• Daily headlines are loud; structural trends change the world quietly
• Technology transforms markets – human psychology remains constant
• Quick update on projects I"ve been working on…

Let"s set the scene with a story…

In 1849, hundreds of thousands of people rushed to California chasing gold.

They showed up with picks, shovels, and the quiet conviction that they were about to get rich. Newspapers ran front-page stories about spectacular discoveries. Entire tent cities materialised as fortunes were made overnight.

But the reality was most miners didn"t strike it rich—they went home broke and disappointed. The tents were packed up almost as quickly as they came.

But one young businessman noticed something the prospectors completely missed….

Levi Strauss wasn"t looking for gold. He was looking at the people looking for gold.

He quickly observed that miners tore through their clothes at a rapid rate, shredding denim climbing hillsides and knee-deep in riverbeds.

Strauss started making hard-wearing pants reinforced with copper rivets—solving a very real, physical problem every single miner had, regardless of whether they struck it rich.

In today"s language, you would say Strauss established "product market fit."

More than 175 years later, nobody remembers the names of the miners who pulled fortunes out of the dirt. However, today everyone knows the name Levi Strauss.

And whilst the gold rush may have been a rags-to-riches story for a few lucky miners, it was really a story about human behaviour.

Human emotions such as excitement, optimism, speculation, and the deep-seated belief that life-changing money could be made overnight drove their behaviour.

This belief and hope pulled thousands of people to places like San Francisco.

Strauss just stepped back and asked a simple question: what is every single one of these people going to need, no matter who actually finds gold?

Today"s gold rush is Artificial Intelligence (AI).

Most of us are fortunate enough to live through at least one of these spectacles.

The advent of railroads, electricity, and the internet were similar booms.

While they"re happening, they feel entirely unprecedented.

They create massive, once-in-a-lifetime opportunities—and they reliably convince smart people that every rule from the past has expired.

For example, listen to the media and I"m sure you will hear someone claim "… but it"s different this time."

Yes, the technology is different and transformative.

And it will continue to change our lives in ways we don"t yet understand.

But there is something which does not change—human nature.

I will explore this more below….

Before we get to that – regular readers will notice I haven"t written a post in over a month.

During that break, I"ve been reading the usual flood of market commentary — from massive AI infrastructure buildouts — to China"s shifting economy — to sticky inflation reports, changes to monetary policy, oil spikes as a result of the war in the Middle East and geopolitics.

And whilst it"s often tempting to share my thoughts on the "noise" —it struck me that everyone is telling the exact same story they"ve always told…

Ignoring the Noise

Imagine sitting down with a newspaper in 1996…

The front page would be dominated by the usual mix of elections, interest rates, foreign conflicts, and quarterly earnings reports.

However, tucked away somewhere in the journal is a story about a fledgling online bookstore called Amazon.

Question: what headline mattered more that day?

Was it the election result? The market hitting a new high? A war happening in the middle east? Cisco reporting record profits due to the massive build out of infrastructure required for the Internet?

I"m sure each of these headlines were important – but history tells us that this obscure website quietly went on to upend global retail.

That is how structural change always plays out.

However, markets have always had a habit of chasing whatever is making the most noise.

Consider some of the headlines over the past few weeks:

• Oil supply bottlenecks from the war in the Middle East;
• Trump"s new 12.5% tariff announcements;
• A hotter-than-expected inflation print;
• Fed likely to hike rates as bond yields surge;
• Hyper-scalers increase their capex estimates etc

I am not saying that each of these events do not matter. But they are almost always symptoms rather than the root cause.

From my lens – I see the global economy is slowly reorganizing itself:

• China isn"t trying to be the world"s cheap assembly line anymore; it wants to lead in core technologies like AI;
• AI is graduating from a science experiment into baseline infrastructure, much like the grid or broadband before it;
• Supply chains are now regionalising (becoming less global post COVID); and
• Governments are becoming more interventionist (sadly) – taking equity stakes in strategic industries.

