Tech Economics

The features generating the most revenue are often the ones companies least want you to understand. Here's the economic logic behind the concealment.

Loss leaders are how grocery stores move milk. In tech, they're how companies buy entire industries and lock out competition permanently.

The FBI's Sentinel project ran years late and hundreds of millions over budget. The reason wasn't bad engineers. It was a lie everyone agreed to tell.

Tech companies don't just slow old devices. They engineer upgrade pressure through software, security, and ecosystem design working in concert.

The data advantage that keeps Google, Meta, and Visa untouchable isn't something they built. It's something you handed them.

Recessions don't kill good ideas. They kill the bad ones crowding them out. Google's 2001-2003 playbook explains why.

Planned software obsolescence isn't a bug or lazy engineering. It's a revenue architecture, and once you see the structure, you can't unsee it.

Microsoft's Windows 11 compatibility requirements didn't emerge from engineering necessity. They were a revenue mechanism disguised as a security policy.

A 4TB hard drive costs less than $100. Cloud storage at that scale runs hundreds per year. The gap isn't about hardware. It's about what storage actually is.

A premium domain and a free subdomain look similar in your browser's address bar. The economics behind them couldn't be more different.

The messiest parts of a dominant tech product are often its best competitive defense. Feature debt isn't a bug in big tech strategy. It's the strategy.

The price difference between a streaming service and a DVD isn't about convenience or costs. It's about what companies learned when they finally had the power to end ownership.

The economics of planned obsolescence favor software degradation over hardware buybacks. Here's the actual math behind that choice.

The real mechanism forcing hardware upgrades every few years isn't a conspiracy. It's structural, and understanding it changes who you blame.

A server costs the same to build whether one person uses it or a million. Software doesn't work that way, and that asymmetry explains almost everything about tech pricing.

Intentional slowdowns during high traffic aren't engineering failures. They're calculated business decisions with real financial logic.

Tech IPOs don't cluster in bull markets by accident. The Federal Reserve's rate decisions reshape the math that makes a public offering worth doing at all.

Venture capital's most durable mental model isn't a spreadsheet. It's a simple ratio that predicts fund returns before a single product ships.