A lot of managers focus more on mentorship, less on coaching, and even less on sponsorship. In reality, knowledge workers are often highly aware of the subject matter and need the ‘mentorship’ only during onboarding. They probably need more help through coaching (since even the best of us get stuck within the confines of specific projects/situations and need to zoom out and think big) and most importantly sponsorship, so that we can put our talents to best use.
Some of the best leaders and role models focus less on projects but more on people and their next set of needs and challenges. However, the first step is to be intimately aware of your people even if that means doing all the hard work just to get to know people across the cross-section of your organization. This article, about a leader who decided to meet all 50 people in her organization, the pains she took, and her learnings, was truly worth reading.
In the same vein, the other side of Coaching and Sponsorship is active career development. This is an article by Erik Torenberg that I sent to a few people in my team last week. I often tell people that the person who has to drive your career is.. (surprise surprise!)… YOU! and you have to actively think about sculpting and managing it. It talks about finding your Ikigai - which should be a combination of what you are good at, what is in demand in the market, and what will do good in the world. If you don't consider all of the three factors, you end up with a suboptimal outcome and limit your impact on the world.
Truth and Transparency in Silicon Valley
One learning I have had over the last several years is when something sounds too good to be true, it probably is. It's so incredible that it really takes a lot of time for even the smartest people to internalize this and I would gladly accept that I'm probably as gullible as every other person. A few stories really made this stark even though this has been repeated again and again over the years:
Trevor Milton and Nikola are the most recent examples of this. The story sounded too good to be true right from the beginning. I will not belabor this, since Alex Danco already wrote about it that in his own inimitable style. What stood out to me in the whole article was this quote, which I could make neither head nor tail out of. When I see people using technical mumbo-jumbo just to confuse their audience, it’s clear there's something fishy
'The entire infotainment system is a HTML 5 super computer,’ Milton said. 'That's the standard language for computer programmers around the world, so using it let's us build our own chips. And HTML 5 is very secure. Every component is linked on the data network, all speaking the same language. It's not a bunch of separate systems that somehow still manage to communicate.'
Magic Leap is another one of those. I could never figure out what they did. Turns out, nobody else ever did either. I often wonder what Rony Abovitz got everybody to smoke, given they invested billions into his vacuous vision. And I genuinely feel sorry for Peggy Johnson, who is trying to salvage it after such an illustrious career at Qualcomm and Microsoft.
The grandmommy of this behavior, of course, is Elizabeth Holmes. For anybody who hasn't read John Carreyou's book on Theranos, read it. Stat.
Only the most highly gifted people can challenge this notion - since only the best inventors and orators can alter the reality distortion field.
Just goes to show in the private capital world, everybody is twisting the truth in some ways, and Silicon Valley probably is not the place for you if you suffer from imposter syndrome. A lot of press releases are hyperbole, product announcements are often misleading, zero-value acquisition celebrated and funding rounds with unicorn valuations but fishy clauses are de-rigueur. For an industry that talks about open access and public data, the world of private investment is still a dark art in many areas. Well, it has its Glassdoor now (VC Guide) but there's definitely a need for greater transparency if it has to become more inclusive and safer for non-accredited investors and founders from non-traditional backgrounds.
While some people are monitoring their staff with software that takes screenshots every few minutes, there are other employees who were working two jobs
Either way, the following captures the instructions for 2020 most succinctly
A lot of marketers overestimate the top of the funnel, but don't value the conversion optimization as well. The best ones know better.
Is writing a book really worth it? We all probably know the answer, but I loved how Martin Koppelman broke all the numbers down (actuals). It was also interesting to see how he argued about "creating more value than you capture" — which is something only a book can bring
A fascinating write-up about the science of mood and sentiment analysis. Interestingly, researchers found 60s rock to be the most upbeat and punk and metal to be depairing. Time to play some Led Zep.
This researcher posted about how he uses proceeds from his side "Backup" business (Tarsnap) to fund his personal research and argues that universities are a lousy place to do original research since newly graduated PhDs chase tenure rather than novel ideas. Some truth to that for sure!
Julian Lehr writes about a bunch of pricing experiments that one can do based on popular products. Point #1 really stood out - You can probably charge more!
So how much do you think an average Snowflake employee would have made? This hypothetical exercise about the stock options in Snowflake explains more about the real challenges average employees face - when to exercise, whether to pay taxes or not, and whether you should exercise early (spoiler: you should) — another thing we need more transparency around.
Trump tax returns became public, and everybody in the Startup world piled on.