Hey everyone,I’m building a voice booking assistant for Client's Company using VAPI, and I’m running into a bunch of strange behaviour that doesn’t line up with my prompt or tool logic. I’m hoping someone who has worked with complex VAPI assistants can help me diagnose what’s going on. I have attached the VAPI prompt to this post, I have deleted my client's company from the prompt so if there are any gaps in tool names or text that is why 🔥 Issues I'm Experiencing: 1. The assistant sometimes lags badly There are delays where the assistant just freezes for a second or two before responding. 2. It often says “I could not find that restaurant” even when the restaurant exists The ID lookup tool works perfectly when I test it directly, but inside VAPI the assistant frequently fails to pick up names and jumps straight to “could not find that restaurant”. It especially struggles with: - “Alla Bolognese” → hears it as something completely different - Restaurant names in general 3. The call audio breaks up / interrupts / talks over the user It keeps speaking before I have a chance to confirm details.It will: - Interrupt me mid-sentence - Repeat itself - Apologise multiple times even though nothing actually happened - Talk over the user during confirmations It feels like endpointing or turn-taking is misfiring. 4. Repeats itself and seems “stuck” sometimes At random points, it loops: - Apologising repeatedly - Repeating the same line - Re-explaining a step it already completed This doesn’t match the prompt at all. 5. Tone is inconsistent and sometimes shifts dramatically This one is wild: - It speaks in a normal tone - Pauses - Then suddenly shouts with excitement, like a different TTS voice style - Then goes back to normal It’s like ElevenLabs suddenly spikes in emotion even though stability is low and the prompt asks for calm, consistent tone. 6. Sometimes speaks in another language (!!) While repeating an email address, the assistant suddenly switched to an incomprehensible language for a sentence before coming back.

Problem: Companies have hundreds of open vulnerabilities but don’t know which to fix first. Agent Solution: 🤖🤖 Pull data from Nmap, Nessus, Qualys, or internal scanners.🌞 Rank vulnerabilities using:🌞 CVSS score.🔰 Exploit availability.🔰 Asset criticality.🔰 Business impact.🔰 Give a daily prioritized patching list..🔰 Outcome: Fix critical issues 5× faster..🔰 What's your opinion please share into this. ✨✨✨✨✨✨✨✨✨✨✨✨✨✨✨✨✨Happy Cybersecurity Day 2025. 🥳🥳

🔁 MASTER WORKFLOW When any alert is provided: Agent 1 normalizes Agent 2 classifies Agent 3 recommends the next action Agent 4 produces the final JSON 🎯 What this gives you? With this single prompt, Gemini 3 will create a realistic multi-agent cybersecurity system: ✔ Alert Normalization Agent ✔ Threat Classification Agent ✔ Threat Response Agent ✔ Reporting Agent

Which of these three AI deployments are you most interested/focused on learning?

We've had an AI Voice Agent running live in production for a client for the past 2 years. It's handled over 2,500 calls, saved hundreds of hours, and generated an ROI of over $48,000. In this video, I'm giving you a complete breakdown of this AI receptionist system. I'll show you the real-world data, the tangible business benefits, and a step-by-step walkthrough of how we built it using Retell AI and Make.com. This is a must-watch if you are a business owner tired of handling inbound calls, or an aspiring AI builder who wants to sell these systems to clients.