The feed is full of "what are you building with Fable 5" right now, so instead of asking, I went through Anthropic's actual prompting guide and pulled the parts that change how you'd use it, especially if you build automations. Sharing the useful bits. A few that surprised me: Default to high effort, not xhigh. On the older models the move was crank effort to max. Anthropic says the opposite for Fable 5: start at high (the default), only go xhigh for the genuinely hard stuff, drop to medium or low for routine work. Their line is that lower effort on Fable 5 still beats xhigh on the older models. Effort is the main dial for intelligence vs speed vs cost, so this is real money if you run it at volume. Delete your over-specified prompts. This one stung. Skills and prompts you tuned for older models are often too prescriptive for Fable 5 and actually make the output worse. It follows instructions well enough that one short instruction beats a long list naming every behavior. Strip your old skills back and check if the default is just better. Make it prove its work on long runs. The one I care about most, because it's the exact thing I keep going on about. For long autonomous runs, tell it to audit each claim against a tool result from the session and only report what it can point to evidence for. Anthropic says in their own testing this nearly eliminated fabricated status reports. If you run anything overnight, that's the difference between "it said it did the thing" and it actually did the thing. Don't ask it to explain its reasoning in the response. A gotcha that isn't obvious: telling it to echo or transcribe its thinking as response text can trip a refusal and quietly fall back to a different model. If you want the reasoning, read the thinking blocks, don't ask for it in the output. Fix your timeouts before you migrate. Individual requests can run for many minutes at higher effort, and full runs can go for hours. If you're calling it from n8n or your own harness, your existing timeouts will bite you. Restructure to check long runs async instead of blocking.

After building AI receptionist systems for service businesses, I noticed something. The technology isn't the hard part. The mindset is. Most business owners hear "AI receptionist" and their first thought is: "Will it sound robotic?" "What if it says the wrong thing?" "My customers want to talk to a real person." And that resistance kills the conversation before it starts. The shift that works: Stop selling the AI. Start selling the outcome. The right conversation isn't: "I want to set up an AI that answers your calls." It's: "Right now, what happens when a customer calls you at 9PM on a Friday?" That question does the work. Because the business owner already knows the answer, voicemail, missed opportunity, customer calls the competitor. Once they say it out loud, the solution sells itself. GoHighLevel makes this even easier because everything lives in one place, the AI, the calendar, the CRM, the follow-up workflows. There's nothing to stitch together. The business owner doesn't need to understand the technology. They just need to see what happens when nobody answers, and understand that it doesn't have to be that way. That's the mindset shift. Sell the missed call. Not the AI. What objections are you running into when pitching AI receptionist systems to clients?

I've been using Claude Pro for a while and I want to build an "AI second brain" with it at the core. A few specific problems I'm trying to solve: - Remembering what I've already learned or researched - Speeding up how I consume and retain information - Getting help with writing and content — not just one-off prompts - Staying on top of tasks and projects without losing context I'm leaning toward combining Obsidian with Claude, and possibly using Claude Code to build automations around it (things like scripts to summarize notes, surface past research, or sync context). But I'm not sure how to connect these pieces in a way that actually works day-to-day. For anyone who has built something like this: → Where did you start — notes, tasks, writing, or something else? → Has anyone integrated Obsidian with Claude to auto-summarize notes or pull up past research? How did you set that up? → What's one thing you wish someone had told you before you started? Looking for real-world experience, including the parts that don't usually get talked about.

Is n8n still suitable in big 2026?

Honest question for the solo operators here, because I don't have a clean answer. What makes a solo operation fragile isn't the building, it's that I am the bottleneck on everything that matters. Every deliverable, every fix, every judgment call routes through me. That caps how much I can take on, and nothing ships when I step away. The obvious answer is delegate, to people or to agents. The part nobody tells you is that quality usually drops the moment you hand something off, so you end up redoing it, which is slower than just doing it yourself. So you pull it back, and you're the bottleneck again. What I've tried so far: writing the boring repeatable parts down as steps, handing off the pieces where wrong is cheap and easy to catch, and keeping a human gate on anything client facing. It helps at the edges, but I'm still the single point of failure on the core work. So the real question for anyone who's actually done it: how did you take yourself out of the critical path without the quality dropping? Was it better SOPs, hiring a specific role first, leaning on agents for a slice of it, something else? What was the first thing you successfully stopped doing yourself?