In this update, we will cover our thinking on the threats to SaaS in the age of AI. In the next installment, we will discuss the defences that SaaS companies can use against these threats, and finally, the opportunities that AI offers to technology businesses (they’re big).

Let’s start with an extremely brief summary of what we know so far.

The end of coding (as we knew it)

In November of 2022, OpenAI released ChatGPT. Although large language models had existed previously, the nature of the ‘Chat’ implementation was revolutionary in its ability to maintain the context of a conversation. ChatGPT was also immediately useful for computer programming questions, albeit with a lot of mistakes and hallucinations.

New models continued to be released, with ever-increasing capability, and the next big leap was the release of the first ‘reasoning’ model called o1, again from OpenAI, in September 2024. Reasoning models use additional inference to ‘think’ for longer and to plan a series of steps. This allows the LLMs to handle radically more context and produce far more advanced outputs. Again, this was particularly useful in computer programming.

A few months later, in February 2025, Anthropic released Claude Code, whereby the LLM acted as an ‘agent’ able to autonomously write and improve code itself (with human supervision) directly from the same terminal that a computer programmer would typically use.

The leaps in programming capability over the past few years have been astounding.

For anyone who was coding before 2022, the process was to have an idea of what you wanted to build, to write some code, hit an error or problem, and then figure out a way around that problem. Coding was a battle of logic and perseverance. It was overcoming one problem after another, all leading to solving the much bigger and more complex problem of what you were trying to build.

When stuck with a software bug, one of the tools that programmers leaned heavily on was Stack Overflow – a forum where coders could ask and answer questions on programming. Typically, someone else had already asked your question beforehand, and so you could often immediately find the answer you were looking for (or something close to it) without even having to ask your own question. It was a wonderful two-sided network, and it became core to the daily life of a developer.

However, over the past few years, that has all changed with the rise of LLMs and then coding agents.

AI’s immense disruption of software is perhaps best shown in the number of questions asked on Stack Overflow over time:

As of early 2026, the Stack Overflow era is over.

I can attest to this with my own programming journey. In 2018, after teaching myself to code, I set out to build a web app to ‘process’ ASX announcements and send me (and any other user that signed up) alerts based on certain keywords, etc. This took me months of learning and coding in my nights and weekends to build. I would be stuck on a single problem for a week, writing and rewriting code to figure out one bug, only to unlock the next level of bugs. It was rewarding, but wow, it was a painful slog at times.

In late 2023, I rebuilt much of the functionality with AI again from scratch in a few weeks. In 2025, I rebuilt everything (with a few improvements and with AI-powered summaries) in a few days.

Last week, in 2026, I rebuilt this same functionality but vastly improved it, including a way for me to chat with an AI agent about the database, from scratch, in a single evening. And this time, it’s not really fair to say that I built it. In truth, I asked my coding agent to build it, and then it built it, shaped a little by my feedback along the way.

The end of coding was perhaps best captured by this bittersweet tweet from Aditya Agarwal, former CTO of Dropbox.

Writing code is now free and abundant.

Writing code, the prized and scarce competence that we told kids to study to guarantee a high salary, is now free and abundant.

There are huge positives to this, and when things become free and abundant, there are always immense fortunes to be made. The miracle of software is that it is ‘infinitely replicable at zero marginal cost.’

Well, now software is also ‘infinitely producible at zero marginal cost.’

And it’s not just software. Although code may be the ‘tip of the spear’ for AI capabilities, AI agents are rapidly developing competency in all sorts of knowledge work, from writing, drafting PowerPoints, and analysing Excel spreadsheets. For the purpose of this post, we’re going to focus on software, but we think that many of the most attractive investment opportunities will come from other areas, like applying AI to services.

As we mentioned at the top, we’re going to focus on the threats in this update, but Enterprise SaaS businesses do still have many defences that we will touch on in our next update. Even better, we think some (those we own) actually have an immense opportunity to leverage AI to grow even bigger.

But for today, the threats.

The Threats

Free and abundant code provides several disruptive threats to the traditional Enterprise SaaS business model. We’re going to outline five prominent ones:

#1: I Did It My Way: The Rise of Self-coding Customers

This is commonly derisively called ‘vibe-coding,’ but we mean something bigger than that; by self-coding, we mean any customer that decides its software is something that is worth doing themselves.

For any business resource, a company must decide if it is better to build it themselves or to buy it. When it comes to software, this has been an easy decision for most businesses for the last few decades: unless you had some expertise in software development, it was almost always better to buy than to build.

A primary driver of this was the pace of technological change. Moore’s law and continuous technological improvements meant that to have decent software, you had to constantly invest in improving and updating it. It also meant that to be competent enough to create it, you had to constantly invest in improving and updating your own software writing skills.

If a plumbing supply business wanted to have great warehouse management software, it had to be both great at plumbing supply and great at software development.

