Whenever I want a prototypical example of “here's what an effective B2B startup salesperson looks like”, I think of Chris Degnan. Degnan was the first sales hire when Snowflake was a 16-person stealth startup. 7 years later, he was CRO of an $81B company. Pretty good prototype!

Two weeks ago I wrote an essay titled "How to Make Sense of AI." It struck a chord. Folks shared it with their friends. One friend printed it out to give copies away. That essay laid out a method of making sense of AI developments without losing your head. But it was not enough.

I don’t say this enough, but I find @DellAnnaLuca’s writing incredibly clear, pragmatic, and useful. I recommend everyone who is interested in operational excellence to buy his books.

Surprise, surprise: Steve Jobs understood process control. I didn't realise that he learnt quality from Joseph Juran, a Deming contemporary. This is, incidentally, where “blameless post-mortems” and “fix the system, don’t blame the person” comes from.

There’s a weird divide in the world of demand frameworks that most people don’t notice. Some frameworks help you understand demand AFTER you have customers. Other frameworks claim to help you FIND demand when you have zero customers. These are very different problems.

I think more people should build private communities (with their friends, colleagues) to share detailed AI field reports of use. Instead of sharing takes, or predictions, or getting all hyped up (or doomer) about AI. Here's what I mean.

People saying ‘moats don’t matter in AI’ are partially right. But they’re right for the wrong reasons. It’s not true that AI has changed the fundamental dynamics of competitive advantage. It’s that we’re in a gold rush — and gold rushes have very specific properties.

Legendary investor Howard Marks once had a 1984 BusinessWeek article written about him where he said “Real men don’t buy converts, so chicken like me can buy cheap.” Makes one think.

It took me 5 years to figure out how to apply Cognitive Transformation Theory — a theory of accelerated expertise. This is what made it finally click. In January this year, we ran Speedrunning the Idea Maze — a live course about searching for product market fit (PMF).

Most corporate leadership training is worthless. You know this. I know this. Offsite workshops, case study seminars, executive education programs — they produce few actual leaders. And so it’s very surprising when you encounter an exception.

If you reacted in fear as a result of a viral essay recently, your attention has probably been compromised. You don’t have to be scared of AI. You don’t have to read hype takes, or doomer takes. You just need to sensemake aggressively: commoncog.com/how-to-make-...

Too many correlational studies, not enough causal arguments.

There is a super power in ignoring things. You should probably ignore that AI doomer take. Unless you consumed every Internet doomer take in the late 90s. In which case, you've learnt nothing, go right ahead.

This was lovely. And as a fellow writer who still writes the old fashioned way, it hits home.

Also, this Brian Eno quote has been really stuck in my head for weeks: "The great benefit of computer sequencers is that they remove the issue of skill, and replace it with the issue of judgement. ... the question then is, "Of all the things you can now do, which do you choose to do?""

Was a pleasant surprise when I heard Michael Helbling call out Commoncog as a really great place to build business acumen: "If you're in a role where you're trying to ramp up on your business acumen, Commoncog might be a great resource to leverage."

I was asked recently how I find and keep business mentors. I realise that my essay on this topic is now four (!!!) years old. At this point I know more than a handful of senior folks who have shared this repeatedly with junior people. And it's a REALLY simple protocol.

A week ago I subjected 9000+ subscribers to the most Singlish that I've ever put into a Commoncog essay. 🤪 This piece talks about an under-examined trait: 'being commercial'. You know how some folks are very good at making money? Yeah, that.

What has Warren Buffett and Charlie Munger said about how to read biography? (Or Value Line numbers? Or annual reports?) Yesterday, I published a thing about learning from case studies WITHOUT survivorship bias. I cited Munger and Buffett, natch.

Here are two big contradictions about reading business history: 1. Survivorship bias is a problem when reading history, especially business history. 2. Famous investors and businesspeople tell you to read lots of business history. So ... how do you reconcile this?

Over the course of 2025 we published a series on Asian Tycoons. At the end of last year, we finally arrived at what is my favourite case of the entire series. This was about Singaporean tycoon Kwek Leng Beng, who bought New York's Plaza Hotel from a distressed Donald Trump.

Pattern that I've noticed for a few years now: if a founder in the Singapore context opines about the Singaporean 'startup ecosystem' (usually on LinkedIn, usually very loudly because it gets attention) it is almost guaranteed said founder will fail. Sad but true.

How can we test theories of accelerated expertise in business? Last year, we ran an experimental course called Speedrunning the Idea Maze. It was an excuse to test many things, but it was also an excuse to test two remarkable learning theories. Here's what we learnt.

