0:00 The Hallucination Problem Nobody's Talking About 0:31 Why Most People Never Catch the Errors 0:56 The Fix: Better Prompts from the Start Everyone says newer AI models are getting more accurate. A company called Vectara tested them all in May 2026. every single one hallucinated more than 10% of the time. And newer models are making it worse, not better. 🔍 Why Newer Models Are Actually More Dangerous • Chain-of-thought reasoning means small errors compound across long chains • The output sounds like a Harvard paper and cites sources that don't exist • Most people never catch it — it reads confident and authoritative • You're paying more for longer reasoning that's getting things wrong more often If you've ever used an AI response without verifying it, there's a real chance it made something up. Start catching it before it costs you. 💸 The Hidden Cost Problem 1. The longer your conversation runs, the more you pay per response 2. Context windows fill up — AI starts forgetting what you said at the start 3. Hallucinations increase as the model tries to fill gaps it can't remember 4. Both problems share the same root cause: a weak prompt from the start Track what you're spending on AI responses and compare it to output quality. You'll find the correlation fast. 🛠 The Fix: Right Context from the Start • Better prompts mean AI doesn't have to fill gaps with fabrications • You stop paying to repeat yourself across long conversations • AI stops forgetting context it never had in the first place • promptanything.io builds prompts with the right context before you start Stop building agents and workflows on bad prompts. Start for free at promptanything.io

If your AI agent keeps producing off results, the problem isn't the model, it's the architecture. This video breaks down why single-agent setups fail and how a multi-agent system replaced an entire outbound sales process from lead to close. 🔍 Why Single-Agent Setups Break Down • One agent handling multiple tasks loses context fast • Hallucination rates increase as task complexity grows • AI performs best on simple, clearly scoped instructions — not broad mandates • Giving one agent five jobs is why results keep coming back "almost right" Watch the full breakdown and spot exactly where your current setup is breaking down. ⚙️ How a 5-Agent Sales System Actually Works 1. Agent 1 scans for leads matching your criteria 2. Agent 2 scores each lead 3. Agent 3 looks up verified contact info 4. Agent 4 writes a personalized message 5. Agent 5 sends it The only human touchpoint is the sales call. Map your workflow against this to find what you can hand off today. 🧠 What Anthropic's Research Confirms • Real-world results come from specialized agents, not one powerful one • Each focused agent reduces hallucination and context collapse • The system works because no single agent is asked to do more than one thing https://youtube.com/shorts/TqmvUNeNOAU?feature=share

Had a few Internet issues, but we are alive now we are live till 5:00 hop on! If you have no questions, you can just follow along as I build out my prompt anything tool using Claude and Vercel, and build operating systems for AI agents.

Hi all - glad to be here. I'm a sponge for AI, can't wait to see what this community holds. Alllllll aboard 🚀