Put simply, if coding hadn’t changed much in the last hundred years, then it would have become an easily learnable skill, and many more companies would have managed it internally. For example, customer service is a very important business process, but most businesses run it internally because they get some benefits (learning more about what their customers like) without many drawbacks (versus outsourcing).

As software becomes free and abundant to produce, it makes it easier for businesses to build the code they need to run their business internally. This ranges from a business hacking together a ‘good enough’ self-coded solution for a non-critical piece of software, to a large complex business that already has a dedicated dev team and builds some of its own software deciding to move even further into building all of its own.

So far, the impact has only been seen with simpler software, what is often called a ‘point solution,’ such as a piece of software whose entire job is to check if an email address is real. There are millions of little ‘point solution’ pieces of software like this that businesses may use (such as to run a mailing list). These small SaaS businesses, usually too small to be publicly listed, are already being replaced by self-coding.

The damage has been limited to these simple solutions because the coding agents themselves could only handle a certain amount of context before they got confused and began to spiral.

The big change that came in December was a combination of better models, bigger context windows, and simple new innovations like automatically compressing and compacting projects to maintain coherence. The result was that the level of software that could be self-coded increased dramatically.

We are still not at a point where it is easy for a customer to self-code something as complex as an Enterprise resource planning system used by thousands of employees across multiple countries. But the direction of travel is important.

We can think of the build versus buy decision in Enterprise software as a landscape, where software complexity is the elevation above sea level. Everything below the water level represents software that businesses can build themselves.

Before AI coding agents, the number of software jobs-to-be-done that could be built internally was pretty small—perhaps just a few Excel macros and bespoke scripts at most businesses. But over time, as AI agents increase in ability, the water level rises, and more and more complex tasks could now conceivably be self-coded.

The question now isn’t whether AI coding agents will keep getting better. With model size increases and other innovations that expand context windows, they almost certainly will.

It’s whether the before and after will look like this, with most software still outsourced to Enterprise SaaS providers:

Or this, with only the most complex and defensible SaaS being immune:

With more complexity comes a greater threat to Enterprise SaaS because it becomes increasingly possible for a business to develop its own software without having to invest in also being great at developing software.

But as anyone who has tried cutting their own hair knows, just because something is technically possible, doesn’t mean it’s a great idea.

Taking the small-business accounting software platform Xero as an example, it’s possible that AI coding agents will keep progressing to a point where a tradie small business owner customer could self-code a replacement AI platform. But there are a lot of reasons to think that it would be both a bad idea, and the tradie would much rather pay someone else to do it so he could get back on the tools.

So in Xero’s case, self-coding does indeed seem to be a limited threat. It could possibly limit pricing power for the marginal customer, but for most of their small business customers the hassle and risks of self-coding would outweigh the advantages.

For larger Enterprise software providers with sophisticated, giant clients that already have some technology capacity internally? Well, that might be a different story.

#2: Ultra-lean Startups: Your Margin Is My Opportunity

Another obvious threat, as building software trends towards being free and abundant, is from a new wave of ultra-lean startups.

One of the defences for large Enterprise SaaS businesses previously was that software took a lot of money, and most importantly, a lot of time to build. AI coding agents mean it is now feasible for an ultra-lean small team of developers (say 5-12 people) to use a swarm of AI coding agents to replicate a large SaaS product.

Since the total cost to replicate the SaaS product has fallen, this new startup now requires less total revenue to earn an attractive return on its investment. This means the ultra-lean startup could offer its product at a significantly lower price than the incumbent. It also means that the new startup only needs to win a much smaller number of total customers to continue covering its costs and keep sniping away at the larger player.

On its own, we don’t see this threat being particularly damaging for most SaaS businesses. The margins in SaaS have always been absurdly attractive at scale, and we don’t usually see customers switch due to price alone. But we mention it because this change alone could conceivably reduce the pricing power for an Enterprise SaaS product.

Looking at Xero again, their strategy (and valuation) prior to this latest AI-driven selloff had become heavily based on pricing power—i.e., aggressively increasing prices by 10–15% a year. This is where ultra-lean startups are most threatening in our view, not in killing an existing business, but in limiting their ability to raise prices aggressively by making it dramatically cheaper for a competitor to enter the market at a lower price.

It would only be the marginal customer that switches due to price, but over time, that incremental churn threat can add up to limit the ability for a large Enterprise SaaS player to ‘raise the rent’ forever.

#3: Watch The Flanks: The Threat From Horizontal Entrants

Related to Ultra-lean startups, we see a more dangerous threat coming from large technology businesses that decide to expand horizontally into new areas.

As software becomes more abundant, what is stopping an online stock broker like Robinhood also offering personal tax management software? Or DoorDash stepping into offering restaurant Enterprise Resource Planning software? Or Stripe expanding into small business accounting software? (hello Xero).

