It's tempting to mock corporate language ("why not just say what you mean?").
These non-offensive phrases that can be interpreted multiple ways are used when working with people you don't have trust with yet & save time vs damage control if your direct message is the wrong one.
When I hear people complain it’s hard to hire good software engineers I often think back to this company in London:
Most their seniors were 55-60+. Then they partnered with a bootcamp and hired their grads. It worked very well.
They hired from two groups few companies ever do.
I observed this company do this strategy around 2015. A few interesting things came out of this:
1. Interviews were sensible. The “older folks” designed it and it was practical, no “Leetcode” or algorithms.
2. Even though a “traditional” company, they did TDD, pairing etc.
3. Work-life balance was very nice and what kept a lot of the “older” folks there. Because they got to put sensible practices in place (eg tests everywhere, CI/CD, knowledge sharing) things were predictable.
4. Given pairing was part of the DNA, bootcampers onboarded easier.
20% or more attrition is usually a bad sign everywhere.
@gitlab is an interesting one, as 15% attrition is not standout, although pretty good. But GitLab is a common "target" for Big Tech going remote to hire from.
Thanks to @mar15sa for sharing these insights in a DM. If you're not following her yet, I suggest you do so for remote work insights. She writes the newsletter Remotely Interesting which I enjoy and you can sign up here (it's free!):
I "missed" the launch of the iPhone and Android app marketplaces, and was determined to be there when Windows Phone launched.
I built a few apps for launch. One became very successful: a flashlight app. More than 12M people used it over the years. Why I think it was successful:
1. Capitalize on a missing feature.
On launch, Windows Phone had no flashlight app. Kind of a big deal.
Clearly, a flashlight app that worked would become successful very quickly.
I built one that was a white screen - there was no LED API on launch - and some other gimmicks.
2. Break the rules.
There was no official API to control the LED. But clearly it was there, as the camera used it! I used reflection to map out, then invoke this API. It worked locally! Using undocumented APIs was against store guidelines.
When we think about “what is the next platform in computing that will leap the industry ahead dramatically”, some bets include crypto, VR, quantum computing.
A platform that I think will be much bigger than these, much earlier. It’s already here.
Applied AI/ML.
Four examples:
AI/ML applications are invisible, but everywhere. Sometimes you don’t even realize its ML systems doing all the work.
1. Human understandable analytics. This is what YouTube is doing at a massive scale. It’s making a dent in creator earnings and YouTube dominance:
2. ML used in B2C / B2B applications. Like hoe Stripe uses ML to auto-correct credit card address information entered, adjusting for bugs in issuing bank systems.
Years of working in Uber’s payments team changed my view on distributed systems where participants can make money.
I don’t believe any such distributed system can be as efficient as a centralised one.
A centralised system spends SO much on fraud reduction and customer support.
In ~10 years there’s been much talk on building a P2P version of Uber. Yet it never gained momentum.
Any such system is doomed to fail as many drivers & riders would abuse the system to maximise short-term profits. Incredible what both parties do to make or save money.
This is similar with distributed payments system based on blockchain vs a central entity (eg banks / FinTech companies).
The only successful blockchain-based projects add centralisation, fraud reduction and customer support. It’s the only way they have a path to go mainstream.
Incredible how so many of the former Amazon engineers I talk to HATE the company with a passion I've never heard before.
Why?
All share how, after 4+ years of tenure, they were put on PIP under a new manager.
Why?
Because this is Amazon's Focus/PIP culture w internal targets:
I am not sure if it's deliberate, but Amazon is permanently losing otherwise solid software engineers. Not only that, but they spread the "stay away from Amazon" to their whole network a passion I rarely hear.