alt Hacker NewsEveryone who has built software knows that the hardest parts involve making complex, tricky decisions with tradeoffs. Let’s say you make a grocery list app. Now you have to make decisions about all the different ways to specify quantity. Units, weight, dollars, bunches… oh, and fractional vs. decimal weight, etc…
The claim is that now every random person now will build their own app and have to make those hard decisions instead of paying $5 a month for someone else to do that work. Comparative advantage doesn’t just apply to the cost of writing code, but also the effort of making product decisions.
Edit: I don’t mean that a grocery app should cost $5/month, the grocery app was a toy example and the $5/month refers to an example of a separate app you’d pay for with much more value.
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This thread hits very close to home for me. I'm engineering the frontend for a grocery list app as a capstone project right now and I'm handling a lot of the product and feature decisions, and the discussion about "just prompt Claude to build it" versus the reality of those decisions is something my team deals with constantly.
The example of reverse-engineering your grocery store's API and building a custom solution is awesome, and it's exactly the kind of thing that's now possible. But what I've found is that even with AI assistance, there are so many interconnected decisions that make this more than a one-shot prompt project.
I pushed for us to build a mobile app specifically to take advantage of portability (use it at home for planning, at the store for shopping) and the camera (image recognition with OpenAI and scanning barcodes with expo-camera). That sounds simple, but it cascades into hundreds of UX decisions about offline-first architecture, gesture patterns, camera permissions, and more.
The units and quantities problem mentioned in this thread is just the tip of the iceberg. I'm trying to figure out a data model that mirrors how people naturally think about groceries: how they categorize items, how they plan meals versus staples versus impulse buys, how they track what's running low. Modeling those mental models is genuinely hard.
What helps is that I worked as an ecommerce shopper at Whole Foods, and I learned that stores are meticulously organized with numbered bays and predetermined routes optimized for efficiency. Translating that knowledge into a system that can intelligently sort a shopping list based on store layout (which varies by location!) and typical shopping patterns is genuinely complex.
One of my teammates put it well: this is a simple idea, but it requires a level of care, expertise, and experience to get it right. AI's incredibly helpful for implementing solutions once we've made these decisions, but the decisions themselves require domain knowledge, user research, and taste. That's the part that's hard to automate, and it's what makes this a real engineering project rather than a weekend Claude experiment.
Some things are just not suited to an app. It's still easier to jot down a shopping list on a piece of paper than to use an app and a janky mobile phone keyboard. And bonus, nobody gets to sell your shopping preferences or blast you with ads as you're trying to use it!
Exactly. I think only software developers believe AI is going to kill app subscriptions, because they're the ones who can actually wrangle the output into something maintainable.
For anyone without dev or product experience, getting beyond a basic feature set and keeping it running reliably (or roll it out to > 1 user) is still a massive challenge.
Or is the claim that someone will write the app and sell it for $5 one time or give it away free?
A grocery list app is the perfect example of the kind of thing that AI will make obsolete. Why would I pay $5/month for a list app when I can pay Claude $0.30 one time to make it for me?
I in fact did just that. I used Claude to reverse engineer my grocery store's API and build a grocery list app that automatically pulls in the aisle information for each item and sorts it by how I typically walk through the store. It's the kind of thing that would be incredibly difficult to scale but works just fine when you only have one user. No SaaS grocery app can hope to compete with me being able to tailor my own shopping list app to my exact preferences.