None of these shifts happen in a single week or finish in a year.

And that precisely is why they matter.

But despite this – investors will typically obsess over next month"s CPI print; what the next Fed decision will be; or try to forecast a target for the S&P 500.

Why?

Because those numbers are measurable and right in front of us.

But far fewer people will spend time asking what the world is going to look like ten years from now. That is where real investment fortunes are built.

Innovation Rarely Rewards the Obvious Winners for Long

Whenever a major new technology shift emerges, most investors make the same mistake.

That is, they assume they can spot the ultimate winners right out of the gate.

But the reality is most will almost always guess wrong.

Let"s go back to our 1849 gold rush story in California…

It was the merchants supplying the ecosystem who built much more durable fortunes than the people chasing the raw asset.

Technology investing follows the same rhythm.

• When railroads swept across America, the initial mania centered on the railway operators themselves. Eventually, the real economic winners turned out to be the steel mills, retailers, and manufacturers whose shipping costs collapsed, unlocking entirely new business models.
• Electricity followed the same playbook. Early investors piled into generator companies and power stations. The massive economic windfall arrived decades later when factories completely re-architected their physical layouts around electric motors instead of steam shafts.
• The internet looked like a pure networking and hardware play in the late 1990s. Early winners were companies like Cisco, Intel, and Nortel etc. However, the ultimate winners were Google, Apple, Amazon, Microsoft and Meta – who came up with the very compelling use-cases.

For example, it was use cases such as (not limited to) internet payments, cloud storage, logistics, security, advertising and streaming that have produced enormous cash flows for these companies.

Did anyone map out that exact evolution in 1999?

Of course not.

Artificial intelligence is very likely to march down the same path.

For the last couple of years, every conversation has centered on chip designers and a handful of mega-cap tech giants. And the ripple effects are obvious:

• Utilities are scrambling to meet surging power demands
• Industrial firms are retrofitting factories
• Healthcare companies are rewiring diagnostics; and
• Software companies are quietly embedding intelligence into decades-old products.

The lesson of innovation isn"t about who invents the breakthrough (or the next frontier AI model).

It"s about who quietly figures out how to use it better than everyone else.

History suggests those are rarely the same companies.

Human Nature is the Only Constant

Technology evolves at a breakneck pace.

Working in Silicon Valley the past ten years with Google in the AI space – I would often comment that "one quarter felt like a year" in terms of the pace things evolved.

Despite the rapid change – we also find that markets adapt and economies cycle.

However, human psychology rarely changes how it"s wired.

Benjamin Graham wrote in The Intelligent Investor that an investor"s worst enemy is usually looking right back at them in the mirror.

He published that in 1949 however it could have been written today. Warren Buffett and Charlie Munger would often echo this observation in shareholder meetings.

I"ve been investing for roughly thirty years…

I started in the early stages of the dot.com boom (mid 90s) – feeling all the emotions I described earlier. It was incredibly exciting.

Needless to say, my emotions did not serve me well. Initially I made money buying stocks like Cisco and Netscape – however by 2001- I had given it all back (and more).

My profits turned to losses.

That said, I consider myself extremely fortunate to have invested (and worked) through the boom and busts of 2000 and 2008. They taught me things that no university degree ever could.

What I learned is there is nothing more important than what happens between your ears.

Think about it – every market bubble starts with a kernel of truth:

• Railroads genuinely did transform America.
• Radio genuinely did revolutionize communication.
• The internet genuinely did reshape commerce.
• Artificial intelligence is genuinely changing how businesses operate.

No-one is arguing that AI isn"t transformative. And I honestly feel it will be bigger than the internet.

But the danger isn"t the underlying technology — it"s the human behavior that rushes in to exploit it.

• Excitement slowly hardens into certainty.
• Certainty breeds overconfidence.
• Overconfidence relies on leverage.
• Market prices detach from operational reality; and eventually
• Reality catches up.