What might have been seen as a distraction before now becomes much more viable if the software build can be accomplished by a small internal team. Imagine that the ultra-lean startup team is instead working for a giant in a related space with deep pockets and existing distribution relationships with customers. Any incremental revenue from the same client is a bonus, and it allows the horizontal entrant to more deeply integrate into their customer’s operations.

This is also an opportunity of course for any given Enterprise SaaS business, if they can be the ones that expand horizontally (or vertically) into another business’s turf and eat their lunch. But the net result is likely to be greater competitive intensity and once again, investors need to be much more selective over carefully picking winners.

#4: AI-native Startup: Built Different

Like the ultra-lean startup, this is the threat of a new entrant to the industry. But unlike simply doing the same old SaaS but at a lower cost-structure, the AI-native software startup has built a product that serves the same customer job-to-be-done, but in an AI-first way.

To give a Xero example, an ultra-lean startup competitor would be offering small business accounting software, but cheaper. An AI-native startup may offer something more akin to the accounting service itself, with most of the jobs (reconciling bank feeds, payroll, etc.) automatically performed, and the software interface only used to handle edge cases.

Or alternatively, it could be offered as an accounting service (with some humans involved by AI) but heavily powered by AI to lower the total cost, and with some type of dashboard software for the customer to pull reports.

These are obviously not happening today, but they are probably on the edge of what is already possible in our view, with how far AI agents have already progressed.

#5: Pure Agentification: The Omega Threat

We mentioned this one last because it requires continued development of AI models over the next few years. We aren’t there yet, because the AI models acting as agents just aren’t good enough. But if agents continue improving at a similar pace to recent years, then we think this is the direction of travel.

Pure agentification would occur if your primary way of getting a particular job done is to talk to your favoured leading-edge AI model, whether that is OpenAI’s ChatGPT, Anthropic’s Claude, Google’s Gemini, or if you’re particularly edgy, Elon Musk’s Grok. The AI model would then operate everything itself, talking to other software as needed, and liaising across multiple technology and service providers to get things done.

This single ‘Super Agent’ would be trusted with access to all of your most sensitive data, all of your queries, discussions, and questions; it would connect to all of the services that you use, and it would bring the world’s most advanced artificial intelligence to bear on solving the problems that you care about most.

Taking the Xero example again, a Super Agent would connect to your banks directly (probably through open banking, or just by using your browser) to ingest data, it would connect to the ATO through a portal, it would connect to your point of sale provider, and your payroll, and it would just get things done.

Since the Super Agent has access to not just your accounting software, but to everything, it is likely to be much more powerful and useful than any AI built into your accounting software could ever be. It could also do work for you, not just ‘accounting’ tasks, but administration and operations - the kind of thing that you might have hired someone to do before.

In this scenario, Xero may still exist at the lowest level of the stack as a ‘system of record’ that the agent uses, but it relegates the importance of that software and thereby the customer’s willingness to pay. Over time, it could also threaten to disintermediate Xero by displacing it as the system of record itself.

Again, it is worth noting that this is not possible today. But with frontier labs set to invest over a trillion US dollars in capex over the last year and this one, they will be hungry for more revenue streams to justify all that investment. The biggest economic pie of all is to directly replace both workers and the tools that they use by performing a job directly.

This is obviously a massive threat to many businesses (and many employees!) which is why we are calling it the omega threat. But there are several defences available, and we think there are some businesses that will be particularly hard for the frontier labs to crack. We also think that there are some businesses outside the frontier labs that are set to be massive beneficiaries of this if it does indeed materialise.

But we will leave those thoughts to the next installment!

In Conclusion

The threat that AI poses to Enterprise SaaS is multi-faceted. The days of blindly buying anything Enterprise SaaS and winning are over. But that doesn’t mean that many Enterprise SaaS businesses won’t survive or even thrive in this new environment.

Enterprise SaaS has been the king of business models for many years, but the best returns came during the initial period of disruption in the 2010s. We are again entering one of those periods of disruption, and are immensely excited for the hunt to find the new emerging leaders.

The King is dead, long live the King!

I am republishing now because I want to write an update on geopolitics soon and to refer to this. It is pretty clear now that the ‘Hemispheric Empire’ team won - The Department of War is literally tweeting stuff like ‘This is OUR HEMISPHERE - or is at least currently winning. So I feel like with almost a year’s hindsight, some stuff was pretty on the money. Anyway, here it is, the original piece from April 2025.]

The world is watching the United States unleash a global trade war. Markets are tumbling. Allies are confused. Analysts are scrambling for logic to understand what the plan is.

But logic won’t help. Not here.

Because this is not a conventional presidency, and there is not a conventional plan. There are many plans that are fighting for dominance and that are championed by different groups. Some of these plans overlap with each other, while others are in conflict.

Trump Presidency 2.0 is a medieval aristocratic court dressed in modern clothes.

Around the King, rival factions battle for influence. Some dream of empire. Others, deregulation. Still others wage war over culture itself.

