AI’s Big App Problem Ever wonder why so many AI apps feel disappointing? It’s not because the tech isn’t powerful—it’s because most apps don’t know how to take AI’s incredible general intelligence and apply it to specific problems. AI is like a massive engine with limitless potential, but most builders fail to connect that power to actual workflows. Right now, users want AI—but they don’t know why. They’re intrigued by the hype but stuck in a fog of buzzwords like “transformative AI” and “next-gen automation.” Builders, meanwhile, throw AI into apps without truly solving real-world problems. The result? A lot of shiny products that don’t deliver. The real opportunity lies in the app layer, where AI can be tailored to specific workflows, driving 10x improvements. Success isn’t about making more general AI tools—it’s about embedding AI seamlessly into apps that solve real problems without users even realizing how much tech is under the hood. By 2027, we’ll move from “cool AI demos” to purpose-built AI products that feel essential. The winners will be companies that understand niche workflows, design products that just work, and hide the complexity behind an intuitive interface. They won’t market “AI”—they’ll just deliver value. We’re still in the mining phase, figuring out how to extract gold from general AI. But when builders finally crack that code, the app layer will be where the next tech giants emerge. #product #productmanager #productmanagement #startup #business #openai #llm #ai #microsoft #google #gemini #anthropic #claude #llama #meta #nvidia #career #careeradvice #mentor #mentorship #mentortiktok #mentortok #careertok #job #jobadvice #future #2024 #story #news #dev #coding #code #engineering #engineer #coder #sales #cs #marketing #agent #work #workflow #smart #thinking #strategy #cool #real #jobtips #hack #hacks #tip #tips #tech #techtok #techtiktok #openaidevday #aiupdates #techtrends #voiceAI #developerlife #cursor #replit #pythagora #bolt #app #thinking #tellme #question

Excellent software meets the user need that you didn't even know was there in a way that when you see it, you go, aha, I really needed that. That's true for hardware too. AI apps don't do that yet. They really don't. Almost no AI app is able to meet a user need that you didn't know you had and immediately clearly explain how that need is fixed uniquely by a large language model in a way that 10x is your workflow. That is the bar you should be holding as users of apps. That is the bar that builders of apps, if you're in product, if you're in engineering, if you're a solopreneur, a founder, that's the bar you should have. But almost every app I see that is in the AI space today does not meet that bar. And we fail as builders precisely because these tools are so powerful. An intelligence layer can do anything. I know people who are using Rufus, which is the Amazon large language model for reviews, and they're sticking prompts to build Python code into Rufus. And Rufus cooperates because it's a large language model. And perhaps because Amazon didn't put guardrails in. But the point is that these models are so wide, they're so general purpose, that as app builders, we are struggling to make them specifically useful to people who do not have a clear understanding of the specific value that a piece of intelligence could provide their use case. So over and over again, I see people saying I need AI in my business. But if you ask them what they need AI for, they just throw out more generalities and more corporate jargon, they don't actually know. And that's not really their fault, because no one's ever helped them understand enough about large language models, so that they can figure out, oh, this would be really useful. That is starting to change. And I firmly believe that as the market understands AI better over the next three, four years, we'll really see a shift in fluency. And that will lead to smarter consumers, which is good for everybody. But for now, if you are building in the space, you need to be the one to provide users with onboarding flows that help them to specifically imagine what they can do with your app. Because otherwise, people are going to do whatever they can figure out to do and oftentimes be dissatisfied, because you didn't set up the expectations. Well, this is a major issue with AI apps. And I think it's unique to the widely applicable intelligence power that large language models bring. Tell me about apps that get this right.