I’ve spent the last few months building an Agentic Voice AI platform. Like everyone else, I started with the "standard" stack: Vapi (Orchestration) + Deepgram (Ear) + GPT-4 (Brain) + 11Labs (Mouth). It works, but the margins were killing me. I just re-architected the entire backend using the new Google "Antigravity" stack (Vertex AI + Gemini 2.0 Flash Live), and the math is actually insane. 1. The Economics (82% Savings) The "Middleware Tax" is real. By stripping out the orchestrator and going native, the unit economics completely flipped. To put it in real dollars: - Old Stack: For 4,000 minutes of conversation (~1,000 calls), I was paying $1,020/mo ($0.26/min). - New Stack: For the exact same volume, my bill dropped to $180/mo ($0.045/min). That is nearly $10k a year in pure profit recovered just by switching infrastructure on a relatively small volume. 2. The "Real" Agentic Shift (Voice + Browser) The biggest unlock isn't even the cost; it's the "Action Layer." Instead of just a chatbot that takes notes, I’m running Headless Browsers (Playwright) inside Google Cloud Run containers. - The Agent (Gemini 3 Pro) doesn't just "speak" via API. - It autonomously logs into legacy SaaS portals (which have no APIs), clicks buttons, and executes complex workflows while talking to the user in real-time (<500ms latency). 3. The Architecture - Voice: Python/FastAPI on Cloud Run (handling WebSockets). - Model: Gemini 2.0 Flash Live (Handling the interruptions/turn-taking natively—no Vapi needed). - Memory: Context Caching (Upload 50-page SOPs once; pay near-zero to query them on every call). - Scale: Terraform scripts spin up isolated, secure environments for every new client in 5 minutes. If you are still chaining together 4 different APIs to make a voice bot, you might be over-paying for a "wrapper" when you could own the infrastructure. Happy to share more on the Terraform setup if anyone is interested. This feels like the moment the industry shifts from "Chatbots" to true "Action Engines."

Hey 👋 Which of the following are you struggling with the most right now?

Hey, If you haven’t already feel free to send me a connection on LinkedIn and mention you are coming from the community, I’d be more than happy to connect with you on LinkedIn. 💪 Drop a like on this post while you’re at it 🔥 https://www.linkedin.com/posts/brendanjowett_over-the-past-few-months-my-free-ai-community-activity-7407400496161767425-ttoQ Cheers, Brendan

A system that can bring $80k-$200k/mo in qualified pipeline and help you make money from the thin Air. (Note: make sure the client closes high-ticket deals only) 1. Signal-based lead generation Instead of blasting strangers… Go after the people already raising their hand through real signals. A few examples: IT companies posting about breaches → cybersecurity firms reach out within 24 hrs Recruiting firms posting new openings → staffing automation vendors contact same day SaaS companies hiring SDRs → sales enablement tools get in early Pull signals from Apollo, Sales Nav, Clay, Exa, public directories — wherever your ICP shows intent. Enrich → verify inbox → done. Stop guessing. Start timing. 2. Hyper-personalized icebreakers (15 sec each) If your opener sounds like: “I saw you’re doing great things at [Company]…” You already lost. Use THEIR: LinkedIn activity website data hiring/job signals industry context Example: “Saw you're hiring 3 SDRs this month. Before adding headcount, thought I’d share this — we’re producing 17x SDR output using AI workflows targeting only your ideal profiles. Worth a quick look if it adds $20k+ in qualified pipeline?” This takes 15 seconds with the right workflow. Which means your team can hit 100 targeted leads/day, not 20 generic ones. 3. Emails that de-risk the decision Every email must prove three things: They have the pain (reference their real situation) You have the solution (clear, simple, believable) You’re the safest vendor for it (proof, credibility, performance terms) Formula: Personalization → Pain/Solution → Proof → Soft CTA No 8-paragraph novels. No hype. And add de-risking lines like: “If I don’t produce X, you don’t pay.” “I’ll work for $0 until this outcome is hit.” Let them feel the before/after in their world. 4. 4–5 follow-ups (each with new value) Most teams stop after 2 emails. Top performers don’t. Each follow-up must bring something NEW: Short case study from their niche

Don’t be that nice guy on socials... Even on LinkedIn. Got a lead from Skool. He said he liked my posts on AI sales systems. Even mentioned the $40k CRM lift I talk about. Cool. I’ve been burned by tire-kickers before, so I decided to qualify first. Asked a few direct questions. Replied late (2-3d later). Vague (not understandable). Clearly AI-generated answers. No signal. No clarity. No ownership. Then out of nowhere: “You know… I can tell your posts are AI-generated. Your services and pitch are all over the place. But let’s see. This is what I need…” Then he pasted my own posts back to me like evidence. Cringe. I replied politely and clarified: I use Claude.ai to format. Stories, insights, experience = mine. Anyone who actually reads can tell. His response? “You disqualified yourself. If you post something, you should know exactly what you offer. Sales 101.” I was done. Not angry. Not defensive. Just clear. “I’m good, brother. I don't know what I post about, what I offer, who I am!” A lesson I learned the hard way: Tire-kickers don’t just waste time. They quietly mess with your confidence. They poke. They project. They test you without ever intending to buy. And if you’re too “nice,” you’ll entertain them longer than you should. This isn’t about starting wars or dunking on people. (Although platforms like X, admire controversies) I keep conversations respectful. But I’m also raw with boundaries now. If someone can’t: – answer clearly – respect your work – engage like an adult They’re not a prospect. They’re noise. The faster you spot them, the more energy you save for people who actually matter. "Being kind doesn’t mean being available to everyone." Share if you've a same sort of story.