This is a pattern that repeats. For example, we saw it with each of:

• The Nifty Fifty in the 1970s
• Japanese equities in the late 1980s
• The dot-com mania
• Pre-2008 housing bubble; and more recently
• The mania (and gradual bust) in cryptocurrencies

But here"s the thing — it doesn"t always take a massive financial crisis to spark a correction.

What typically happens in these cycles is expectations simply grow so bloated that they become mathematically impossible to satisfy.

Today, we observe (super) leveraged single-stock ETFs, momentum chasers piling into whatever hit a new high yesterday, and wild valuation swings for companies with loose ties to AI.

But what remains constant?

The emotions of fear, greed, envy, fear of missing out, and hope.

Despite all our algorithms and AI tools to make "better" investing decisions — the market is just a giant room full of humans trying to outsmart other humans.

If you agree with that premise – it means psychology will forever matter just as much as cash flow, profitability and balance sheets.

Putting it All Together

One of the hardest mental hurdles in investing is accepting that 90% of the daily noise deserves none of your attention.

If you could convince people of that – the business models of CNBC, Bloomberg, Wall Street Journal (it"s a long list) would collapse.

Their entire business model thrives on market noise and your emotions… with shows literally called "Fast Money" (and similar).

That doesn"t mean geopolitical conflicts, inflation, and political shifts don"t matter.

They do.

But markets possess a remarkable capacity to absorb short-term shocks while quietly compounding wealth for people who keep their eyes fixed on a longer horizon.

The person who spent the last ten years sweating every geopolitical headline likely ended up stressed and underperforming.

The person who spent that decade tracking structural shifts—software, cloud computing, demographic trends, or the boring execution of exceptional businesses—almost certainly did fine (e.g., Buffett with Apple).

Markets don"t reward the person who consumes the most news. They reward the person who can reliably tell the difference between signal and noise.

There"s an old military maxim that generals always prepare to fight the last war.

Investors tend to do something similar; i.e., burning energy explaining why the previous correction happened while completely missing the slower, quieter currents shaping the next twenty years.

The biggest opportunities rarely announce themselves with breaking news alerts. They arrive quietly and can feel uncomfortable. And in most cases – look downright boring. Buffett invested in Apple eight years after they invented the iPhone.

They demand patience long before they reward brilliance.

The good news is that patience doesn"t require a genius IQ — it"s available to everyone.

If someone asked me what matters most for long-term investing, I wouldn"t point you to interest rate projections, oil prices, or the latest frontier AI model. I"d point you to the lessons from history:

• Technology changes civilizations for the better.
• Innovation always spreads much further than its creators initially imagine.
• Human beings consistently overreact in both directions; and
• The most important tool in your kit is a healthy dose of humility.

A few years ago, when I was at Google, I had the chance to meet Vint Cerf—one of the foundational architects of the internet.

I asked him what he and his colleagues failed to see coming back in the late 1970s and early 1980s.

His answer was simple: "While we could see millions of computers connected across the globe, we completely missed the mobile phone and the power of a computer in everyone"s pocket."

The point is the future is unknowable. Bezos didn"t see AWS when he was thinking about creating an online book store. And Google didn"t see the mobile phone when it was indexing the web in the year 2000.

The headlines will shift and the tech giants who lead the market today will eventually be replaced (read this).

But the core pillars of long-term success—owning productive assets, thinking in decades, ignoring the noise, and keeping your own psychology in check—have survived every war, recession, and technological revolution of the last two centuries.

They will likely outlive the next two as well.

Things I"m Working On…

Since leaving Google in August last year – I took time to reflect and think about projects I wanted to work on. A couple of updates:

• I accepted a role as Board Chairman of a technology start up. We raised $800K in seed capital earlier this year; and about to raise another $2M (pre Series A – we expect in ~12 months). This business is transforming the highly fragmented online rental industry. In less than 12 months – we"ve signed up over 500 businesses with ~5,000 items. GMV at ~$1.2M.
• I"m also looking to join two other companies in either a Board or Advisory capacity. One in the security software space; and the other creating 3D virtual twin environments.