The “Idea Maze” is a delightfully useless idea. In 2024, I wrote a somewhat controversial essay about it that now ranks in the number 1 or 2 spot on Google for the phrase 'Idea Maze'. Folks like to think that there's a 'method' to finding PMF. They're mostly wrong.

Useful model: when reading an opinion piece / listening to a podcast, ask yourself how the expressed opinion is self-soothing for the person. Folks cannot express opinions that make them uncomfortable. They will follow up with a hedge if so. Gives you a new way to read them.

I see the bots have arrived.

Jeff Bezos wanted to go to space, which requires money, so he started Amazon.com and ran it for 27 years to get rich. He now runs a rocket company, which he funds with periodic sales of his Amazon stock. He's also been to space. Generalised life advice is tricky.

The frame that I like the most about open source business models was from the CTO of a major open source startup (one that’s name brand famous) who, in Commoncog’s forums, argued that OSS businesses are exactly backwards. I thought that OSS = better distribution …

There are certain things in business you DON'T want to learn by doing. You want to learn them by reading instead. This week’s Commoncog essay is about exactly this odd phenomenon. It was sparked by a conversation that I had on Twitter:

Presented without comment.

This is a bit of a small TAM interview, but I was on @kchongl's podcast a month ago talking about business, Asian tycoons, and entrepreneurship in Singapore. This interview was just released a week or so ago; here are a few thoughts on what we covered.

This seems to have spread through word of mouth, so I think I should give this a boost. Over the past 3 years or so, I've seen a number of "what to do about AI posts". Most of them are bad, because they are built around a flawed idea: that you have to predict the future to act.

"If I were stranded on a desert island and could only receive updates from five websites, Commoncog would be one of them. It's that good." ☺️

Oh my god.

PSA: I've published two summaries on navigating tech bubbles in the Commoncog members forum. The first is a summary of Engines That Move Markets, which examines every tech bubble since the canals. The resulting framework helps you navigate the current bubble.

commoncog.com/how-to-use-a... I enjoyed this essay by @cedricchin.bsky.social quite a bit (which is a normal reaction for me). Super practical, super applicable, deeply rooted in humanism and compassion.

@commoncog.com.web.brid.gy by @cedricchin.bsky.social is probably the most influential resource I’ve discovered on the Internet in the last couple of years. mirekdlugosz.com/blog/2025/fo... #testing #thinking #mentalmodels #blog #software

HOW do you use AI without becoming stupid? Over the past couple of months, a small group of members on the Commoncog forums (myself included!) have been testing a universal rule for AI use in our businesses and careers. It's out today.

Sometimes I am asked “Cedric, why are you still in Singapore?” The question behind the question is: “I want to aim for a billion dollar outcome. I cannot imagine being a founder if the upside is not at least a billion dollars. Why bother with SG, when the upside is so small?”

If you attend the average founder meetup, the odds are pretty good that you’re going to meet folks who are playing a lottery game, not a business building game. The two approaches use very similar language (‘markets’, ‘demand’, ‘revenue’) but are fundamentally different.

I was back in my hometown a few weeks ago and realised that my dad was treating LLMs like he would another human. This was … bad, for reasons. So I started looking for a vaccine to inoculate him against anthropomorphising the AI apps he was using.

My old company got acquired by Ant Group a few months ago. It's funny how these events can prompt reflection. I was celebrating with my old boss, who I'd helped build the company with years back, and I realised that perhaps I'd learnt the wrong lessons from my time with him.

I want to call out an example of some remarkable thinking that I've had the privilege of observing up close. About 2 years ago, @vaughn_tan started a project to come up with better thinking around 'uncertainty'. This MIGHT be important to business! MIGHT! But I was unconvinced.

I am still waiting for a concrete example of a notetaking influencer improving their thinking through notetaking. Getting a book about notetaking published does not indicate better thinking. 😉 I don't want this tweet to be a dunk, though, so I'll list concrete alternatives.

I know folks mean well, but, uhh, if I had a dollar for every time someone brings up Wardley Maps when I talk about strategy … I’d probably be rich.

Been reflecting on this line, said in passing by a friend: “Winning doesn’t require popularity. Just results.”

Sudden realisation that ambition, on its own, is not a virtue. A simple thought experiment: would you admire a super ambitious man who took on too much debt and blew up and is now homeless?

A gentle reminder that if you want to speed up your intuition, you will do a lot better if you have an actual mental model of what expert intuition *is*. The most useful model is the one below: It gives you more handles on how to improve.

You know what's the biggest giveaway that an "we adopted AI and now our metric requests are completely solved" story is fake? There's no mention of metric definitions. And I don't mean "what is the SQL query that produced this?" but "how is this measured?"