Alpha with AI is now my full time work.
I have stepped back from client projects. A few existing engagements continue, and
everything else has stopped. From this month my entire working week goes into this
publication: reading filings, tracking the macro picture, and researching businesses
one at a time.
I have never laid out in one place what the paid side of this publication actually is.
That is what this post does. There are also two things landing in the next two weeks
that are worth knowing about before they arrive.
HOW I INVEST
Most analysts I have worked alongside took the standard route: theory first, the
certifications, then markets. I came the other way around. I was investing my own money(parent’s money if I’m honest) before I ever studied the discipline formally, and I later managed client money in direct equities. That order shaped how I work. I care less about elegant models and more about whether I can defend a position when it trades well below my cost.
Three questions decide every piece of research I publish.
Is the macro with the business or against it? Interest rates, the capex cycle, regulation, trade policy. A good business in a hostile cycle can stay cheap for years,
and I want to know which side of the cycle I am standing on before I read anything else.
Can earnings actually grow from here? Not the story, the arithmetic: the revenue
drivers, the margin structure, what management guided and what it then delivered. Over any period that matters, share prices follow earnings.
What is the business worth against what the market is asking? I value the whole
company, set it against the price, and insist on a margin of safety wide enough that I
can be wrong about something and still come out whole.
And one filter on top of all three: I only hold businesses I am comfortable holding
through an earthquake. If a falling price would shake me out of a position, the
research behind it was never finished.
WHAT PAID SUBSCRIBERS GET
3-4 AI workflow editions a month. The research systems I use to
produce all of the above. These deserve their own section, just below.
2-3 Research Dives a month. One company per dive, US-listed and other global names.
I read the filings myself, rebuild the numbers, and put a value on the business with
the working shown. Each dive ends with a decision: I am buying it in the model
portfolio, I am waiting at a lower price, or I am declining it. The declines get
published too. Knowing why I walked away from a popular name is worth as much as
knowing what I bought.
The equity model portfolio. Every dive decision is executed in the model portfolio
on publish day and stays on the record, wins and losses alike. You can audit any
position back to the research that created it. This is the book today:
Every buy and sell sits in one running ledger, oldest first, linked to the dive that
caused it:
The watchlist. For every company I have fully researched, my valuation and the
level where I would add are on record before the market moves. When a selloff comes,
the decision is already made. Below the researched names sits the radar: the companies
waiting their turn for the full work:
WHAT AI PRIME ACTUALLY IS
The workflow editions need their own explanation, because the word “prompts” undersells them badly.
I am a fundamental investor who has used AI in my research every working day for more than two years shamelessly, and the workflows are where the two disciplines merge: investing principles first, AI built around them. Each published edition is the survivor of a longer process. I take one research problem, experiment with several approaches to it, burn millions of tokens testing them against real filings, and throw away the versions that break. What gets published is the one that held up, end to end, with the exact prompts.
So what you receive is not a prompt collection. It is a tested research system with the
failed experiments already paid for. I have read what gets published on this platform
about AI and investing, and no one is doing this work the way it is done here. That is
also why this tier is priced the way it is: 3-4 new editions arrive every month, and
the library already holds more than forty.
Workflows like this: take your pick.
SIX COMPANIES WENT ON THE WATCHLIST THIS WEEK
A company earns a watchlist row when I can name the specific thing the market is
worried about and the evidence that would settle it. Six businesses earned one this
week. The names are in this week’s paid note. The businesses, so you can see the ground this list covers:
an ice cream company that owns about three million freezer cabinets standing in shops it does not own
a company that gets paid for decades every time certain jet engines come in for
servicingthe company that built the weight loss drug market, now playing catch-up in it
a Japanese maker of the miniature ball bearings that robot hands will need
the maker of the unglamorous chips that run the locks, the battery and the radar in your car
an armoured truck company that collects cash from shops and ATMs
The paid note covers all six: what each business does, what broke, and the number I am waiting on before the full research begins..
THIS WEEKEND
A new AI post is on the way. It is an important one, especially if you have implemented at least one of my workflows. More on that when it ships.
THE BOOK IS JUST GETTING STARTED
The model portfolio is six weeks old. Four positions, and more than 90% still in cash.
That cash is about to go to work. The dives now come at full-time pace, and over the
coming months I intend to deploy most of that cash, possibly all of it, into businesses
that pass the three questions above. Steadily, and aggressively when the research earns
it.
Whatever the pace, the care stays the same. We are in a bull market, and I treat it as
a prudent bull market. There is an old rule about being careful about who you go into business with. Buying a share is going into business with a company, and every name that enters this book passes through exactly that level of care.
Joining now means being in at the start of the record, with the cash still waiting and
every decision published with its reasoning as it happens.
One more thing, briefly. Most of my own investing over the years has happened outside the US, and only a very small portion of my personal portfolio was in the US market, so I largely missed the US rally of the last two years. Apart from my other portfolios, I have now started managing a new family account in the US market, where I will deploy slowly and steadily. Paid subscribers will be able to see those positions too, kept fully separate from the model portfolio.
WHAT IT COSTS
This post is free in full, so you can judge the work before paying for any of it.
A word on these numbers. I restructured the offering this month. The research tier,
the dives, the model portfolio and the watchlist, is now priced at a fraction of what
this work cost here earlier. That drop is deliberate but it is not permanent.
AI Prime is the exception, for the reasons laid out above. Its price does not drop.
What it carries today is a temporary reduction, and it returns to its original price
soon. If the workflows are what you came for, the arithmetic favours joining before that happens.
Here is what the next two weeks hold on the paid side: the full note on the six
companies above, the model portfolio acting on its written levels if the market touches
them, and the AI post. The free half of every edition will keep reaching you either
way. The story is in the free half. The numbers, the valuation and the decision sit in
the paid half.
If you have been reading the free halves for a while, you already know whether this
work is for you.
And a last word for those who were paid subscribers before this restructure. The AI
workflow editions are becoming exclusive to AI Prime, and you have been moved to AI
Prime at no extra cost, as the thank you for backing this early. You keep access to
everything. If you paid the earlier full price, your renewal is being adjusted down to
the current AI Prime price as well; that conversation with Substack support is already
underway.
*Disclaimer: Alpha with AI covers US-listed and other global securities for
educational and research purposes only. Everything in this edition is my personal view
and, where stated, my own portfolio action. None of it is investment, legal, or tax
advice, a recommendation to buy, sell, or hold any security, or tailored to anyone’s
situation, and I am not a registered investment adviser or research analyst. The
valuations here are my opinions with the method shown, not price targets or calls to
act. The model portfolio is a model book, tracked on notional capital, and is not a
record of real trades. I may hold or take positions in the securities discussed, my
views can change without notice, and when they do, you will read about it here. Every
figure traces to a primary public filing, accession numbers on file, but filings can be
misread and models can be wrong, so verify against the source before acting on
anything. AI tools, including Claude Code, were used in the research and drafting of
this edition, with every number checked back against the filed documents. Investing
carries risk, including the loss of capital. Do your own research and consult a
qualified professional in your jurisdiction before making investment decisions.*
Financial Clarity. Insightful Ideas.