The AI Why with Liam Lawson

In this episode, Andrew Warner, founder of Mixergy, host of over 2,500 founder interviews, and creator of The Next New Thing, reveals why the most exciting business opportunity in AI right now isn't building another chatbot or SaaS tool. It's building for AI agents as customers. Andrew shares how one founder went from $3K to $70K/month by simply pivoting his social media tool to serve AI agents instead of humans, why Jason Fried at Basecamp is now adding agent-first features, and what this means for every entrepreneur and operator watching the AI wave.

Andrew breaks down his own AI tech stack (Claude Code, VS Code, Atlas Browser, OpenClaw), why he keeps a separate laptop just for AI agent work, and the brutal honesty about how much time we're all spending "playing" with AI vs. actually building revenue-generating products. He and Liam go deep on the "SaaSpocalypse" debate, whether intelligence becoming a utility makes audience and distribution the only real moats, and why the agent-to-agent economy, where software sells to other software, might be the biggest shift since mobile.

Key Topics Covered

How Andrew built a $30M/year email newsletter business in his 20s and what he learned about monetization

The origin story of Zapier: Andrew was their first paying customer before they even had a product

Why AI's "shiny object syndrome" is the biggest trap for builders right now

Andrew's daily AI tech stack: Claude Code, VS Code, Atlas Browser, Claude Desktop, and WhisperFlow

How Postiz went from $3K to $70K/month by becoming the social media tool for AI agents

The agent-to-agent economy: why your next best customer might not be human

Is SaaS dead? Andrew's nuanced take after 2,500+ founder interviews

Why audience and platform stickiness are the only real moats when intelligence becomes a utility

Liam's Claude automation workflows: auto-generating guest research, marketing assets in 5 minutes

Vibe video editing and the future of AI-powered content production

Episode Timestamps

00:00 - Introduction and welcome

00:28 - Andrew's background: building a $30M email newsletter empire

02:00 - Selling the business in his mid-20s and traveling the world

06:19 - Starting Mixergy and doing 2,500+ founder interviews

09:39 - The founders Andrew admires most: Wade Foster and Zapier's origin story

12:07 - How solving problems for free changes your career

12:51 - AI's shiny object syndrome: building for fun vs. solving real problems

14:36 - Andrew's mission: helping AI builders find real revenue

17:45 - Andrew's AI tech stack: VS Code, Claude Code, Atlas Browser, WhisperFlow

22:32 - The ideal future of work with AI agents

24:31 - What's most impressive and most underwhelming about AI right now

25:20 - Building a social listening tool with AI

27:08 - The SaaSpocalypse debate: can you vibe-code your own tools?

36:12 - Postiz: from $3K to $70K/month by selling to AI agents

38:17 - The agent-to-agent marketplace future

40:06 - Liam's Claude automation: auto-generating guest research briefs

43:19 - Real-time AI workflows with WhisperFlow and Claude

48:02 - Why investing time in AI compounds exponentially

50:05 - Creating marketing assets in 5 minutes with Claude

51:27 - Vibe video editing: the next frontier for content creators

53:42 - Thought experiment: what's defensible when intelligence is a utility?

55:39 - The bread maker analogy: why SaaS won't actually die

58:01 - What makes software defensible: switching costs and stickiness

01:00:47 - Postiz deep-dive: the agentic social media scheduling tool

01:03:26 - Agent-first businesses: newsletters, chat apps, and tools built for agents

01:08:51 - Where to find Andrew and closing thoughts

Andrew's Socials:

LinkedIn — https://www.linkedin.com/in/andrewwarner/

Website — https://thenextnewthing.ai

Partner Links

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$1.75 trillion SpaceX IPO, Meta's closed-source Muse Spark, Anthropic's restricted Claude Mythos, OpenAI's four-day work week proposal, and Google's open-source Gemma 4. This week, the biggest companies in AI are making very different bets on power, access, and what happens next.

AI News in 5 is your fast, no-fluff weekly AI news roundup for founders, operators, and executives who need to stay current. Every Tuesday, in 5 minutes.

Stories Covered This Week:

Meta launches Muse Spark, its first closed-source AI model under Alexandr Wang's $14B deal

Anthropic restricts Claude Mythos to 50 partners via Project Glasswing over cybersecurity concerns

OpenAI publishes 13-page policy calling for 32-hour work weeks and a "robot tax"

SpaceX files for $1.75T IPO after $1.25T merger with xAI to build orbital data centers

Google releases Gemma 4, open-source models running on a single laptop

Timestamps:

00:00 Intro

00:25 Meta launches Muse Spark, goes closed-source

01:15 Anthropic holds back Claude Mythos over hacking risks

02:10 OpenAI proposes four-day work week and robot tax

03:05 SpaceX files for $1.75 trillion IPO

03:55 Google releases Gemma 4 open-source

04:45 Outro

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In this episode, Yasmeen Ahmad, Managing Director of Product Management for Data & AI Cloud at Google Cloud, reveals why 80–90% of enterprise data is "dark" and untouched — and how Google Cloud is building the tools to finally unlock it. Yasmeen shares how BigQuery's new Knowledge Engine captures the invisible business context that human analysts have always carried in their heads, and why this semantic layer is the real unlock for enterprise AI in 2026.
Yasmeen breaks down how enterprises are scaling from 50 to 2,000 autonomous AI agents, why continuous evaluation (not unit testing) is the only way to keep agents trustworthy, and what Google learned from seeing 50% of its own code now written by AI. She also explains why 95% of AI pilots produce zero measurable ROI — and why companies that partner with a platform like Google Cloud see dramatically different results. Plus, her contrarian take on governance: it's not the brake, it's what lets you drive 150 mph into the bend with confidence.
Key Topics Covered