Throughout history, a court of advisors has always formed itself around the ruling King or Queen. The courtiers would vie with each other for power and influence over the King’s decisions, whilst always ensuring - if they were smart - that they never outshone their master.

Trump acts in a way that means many have compared him to a King, yet few seem to make the obvious connection to the King’s Court. In this analysis, we’ll focus on each group’s support for (or opposition to) the recent trade war announcement.

We expect this framework will come in handy over the next four years of the current Trump administration.

There are five major courtier groupings within Trump’s Court that we see; and for each we’ve listed the most visible champion.

1. Tariff-walled alliance - Howard Lutnick

2. American empire - Steve Bannon

3. Revamped American-led order - Marco Rubio

4. Deregulation bros - Elon Musk

5. Culture warriors - Elon Musk

These are just the biggest and most visible groupings; everyone in Trump’s inner circle, including his family, is a courtier too.

An individual courtier can also belong to more than one group, as Elon Musk shows by being a senior player in both the Deregulation Bros and the Culture Warriors. Individuals also shift over time. Think of the groups like an alliance in an episode of Survivor: continuously shifting and reforming.

For now, we count five big groupings, but this could change over time if more groups emerge (or existing groups are sidelined).

Tariff-walled alliance

In our view this is currently the most influential group in Trump’s court. The broad tariffs on the whole world that were announced on April 2nd support this argument - although the next few weeks will likely be crucial for evaluating this group’s influence.

The tariff wall plan would see America put very high tariffs on every country that is not part of the alliance (like what was announced on April 2nd).

The U.S. would then offer allies the opportunity to join the trade alliance.

To join, a country must adopt the U.S. level tariff on every other non-alliance country. For example, if the U.S. has a 54% tariff on China, and Australia wanted to join, then Australia would need to also apply a 54% tariff on China (and match every other U.S. tariff on every other country).

In exchange for this, the allies get to keep U.S. military protection and also get access to lower tariff rates to the U.S.

The military protection part is really key here because it is what makes it an alliance and not just a free trade agreement. It is closer to an empire than a trading bloc.

The leading proponent of this view seems to be US Commerce Secretary Howard Lutnick, though Scott Bessent also appears to be in support.

In a private meeting at the Australian embassy in Washington in late February, Lutnick briefed Australian government and business leaders, including seven superannuation fund senior representatives, on what they should expect from the U.S.

The room was shocked by what they heard from Lutnick, as outlined in an AFR article written based on recollections of those present:

“Lutnick spoke about building a tariff wall. Allies and friends – such as Australia – could choose to be inside or outside the wall…Lutnick said much of Trump’s trade strategy was aimed at Beijing. So far, this includes a doubling of tariffs to 20 per cent, but this is only an opening shot in a trade war that could go much further unless Trump and Xi Jinping cut a deal.”

Meanwhile, the analysts looking at these tariffs through the lens of economic efficiency are saying that they make no sense. And they’re right!

These tariffs don’t make sense under an efficiency lens because for this group, that’s not what they are for - the tariffs are to prepare the United States (and her allies) so that they are capable of opposing China geopolitically. The tariffs are about building resilience and capacity, not efficiency. Ultimately, they are about preparing the United States to be able to fight a great power war, if it came to that.

To fight a major war, a country (or at least its allies) must be able to quickly manufacture all of the weapons needed for that war, while also being able to produce all of the goods and services that its society depends on.

Right now, the United States can’t do that, and in this group’s view, that needs to urgently change. Hence the dramatic April 2nd announcement.

If this group continues to hold the favor of the King then we should expect to see the U.S. begin to offer allies the opportunity to go “behind the tariff wall” and Australia may be offered a stark choice: start a trade war with our biggest trading partner in China, or lose American security protection.

This is not the only group pushing for a strong tariff wall. In fact, one group wants to go much further.

Hemispheric empire

The Hemispheric empire is one of the most radical groups, but just because it is radical doesn’t mean it isn't influential.

This group is championed by Steve Bannon, and at the beginning of the Trump 1.0 administration Bannon was initially so influential that he was on the cover of Time Magazine and was often thought to be the real power behind Trump’s throne.

Outshining the master is a fatal flaw for any courtier (watch out Elon!), and Steve was soon dismissed from Trump’s Court and pushed out of the administration altogether.

Bannon didn’t go away, though, and continued to influence the MAGA narrative and online idea space. Today, Bannon is often called the ‘Godfather of the MAGA right’.

One of the core tenets of Bannon’s worldview is the importance of white Christian culture and spheres of influence. This focus on race, tradition, and religion means this group is quite fond of Putin’s Russia which it sees as a natural ally with white Christian values. To them, a “woke” Europe is, in many ways, a key enemy.

However, an even bigger enemy for this group is China, which it sees in a civilisational battle against the U.S. This group doesn't want a rules-based order. It wants an old-fashioned empire.

How influential is this seemingly radical group? Well, it is notable that Russia wasn’t on the tariff list for the recent Liberation Day announcements (Ukraine, meanwhile, received a 10% tariff).

