Lesson : individual compensation in commerce

This quarter, it will be 20 years since I began studying commerce. Spending my days alone, on sabbatical over chores, I review past lessons.

I graduated about 21 years ago, but my first job was in a think tank supporting Putrajaya. The pace did not suit me, so I dove into commerce, finally, in 2006. After short stints in management consulting, and asset management, I worked at my first startup. At this little company, I got to work with some really nice people, who had accomplished many things in their private careers, and were now religiously motivated to run a social enterprise. 

We raised $1 million on a $2 million valuation, largely on my work projecting financial statements and fluffing up their intellectual property assets. After funding, I was offered something like $10,000/year, so I declined to participate. For the setup work, I had been paid about $5,000. I thought nothing of it at time, figuring that it was an ordinary collection of cultural experience, neither surprising, nor encouraging in any way. 

It taught me however, to structure my time more around commercial agreements, and to simply discount the positive aspects of anyone involved. The world is full of clever, well-intended people. But they cannot all be expected to act in the interest of others. My short experience with this little company taught me also how to be a better employer. I have since always practiced the method of explicitly discussing the economic motivations of staff, on an individual basis, when hiring.

My next job after this, was learning how to tend a bar.

What's the matter with Private Credit?

... my friend asked. Well I'm no expert, but this is what I told them.

PC is basically "more negotiable debt", than bonds which are regulated as securities. The original intent is for, of course, relationships among premium people to translate to premium alpha. 

The nature of debt markets is that macro has a bigger effect on everyone. Because the bag holders are skewed towards the conservative personalities, it is always doom and gloom : pessimistic motivation to invest + pessimistic reaction to news + pessimistic appreciation of macro 75% of the time.

BTW they have PC-backed CDOs now ( bags of PC that are securitised and resold ). CDOs for residential mortagages being the Lehman issue <- for reference.

My current understanding, superficially : banks are not under significant pressure, so the debt market in general is well buffered. 2-3 years ago the SVB and related stress issues were very well contained. So while US mortgage market is currently stressed, individuals suffer but there is "unconcerning" systemic risk. Some big players to watch may be the % of residential mortgages held by non-individuals.  The reason we talk about the US debt markets so much, is because the backstop is the US banking system.

A side issue of interest is the whole Trumpian stablecoin regulation : attempting to tie cryptocurrency innovation to USD by requiring US-domiciled stablecoin issuers to hold USTs as collateral. What this does simply is make USTs more exposed to volatiity in crypto. Of interest to credit analysis, is that fact that stablecoin-cos do report their collateral, but it's generally not audited with great reification : case in point USDT-co.

🤡tq for coming to my ted grumble. 

filtering out manic optimists during hiring

Commenting on hiring people who challenge you, versus yes-people.

I find the hardest part is hiring 10 people you know who will be culled down to 2 or even 0 eventually, with the best of intentions. Especially when the hired are more optimistic than the hirer, and when the hirer is expressly warning the hired that the bar is high.

Then, watching the hired gradually face depression and dismay in their disregulated bipolarity by having their pathological optimism ground up in the face of reality.

I think we can all be more careful with each other.

educating boards on AI

AI is fundamentally an augmentation of the human factor. I once designed a framework for organisations where the three main classes of stakeholder ( or in ISO terms, "interested party" / IP ) are 

• 1. investors : moves first with capital, gets paid last
• 2a. staff : the first supplier, gets paid first, closes loop
• 3. customers : pays first

Depending on business model of course, there are other IPs, like 

• 0. the government,
• 2. suppliers ( superset of staff ), 
• 4. neighbours,
• 5. competitors, 
• 6. criminals

etc. 

It becomes interesting to run brief simulations over a cup of coffee about what happens when the cost of doing business for each of those parties gets impacted by AI. Basically if the cost of thought drops for everyone, the government is going to want a higher standard of compliance, investors are going to allocate capital differently, staff either get lazier or more productive, suppliers are expected to increase performance, customers have different behaviours depending on their own operating models, competitors are simply trying to leverage off the same thing in different dimensions, and thieves are getting sneakier.

