Replace Yourself With Systems: How AI Helps You Work Less
04/25/25 • 42 min
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This week on The AI Report, Liam Lawson is joined by Matthew Cohn, the founder of Future Flow, to talk about one of the most practical applications of AI today: voice agents.
Matt doesn’t write code. He’s not a machine learning engineer. But he’s built a thriving business that automates sales, lead qualification, and customer follow-up using tools like Vapi, N8N, and custom GPT agents. In this episode, Matt explains how he went from university marketing projects to running voice agents that act as round-the-clock sales assistants for real businesses.
They dig into the real pain points these agents solve—missed calls, slow follow-ups, and overworked sales reps—and how small to mid-size businesses are starting to catch on.
Also in this episode:
• What makes a great voice agent prompt
• Why prompting is the core skill for non-technical AI builders
• How Matt handles imposter syndrome and subcontracting
• A breakdown of the orchestration layers and tools he uses daily
• What it takes to serve enterprise clients with AI systems
If you’ve been curious about AI agents, automation workflows, or what it takes to build a lean, scalable AI business without writing code, this is a must-listen.
Subscribe to The AI Report:
https://theaireport.beehiiv.com/subscribe
Join the community:
https://www.skool.com/the-ai-report-community/about
Chapters:
(00:00) Why Speed-to-Lead Still Wins Deals
(01:13) Matt’s Non-Technical Path to Building With AI
(03:45) Early AI Projects and First Use Cases
(06:05) Automating Business Docs With ChatGPT
(08:14) Leaving the Agency to Go All-In on Future Flow
(11:00) Pitching AI Solutions From a Sales Job
(13:20) Ghostwriting With GPT and Finding a Real Offer
(15:30) How Voice Agents Handle Inbound and Outbound
(17:45) The End-to-End Sales Process With AI
(20:00) End-of-Call Reporting and CRM Automation
(23:00) The Tools Behind It All: Vapi, N8N, GoHighLevel
(25:00) Leveraging Subcontractors to Scale
(28:00) Building With Confidence as a Non-Engineer
(30:30) Thinking Bigger: Serving Enterprise Clients
(33:00) Advice for Non-Technical AI Builders
(36:00) Start With Prompting, Then Automate
(39:00) What’s Next for Matt and Future Flow
This week on The AI Report, Liam Lawson is joined by Matthew Cohn, the founder of Future Flow, to talk about one of the most practical applications of AI today: voice agents.
Matt doesn’t write code. He’s not a machine learning engineer. But he’s built a thriving business that automates sales, lead qualification, and customer follow-up using tools like Vapi, N8N, and custom GPT agents. In this episode, Matt explains how he went from university marketing projects to running voice agents that act as round-the-clock sales assistants for real businesses.
They dig into the real pain points these agents solve—missed calls, slow follow-ups, and overworked sales reps—and how small to mid-size businesses are starting to catch on.
Also in this episode:
• What makes a great voice agent prompt
• Why prompting is the core skill for non-technical AI builders
• How Matt handles imposter syndrome and subcontracting
• A breakdown of the orchestration layers and tools he uses daily
• What it takes to serve enterprise clients with AI systems
If you’ve been curious about AI agents, automation workflows, or what it takes to build a lean, scalable AI business without writing code, this is a must-listen.
Subscribe to The AI Report:
https://theaireport.beehiiv.com/subscribe
Join the community:
https://www.skool.com/the-ai-report-community/about
Chapters:
(00:00) Why Speed-to-Lead Still Wins Deals
(01:13) Matt’s Non-Technical Path to Building With AI
(03:45) Early AI Projects and First Use Cases
(06:05) Automating Business Docs With ChatGPT
(08:14) Leaving the Agency to Go All-In on Future Flow
(11:00) Pitching AI Solutions From a Sales Job
(13:20) Ghostwriting With GPT and Finding a Real Offer
(15:30) How Voice Agents Handle Inbound and Outbound
(17:45) The End-to-End Sales Process With AI
(20:00) End-of-Call Reporting and CRM Automation
(23:00) The Tools Behind It All: Vapi, N8N, GoHighLevel
(25:00) Leveraging Subcontractors to Scale
(28:00) Building With Confidence as a Non-Engineer
(30:30) Thinking Bigger: Serving Enterprise Clients
(33:00) Advice for Non-Technical AI Builders
(36:00) Start With Prompting, Then Automate
(39:00) What’s Next for Matt and Future Flow
Previous Episode
How One Founder Replaced a 20-Person Team With AI Tools
On this episode of The AI Report, Liam Lawson sits down with Avi Hacker, founder of the AI Consulting Network and one of the most prolific solo operators in the AI world.
