For the last decade, the unspoken social contract of the $1,500-to-$2,000 computing ecosystem was simple: you weren't just buying aluminum, glass, and silicon. You were buying an entry ticket to a world-class software ecosystem.
When you dropped two grand on a flagship device, a massive chunk of that margin was justified—at least spiritually—by the thousands of hours of human engineering poured into the operating system and the third-party apps that ran on it. You were paying for senior systems architects agonizing over frame pacing, UI designers obsessing over spring animations, and domain experts translating complex workflows into rock-solid native code. Craftsmanship costs money. We accepted the hardware tax because the software inside the box was bespoke, high-effort human labor.
Then came the Great Automation.
Over the past twenty-four months, CEOs across the valley have tripped over themselves on earnings calls to brag that 30%, 50%, or 80% of their production code is now written by large language models. They laid off tens of thousands of engineers, slashed QA departments, and replaced entire localization and frontend teams with automated agentic pipelines. The cost of generating a line of code has collapsed by 99.7%.
Which leaves me, the person standing at the checkout counter with a credit card, asking a basic economic question: If the code running on these machines is now mass-produced, zero-marginal-cost AI slop, why am I still paying $2,000 for the privilege of running it?
The Ikea Shrinkflation of Silicon Valley
Imagine walking into a high-end furniture showroom. For years, they sold you a $2,000 dining table because a master carpenter spent three weeks hand-carving solid walnut and joining it with mortise-and-tenon joints.
Now, imagine you walk in today, and the salesperson beams with pride: "Great news! We fired the carpenter. We now extrude sawdust and glue through an automated press in four seconds. The table warps if you put a warm mug on it, and sometimes it spontaneously grows a fifth leg in the middle of the night. That’ll be $2,200, plus a $19.99 monthly subscription to keep the legs attached."
You would laugh them out of the building. Yet this is the exact economic model of consumer technology right now.
Software has undergone the most aggressive ingredient substitution in industrial history. We went from hand-rolled, architecturally reviewed native code to stochastic parrot output—what is essentially the high-fructose corn syrup of logic. When a company replaces a $250,000-a-year senior engineer with a $0.10-per-million-token API call, their R&D overhead plummets. In any functioning competitive market, when the cost of production drops through the floor, consumer prices follow.
Instead, hardware prices are hitting all-time highs, and Federal Reserve data shows "computer software and accessories" inflation surging at a record 73% annualized clip. Where did the deflation go?
The Debate: Why the Suits Say You Still Owe Them Two Grand
If you corner a hardware VP or a SaaS founder after their third Negroni and ask why we are paying luxury prices for automated garbage, they will give you two defenses:
- "You are paying for the outcome, not the keystrokes." They argue that consumers shouldn't care how the sausage is made. If an app manages your finances or edits your photos, does it matter if a human wrote the Swift code or an LLM regurgitated it from a training set of scraped GitHub repos? Plus, they argue, the $2,000 device price is driven by physical realities—DRAM and SSD prices have spiked over 130% this year because hyperscalers are hoarding every memory wafer on earth to build data centers.
- "AI makes the software do more." By automating the boilerplate, teams can supposedly ship 10x the features in half the time, giving your $2,000 machine unprecedented capabilities.
Let’s dismantle both of those right now.
First, the memory shortage driving up my phone and laptop prices is caused by the very AI infrastructure generating the slop. Asking consumers to pay a supply-chain premium on RAM so tech giants can build more clusters to replace human software engineers is like a burglar charging you for the crowbar he used to break into your house.
Second, we aren't getting "10x the features." We are getting 10x the surface area with 0.1x the structural integrity. You do care how the sausage is made when the sausage is full of glass shards. You feel the absence of human engineering every time your native OS settings menu stutters, every time an update breaks basic Bluetooth routing, and every time a core utility app balloons to 1.4 gigabytes because an unmonitored coding agent imported three separate Chromium instances to render a toggle switch.
The Value Extraction Trap
Here is the cold truth: AI was never deployed to make software cheaper or better for you. It was deployed to convert engineering payroll into executive margin.
When you buy a $2,000 machine today, you are no longer buying into a curated garden of human ingenuity. You are buying a gilded, anodized-aluminum trough designed to feed you the lowest-cost, highest-margin digital gruel corporations can legally ship. The hardware is an immaculate, 120Hz OLED theater; the play being performed on stage is written by a mad-libs generator and directed by nobody.
If the industry wants to treat software as disposable, zero-cost synthetic filler, then the ecosystem needs to be priced like it. Give me a $300 dumb-slab to run your $0.02 machine-generated code. Until then, don't ask me to pay Michelin-star prices when we can all hear the microwave beeping in the kitchen.