Thesis
Despite massive investment in AI infrastructure, we're seeing remarkably few transformative consumer AI applications emerge. The gap between AI capability and useful products suggests fundamental challenges in productizing AI.
Key Arguments
- AI infrastructure investment dwarfs actual consumer product innovation
- Most AI wrappers provide marginal improvements over existing solutions
- The best AI products are invisible - they enhance existing products rather than being standalone
- The 'killer app' for AI might not be an app at all, but background intelligence
Examples Cited
- ChatGPT remains the dominant consumer AI product despite being a generic chat interface
- Most funded AI startups are infrastructure plays, not consumer products
- Successful AI integrations like GitHub Copilot work within existing workflows
Call to Action
Stop building AI apps. Build products that solve problems and happen to use AI.
Discussion Personas
The Builder's Dilemma 35%
Founders frustrated by the gap between AI capability and product-market fit
Core argument: AI capability has outpaced our understanding of what problems to solve with it
Quotes
"This remains me so much of the .COM bubble in 2000. A lot of clueless companies thought that they just need to “do internet” without any further understanding or strategy. They burned a ton of money and got nothing out of it. Other companies understood that the internet is an enabling technol..."
— vjvjvjvjghv
"I mean how else could it be? Some app for Grampa? Junior? The scope of complexity of these problems (which build on tech the viber need not make) is small. There's no serious support dimension or risk. The last step matters. When I'm talking about "apps" as a professional software engineer, I'm t..."
— scrubs
The Infrastructure Bull 25%
Those who argue we're still early and infrastructure matters
Core argument: Consumer apps lag infrastructure investment - this is normal technology adoption
Quotes
"A friend of mine who is tech savvy and I would say has novice level coding experience decided to build his dream app. Its really been a disaster. The app is completely broken in many different ways, has functionality gaps, no security, no thought out infrastructure, its pretty much a dumpster fire."
— nyc_pizzadev
"I think this is a great question to ask and maybe I need my own blog to post about these things as I might reply with a big comment Making Unpublished Software for Themselves One issue is, I think maybe a lot of people are making software for themselves and not publishing it - at least I find mys..."
— erelong
The Enterprise Convert 25%
Those pointing to B2B as the real AI opportunity
Core argument: The real AI app revolution is happening in enterprise, not consumer
Quotes
"By "apps" this author apparently means "PyPi packages". This is a bafflingly myopic perspective in a world of myopic perspectives. Do we really expect people vibecoding "apps" to put anything on PyPi as a result? They're consumers of packagers, not creators."
— andrewflnr
"We have to differentiate a bit between consumer and enterprise environments a bit here. My comment was in regards to the latter, where other people's computers basically were under our full control."
— steve1977
The Skeptic 15%
Those questioning whether AI delivers on its promises
Core argument: The lack of killer apps might indicate AI is less transformative than claimed
Quotes
"This is so stupid. I don't know whether AI has improved things but this is clearly cope, we're not even a year into the transition since agentic coding took over so any data you gather now is not the full story. But people are desperate for data right? Desperate to prove that AI hasn't done shit."
— threethirtytwo
"I think it is great! The issue is that validation needs presence and it is the limiting factor - common knowledge, but is part of the “physics”. Also maintenance gets really tricky if the codebase has warts in it - which it will have. I get much more easy to understand architecture out of an..."
— nevertoolate