Avi doesn’t know how to code, but that hasn’t stopped him from building a business powered entirely by custom GPTs, Airtable workflows, Make.com automations, and a relentless commitment to experimentation. He’s automated everything from daily newsletters to podcast production and does it all without a technical team.
This conversation dives into:
- How Avi scaled from law school grad to AI consultant
- Why he operates like a 20-person team with zero employees
- The real cost of automation and what clients often misunderstand
- How he built tools for LinkedIn growth, blog creation, and deep research
- The tech stack behind his daily content engine
If you’re interested in the intersection of AI, automation, and solopreneurship, this is one to queue up.
Subscribe to The AI Report:
theaireport.ai
Join our community:
skool.com/the-ai-report-community/about
Connect with Avi:
linkedin.com/in/avihacker
Chapters:
(00:00) Building Anything Without Knowing How to Code
(01:00) From Law School to AI Consultant
(03:05) Starting the AI Consulting Network
(05:12) What Clients Get Wrong About AI
(07:00) Understanding Time ROI in AI Projects
(08:14) Live Walkthrough: Automating The AI Report Newsletter
(11:00) Building a Custom Workflow with Make and Airtable
(13:20) Why He Doesn’t Do One-Time Builds
(15:00) The Internal Tools That Power His Growth
(17:45) Working Like a 20-Person Team Using AI
(19:14) Future Plans and Scaling the Business
(21:00) Experimenting With AI Agents
(23:00) Training AI-First Operators
(25:00) Big Ideas, Small Teams, and the Power of Leverage
(30:00) Explaining His Job to Non-Tech Folks
(32:00) Where to Find Avi Online
Next Episode
The Hidden Risks of AI Mental Health Apps No One Talks About
This week on The AI Report, Liam Lawson is joined by journalist Kate Farmer to discuss a growing trend in mental health: the rise of AI therapy apps.
Kate recently published an investigative piece on Wysa, Woebot, and other mental health platforms that use AI to simulate therapy conversations. In this episode, she shares what it was like to interact with these tools firsthand, what users are actually experiencing, and why many of these apps are skating a dangerous line between wellness support and clinical treatment.
They also explore how these apps bypass regulatory scrutiny, the ethical challenges of relying on AI for emotional support, and how vulnerable users, especially those waiting for real therapists, are often left with few other options.
Also in this episode:
• Why rule-based AI might be better than LLMs in mental health
• How companies use marketing language to dodge legal oversight
• The limits of empathy, personalization, and context in AI
• What’s actually happening with your health data when you use these tools
• Why CBT still matters and how to use these platforms safely
This is a powerful, clear-eyed look at how AI is entering spaces once reserved for humans and what this means for trust, privacy, and care.
Subscribe to The AI Report:
https://theaireport.beehiiv.com/subscribe
Join the community:
https://www.skool.com/the-ai-report-community/about
Chapters:
(00:00) Why AI Is Not a Therapist
(01:06) Kate’s Background and Reporting Focus
(04:35) Revisiting AI Therapy Post-ChatGPT
(06:13) How Wysa Actually Works
(09:45) Empathy, Context, and Their Limits in AI
(11:13) Why Intake Matters in Mental Health
(13:39) False Personalization in Therapy Apps
(14:47) Real User Reactions to Wysa and Woebot
(16:28) When AI Becomes a Stopgap for Care
(18:05) The Case for Rule-Based CBT Tools
(22:08) AI Safety in Mental Health Tools
(27:30) Scale vs Support: The Infrastructure Gap
(29:25) Avoiding FDA Regulation with Clever Framing
(31:06) “Line Skating” and Legal Grey Zones
(34:42) The Health Data Economy Behind These Apps
(39:00) How Much Your Mental Health File Might Be Worth
(43:04) Accepting Flaws When There’s No Alternative
(44:02) CBT’s Real Strengths and Use Cases
(45:18) How to Use These Tools Without Risk
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