I generally say that most business problems are talent management problems - and that the only long-term difference between machine and human intelligences is legal personhood. In the pathology of behaviour, we again a simple framework is to determine if the problematic party is (a) stupid, (b) lazy, or (c) malicious - there being various formulations of reduction and expansion about this. So much fun to think about, but more fun to think about as an educator of students who don't understand this thoroughly.

( Someone was looking for board-level non-technical AI-subject-matter training the other day, so I dropped a random comment and buggered off. Thought about it a bit more over the week. )

the whole point of dating

Successful date : paraphrased

• Me : do you like walking up [ local ] hill?
• She : i went once many years ago; i only go very early before the sun is too strong, and I am afraid to go alone in case i am unprotected from monkies
• Me : i think you are too sensitive for partnership, but we can be friends and grab coffee
• She : i would not like to be friends; blocks

1. This is modern dating : not all conversations involve meeting up.

2. A date is great, if the outcome establishes information.

As I was explaining to a critic : the point of dating is not to close deals, but to close the better deals.

new study portfolio : realestate

 Realestate, is for the rich. I don't consider myself rich, so I have never made a point to study realestate in detail. 

Around the age of 27, I made a token investment in realestate - a leasehold suburban flat, the cheapest I dared pay for. Around the age of 39, I made a second investment - a freehold urban apartment, mainly useful for entertaining guests. The shopping process for each of these involved a vast survey of the city's options for residential flats, and nearly nothing else.

Around the age of 42, I found myself looking to simplify logistics for the maintenance of old people in my family, so I began to survey all sorts of realestate, commercial and residential, land and buildings, throughout the peninsula of Malaysia. That was the last month, or so. 

I figure, over the next 20 years, so roughly until I am 62 ( 2045 ), if I live that long, in Malaysia, and undistracted by greater responsibilities ... then I shall acquire more knowledge of realestate economics and property development. Also I should aim to save up enough to purchase a commercial-zoned property as an option to live in, for the longer term, while having the opportunity to hawk goods and services from time to time.

We shall see how that turns out. Either someone might have killed me, or revoked my citizenship, or jailed me, or ... gainfully employed me elsewhere. 

Commercial Present Value, of Engineering Paradigms

Folks talking about AI models, seem funny, often enough.

You guys gotta stop throwing model names, and look at the fundamental difference between model structure. The main two aspects of computation are space and time : corresponding to data and operations on data.

2x2 matrix renders :

• - good operation, on good data
• - good operation, on bad data
• - bad operation, on good data
• - bad operation, on bad data

Consider for each model you have named, where it falls on such a matrix in the present SOTA, and where you would expect it to fall on a future SOTA ... now you have a cube of which models are good now, but eventually going to be replaced, and which are poor now, but eventually going to be dominant. 

Negative expectations, Positive hope

I got nothing against folks who chase their dreams. We all have different dreams.

I like pitching products which I have a predictable grasp of, with a very low rate of error. Usually I'll include in the pitch, that where there's uncertainty, you should expect negative returns. That's just how I roll - you can HOPE for positive returns, but statistics often are very clear on the history of a thing, unless you are doing something very new. And if you are doing something new, that is not something to be expecting success from. So any positive hope MUST be coupled with explicit expectations of neutrality or failure, UNLESS the data provides an exception.

I don't particularly enjoy telling people to cheer up based on hope - I find that is quite a degenerate approach to life. Perhaps I am biased because I grew up in a country that governs based on a notion of the afterlife ... hahaha. Whatever the case, just not my flavour.

The Governance of Men and Machines

1. 

I know everyone thinks I'm a weirdo but ... the only reason I spent time during my commercial period ( about 25% of 2006-2023 ) in software was ... that I wanted to know "just enough about how software works, in order to effectively manage software operations talent".

2.

This is pretty much the same reason I'm still studying software and math, on sabbatical. ( It's mainly a hobby, but there remains a commerciable alignment. ) Right now I'm stuck at fucking ENGLISH grammar, because it's part of the HCI stack.

3.

