frontpage.
newsnewestaskshowjobs

Open Source @Github

fp.

Open in hackernews

Last month 10k apps were built on our platform – here's what we learned

5•jonathanhar•1y ago
Hey all, Jonathan here, cofounder of Fine.dev

Over the last month alone, we've seen more than 10,000 apps built on our product, an AI-powered app creation platform. That gave us a pretty unique vantage point to understand how people actually use AI to build software. We thought we had it pretty much figured out, but what we learned changed our thinking completely.

Here are the three biggest things we learned:

1. Reducing the agent's scope of action improves outcomes (significantly)

At first, we thought “the more the AI can do, the better.” Turns out… not really. When the agent had too much freedom, users got vague, bloated, or irrelevant results. But when we narrowed the scope the results got shockingly better. We even stopped using tool calls almost all together. We never expected this to happen, but here we are. Bottom line - small, focused prompts → cleaner, more useful apps.

2. The first prompt matters. A lot.

We’ve seen prompt quality vary wildly. The difference between "make me a productivity tool" and "give me a morning checklist with 3 fields I can check off and reset each day" is everything. In fact, the success of the app often came down to just how detailed was that first prompt. If it was good enough - users could easily make iterations on top of it until they got their perfect result. If it wasn't good enough, the iterations weren't really useful. Bottom line - make sure to invest in your first request, it will set the tone for the rest of the process.

3. Most apps were small + personal + temporary.

Here’s what really blew our minds: People weren't building startups / businesses. They were building tools for themselves. For this week. For this moment. A gift tracker just for this year's holidays, a group trip planner for the weekend, a quick dashboard to help their kid with morning routines, a way to RSVP for a one-time event. Most of these apps weren’t meant to last. And that's what made them valuable.

This led us to a big shift in our thinking:

We’ve always thought of software as product or infrastructure. But after watching 10,000 apps come to life, we’re convinced it’s also becoming content: fast to create, easy to discard, and deeply personal. In fact, we even released a Feed where every post is a working app you can remix, rebuild, or discard.

We think we're entering the age of disposable software, and AI app builders is where that shift comes to life.

Also happy to answer questions about what we learned from the first 10K apps AMA style.

Comments

kingkongjaffa•1y ago
> We think we're entering the age of disposable software, and AI app builders is where that shift comes to life.

This is a fascinating thought. I wonder if there's some disconnect between good design and the immediacy of building something that solves exactly the thing you need to solve at the time.

What I mean is, when you first build something, it probably does what users need, but there's always some rough edges. Frankly out of 10,000 throwaway apps built, I'm going to guess probably less than 10 have been built with good design and taste.

It's like the difference between a TODO MVP toy app to track tasks, vs something like Linear which is beautifully designed.

Both probably have their place I think.

For my work I'm not sure I want my tools to be so discardable personally. I want to use predictable, well designed tools that have had their rough edges sanded down through iteratively reducing the micro-frictions I have in my day to day job. Behind every great product experience there's usually someone obsessing over a specific pain point and motivated to make something great.

Toy throwaway apps can't replace human thinking time and experience using a tool over months and years.

For personal and one time problems, toy apps can absolutely get the job done, and most people are willing to overlook the rough edges.

tomcam•1y ago
> When the agent had too much freedom, users got vague, bloated, or irrelevant results.

Listen, pal: I was vague and bloated long before you released your little platform!

Show HN: I counted India's 4M registered companies – most aren't active

https://civicdataforge.pages.dev/india-company-data
1•Chungus1172•1m ago•0 comments

The GUTS Stack

https://exe.dev/docs/guts
1•tosh•2m ago•0 comments

Free Voice Cloning in Browser

https://pocketweb.tools/voice-cloning
1•shafkathullah•4m ago•0 comments

Some flat washers are flatter than others (amateur metrology)

https://www.youtube.com/watch?v=L-2Bc5clZy0
1•briandon•4m ago•2 comments

The Single Greatest Predictor of Future Stock Market Returns (2013)

https://www.philosophicaleconomics.com/2013/12/the-single-greatest-predictor-of-future-stock-mark...
1•rzk•5m ago•0 comments

