How can I build an auto dialer with recording and note features, and what prompts and tools do I need?

#288 · stop giving away n8n templates, sell outcomes

How can I build an auto dialer with recording and note features, and what prompts and tools do I need?

Your main challenge is the auto dialer itself—power dialers are complex infrastructure, not just a simple front‑end app. For example, Clearvo is far more infrastructure than a basic app that triggers three dials on Twilio. For prompts and tools we rely heavily on Claude Code, supplementing with Codex models when Claude underperforms or a new Codex model drops. GPT‑5.6 was sold a couple months ago. We’re also experimenting with Cursor in our workflow; it’s just tagging it like Claude, and I find it a little bit better. Since these models change constantly, it’s not a big deal either way.

auto dialerclaude codecursorprompts

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youtube ↗AI & Automation

Can you make a tutorial on building an auto‑dialer using cloud code, without fully decoding your SAS?

Sure, I can make that tutorial. You’ll need to connect to an infrastructural partner that provides a call room under the hood—this handles the dialing for you, so you don’t have to place calls manually. When someone picks up, you’re connected into that room. It’s a high‑level overview, but if you ask Claude Code for help, it could get you about 80 % of the way there. In practice, we worked with specialists who know how to build high‑quality dialers to finish the rest.

auto dialercloud codeinfrastructure

youtube ↗AI & Automation

What are your thoughts on using real‑time voice agents like GPT Realtime 2.1, Gemini 3.1 flash preview, or Grock Voice Think Fast 2.0, given your skepticism about voice agents?

I’m still not a fan of voice agents overall, even with low latency, because there’s always a chance a human will notice something off and realize they’re talking to a robot, which usually leads to disgust. I don’t want to risk that trust with people calling to book appointments or rebook after paying. While I’ve tried models like GPT Realtime 2.1 and they’re faster and handle interruptions better, they still have gaps in contextual awareness and can bug out occasionally—something humans don’t do. My take is that, for now, the reliability and grace of a real person outweigh the speed benefits of these AI voice tools.

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youtube ↗Agency Operations

Okay, Gucci Lochi. Hey, Nick. This is Z. I want to schedule a demo for the power dialer, but please fix this issue, the show blank page on the scheduling portion. Thanks. Uh, what are we seeing here? Are we showing a blank page?

Let’s see—I’m not sure if the blank page is on my end, but it looks fine; this is how you book a meeting. Unfortunately we’re getting a lot of spam because people are doing this all day, so I’ll probably have to add a capture plus another mechanism. If you’re not making at least $100‑$200 a day, I probably wouldn’t recommend signing up for Clarvo; it’s more of an enterprise‑level offering, though if you run a thousand calls a day across your organization it can majorly benefit you, while lower volume probably isn’t the right fit. I could build a SaaS in cold email, but I chose cold calling because I prefer work that will stay valuable for a while. Cold calling is far less efficient than cold emailing and has more room to improve; it’s also one step down from text, which is easily automatable. I foresee totally automated cold‑email systems within the next 12 months, so I’d rather do something where my work still has value.

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youtube ↗AI & Automation

What are your thoughts on building and optimizing prompts?

I use an informal Google‑sheet approach: I take a prompt, run it on about 10 different inputs, score the outputs, and pick the prompt with the highest score. It’s not perfect, but it’s directionally correct and works well for quick iteration. For getting a voice agent to pause, you can try adding pause tokens like little stars or special symbols; whether it works depends on the specific voice model, as some are trained on audiobooks or transcripts that include pause tokens. It’s not guaranteed every time, but it can help depending on the model you’re using.

prompt engineeringvoice agentpausesml