ABOUT TECHBREAKDOWNS
I’m Ash Anderson. I built TechBreakdowns for investors who want to understand the business behind a tech stock before deciding whether to own it.
I use maps and visual stories to make the moving parts visible. Then I build models you can change yourself, because a valuation is more useful when you can test the assumptions behind it.
A stock thesis should be something you can see, question, and change.
WHY I BUILD IT THIS WAY
I love drawing the path from customer to owner. Financial statements tell me what happened; a map makes me show who paid, who earned, and what a competitor could take away. If I can’t draw the business clearly, I probably don’t understand it well enough yet.
I love being able to play with a valuation instead of staring at one price target. Change growth, margins, stock compensation, or the price paid for buybacks and see how the possible return responds. The point is to ask what the stock already assumes and where my view could be wrong. These are scenarios, not forecasts.
HOW TO USE A BREAKDOWN
Start with the business, follow its economics, then decide which assumptions you believe.
The opening gives you a customer moment, the business model, a possible advantage and the tension worth testing. In a minute or two, you should know why the company merits a closer look.
Find a company →Trace customers into revenue, costs and the cash or earnings available to owners. Reported flows and illustrative model flows are labeled separately. Banks need a different lens: deposits are customer liabilities, not spare shareholder cash.
Explore company stories →Choose a bear, base or bull case, then change growth, margins, compensation or capital returns. The company page keeps the narrative, annual money flow, detailed inputs and sources together.
Try a model →HOW THE WORK HAPPENS
I use screens to narrow a large universe, then work through the business and the price one company at a time.
What does the product do for a customer? Why do they stay? How durable are the economics, and who is trying to take them?
Follow revenue into owner cash, including the cost of stock compensation. Ask what has to go right for today’s price to make sense.
Separate reported facts from assumptions, revisit the thesis when evidence changes, and leave earlier calls visible. Buying and passing are both useful conclusions.
THE INVESTMENT LENSES
These are frameworks for asking better questions. A label alone never makes a stock attractive.
Cash-generating companies can retire shares. I look at the repurchase price, the cash that funds it, and the share count left after employee compensation.
Growth matters when capital invested in products, distribution and infrastructure can earn an attractive return over time.
READING THE NUMBERS
The diagrams and scenarios are tools for testing a thesis. Their dates and limits stay visible.
Bear, base and bull cases are assumptions, not predictions or assigned probabilities. The annualized return is a price-return sensitivity over the model horizon, before personal taxes.
A modeled money flow may normalize a year to $100 of revenue. Category allocations and margins can be analyst estimates. The full valuation also accounts for cash, equity compensation, shares and funded buybacks where relevant.
A bank model values earnings after funding costs and credit losses; customer deposits are not added to shareholder value. Buyback announcements are not cash already spent, and gross purchases can differ from net share retirement.
Reference prices and operating inputs are dated research snapshots. Changing a slider does not update a quote or filing. Your edits run in the browser; reloading restores the published case.
THE DATED RECORD
The Cannibals and Reinvestors model portfolios show dated entries and results under two different investing lenses. They are a way to follow the decisions and the evidence after a company first looks interesting, with the live record kept separate from historical screen research.
Explore the model portfolios
ABOUT THE AUTHOR
I’m a software engineer and a lifelong markets enthusiast. I started writing about stocks in the early days of The Motley Fool and later wrote for Seeking Alpha. My product and engineering background shapes the questions I ask here: why people use something, what makes it stick, and how that turns into cash for the owners.
I care about the downside as much as the upside. A great product can still be a poor investment if the price assumes too much. TechBreakdowns is my public working notebook for thinking that through.
START EXPLORING
Start with a market map, open a company story, or move the assumptions in a model. See where your own view leads.
TechBreakdowns publishes independent research and illustrative, dated models. Nothing here is personalized investment advice.