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The next decade in SaaS won't look like the last

Summary: The displacement of in-person developer events has vaulted Developer Advocacy forward by...

SWIFT operates a messaging protocol which ties banks together with correspondent banks. This collaboration enables most international wires.

Feisty indies that do too well don't stay indie for long

A look at what Zscaler provides in Zero Trust and SASE, and what it is focused on next.

The advertising has shifted from a Google-Facebook duopoly to one where Amazon and potentially Apple are major forces.

What does it mean when we say that developers spend most of their time figuring the system out? Why is it important? And how else could we look at this problem?

There are few things more exciting than being at a company during hypergrowth, but it’s easy to let hypergrowth get away from you, and to end up reacting instead of planning. It’s hard to steer when you’re rebuilding a plane mid-flight, but you can always nudge it in the right direction.

This is my personal story of starting the SRE organization at Uber. If you want advice rather than reminiscence, take a look at Trunk and Branches Model and Productivity in the age of hypergrowth. After I left SocialCode in 2014, I spent a month interviewing at a handful of companies trying to figure out what to do next. I was torn between two different paths: (1) leading engineering at a very small startup, or (2) taking a much smaller role at a fast growing company, with the expectation that growth would create opportunity.

Early on in your company’s lifetime, you’ll form the seed of your infrastructure organization: a small team of four to eight engineers. Maybe you’ll call it the infrastructure team. It’s very easy to route infrastructure requests, because they all go to that one team. Later on, things are easy as well. You have seventy engineers spread across eight to ten mutually exclusive and collectively exhaustive teams with names like Storage, Traffic, and Compute.

A look at how endpoint protection providers are morphing into XDR.

The introduction to this series can be found here. Summary: There are many ways to put a human life together, including for sex and love. Each path has tradeoffs. __________________________________…

Cloud computing, DevOps and agile development, data infrastructure, AI/ML, enterprise apps and collaboration tools, and security.

Small businesses don't grow large by accident. But most hit an invisible ceiling on the way up. Does strategy matter for breaking past this ceiling?

If rationality is so important to success in business and in life, how is it possible for an entire generation of superstitious Chinese businessmen to succeed?

Education robs us of the ability to do trial and error. And yet trial and error is how a generation of traditional Chinese businessmen learnt their craft.

Career moats are inspired by Warren Buffett's conception of a business's 'economic moat'. Here we take a look at a particular type of economic moat, to see what we can take from it when applied to an individual career.

A reading technique that's ridiculously simple, and surprisingly effective when used in service of reading for career goals.

David Maister's Managing the Professional Service Firm reveals some very fundamental principles about the business of consulting.

The Chinese Businessmen Paradox: what is it that makes uneducated, superstitious Chinese businessmen successful?

How to take ideas from books and blog posts and turn them into effective personal experiments.

A summary of everything a practitioner needs to know about memory retention when learning, in the pursuit of building career moats.

Five ways to do noise reduction, from the field of judgment and decision making.

Results from the BIN paper, or why reducing noise in your decision making is far easier than fighting your cognitive biases.

Is it really worth it to generate well-calibrated probabilistic predictions? Or would you do better if you assume that all prediction is too difficult, and act as if this were the case?

A comprehensive summary of superforecaster techniques from Philip Tetlock & Dan Gardner's Superforecasting. Because — let's face it — you want to predict the future, don't you?

What happens when you adapt the scoring system of the Good Judgment Project to your intuitions at work?

Why it's useful to study the results of the Good Judgment Project in service of building expertise.

An incredibly concise articulation of the difference between experience and expertise, by way of psych professor Greg Northcraft.