This is ALSO the main reason I have no reason to use AI yet ... the problem with governance is never telling someone to do something, and having it reported back as done. The problem is always figuring out how to verify that it got done the way I wanted. There's basically no difference between managing humans, and managing anthropomorphic machines - both are black boxes, both have motivations and emotions, and both are subject to manipulation of civil and uncivil degrees.

4.

The question is always how, not what. But, I get it ... most business people are concerned with short-term results. They want to focus on the what, get paid, and exit before the how breaks down and kicks the asset owner in the ass. Well you see, generally, I decided not to be that sort of business person. But ah, that's a lot of faff, isn't it? :)

Presumptions of Desire

 So wrong : 

"the assumption that candidate is already interested in working for their company"

Oh my god. Why do hiring managers start conversations with people like this? OK, I get it ... they are like those folks who go on dates presuming the other party is already interested. It's a bit awkward.

But now that I have identified it as an anti-pattern in conversations I've been in from 2007 to 2025, I shall make a point to deescalate such chats from the get go, "hold on, can you please say a bit about why X-talent should be interested in working at Y-corp?"

Clearly I don't go on many job-dates lol. It took so long to ID this.

Drum : Economic Education for 14-year-olds

I generally put it to designers of education systems : the survey of "what jobs exists, how much they are paid, and what is needed to access them" should be available to all 14-year-olds. It's the best time to start planning.

And the incumbent nature of the political economy is that, the absence of such survey data for 14-yos, is how we manage to keep people in lanes for the rest of their lives. :)

The 14-yos who know that the fresh grad pay range in KL is 1.5-20k MYR/mo are not doing what the 14-yos who think it's 1.5-5k are doing. And the expectation diverges for say a 30+yo where some make 1.5k, and some make 400k!

So the strategy of picking education paths depends on education goals, and the goals depend on ... some sort of preliminary life planning survey which is generally unavailable to the masses.

Lord Looked Upon the Land, and the Data was Good

 In the beginning, business was wrought from chaos.

Then came accountants, and there was order upon the land.

In a season of low margins, they were reborn as management engineers.

In another season, as consultants and bankers.

In yet another season, reborn as big data analytics experts.

In YET another season, as data scientists.

Today all the kids are running around discussing degree programs with "data" in them. 

Hello, did you forget the "science"?

Policy wish-list : 80% reductions in synthetic fibre, and single-use plastic, sales

Two things I want for solid waste management in Malaysia : both are not obviously attractive, both require 3-year plans to set up 10-year roadmaps, reasonably. However, both have the potential to spur R&D into globally beneficial supply-chains, which are potential future economic growth vectors.

• 1. Reduce single-use plastics sold, by 80%. ( Plastic food wrappers, etc. )
• 2. Reduce synthetic fibres sold, by 80%. ( Polyester clothing, etc. )

Why does anyone do anything?

What is your PURPOSE? This is a common theme in sentimental discussions in life planning, career coaching, and brand management. Much of it hews towards spiritual masturbation, as folks evade the difficulties of empirical data, and veer off into realms beyond.

Well, why does anyone DO ANYTHING? That's more concrete, and it brings us towards the mode of behavioural economics, petty psychology, and realpolitik : and here we find the money, predatory traders, strategy consultants, venture capitalists, and investment bankers.

The identification of a GOAL, describes the structure of a system. Everything else becomes subsidiary to that orientation. So the interesting discussions in life are never about how to get things done - we denigrate it as "ops" - but rather, about WHAT THE HELL we want done - we idolise it as "strategy". 

To understand what a COLLECTIVE wants done, one must thoroughly comprehend what its INDIVIDUALS want done. And talent management has this in common with software engineering : both are about software, and both are about talent : it is the same discipline : because humans and machines are both fundamentally information systems, designed to chase goals.

I have a partner who often asks me why I'm always developing new business. Why is present business not good enough? Well my dear, it completely depends on what we're doing business FOR, isn't it?

