Posts

I am increasingly convinced that the best way for most people to start using AI is not to ask it to change their life. Ask it to remove one annoying ten-minute task. That sounds less ambitious, but it is much more useful. A lot of AI products talk about universal assistants, autonomous agents, and fully automated workflows. The ideas are not wrong. But when you bring them back into everyday life, the question becomes much simpler: what exact irritating thing can AI help me avoid today? ...

Over the past few days, one idea has become harder for me to ignore: personal agents are finally moving beyond the clever chat box. They are starting to grow a skeleton. For a long time, the default question around AI assistants was simple: how smart is the model? That still matters, of course. But it is no longer enough. A personal agent that can actually help you over time needs more than a strong model. It needs at least three things: rules, memory, and tool access. ...

For a while, the default way to use AI has been pretty simple: subscribe to a closed-source product, open a web chat box, or pay a SaaS tool every month. That path is convenient. Closed-source products are polished, powerful, and mostly painless. You open the app and get work done. But the trade-off is becoming harder to ignore: cost, limits, opacity, and workflows locked inside someone else’s product. The shift I am watching now is this: cheap but capable local AI tools are moving from hacker toys into real alternatives. ...

Over the last two years, people have gotten used to one basic fact about AI: it talks well. It writes copy, summarizes meetings, fixes code, and tidies up messy material into something presentable. But even when those capabilities are impressive, AI still often behaves like an advisor. It tells you what to do next. You are still the one who clicks the button, enters the card, chooses the service, and takes responsibility for the action. ...

For the last two years, the default image of using AI has looked something like this: someone sitting in front of a text box, carefully writing a prompt as if they were briefing a very literal genie. That image is not wrong. In fact, it defined an entire phase of AI product behavior. But lately I have felt more and more strongly that this interface is starting to loosen. Prompting is not suddenly useless. It is simply moving into the background, while voice, screenshots, screen recordings, and raw documents are slowly becoming the more natural front door. ...

The more I watch people use AI for visual work, the more I think many of them are starting from the wrong question. The question most people ask is: how do I get AI to generate better-looking images? But I think the more useful question is: do I actually need a picture, or do I need something that can still be edited, reused, and inserted into a workflow afterward? That is not semantics. That is an efficiency question. ...

Lately I have had a growing feeling while watching Product Hunt. The agents that look most like real businesses are no longer the ones that merely seem smart. They are the ones that sit closest to revenue, launches, customer acquisition, and conversion. That is not abstract theory. Today’s Product Hunt leaderboard made it unusually obvious: Orange Slice: Automate any sales task with AI https://www.producthunt.com/posts/orange-slice-2 Jet AI Agents: Build business AI agents in minutes https://www.producthunt.com/posts/jet-ai-agents Waitlister: The waitlist software to launch your product https://www.producthunt.com/posts/waitlister-3 Put those three products side by side and the pattern is hard to miss. ...

A line I saw this week was a little too accurate: the problem right now is not that we do not have enough agents. The problem is that we do not have enough work to give them. The original post came from Zara Zhang: https://x.com/zarazhangrui/status/2046662237306421608 I laughed when I first read it, not because it was exaggerated, but because it felt uncomfortably close to the truth. To avoid hiding the sources behind linked anchor text only, here are the primary source URLs up front: ...

Lately I have been feeling more and more strongly that one of the most overrated things in AI is the release of a new model itself. Not long ago, every new version triggered the same reaction: how much smarter is it, how much stronger is it, how high will it climb on the charts. That reflex is starting to wear out. It is not that models no longer matter. It is that users, especially developers, have become much more practical. Fine, you shipped an upgrade. But the real question now is: so what? ...

The shift happened fast. Not long ago, the AI conversation was dominated by one question: whose cloud model is stronger? Now a growing number of products are pushing back toward the desktop, and very specifically toward the Mac desktop. Put Gemini on Mac, Ollama v0.19, and Google AI Edge Gallery side by side, and this no longer looks like coincidence. It looks like a market signal. My take is simple: what users actually want is not just a stronger model, but a lower-friction experience. Model quality matters, obviously. But if using the model means opening another tab, waiting on the cloud, wiring tools together, juggling prompts, and constantly losing context, even a great model starts to feel annoying. And once a tool feels annoying, it rarely becomes a habit. ...