The video you just watched made itself. I gave Claude Fable 5 one prompt inside Claude Code, walked away, and came back to a finished video I never filmed, edited, or even watched while it was being built. In this one I show you what Anthropic's new Mythos-class model can actually do, then break down exactly how it wrote the script, cloned my voice, rendered the avatar, built every motion graphic, and edited the whole thing on its own.

I just unlocked a much better way to run Hermes Agent. Instead of using OpenRouter or setting up OpenAI API keys, I connected Hermes Agent directly to OpenAI Codex using my existing ChatGPT Plus subscription. That means: • no separate OpenAI API key • no OpenRouter dependency • no extra per-token API setup • Docker-based Hermes Agent on macOS • GPT-5.5 available inside Hermes For anyone already paying for ChatGPT Plus / Pro, this feels like getting a powerful agent runtime almost “for free” on top of the subscription you already have. The setup uses OpenAI Codex device-code authorization: hermes auth add openai-codex After signing in through ChatGPT, Hermes can switch to the OpenAI Codex provider and use models like: • gpt-5.5 • gpt-5.4 • gpt-5.4-mini I wrote a full guide with commands, Docker setup, troubleshooting, and the small entrypoint fix I needed for skills_sync.py. Hope this helps other people building serious local AI automation workflows with Hermes Agent.

Stop learning n8n in 2026. Seriously. If you’re still trying to learn n8n in 2026, you might be focusing on the wrong thing. In this video, I explain why you should stop learning n8n in 2026 and what you should learn instead. If you’re thinking about learning n8n in 2026, watch this first. I break down why some creators say to stop learning n8n in 2026, what the better alternative is, and how you can stay ahead by learning the right automation skills instead. Enjoy!

But it also has an expiration date. Right now, sticking "AI" in front of "consultant" is a real edge. The search demand is there. The budgets are there. Companies are actively hunting for someone who can walk in, look at their operations, and tell them what to actually do with this stuff. So if you're trying to position yourself, take the label. It works. But the label is the temporary part and we've seen this cycle before. → When Excel showed up, people might've called themselves "Excel accountants." But how ridiculous would it be if someone introduced themselves like that today? → When the internet showed up, people spun up "internet marketing" agencies. Now that's just marketing. AI is doing the same thing to consulting because AI is going to seep into everything. In a few years, the qualifier drops. The consultants who aren't AI native won't be winning business. They'll just be bad consultants. The job under the hood doesn't change. A consultant walks into a business, finds the actual constraint, and prescribes a solution. The newest tech is the toolbox, not the job description. But people take the "AI consultant" title and assume the answer always has to be AI. Sometimes the right call is a database restructure. Sometimes it's a better SaaS tool. Sometimes it's a deterministic workflow with zero AI in it. I'm not saying AI is never the answer. It's the highest-impact tool we've had in a long time. But forcing it where it doesn't belong is how clients lose trust fast. I think about it as a pyramid. → Bottom: deterministic workflows. No AI. Cheap, fast, reliable. → Middle: AI workflows. More power, more cost, more failure modes. → Top: AI agents. Maximum capability, maximum risk, longest time to ship. The higher you climb, the more it costs, the longer it takes, and the more ways it breaks. More risk. Start at the bottom. Only move up when the problem actually demands it. The label "AI consultant" gets you in the door right now. The discipline of solving the real problem with the simplest possible solution is what keeps you there once everyone else catches up.

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