For this group, a tariff wall would be just the start of something that looks much more like an old school empire. Ideas like the U.S. annexing Greenland or Canada might sound wild, but for this group, they aren’t. This group believes that might makes right, and wants the U.S. to be the mightiest empire of them all.

Here’s Steve Bannon talking to a Canadian interviewer about Trump’s proposal to make Canada the 51st state of America: “Let me be brutally frank. Geo-strategically, you don’t really have an option [but to join us] if you want your sovereignty because from the north, from the Arctic, it’s going to get encroached in a great power competition that you don’t have the ability to win.”

Bannon refers to this as ‘Hemispheric defence’ with the United States controlling North and South America, along with Greenland; the ‘Western Hemisphere’.

So, to the extent that this group is influential, we can expect it to support the Liberation Day tariffs (and more).

Revamped American-led order

If you liked the rules-based international order that has largely maintained peace over the past 80 years, and led to historic human flourishing around the world, then within Trump’s court, this is the group for you.

Most mainstream republicans would fall into this group, which wants to largely maintain the current rules-based order, but with a few changes. It wants to get the trade deficit down, and it could get behind a few targeted sanctions based on reasoned plans. This group also wants to pivot America’s focus toward China, and get Europeans to pay more for their defence. But it doesn’t want to ally with Russia either.

This group wants change, but the changes it wants are incremental, measured, manageable and organised.

Within Trump’s inner circle, the champion of this group is Marco Rubio, who appears to be fighting to maintain some kind of American-led rules-based order amidst an administration with quite different goals.

This group is generally very influential in the formal corridors of traditional power such as the Senate, but so far seems to hold less sway in the Trump administration.

We will know that this group is winning if the Liberation Day tariffs are quickly rolled back and replaced by specific targeted tariffs on particular industries.

Deregulation Broligarchs

This group wants deregulation. It is composed of elite billionaires, typically tech billionaires, who are sick of bureaucrats getting in their way.

While several other groups are focused on the world order, this group doesn't really care if there is a rules-based order, or who runs it, just so long as whoever is in charge doesn't interfere with their businesses.

This group loves the idea of the DOGE (department of government efficiency) because they see democratically elected governments as just another service provider to their empire, and they want their service provider to be cheap and efficient.

This group is not in favour of tariffs. In fact, they are actively against them. Not for any noble reasons about the value of international collaboration or fairness, but because tariffs are a tax, and taxes are bad for business.

All of the pro-Trump tech-elite fall into this group. Marc Andresson is a notable figure, but this group is also championed by Elon Musk. The tech elite were a very influential group in getting Trump elected. Musk alone donated US$288 million to Trump’s Election campaign and is obviously extremely influential.

This group is already breaking ranks on the tariff issue, with both Elon Musk and Bill Ackman speaking out on the tariff policy being misguided. Musk is even openly attacking the motivations of Peter Navarro, one of the intellectual champions of the tariff-wall alliance group.

These battles are normally subtle and indirect, but there is now an open war in the King’s Court. This is a big deal because they could be at the vanguard in halting or reversing the Liberation Day tariffs, if their lobbying of the King is successful.

Although Elon is the leader of the deregulation broligarchs, it isn’t even his main motivation. For Elon, it’s really all about culture.

Culture Warriors

This is a big and influential group, especially online. Some analysts think that the MAGA movement itself is best thought of as an online cultural movement.

The culture war is all about those U.S. battles that anyone who is even a little online will be all too familiar with. Stuff like DEI programs, transgender sports participation, ESG mandates, etc.

Elon has said his main motivation in supporting Trump was to “destroy the woke mind virus” after his son came out as transgender and disowned him.

Culture wars explain a lot of the early moves at DOGE, which has, thus far, seemed to focus much more on rooting out cultural opposition groups in government (like DEI committees) and not so much on genuine efficiency programs. U.S. Aid was completely disbanded as it was seen as supporting a plethora of progressive causes. The Department of Education is next on the chopping block, and again because of its role in shaping culture.

Understanding the culture war group is useful when considering where DOGE will target next, but so far it has been a neutral player on the tariffs issue.

The cloud of personal patronage (or what critics call grift)

Sitting around and on top and inside of all of these groups is a cloud of personal patronage whereby individual courtiers petition the King for decisions which will personally enrich or benefit themselves. This is inevitable in any royal court, although it does appear to be more widespread in this one than in most.

This cloud of patronage doesn’t appear to have much of a role in the tariffs so far, but keep an eye out. If the U.S. starts to negotiate individual specific exemptions to the tariffs for particular countries, industries, or businesses, then patronage could be a factor in which ones win an exemption.

The Wild King

Finally, we have the King himself. Trump is a particularly interesting King because he is also a wild card.

Some powerful rulers are heavily committed to a particular worldview. Putin, for example, seems genuinely committed to the idea of restoring the Russian empire, and his public comments are steeped in hundreds of years of historical references.

