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Leadly – AI lead generation for small businesses at $9/month

https://willowy-kulfi-0cbaff.netlify.app
1•Leadly•1m ago•0 comments

Apple to Pay $250M to Settle Class Action over Delayed Siri Features

https://www.macrumors.com/2026/05/05/apple-class-action-siri-lawsuit-settlement/
1•mgh2•1m ago•0 comments

Trustworthy JavaScript for the Open Web

https://hacks.mozilla.org/2026/05/trustworthy-javascript-for-the-open-web/
1•nnx•5m ago•0 comments

Linear's MCP server accepts HTTP:// redirect URIs for confidential OAuth clients

https://github.com/korrel-dev/mcp-audits/tree/main/audits/linear
1•issazangana•8m ago•0 comments

Canadian fiddler sues Google after AI wrongly claimed he was a sex offender

https://www.theguardian.com/music/2026/may/05/canadian-ashley-macisaac-fiddler-musician-singer-so...
1•Teever•8m ago•0 comments

Bevy and egui desktop app in production

https://nominal.io/blog/nominal-connect-shipping-realtime-desktop-software-with-rust-bevy-and-egui
1•phsilva•9m ago•0 comments

Sample App – On-Device AI Assistant for Android

https://github.com/ajay-sainy/GemOfGemma
1•qarue•11m ago•0 comments

Skelm – Build AI agents in TypeScript without losing your mind

https://github.com/scottgl9/skelm
1•scottgl•11m ago•0 comments

Lessons on Building MCP Servers

https://taoofmac.com/space/blog/2026/04/29/2341
1•gmays•12m ago•0 comments

StarFighter 16-Inch

https://us.starlabs.systems/pages/starfighter
1•signa11•12m ago•0 comments

Security Engineering Is a Context Problem

https://aseemshrey.in/blog/security-engineering-is-a-context-problem/
1•LuD1161•14m ago•0 comments

Show HN: Library to make your own Windows program launcher (like dmenu)

https://github.com/cristeigabriela/wintheon
1•gabriela_c•18m ago•0 comments

Google is building an AI agent that could be its answer to OpenClaw

https://www.businessinsider.com/google-ai-agent-openclaw-remy-gemini-assistant-2026-5
2•droidjj•20m ago•0 comments

FFmpeg developer calls out OxideAV for AI license laundering of his code

https://github.com/OxideAV/oxideav-magicyuv/issues/3
2•dmitrygr•25m ago•0 comments

Telus using AI to alter the accents of customer service agents

https://www.theglobeandmail.com/business/article-telus-ai-accents-customer-service-agents/
2•gnabgib•26m ago•0 comments

R2-D2 Monitor – TUI for Windows Administrators

https://github.com/Victxrlarixs/r2d2-monitor
2•unixero•29m ago•0 comments

"More transgender people committed homicide than were victims" in Britain

https://papers.ssrn.com/sol3/papers.cfm?abstract_id=6182901
6•rdevilla•30m ago•0 comments

HN: GapMap – A quantitative index of knowledge gaps between Wikipedias

https://www.gapmap.wiki/
2•mucho_mango•31m ago•0 comments

OpenAI delivers low-latency voice AI at scale

https://www.google.com/
3•midoxbe•32m ago•1 comments

Show HN: How I Separate Signal from Noise in the AI Firehose

https://laxmena.com/how-i-separate-signal-from-noise-in-the-ai-firehose
3•laxmena•33m ago•0 comments

Simpler JVM Project Setup with Mill

https://mill-build.org/blog/17-simpler-jvm-mill-110.html
2•lihaoyi•34m ago•0 comments

Telus Uses AI to Alter Call-Agent Accents

https://letsdatascience.com/news/telus-uses-ai-to-alter-call-agent-accents-a3868f63
5•debo_•37m ago•1 comments

Dawkins, Claude and the Myth of Consciousness in Artificial Intelligence

https://www.lucasaguiar.xyz/posts/dawkins-claude-consciencia-ia/
3•isfttr•42m ago•0 comments

Ask HN: Ten Yrs from now, when only AI codes, what's the stack?

3•jpcapdevila•44m ago•1 comments

Programming in 2026: excitement, dread, and the coming wave

https://amontalenti.com/2026/04/23/excitement-and-dread
4•blenderob•44m ago•0 comments

Store Tags After Payloads

https://www.scattered-thoughts.net/writing/store-tags-after-payloads/
3•blenderob•47m ago•0 comments

Show HN: Docx-CLI – let agents edit your Word files safely

https://github.com/kklimuk/docx-cli
3•kirillklimuk•50m ago•0 comments

Show HN: Zift – find authorization logic in your code

https://github.com/enforceauth/zift
3•boorad•52m ago•0 comments

RAG retrieves the refutation and still gets it wrong

https://reyes.id.au/posts/anchor-catching-the-failure-mode-where-rag-retrieves-the-refutation-and...
3•aeyer•55m ago•0 comments

Sendapi.co – One API for WhatsApp, SMS, and Email

https://sendapi.co/
3•nimana•56m ago•0 comments
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!