AI

I increasingly think the most important race in AI video is not who understands prompts better. That may sound odd. For the past two years, AI video has been almost inseparable from prompting: how to describe camera movement, how to specify style, how to keep characters consistent, how to avoid broken hands, fake text, and weird cuts. People who write better prompts do get better results. But that is also the problem. ...

I have seen too many versions of the same meeting recently. Someone says the company needs to “go all in on AI.” A vendor shows a polished agent demo. A manager imagines every employee suddenly having three tireless digital coworkers. The deck looks great. The numbers look even better. Then the work hits reality. The data is messy. The process was never clearly defined. Permissions are vague. Nobody knows who verifies the output. The agent produces something plausible, someone trusts it too early, and now the team is spending more time cleaning up after AI than doing the work itself. ...

A clear signal showed up on GitHub Trending today: agent skills are having a moment. On the daily chart, obra/superpowers reached rank 2 with an agentic skills framework and software development methodology. K-Dense-AI/scientific-agent-skills reached rank 3 with ready-to-use skills for research, science, engineering, analysis, finance, and writing. The monthly chart is even louder: mattpocock/skills, multica-ai/andrej-karpathy-skills, ComposioHQ/awesome-codex-skills, addyosmani/agent-skills, NousResearch/hermes-agent, zilliztech/claude-context, and rohitg00/agentmemory all appear in the same cluster. This is not just another batch of prompt templates. ...

OpenAI recently brought Codex into the ChatGPT apps for iPhone, iPad, and Android. At first glance, that sounds simple enough: now you can use Codex on your phone. I do not think that is the interesting part. Honestly, who wants to review code diffs on a phone for half an hour? That sounds more like punishment than productivity. The real point of Codex Mobile is that it turns the phone into a remote control for AI coding agents. The code still runs on your laptop, Mac mini, devbox, or remote environment. The phone is there for checking progress, answering questions, approving commands, changing direction, and dropping in a new task when an idea shows up. ...

If you still think “AI for creators” means typing one prompt and getting a viral post, you are looking at the wrong layer. The interesting shift in 2026 is not that one tool can write a better headline. It is that every step of the creator workflow is starting to grow an agent around it. One tool looks for SEO opportunities. Another turns your voice and screen into a video. Another schedules posts across social platforms. Another generates short videos. Another turns documents into editable slides. ...

For the last year or so, many of us have built a simple habit around AI: ask a question, wait for a long Markdown answer. Headings, bullet points, tables, bold text, code blocks. It looks organized, and it is genuinely better than plain text. But lately I have been feeling that asking AI only for Markdown is a bit like buying a color TV and using it as a radio. ...

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. ...