Trump does have his preferences. He clearly likes tariffs, for example, and has for decades.

One of his favourite quotes is “Tariff is the most beautiful word in the dictionary.” This love of tariffs is how he has attracted so many other tariff fans to his court.

However, Trump also doesn’t appear to be a fanatic of a particular ideology. He just doesn't seem to care about that stuff, much.

Take the current moment: last Wednesday evening, Trump dropped the biggest change to the global order in 80 years with his Liberation Day tariffs on almost the entire world. He then went and played golf for a few days.

This lack of commitment to any particular ideology provides a lot of room for the courtiers to influence him in a wide range of different directions.

Dropping a bombshell and then driving away in a golf cart while the courtiers all squabble over what happens next is also the kind of power move that a Wild King loves.

Layer on top of this that Trump enjoys being unpredictable. Before becoming President, Trump was the world’s biggest reality TV star. He has a natural talent for gaining attention, and in order to keep getting attention, he needs to make increasingly shocking and outlandish statements.

Some of Trump’s wildest ideas (like ‘Trump Gaza’) could have originally come from a particular courtier (in this case, son-in-law Jared Kushner is suspected), but they can also be seen as Trump reaching for something shocking to dazzle his audience and reel their attention back in. As the audience gets used to each level of shock, the next announcement needs to be even more shocking in order to keep grabbing attention.

In Trump 1.0, the Wild King was surrounded almost entirely by mainstream republicans that would fit into the Revamped American-led order camp. Trump might make some wild statements, but these advisors limited his freedom of movement, at times actively working to limit his most extreme moves.

Today, however, in Trump 2.0, the Wild King has a wide open space for movement, and plenty of courtiers that will encourage him to move even further in certain directions.

This wild-card attention-grabbing makes it difficult to read too much into any policy announcement. To see if a new wild policy has legs, it is more useful to consider if the policy matches one of the leading group’s interests.

Trump also likes to make a big first ask in a negotiation, so no matter which team ultimately wins out, it is likely that the announced tariffs are a high water mark for what gets negotiated for most countries.

The Tariff Battle

This framework means that we shouldn’t think of the Trump administration as a single entity, but as an aristocratic court with groups that rise and fall in the King’s favour.

We should, therefore, expect that where these tariffs land will depend on which team is winning. This is useful when we process a particular piece of news flow to determine what it means.

For example, Steve Bannon is openly at war with Elon Musk calling him “a parasitic illegal immigrant” who doesn’t respect “the country’s history, tradition or values”. If Elon Musk is pushed out of Trump’s court, that would be a big hit to the Deregulation Broligarch team, and we can then expect that it is more likely that the high tariffs stick.

Conversely, if mainstream Republicans find their voice and start denouncing the tariffs, then that would add weight to the Revamped American-led order group, and we should expect the tariffs to be watered down.

This framework also means that we should not be analysing the Liberation Day tariffs purely in terms of economic efficiency. Several of the key groups - including the currently leading ‘Tariff-walled alliance’ do not appear to be primarily driven by economic efficiency, but rather by geopolitics, resilience, and ultimately preparation for a potential war.

If the market continues to fall, then we can expect that to add to the support for those groups that do care about economic efficiency (like the Deregulation Broligarchs). And so this man-made sell-off could be self-correcting.

Although this framework can’t predict which group will ultimately win, it does allow us to respond quickly to process any news. A King’s Court is driven by power politics, personalities, and the clash of warring worldviews, much more than any sober rational analysis. Reading Machiavelli or watching a series of Survivor is better preparation for understanding what is happening than brushing up on our Excel modelling skills.

In this court, policy is not forged by principle, but by proximity to the throne. The tariffs may rise or fall, not by logical analysis, but by who whispers loudest in the King’s ear. And so, investors must do what every courtier has done for centuries: read the room, watch the throne, and never forget, this is a game of power, played with real-world stakes.

The King plays golf. The courtiers draw swords. The empire holds its breath.

Thankfully, there is a better way that is lying dormant within us. This alternative approach has the potential to improve almost every area of our lives. For investors, it also happens to be the best way to identify the businesses that have the potential to generate huge, life-changing returns.

To understand what’s at stake, let’s start with the story of Chairman Mao vs. the sparrows.

Mao’s Tragic Mistake

In the late 1950’s, China’s leader, Chairman Mao Zedong faced a challenge. China’s population was growing rapidly and China needed to boost food production so that some farmers could be freed up to go work in factories. This would be the first step on the journey to becoming a major industrial power. 

To boost food production, the government aimed to identify all the ‘problems’ that limited China’s food production, and eliminate them. One of the biggest 'problems' identified was nature itself. Sparrows—along with rats, flies, and mosquitoes—were targeted for elimination. The logic was simple: sparrows eat grain seeds, and so if we kill all the sparrows, we will have more grain.

