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AI Agents & Lead Follow-Up Systems - Learn How to Build Your Own with Chris Lannon
Published November 14, 2024 · 139 views on YouTube
Key takeaways
- A voice AI agent can call a lead, pull a customized document (like a personalized report) into its context, and discuss it live on the phone.
- The demoed workflow: a lead magnet report is emailed, a follow-up text asks the lead to opt in, an opt-in reply tags the contact, and the tag triggers the AI voice call.
- The agent can hand off to appointment booking mid-conversation, checking calendar availability and confirming a time without a human involved.
- The system runs on GoHighLevel (CRM, tagging, automations) combined with Make.com (automation/tool calls) and OpenAI (the model powering the agent).
What does a voice AI lead follow-up agent actually do?
In this webinar, software engineer and Chief AI Officer Chris Lannon demonstrates a voice AI agent named “Haley” that calls a lead after they receive a personalized report, discusses the contents of that specific report on the phone, and can book a follow-up appointment on the lead’s calendar, all without a human on the call.
How does the agent know what to say about a specific lead’s report?
In the demo, adding a tag to a contact record in GoHighLevel triggers a Make.com automation that retrieves that lead’s specific report (in this case a “Market Sauce” report) and loads it into the agent’s context before the call connects. On the first attempt in the demo, the automation wasn’t running yet, so the agent only had generic company information and couldn’t answer questions about the lead’s actual report. After Chris restarted the automation and re-added the tag, the agent called back with the report loaded and was able to discuss specifics like the target market’s psychographics, geographics, and even generate an audience avatar and role-play as that avatar on request.
What is the full lead follow-up sequence shown in the demo?
- A prospect fills out a form and receives a customized lead magnet (in the demo, a “Market Sauce” report) by email.
- A follow-up text message is sent asking the lead to reply (e.g., “AI”) to opt in to a conversation about the report.
- The opt-in reply tags the contact in GoHighLevel.
- The tag triggers the voice AI agent to call the lead.
- A Make.com automation retrieves the lead’s specific report and loads it into the agent’s conversation context.
- The agent discusses the report’s content, answers questions, and can pivot to booking an appointment by checking calendar availability and confirming a time.
What platforms and costs does the system run on?
The stack combines GoHighLevel (CRM, tagging, automations, and the voice/chat/SMS agent platform), Make.com (for the tool-call automations, such as retrieving a lead’s report), and OpenAI (API tokens for the underlying model). In the webinar, Chris also announced a six-week course teaching how to build this system, priced at 1,497 with a 50% webinar discount (748), including a GoHighLevel sub-account and two months of the platform free before it converts to 297 per month; voice minutes (14 cents per minute), Make.com operations, and OpenAI tokens are separate pass-through costs.
Is this a tutorial or a live demo/course pitch?
This session is a live workshop replay and course announcement, not a step-by-step build tutorial. Darby hosts Chris Lannon, who replays a voice AI agent demo from an earlier “Scale with AI Summit” session, explains the agent/automation architecture behind it, and introduces a six-week course where students build their own version of the system alongside him.
Full video transcript
What’s going on y’all, Darby here, soon to be joined by Chris Lannon to discuss some cool developments in the world of voice AI agents that Chris is going to be walking a group of people through in an upcoming program that he has put together, and you’ll also be set up to tap into some additional resources and watch some demos on this call.
Darby introduces Chris Lannon, a software engineer by trade who has been focused on generative AI and related tools and technologies. Chris previously ran an Amazon brand and is now transitioning from a software engineering career into AI. He is a certified Chief AI Officer through Chief AI Officer.com, where he is also a fellow and mentor. Chris and Darby have collaborated on several projects, including the backend systems and automation behind Darby’s Market Sauce platform and Buyer Briefs products. The session covers how Chris applies “hands-off AI-driven lead gen” for himself and his clients, and introduces an upcoming course teaching others to build the same kind of system.
The two replay a demo Chris gave at the Scale with AI Summit. In the recording, Chris adds a tag to a contact record in GoHighLevel to trigger a call from “Haley,” a voice AI agent built for the Market Sauce brand. On the first attempt, the automation that retrieves the lead’s specific report hadn’t been started, so Haley only knew general information about Market Sauce and couldn’t answer questions about the caller’s actual report. Chris restarts the automation and re-triggers the tag; on the second call, Haley successfully retrieves the caller’s Market Sauce report and discusses its contents, including the target market’s psychographics (efficiency, growth, and innovation-focused coaches and consultants) and geographics (English-speaking countries including the US, UK, Canada, and Australia). At Chris’s prompting, Haley generates an audience avatar named “Alex Coachman” and role-plays as that avatar, describing pain points a voice AI system could solve and desires it could address. When Chris says he isn’t feeling well, Haley offers to schedule a coaching call, checks availability, and books an appointment for 8:30 the next morning, then politely ends the call when Chris asks for a soup recipe.
After the demo, Chris explains the broader framework: he builds customized lead magnets (of which Market Sauce is one example) for coaches, consultants, and other businesses. A voice AI agent then follows up once the lead magnet is delivered, retrieving the specific document generated for that lead and using it as conversational context, much like it did with the Market Sauce report in the demo. Chris describes the six-week course he is launching, which will teach this end-to-end process: building the lead magnet, delivering it, and following up by voice and text, including appointment booking. Chris frames the course as a hands-on lab where students build alongside him and experiment with additional automations. The course runs one hour of live teaching and one hour of office hours per week, and includes a GoHighLevel sub-account with two months of the voice AI platform included.
Chris reviews concepts he covered previously at the summit: what an AI agent is (a digital assistant capable of decision-making with access to tools, operating independently or with human supervision), the distinction between automations (repetitive, rule-based tasks) and agents (more autonomous, complex decision-making), and the benefits of agents including time savings, constant availability, easy duplication, fewer errors than humans, and the ability to scale entire “departments” of agents. He walks back through the Market Sauce workflow: a customized report is generated and emailed to the lead, a follow-up text asks the lead to opt in by replying, the opt-in reply tags the contact, the tag triggers the voice agent to call, and a Make.com automation retrieves the lead’s specific report so the agent has it in context during the call, including the ability to book an appointment once the report has been discussed.
Chris notes the platform integrates with GoHighLevel’s tagging and automation system, and that it also supports SMS chat and an embeddable voice “orb” for websites, showing an example built for a law firm (though a live demo of the orb is affected by a platform outage during the call). He offers course participants access to all of the automations he has already built, plus a community for sharing what works. As an added bonus, he offers a coupon for 50% off a Chief AI Officer certification program (normally 10,000).
Chris then breaks down pricing: the course plus two months of the platform is normally 1,497, discounted 50% for webinar attendees to 748, converting to 297 per month after the two free months. Separate pass-through costs include voice minutes (14 cents per minute, with 500 minutes included), Make.com operations (billed per module run, with a teams plan starting around 348 per year for 120,000 operations, or 2.90 per additional thousand operations), and OpenAI API token costs, which require the student’s own OpenAI API key.