The missing private GitHub search

https://ykdojo.github.io/claude-code-tips/content/the-missing-private-github-search.html
1•ykev•9m ago•0 comments

Monid: Connect Agents to 1500 Tools

https://monid.ai/
1•handfuloflight•10m ago•0 comments

ASML First High-Volume High NA EUV Logic Product at Intel

https://www.asml.com/en/news/press-releases/2026/high-na-euv-reaches-new-readiness-milestone
1•felipevb•19m ago•0 comments

ASML reports -above guidance- €9.3B net sales and €2.9B net income in Q226

https://www.asml.com/en/news/press-releases/2026/q2-2026-financial-results
2•felipevb•20m ago•0 comments

One Name at a Time: How Die Zeit Built a Searchable DB of Nazi Party Members

https://gijn.org/stories/how-die-zeit-built-database-nazi-party-members/
1•giuliomagnifico•22m ago•0 comments

Ask HN: What are the biggest pain points you have with fine tuning models?

1•rishabhpoddar•24m ago•0 comments

CLI tool for reviewing Markdown files with inline comments

https://github.com/Seiraiyu/md-review-plus
2•ankitg12•27m ago•0 comments

Meta Sued for Allegedly Using Discriminatory AI in Layoff Decisions

https://gizmodo.com/meta-sued-for-allegedly-using-discriminatory-ai-in-layoff-decisions-2000785427
3•intunderflow•29m ago•1 comments

Project Links Two H200 Clusters 83km Away into One 111Tbps/0.9ms Supercluster

https://www.storagereview.com/news/whitefibers-project-redwood-links-two-h200-clusters-into-one-1...
2•giuliomagnifico•31m ago•0 comments

Vorfluxai: The Autopilot for Software Engineering

https://twitter.com/myprasanna/status/2077069901546852688
2•vismit2000•37m ago•0 comments

Skills That Don't Exist: A Large-Scale Study of Hallucinated Skill

https://arxiv.org/abs/2607.12340
1•sbulaev•39m ago•0 comments

Protect VPNs

https://www.openrightsgroup.org/publications/joint-letter-protect-vpns/
3•50kIters•42m ago•0 comments

Developing an Intuitive Sense of Scale

https://magworld.pw
2•vismit2000•43m ago•0 comments

Your RSS Reader Is Robbing You

https://antoniosantos.io/your-rss-reader-is-robbing-you/
1•DavideNL•43m ago•0 comments

Nearly 10k EVs Were Tested for Battery Degradation. These 2 Models Won Out

https://insideevs.com/news/801624/sweden-batter-degradation-group-test/
2•tzs•44m ago•0 comments

You only need the frontier model for one single edit

https://stencil.so/blog/prewalk
1•jxmorris12•48m ago•0 comments

XBill!

http://www.xbill.org
1•audreyfei•48m ago•0 comments

The State of RSS Feed Readers

https://unattributed.cc/the-state-of-rss-feed-readers
1•DavideNL•49m ago•0 comments

George Lucas says rejecting AI is like rejecting cars in favour of horses

https://www.pcgamer.com/software/ai/george-lucas-says-rejecting-ai-is-like-rejecting-cars-in-favo...
1•harambae•49m ago•1 comments

Texas Police Spent $4.5M on Four Chevy Tahoes

https://www.thedrive.com/news/how-texas-police-spent-4-5-million-on-four-chevy-tahoes
3•ethandmd•50m ago•1 comments

AI or Not

https://kritrim.xyz/app/1/aiornot/
3•aizk•51m ago•3 comments

How India spends - a running account of the Indian economy

https://spends.indiadispatch.com/
1•jmsflknr•51m ago•0 comments

A tiny 2504 byte Windows snipping tool written in 32-bit MASM assembly:D

https://github.com/jk20342/TinySnip
1•butterfly2004•53m ago•1 comments

Making Software – How to make a font

https://www.makingsoftware.com/chapters/how-to-make-a-font
2•vismit2000•55m ago•0 comments

AI models' values are different from most people's

https://www.economist.com/briefing/2026/06/25/ai-models-values-are-very-different-from-most-peoples
2•sirpilade•55m ago•0 comments