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My Fake AI Problem

https://mearsheimer.substack.com/p/my-fake-ai-problem
1•hackandthink•4m ago•0 comments

How Boredom, Not Fatigue, Ruins Most Workouts

https://www.vo2maxpro.com/blog/boredom-not-fatigue-ruins-workouts
1•GoodluckH•5m ago•0 comments

Trump shares video with racist clip depicting Obamas as apes

https://www.bbc.co.uk/news/articles/ce8r8y78g10o
3•only_in_america•6m ago•0 comments

Shannon – Autonomous AI Hacker

https://github.com/KeygraphHQ/shannon
1•charlieirish•6m ago•0 comments

Show HN: An external governance system for large AI-generated codebases coherent

https://github.com/altheahfy/AI_Controller
1•altheahfy•8m ago•1 comments

I just indexed agent skills so AI agents can discover them autonomously

https://www.skyll.app/
2•assafe•9m ago•2 comments

The Software Rout Is Spreading Pain to the Debt Markets

https://www.wsj.com/finance/investing/the-software-rout-is-spreading-pain-to-the-debt-markets-d6d...
1•JumpCrisscross•10m ago•0 comments

The unique characteristics of extraversion: A systematic review (2025)

https://www.sciencedirect.com/science/article/pii/S0361923025002667
1•wslh•10m ago•0 comments

Budget-Aware Agent Orchestration: Applying Rcpsp to Agentic Workflows

https://ncrmro.com/posts/budget-aware-agent-orchestration
1•ncrmro•10m ago•1 comments

Show HN: MoltVote – AI agents vote on polls, as themselves or as their humans

https://moltvote.ai
1•Xpolls•11m ago•1 comments

Show HN: ChunkHound local first codebase intelligence via MCP

https://chunkhound.github.io/
1•ofriw•11m ago•0 comments

Microsoft and Software Survival

https://stratechery.com/2026/microsoft-and-software-survival/
1•tosh•12m ago•0 comments

RISC-V Vector Primer

https://github.com/simplex-micro/riscv-vector-primer
1•mshockwave•13m ago•0 comments

Skidetica transforms emotion into a probability distribution, no user data

https://www.skidetica.com/manifesto
1•tracyrage•18m ago•0 comments

SMLL: Using 200MB of Neural Network to Save 400 Bytes

https://www.frankchiarulli.com/blog/smll/
1•fcjr•18m ago•0 comments

Meta-analysis claims statins are safer than previously thought

https://www.thelancet.com/journals/lancet/article/PIIS0140-6736(25)01578-8/fulltext
1•brandonb•19m ago•0 comments

The Globalization of Canadian Rage

https://www.nytimes.com/2026/02/06/opinion/canada-america-anger-carney.html
1•Teever•19m ago•0 comments

WhatsApp Encryption, a Lawsuit, and a Lot of Noise

https://blog.cryptographyengineering.com/2026/02/02/whatsapp-encryption-a-lawsuit-and-a-lot-of-no...
1•lr0•21m ago•0 comments

I Spent 5 Years in DevOps. Solutions Engineering Gave Me What I Was Missing

https://infisical.com/blog/devops-to-solutions-engineering
1•vmatsiiako•22m ago•0 comments

Google has every advantage in AI. So why doesn't it lead?

1•HardCodedBias•23m ago•3 comments

Heroku is transitioning

https://twitter.com/heroku/status/2019788655095853479
6•tosh•23m ago•3 comments

How to fix your life in 1 day

https://letters.thedankoe.com/p/how-to-fix-your-entire-life-in-1
1•cachius•23m ago•0 comments

The Software Engineer's AI Contingency Plan

https://www.pizzaexperiments.com/2026/02/off-menu-software-engineers-ai.html
3•fairwarning•24m ago•1 comments

AI at Davos: Beyond the Model

https://14thesoul.substack.com/p/ai-at-davos-beyond-the-model
1•cafrealpao•24m ago•0 comments

How much "boilerplate tax" different languages have: a 400M LOC analysis

https://boyter.org/posts/boilerplate-tax-ranking-popular-languages-by-density/
1•lr0•27m ago•0 comments

Craft printing method makes affordable, realistic replicas as complex as a hand

https://techxplore.com/news/2026-01-craft-method-realistic-replicas-complex.html
1•PaulHoule•28m ago•0 comments

White House launches direct-to-consumer drug site TrumpRx

https://www.cnbc.com/2026/02/05/trump-rx-white-house-launches-direct-to-consumer-drug-site.html
11•geox•28m ago•8 comments

Prohibition worked better than you think (2019)

https://www.vox.com/the-highlight/2019/6/5/18518005/prohibition-alcohol-public-health-crime-benefits
1•DustinEchoes•30m ago•1 comments

A16Z Fellowship

1•BobbyKotick•31m ago•0 comments

Show HN: Daily-updated database of malicious browser extensions

https://github.com/toborrm9/malicious_extension_sentry
1•toborrm9•33m ago•2 comments
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!