Why 80–90% of enterprise data is "dark" unstructured data that GenAI can finally unlock

How BigQuery's Knowledge Engine captures the invisible business context analysts carry in their heads

The semantic layer: why the next big unlock is context, not just more powerful models

How enterprises are scaling from 50 to 2,000 autonomous AI agents

Intent-driven agentic AI: giving agents outcomes instead of step-by-step instructions

Why continuous evaluation is replacing traditional unit testing for AI agents

Google's internal AI adoption: 50% of code written by AI, 10% engineering efficiency gains

Why 95% of AI pilots produce zero ROI and what changes that outcome

AI governance as an accelerator — the "brakes that let you drive 150 mph" framework

Why culture and founder mentality matter more than technology budget for AI success

Episode Timestamps
00:00 - Introduction and welcome
00:50 - Being Scottish in Silicon Valley and the power of community
03:13 - The career thread: curiosity, pivots, and getting outside your comfort zone
06:20 - What makes data fascinating: the hidden stories inside numbers
07:48 - Why data is the lifeblood of enterprise AI
10:19 - 80–90% of enterprise data is "dark" and untouched
12:59 - What BigQuery actually does (explained simply)
14:50 - The invisible work: knowledge layers and business semantics
17:38 - The agentic AI moment: agents that think, plan, and execute
20:41 - From 50 to 2,000 autonomous agents inside enterprises
22:07 - Why you can't evaluate AI agents like traditional software
25:46 - Signals of AI readiness: Google's 50% AI-written code and Honeywell's 30% efficiency gains
30:21 - Why 95% of AI pilots produce zero ROI
35:37 - Governance as a speed accelerator, not a brake
39:53 - Who's best poised to win: culture over budget
45:59 - Why do you do what you do?
Yasmeen's Socials:
LinkedIn — https://www.linkedin.com/in/yasmeenahmaduk/
Partner Links
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In this episode, we break down the "Agentic Brain" — the architecture behind AI agents that can think, plan, and execute multi-step workflows with minimal human oversight — and why the agentic AI market is about to explode from $7.8 billion to over $52 billion by 2030. We reveal how the smartest enterprises are already deploying autonomous agents that handle everything from customer service to internal operations, and why only 14% of companies have production-ready agentic solutions despite all the hype.
We go deep on what "bounded autonomy" actually means in practice, how multi-agent systems work (inquiries surged 1,445% in just one year), and why Gartner predicts 40% of enterprise apps will embed AI agents by the end of 2026. We also cover the real-world examples of companies using agents to handle 80% of customer service autonomously, the difference between "agentic AI" and a chatbot with extra steps, and what operators and executives need to understand before deploying agents inside their organizations.
Key Topics Covered

What the "Agentic Brain" is and how it differs from traditional chatbots and copilots

Why the agentic AI market is projected to grow from $7.8 billion to $52 billion by 2030

How multi-agent systems work: planning, reasoning, tool use, and memory

Why only 14% of companies have production-ready agentic solutions despite massive investment

The concept of "bounded autonomy" and why it matters for enterprise deployments

How some companies are already using AI agents to handle 80% of customer service autonomously

Why multi-agent system inquiries surged 1,445% in one year

Gartner's prediction that 40% of enterprise apps will embed AI agents by end of 2026

The difference between real agentic AI and hype — how to tell what's actually production-ready

What executives and operators need to know before deploying AI agents in their organizations

Episode Timestamps
00:00 - Introduction and meet the Agentic Brain team
00:39 - Today's agenda: three practical AI agents
01:09 - Agent 1: Personalized learning agent
03:05 - How the learning agent works
09:25 - Live demo: testing the learning agent
16:50 - Future of personalized learning with AI
24:51 - Agent 2: Sales analysis agent
28:31 - Demo: Sales performance dashboard
32:41 - Call quality and feedback analysis
46:18 - Real-world impact: proactive team management
49:26 - Agent 3: Customer service agent
50:52 - Multi-agent systems and scaling
78:55 - Closing remarks and thanks
Partner Links
Work with Agentic Brain — https://cal.com/forms/44f75adf-4741-4c5e-88d5-3249592ada99
Book Enterprise Training — https://www.upscaile.com/
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This week on AI News in 5: OpenAI kills Sora just six months after launch — blindsiding Disney and losing a billion-dollar deal. Amazon drops $50 billion on OpenAI, putting Microsoft on the warpath. Apple dumps OpenAI and partners with Google to rebuild Siri. OpenClaw becomes the fastest-growing open-source project in history. And a hacker infects a popular AI tool downloaded 3.4 million times a day.
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Connect with Liam — https://www.linkedin.com/in/not-the-f1-driver-liam-lawson/
Get free AI resources: https://community.theaireport.ai/checkout/the-ai-report-welcome-gift?coupon_code=WRTH
About The AI Why with Liam Lawson:
The AI Why breaks down what's actually happening in AI — who's building it, how it's being implemented at scale, and why the people building it do what they do. New episodes every Tuesday (AI News in 5) and Thursday (founder and exec interviews).