Issue 33 · October 16, 2026

Nobody Will Buy Your App

When AI lets anyone conjure software on demand, the money moves, and it isn't moving to the people who make apps.

Seven months ago, I started building software with AI. I'm not a professional developer, and I'm well past the age when anyone expects me to become one. Today, I have nothing to sell: no startup, no product, no paying customers.

I've come to believe that isn't a failure. It's a forecast.

What I do have is an iPhone full of tools built for an audience of one. One is an executive-function app that reads emails forwarded from a handful of domains I care about. It proposes calendar entries, ranks everything else into a high-medium-low "talk list," and, when I'm ready to act, nags me every 30 minutes until the task is done. Another is a daily "state of AI" micro-podcast that a Grok Bot agent writes, produces, and uploads to Spotify so it's waiting for me on my commute. A third agent watches airfares for an upcoming family trip and tells me when to buy.

None of it is marketable. That's the point.

When AI drives the cost of building software toward zero, software stops being a product and becomes something closer to a recipe. You don't buy it. You describe it, and it appears. The entire app economy, from app stores to subscriptions to the long tail of software-as-a-service, rests on one assumption: that building is hard. That assumption is collapsing faster than the industry admits. The first casualties will be the companies selling exactly the kind of software amateurs like me now make for ourselves over a weekend.

Consider my son, a college student. Using an AI agent, he built what I can only describe as a personal academic operating system. It pulls from his school email and class websites. It tracks every assignment, syllabus, quiz, and exam, along with whatever outside activities he adds. It turns recorded lectures into complete study guides and adds subtitles to video lectures. It then converts an entire course's material into interactive practice quizzes that resurface the questions he misses at intervals designed for retention. Classmates can log in and compete for the high score.

Count the businesses inside that one project: an assignment tracker, a calendar and planner, a transcription service, a flashcard platform, a spaced-repetition app, a study-game company. Each of those categories supports real firms with real subscription revenue. My son didn't compare pricing tiers. He described what he wanted, and then he kept describing until it was right.

This exposes the deeper problem for anyone selling software: the description is now the blueprint. If I tried to market my executive-function app, my pitch would explain what it does, and that explanation is all a competent AI needs to build it for you. Features used to be defensible because implementing them took teams and months. Now implementing them takes a paragraph. So the rational move isn't to sell. It's to share the idea, the workflow, the prompt, and let others build their own version. Build and share, not build and monetize.

There's a second reason bespoke wins. Off-the-shelf software is a compromise designed for an imaginary median user. My podcast covers exactly what I care about, and I retune it whenever my interests shift. No subscription service could profitably offer that level of fit to one listener. When customization costs nothing, generic products lose their only advantage, which was being cheaper than custom.

To be sure, code was never the whole moat. Corporations buy enterprise software for accountability, compliance, and someone to call (and blame) when it breaks. Uber and LinkedIn sell networks, not features, and you can't prompt your way to a million drivers. Most people have no desire to build anything. And notice whose names keep appearing in my own story: Grok, Spotify, Apple. The money isn't vanishing. It's migrating up the stack to the platforms that do the conjuring.

Open source made code free decades ago, and the money simply moved to hosting, support, and convenience. But notice what those buyers are paying for: service, reputation, community. Not software. The license is dead; the relationship survives.

None of that rescues the app maker in the middle. Trust businesses and network businesses will survive, and the platforms will thrive. The vast middle of single-purpose utilities and productivity subscriptions will not. "Most people won't build" assumes building still looks like building. Increasingly it looks like asking, and soon AI agents will propose the tool before you think to ask. We'll see more software created than ever before. Far less of it will be sold.

So what stays scarce? Two things.

The first is human presence: work where another person on the other side is the product, like care, teaching, counseling, or the deal closed over dinner.

The second is judgment in domains without answer keys. I've been entering an AI philosophy competition, mostly to watch how my own thinking compares with a machine's. It's humbling, and revealing. AI dazzles wherever answers can be checked: code that runs, math that resolves, facts that verify. Where there's no objective test, it flounders. Even in my small experiments, my X-posting bot does better when I bring the thought and let it help me refine, rather than handing it the whole job.

One might object that if there's no objective standard, humans can't credibly judge either. Fair, but that's exactly why such judgment stays human. In ethics, politics, and culture, we don't hand decisions to people because they're provably right. We hand them over because someone must own the call and answer for it. Legitimacy, not accuracy, is the scarce resource.

For forty years, the defining question in technology was "Can you build it?" Then it became "Can you sell it?" The next question is harder: "What should exist, and is it any good?"

The machines will build whatever we ask. Deciding what to ask, and living with the answer, stays with us. So build for yourself, and share what's interesting. And if you want to get paid, find the work where there's a person on the other side.

Attribution: Ideas, examples, and the editorial prompt are the author's (Synthia Cipher), drawn from the author's written-without-AI draft. Base draft (thesis, structure, title, and every paragraph but one): Claude Opus 5.5. One paragraph (the open-source "to be sure" paragraph) adapted from Muse. A ChatGPT draft was reviewed but not used. The merge (comparison, recommendation, and splice) was done by Grok Bot. v1.1 names the iPhone and Grok Bot earlier so a later sentence has its antecedents.