Earlier today I met a chap in his thirties, a moderately successful fellow, in this jelloesque economy. We talked about how we spend time differently. My view was that it doesn't matter when you make money - you can make it earlier, or later with interest ... but you can't respend any particular year of your life, though that's probably why parents heap so many expectations on poor children. The question is never "should I make X money now, or X money later?" It's not even "why should I make X money now, not Y money?" The question for everyone, everyday, is "er, fuck, the day isn't coming back after midnight - what can I do with it now, so that I will have minimal regrets over the rest of 120 years?"

Economics of Product Design : when the product is a programming language

1. I started work in interpreted languages. The ethos/culture at this level is that there's always "something that will make things faster without losing the GC feature". Hence Java, Go, Rust etc. are in this category of sweets.

2. Now I'm just forcing myself to do C to throw out all the mysterious grey optimisation trade-off questionmarks lock-stock.

3. PLT : in lang(or any)-design, the front-end design matters most ... back-end design is boring : we already know how things work. But if someone sells/ships a poorly DESIGNED product, then it handcuffs the back-end implementation options. This continues to be interesting on a daily basis when I think about langdesign.

4. In general, the design of things is "80% can it be built"; "20% can it be sold". Mistakes in marketing are when people sell3 but can't ship what was promised, or can't maintain it past the gotomarketstage.

As usual : study AAPL

20-80 : catch-pull : money management

 20-80 : catch-pull : applies to investment management too

taking money off the table takes 400% the effort of getting money on it

Stablecoins of America

•  1. Once upon a time, everyone trusted the USA.
• 2. The USA is spooking smart-money, and while smart-money isn't dumping all their US assets, they're definitely dumping some in order to diversify out of USTs.
• 3. The Trump administration's stablecoins-of-America policy is simply a device to harvest dumb-money liquidity so that smart-money can exit first.
• 4. This doesn't mean that crypto is going to crash right away - in fact, it can't, otherwise the smart-money can't exit completely.
• 5. Play the players, and get your money off the table, while you can.

"I want to be a manager"

Chatting with a friend from a bulge bracket bank with 8 layers of management. I said, once anyone moves from the lowest layer into a non-IC, line manager, role : at least 70% of their work should be dedicated to force-multiplication via talent management.

This means board mandates, organisational architecture, project and task definition, role design, candidate search, evaluation, hiring, development, retention, and termination. You need to brain laws. But most companies are bad at this :P

Ruthlessly self-unsatisfied people, rule the business world

The greatest gift my parents gave me : was a sense of infinite boredom. They were/are religious folks, whereas you might say I am agnostic. I did not appreciate the structure of their faith in God - but I did appreciate their epistemic tenacity ... which you might call their faith in their own faith : pure arrogance, summoned and dismissed at will, deployed for either operational, political, or epistemic purposes ( some long-term, some short ). The fact that I live in a politically religious country, may have something to do with all of this, but that's a distraction.

I began adult work, with some basic assumptions, after college some 20 years ago ...

• 1. I was highly privileged, having access to powerful tools.
• 2. Others were less privileged.
• 3. I should live among others to understand them.

... so I did that for that much time, with some breaks in between.

More recently I was talking to a close friend who often taunts me about how, I "have not accomplished much" in life. I thought this was really funny. Step 2 in the Klein sequence is ridicule, following willful ignorance, and step 3 is resistance, so I offered, "well, I considered myself over-accomplished at the age of 20, and so all my time since then has been spent trying to figure out how to carry that accomplishment with some modesty".

I write about this often : the absence of satisfaction, drives much of commercial success. The culture of business is to maximise gain by force, tempered only by socialist tendencies. So ruthless domination of peers becomes a defining factor of winning, and moated comparative advantages are the key to trade-dominance. Ruthlessly self-satisfied people don't get into business ... they go into the arts, and social work.

Read again, the title of this essay.

MPT : reformulating Capital for young audiences

 Top-students in Malaysia need to know, the job market is meritocratic - but the rule isn't "how smart you are" it's "how much money you protect".

MPT : Money, power, and time are the same. You can be a dumb shit, and make lots of MPT by protecting MPT for other people.

You can also be a smart shit, and receive 0 chances to make more MPT, because you are not protecting any significant amount of other people's MPT.

It's inherently political! 

Know the game!

Maybe you don't want to make money.