I"m open to these kinds of roles and discussions (technology or otherwise). Let me know if you"re think there"s a good fit – happy to chat.

Beyond that, I"ve been working on a personal (investment) project.

Long-term readers will know I"m passionate about finding high quality companies which trade at reasonable (fair) valuations. This begs two important questions:

1. How do you determine quality?
2. What is reasonable or fair value?

As I"ve shared on this blog over the past decade – I lean into the proven frameworks of Buffett and Munger.

Ideally there would be website (or tool) which can answer the metrics I specifically want in an easy to absorb fashion.

For example, on one page show a company"s 5 to 10-year track record of profitability and operational efficiency; historical valuation ratios relative to today; measures of how well companies are deploying incremental capital etc). That does not exist (that I have seen).

A few come close (e.g., Value Line and Gurufocus) – but they don"t quite meet what I need.

~16,000 lines of code later (which isn"t finished) — the tool is getting closer.

Below are some indicative screenshots (bearing in mind the user interface will change based on testing and user feedback — this is a first draft)

My goal is within 10 minutes – an investor with limited experience – should be able to get an informed view on whether the company is worthwhile following up at the current price.

For example, you will be able to answer questions as:

• 5 and 10-yr performance metrics; e.g., ROIC, ROE, FCF, Profitability Margins;
• 5 and 10-yr valuation history vs forward valuations;
• Evaluating long-term trends and how the Trailing Twelve Months compares;
• What is its ROIC vs ROIIC? The level of capex intensity?
• Balance sheet strength and level of interest coverage?
• Share buy-back trends. Are they issuing stock or buying it back?
• What percentage of profit stays as real cash?
• Peer comparisons for each key metric in its sector (as well as the sector average for that metric)
• 12-18 month analysts forecast and how wide is consensus?
• Does the fundamental data support these forecasts?
• What"s investment signals can be derived from the trends in such things as free cash flow, capex, valuations, returns on capital and margins?

These questions are not exhaustive and are illustrative of what I look for when it comes to finding a quality business.

For example, if I look at Google, my tool is reporting data points such as:

• Severe decline free cash flows (flagging a capex cycle);
• P/FCF valuations well above its historical average (with earnings valuations in line)
• Growing proportion of capex as a function of its revenue;
• Downward pressure on its ROIIC during its infrastructure build out etc.

That said, its earnings and revenue growth, gross margins, balance sheet, profitability etc are outstanding by any measure — giving the company one of the highest quality scores of the ~1,400 stocks I track.

The "quality score" I developed ranks specific profitability and operational metrics I think are most important (based on Buffett"s criteria).

For example, metrics such as free cash flow, return on capital and equity, operational consistency and the quality of its balance sheet. It balances its long-term track record and recent trend.

Once we know a company is of sufficient quality – we turn to what the market is asking us to pay.

Here I share both historical and forward P/E; P/FCF; EV/EBIT and Buffett"s own P/OE.

From my experience, it"s not difficult to find high quality business. However, it"s often very difficult to find them at a reasonable price (especially today).

Perhaps what I like most is the tool also me to rule out lower quality (and highly speculative) companies. Based on the way I invest – that is critical.

I was very close to launching the site last week.

However, after running an audit, I noticed a couple of quirks.

It turns out the Wisesheets data I pay for contains a small number of errors. And whilst these errors are generally few and far between – it"s frustrating to find them.

As a result, I"m writing a script which pulls data directly from a company"s SEC EDGAR 10K submission — to verify each of the 60 metrics I deploy.

It"s a lengthy process (as not all companies report the same way) – but it"s worthwhile.

When I eventually launch – I will be sure to let you know. And from there — I will centre more of my blogs on finding quality stocks at reasonable prices (using my tool to guide the decision making process).

Regards,
Adrian Tout