The ‘Smash Sparrows’ campaign was stunning in its ambition and scale. Everyone from the age of five upwards was mobilised. School children built ladders to tear down their nests. Millions of people hunted sparrows with nets, guns, and sticks. Citizens were encouraged to beat pots, pans and metal drums to scare the birds from landing, forcing them to keep flying until they died from exhaustion.

Estimates are that the campaign led to the death of over a billion sparrows. Problem solved.

But sparrows don’t just eat grain. 

Sparrows also eat bugs. 

With the collapse in the sparrow population, locust numbers surged as their natural predator - sparrows - were no longer around to keep them in check. 

The locust plague that ensued was one of the major contributors to the most horrific famine in modern history. Between 1958 and 1962 China’s famine saw an estimated 20-40 million people starve to death. To call it a famine understates the horror of what happened; it is better described as an apocalypse.

Author Yang Jisheng painstakingly documented the horrors in his 500-page book, Tombstone:

"People died in the family and they didn't bury the person because they could still collect their food rations; they kept the bodies in bed and covered them up and the corpses were eaten by mice. People ate corpses and fought for the bodies. In Gansu they killed outsiders; people told me strangers passed through and they killed and ate them. And they ate their own children. Terrible. Too terrible."

This was one of humanity’s darkest moments. 

Underlying the horror was a fatal assumption. The famine was one of the most extreme examples of what can happen when we make the tragic mistake of assuming that a complex adaptive system is merely a complicated one. 

Complex, not merely complicated

This is a jet engine.

A jet engine is extremely complicated. But a jet engine is not complex. 

A complicated system has many interacting parts, but each of those parts behaves in a predictable way with a clear linear relationship between cause and effect. This allows us to predict what a complicated system will do if we change a single part. It is a miracle of engineering. 

A complex system is a whole different beast, and beast is often the best way to think of a complex system - it is more like an emergent organism in its own right than a passive and lifeless system. 

There are several characteristics that set complex systems apart. 

The relationships between the parts of a complex system are often non-linear. This means that small changes in one variable can have large and unpredictable effects across the system as a whole. This is commonly known as the butterfly effect.

Complex systems are often highly sensitive to ‘initial conditions’ and exhibit vastly different outcomes from small differences in starting points. ‘Initial conditions’ means the state of the system at the time of interaction. If this concept is not clear, try asking your toddler to stop pouring juice on their plate to ‘see how much can fit’ when they are fresh after a great night’s sleep versus when they have just been dragged screaming from the Kia Carnival after a long internment at daycare. This experiment will highlight the sensitivity of a complex system to initial conditions. 

Complex systems also typically display emergent properties that arise from the interactions of different parts, but which are not predictable from properties of the individual parts themselves. Worker ants are simple creatures individually, but at the colony level the ability to build complex structures emerges.

Complex systems are often adaptive, they evolve over time in response to changes in their environment and have feedback loops that enable them to self-organise to maintain system stability.

These characteristics combine to make a complex system inherently unpredictable, dynamic, and, in a sense, alive. 

Going through this list can make complex systems seem like something magical and special. And they kind of are. But they also are not at all. Because complex systems are all around us.

The weather is a complex system. The economy is a complex system. Your backyard is a complex system. Your dog is a complex system. Your family is a complex system. Your workplace is a complex system. Your after-work volleyball team is a complex system. Your body is a complex system. Your bloodstream is a complex system. Your eye is a complex system.

You are a complex system.

Complex systems are everywhere around us. Almost everything, and indeed everyone, that matters to us, is a complex system. 

And yet. 

And yet, we are all guilty to varying degrees of making the same mistake as Chairman Mao. We treat these complex systems, with all their vast depth of interconnectedness and emergent properties, as if they were merely complicated. 

Once we understand that the world around us is mostly complex, and not merely complicated, it becomes clear that we need to change our way of interacting with that world. 

Each type of system, complicated and complex, is best served by a different mode of attention. 

A complicated system can be accurately analysed by a narrow and focused attention on each of its individual parts. This is because a complicated system is equal to the sum of its parts.

A complex system by contrast is more than the sum of its parts, it cannot be understood by breaking it down to its parts. A complex system requires a mode of attention that is broad and open, and that looks at the relationship between parts as they connect together into an integrated whole. 

We need a narrow focused attention, but we also need a broad and open one. 

Lucky for us, nature has provided us with both.

Your forgotten brain

As outlined by Dr Iain McGilchrist in his masterful book, The Master and His Emissary, evolution has provided us with two modes of attention, a narrow focused attention that is primarily associated with activity in our brain’s left hemisphere, and a broad open attention that is primarily associated with activity in our brain’s right hemisphere.

The evolutionary driver for both forms of attention can be simply explained by our role as both predator and prey. We evolved a laser-sharp narrow focus so that we could zero in on hunting our prey. Meanwhile we also evolved a broad awareness of our environment so that we could sense danger and avoid becoming someone (or rather something) else’s lunch. 

