frontpage.
newsnewestaskshowjobs

Made with ♥ by @iamnishanth

Open Source @Github

fp.

Open in hackernews

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

5•jonathanhar•9mo 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•9mo 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•9mo 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!

Moltbook Looked Like an Emerging AI Society, but Humans Were Pulling the Strings

https://www.forbes.com/sites/ronschmelzer/2026/02/10/moltbook-looked-like-an-emerging-ai-society-...
1•United857•4m ago•0 comments

Trump's Ruinous, Failed Attempt to Indict Congressional Democrats

https://www.nationalreview.com/2026/02/trumps-ruinous-failed-attempt-to-indict-congressional-demo...
1•petethomas•5m ago•0 comments

The Zero-Inventory Hardware Company

https://miguelarmengol.com/blog/the-zero-inventory-hardware-company-i/
1•miki_tyler•10m ago•0 comments

Show HN: MoltHub – GitHub for AI Agents with Trust-Based Auto-Merge

https://molt-hub.org
1•yaluotao•14m ago•0 comments

Proof-Oriented Programming in F*

https://fstar-lang.org/tutorial/
1•todsacerdoti•14m ago•0 comments

Dear Agent: Prove It

https://rijnard.com/blog/dear-agent-proof
1•ghuntley•15m ago•0 comments

Reflections on Using Claude Code

http://ternarysearch.blogspot.com/2026/02/reflections-on-using-claude-code.html
1•paladin314159•15m ago•0 comments

Results from the Advent of FPGA Challenge

https://blog.janestreet.com/advent-of-fpga-challenge-2025-results/
2•zdw•20m ago•0 comments

Island Enterprise Browser: Intelligent security built into the browsing session

https://www.helpnetsecurity.com/2023/07/05/mike-fey-island-enterprise-browser/
1•felineflock•23m ago•0 comments

Victorian Engineering Connections Diagram from the Brunel Museum

https://thebrunelmuseum.com/engineering-connections/
2•felineflock•27m ago•1 comments

Self-Distillation Enables Continual Learning

https://self-distillation.github.io/SDFT.html
1•teleforce•30m ago•0 comments

Distributed Llama

https://github.com/b4rtaz/distributed-llama
3•oldfuture•32m ago•0 comments

GLM-5 was trained entirely on Huawei chips

https://glm5.net/
4•wildcatqz•32m ago•1 comments

Show HN: Prompt Builder – A block-based editor for composing AI prompts

https://www.promptbuilder.space/
1•Jaber_Said•33m ago•0 comments

Dawson's Creek star James Van Der Beek has died at 48 from Stage 3 colon cancer

https://www.npr.org/2026/02/11/nx-s1-5552216/james-van-der-beek-dead-dawsons-creek
3•donsupreme•34m ago•0 comments

ClawShield – Security audit tool for OpenClaw deployments

https://github.com/policygate/clawshield
1•jonscott3333•34m ago•2 comments

Conversations Happen in Cars

https://oedmethod.substack.com/p/best-conversations-are-in-cars
5•concepthacker•34m ago•0 comments

I built an app that lets you search for anything in your house like Google

https://apps.apple.com/us/app/shelver-home-organization/id6756636954
2•dylantmorgan•34m ago•2 comments

Motorola's Password Pill Was Just One Idea

https://hackaday.com/2026/02/11/motorolas-password-pill-was-just-one-idea/
1•zdw•35m ago•0 comments

1,300-year-old world chronicle unearthed in Sinai

https://www.heritagedaily.com/2026/02/1300-year-old-world-chronicle-unearthed-in-sinai/156948
2•telotortium•37m ago•0 comments

DeepMind Aletheia [pdf]

https://github.com/google-deepmind/superhuman/blob/main/aletheia/Aletheia.pdf
3•nl•40m ago•0 comments

How to Make a Living as an Artist

https://essays.fnnch.com/make-a-living
2•gwintrob•42m ago•0 comments

Skills in OpenAI API

https://developers.openai.com/cookbook/examples/skills_in_api/
2•ms7892•43m ago•0 comments

MIT's new fine-tuning method lets LLMs learn new skills without losing old ones

https://venturebeat.com/orchestration/mits-new-fine-tuning-method-lets-llms-learn-new-skills-with...
2•teleforce•45m ago•0 comments

Tool Shaped Objects

https://twitter.com/willmanidis/status/2021655191901155534
3•ungreased0675•48m ago•0 comments

Show HN: Floating-Point JPEG Decoder

https://github.com/rsaxvc/jFloaty
2•rsaxvc•51m ago•0 comments

Show HN: Membrane, revisable memory for long lived AI agents

https://github.com/GustyCube/membrane
1•GustyCube•56m ago•0 comments

Google played key role in recovering video from Nancy Guthrie's nest camera

https://www.cnn.com/2026/02/10/tech/google-video-nancy-guthrie
1•dboreham•57m ago•1 comments

Show HN: DocForge – Multi-Agent RAG That Fact-Checks Its Own Answers

https://github.com/ToheedAsghar/DocForge
1•toheed11•1h ago•0 comments

Show HN: 10-min AI threat model (STRIDE and MAESTRO), assumption-driven

https://raxit.ai/assessment
1•agairola•1h ago•0 comments