Sonnet 5 costs more than Opus 4.8 on the Artificial Analysis Intelligence Index

The model I reach for first now isn't Opus. It's GLM 5.2 — a free, open-source model that's days old, runs right inside Claude Code, and on most of my daily work is so close to Opus (5x the price) I genuinely can't tell them apart. I gave both the exact same prompts. Here's the honest result. - Same prompts, both models. A sponsorship CRM app: GLM's was complete and worked (Opus's looked a hair nicer) for $0.40 vs $3. A Minecraft voxel world and an orbiting solar system: both nailed first try, and side-by-side you can't tell which came from which. - Where Opus won. A 30-second launch video. Opus shipped it in one clean 51-min run; GLM broke when its context filled up and needed retries — still $2 vs $14. Opus only really pulls ahead on the longest, hardest jobs. - Why it's cheap. 700B+ parameters but only ~40B switch on per task (mixture-of-experts), plus a ~1M-token window that holds your whole project. About 5–6x cheaper than Opus per token, and the gap widens on big jobs. - Why open-source matters. When Fable 5 got switched off overnight, everyone building on it had no say. An open model nobody can switch off is worth more than the price tag. - Run it three ways. OpenRouter (pay-as-you-go, ~2-min setup — point Claude Code at it with a tiny settings.json), Z.ai's flat ~$18/mo plan (daily use, official), or fully local for private data (but that needs ~$10k of hardware, so most people start on OpenRouter). My take: it doesn't replace Opus — it replaces most of when I used to reach for it. GLM's my default now; Opus stays in my back pocket for the jobs that have to be perfect first try. 📎 Full GLM 5.2 guide PDF pinned below — every build, the benchmarks, the cost, and the exact setup. Every prompt and the full setup are free inside The AI Accelerator (19k+ members). 👉 If you got it running, what's the first thing you'd build with it? Drop it below. [Watch the video here ▶️]

You can now run a "focus group" of made-up-but-realistic customers — each with their own personality, budget, and bias — and watch them react to your decision like a real comment section. Some love it, some hate it, some argue each other into changing their minds. Here's why it matters 👇 Most of us make the scary calls on a gut feeling. You raise your price from $200 to $300, or kill an offer, or launch a new service — and you find out how customers feel *after* the cancellation emails start. The fix: simulate the room first. Paste one prompt, describe your real customers + the decision, and the AI builds a panel that argues it out and hands you a plain report — the most likely outcome, the % at churn risk, the #1 objection you have to answer, and the one change that kills the backlash. (Honest note: it's directional, not a crystal ball — but it's the cheapest market test you'll ever run.) I put together a short step-by-step guide that gives you the copy-paste prompt, the reusable "run the focus group" system you save once, and the do-this-not-that rules so you don't fool yourself. **👉 Grab it here:** https://flicker-celestite-7b6.notion.site/The-AI-Customer-Simulator-Run-a-1-000-Person-Focus-Group-Before-You-Bet-on-a-Decision-38dd180d8c8081b79302c0f785085dbb?source=copy_link What's the one decision you'd run through the room first — a price hike, a new offer, something else? Tell me below 👇

Most people hear "Claude Code" and picture a tool for programmers. I run my whole business on it and have never written a line of code. It's not a chatbot — it's one place that holds your business plus a team of AI workers that actually do the work. Here's the exact setup, every piece that matters. - The model. You're the operator in the middle: your AI team on one side, your real tools (email, docs, CRM) on the other. You hand it jobs, not questions. Anthropic's own legal and marketing teams run real work on it without coding. - The building blocks. CLAUDE.md (memory — your business in plain text, read every conversation), Skills (your SOPs it follows every time), Plugins (box up your skills and hand your team the whole setup in one command), Subagents (specialist "departments" that run in parallel), and MCP (the plug into your real tools). - Staying in control. Plan mode (it writes the plan, you approve), permissions (it asks before changing or sending anything), and an undo button. You still sign off on money and anything client-facing. - Make it run without you. Hooks (auto-check every draft), your own one-word commands, and schedules ("every Monday 8am, build my competitor brief"). Start with the local schedule; the cloud one needs a repo. - The honest part. It's not a magic button — Anthropic's Project Vend had it run a shop and lose money. It bills by usage, so start small and watch it. Garbage in, garbage out. Golden rule: nail ONE workflow three times before you expand. My take: set up right, your job changes from doing the tasks to directing the work and checking the output. That's running a team — you just built this one out of files and instructions instead of hiring for every seat. 📎 Full Claude Code for Business guide PDF pinned below — the building blocks, the controls, the automation, and the real costs. The doc and templates are free inside The AI Accelerator (19k+ members), and if you'd rather we set it up for your team, that's what we do at Reprise.

Your competitors are literally handing you the playbook. They're spending thousands testing ads, running experiments, and figuring out what works. And all of it is sitting in Meta's Ad Library. Public. Free. This n8n AI automation: • Scrapes competitor Facebook Ads • Analyzes winning hooks, creatives, and messaging • Identifies improvement opportunities • Outputs everything into a Google Sheet, ready for your team to review and adapt Instead of starting from scratch, start with what's already proven. Work smarter. Iterate faster. Drop a 🔥 if you want the full workflow.