If we used our brains as evolution intended then we would inherently understand the nature of the complex adaptive systems that surround us, and how best to interact with them.

The problem is that we, both individually and as a society, are now massively over-indexed to use our narrow left hemisphere mode of attention without engaging our broad right hemisphere mode. 

One way that this imbalance toward narrow-mode manifests itself is our adoption of a ‘problem-solving’ mentality where we focus on a single part of the system that we consider to be a ‘problem’ and attempt to eliminate that problematic part at all costs.

This was the madness of Mao’s approach.

The problem with problem-solving

If we were only dealing with complicated systems, a narrow fixation on problem-solving would be fine. 

If a jet engine has a faulty component, you remove that problematic part, and replace it with a new one. This works great. Problem solved. 

But complex systems are just built different.

The interconnected feedback loops, non-linear outcomes, emergent properties, and sensitivity to initial conditions mean that when we narrowly focus on eliminating one problem in a complex system, we almost always create another problem in another part of the system. Sometimes those other problems are small. Sometimes they are monstrously large. 

Problem-solving squeezes the balloon, only for it to bulge out somewhere else.

This problem-solving approach is failing everywhere around us. We invent a GLP1 pill to eliminate food cravings, in a system that is built to encourage people to crave processed food. We build prisons to lock up troubled youth alongside career criminals, while we leave the social structures that grew them untouched. In finance we create esoteric synthetic derivatives in an attempt to eliminate risk while laying the foundation for the next crisis.

In all these cases we are assuming a simple linear cause and effect relationship between the problematic part that we are targeting for elimination and the result we want, while ignoring that in a complex system, everything is connected to everything else.

The result is a patchwork of band-aid solutions stacked on top of band-aid solutions, as the solution to one problem creates another problem to be solved.

Even at its best, problem-solving, by its very nature, can only ever remove something we don’t want, it can’t create something we do want. 

A Whole Brain approach

There is no single answer to how to nudge a complex adaptive system towards the outcomes that we want. And that is kind of the point. Each system is both unique and itself constantly adapting and changing. 

The optimal approach requires understanding the whole system and its current state, in its own right. Like tending a garden we cannot force the system to grow in the direction we want, but with the right care we can nurture it to flourish to its highest potential. 

This system level thinking is the domain of our brain’s right-hemisphere. Millions of years of evolution gave us the broad and open mode of awareness that holds the key to building the systems that we want. 

We urgently need to return to a whole brain approach, and yet we have forgotten how. If we can do so we will have the best shot of reaching our highest potential in our lives, in our businesses, in our investing, and in our communities. 

This substack will be using investing as the lens by which to understand how we can shift to a whole brain approach in understanding the world. 

Investing is a good lens, to invest well requires understanding the most complex systems that mankind has created. Investing is also a domain that gives us loud (though noisy) feedback to tell us over time whether our understanding of reality is correct. And yet, today, finance and investing, like most of our world, is dominated by the kind of narrow linear thinking that is causing most of our troubles. We’ll be working to change that. 

For those that love investing, shifting to a whole brain approach is also the best way to identify the extreme outlier performers that I call Monsters. The small group of companies that generate insane, life-changing returns for shareholders. As Tom Morgan presented at Sohn so brilliantly, this mindset shift is the difference between analyst and PM, and between satisfactory and legendary. In future articles we’ll be digging into the practical and applied steps to implement a Whole Brain approach to understanding business and investing.

For those of you that just want to understand the world and how we can encourage its flourishing, there’ll be plenty for you too. And you might even pick up a few investing ideas along the way. 

We need a Whole Brain approach more than ever. It starts with each of us developing a holistic approach in our own thinking. This allows us to avoid Mao’s tragic mistake and begin to build the world we want. 

Let’s do this.

References:

This piece would not have been possible without the work of several others that I would strongly recommend you check out if this interested you. 

, founder of The Leading Edge has done more than anyone I know to put the hemispheric theory on the map in the world of finance. Tom’s radical openness and vulnerability has opened doors where there were only walls. 

Dr Iain McGilchrist and his incredible body of work on understanding the brain’s two hemispheres forms the foundation of much of what is discussed here and what we’ll be talking about in future articles. 

William Oliver, co-founder of InPractise. Will is an exceptional human that has helped connect so many dots for me personally and to navigate what can be a treacherous path of openness while remaining level headed.

intuits the right hemisphere approach in her substack writings so well and was particularly helpful in putting this piece together.

Robert Fritz, author of Path of Least Resistance along with many other books outlines the problem with Problem Solving and structural dynamics. In future pieces we’ll be exploring how well his work integrates a whole brain approach.

Dr. Daniel Siegel’s work on integrating multiple fields resonates deeply with our Whole Brain approach. If you are looking for a path to be more Whole Brained in multiple aspects of your life, and particularly as a parent, his body of work is a must.