Nov 5, 2025 · 1h 1m · mixergy
#2284 Why is Morning Brew’s founder selling “AI Transformation”?
Arman Hazarkhani · 19m spoken Alex Lieberman · 17m spoken Jesse Pujji · 13m spoken Andrew Warner · 4m spoken
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gold bands on the timeline = statements, start to end. Hover to read, click to jump. CC turns on captions
Morning Brew co-founder Alex Lieberman and Tenex co-founder Arman Hazarkhani join Andrew Warner and Jesse Pujji to break down how their agency combines autonomous AI agents, output-based pricing, and multiplayer transformation to disrupt outsourced software engineering and enterprise consulting.
How this conversation actually went
Every chapter scored 0–10 on four independent dynamics. Hover any point for the reasoning behind the score. Andrew holds 7.8% of the talking time here. How this is scored →
Andrew as informed peer 4.2 Guest teaching 5.9 Guest disagreement 2.1 Andrew pushing back 3.3
speaking balance: gold is Andrew, purple is the guest (3 minute bins)
Sharpest disagreement ▶ 53:47 Alex rejects the corporate displacement narrative
Alex calls the popular truism that 'AI won't replace you, a person using AI will' total bullshit, arguing executives privately acknowledge plans to wipe out internal headcount.
Hardest push from Andrew ▶ 25:08 Andrew challenges business model sustainabilityAndrew directly challenges the core premise of Tenex's transformation arm, arguing that firms eventually run out of human costs to cut.
Biggest teaching moment ▶ 39:56 Arman orchestrates multi-agent parallel workflowsArman shows how cutting-edge engineers operate by spinning up multiple asynchronous sub-agents via Claude Code CLI rather than typing into IDEs.
Andrew holds their own ▶ 26:08 Andrew identifies the structural shift to engineeringAndrew corners the founders on their own stated metrics, arguing their shift toward dev contracts proves pure advisory audits have limited longevity.
the scores for every segment, with the reasoning behind each
| Chapter | Topic | Andrew as informed peer | Guest teaching | Guest disagreement | Andrew pushing back | Why |
|---|---|---|---|---|---|---|
| Defining AI Transformation and Tenex's Business Model | 3 | 5 | 1 | 2 | Andrew opens by probing how AI transformation differs from typical agency offerings. Arman and Alex outline their thesis, explaining multiplayer AI adoption and how engineering as a service acts as a recurring wedge into consulting. | |
| Output-Based Pricing and the Macro Vision for AI Services | 4 | 6 | 2 | 2 | Jesse and Andrew question the company's operating scope and pricing model. Alex and Arman detail their value-based output pricing structure, software margin dynamics, and high-level ambition to build an AI-native equivalent of McKinsey. | |
| Deconstructing Modern AI Engineering Through the SnapExports Project | 4 | 6 | 2 | 3 | Andrew asks for concrete mechanics of an AI-driven development workflow. Arman uses the SnapExports project to illustrate how AI engineers act as architectural managers directing multiple agent terminals rather than manually typing code. | |
| Private Equity Playbook, M&A Potential, and Client Retention | 5 | 5 | 2 | 4 | Jesse challenges the founders on whether AI transformation is merely sizzle compared to core engineering revenue. He lays out private equity roll-up opportunities and retention metrics, prompting the founders to defend their diagnostic lead-generation model. | |
| Executing an Enterprise AI Audit for a Billboard Tech Company | 5 | 6 | 2 | 4 | Andrew repeatedly presses Arman to move past high-level abstractions and walk through a granular client engagement. Arman breaks down the audit process for a billboard technology platform, pinpointing automated moderation and AI-assisted creative generation. | |
| Debating Market Longevity and the Evolution of Management Consulting | 6 | 7 | 4 | 7 | Andrew directly challenges the long-term sustainability of AI transformation, arguing businesses eventually run out of low-hanging efficiency gains. Alex and Jesse counter by comparing their service model to perpetual management consulting and evolving platform implementation. | |
| Live Demonstration of Custom GPTs for Business Operations | 3 | 5 | 1 | 1 | Alex presents a live screen share demonstrating custom GPTs built on Gino Wickman's EOS framework and Matt Mochary's executive playbook. Andrew observes and affirms the value of conversational external processing. | |
| Live Demonstration of Claude Code CLI and Autonomous Browser Agents | 3 | 7 | 2 | 2 | Arman demonstrates CLI tools like Claude Code and Playwright MCP to spawn parallel sub-agents and execute automated browser tasks. Andrew and Jesse watch as the agent autonomously navigates LinkedIn to send a direct message in real time. | |
| The Trajectory of Autonomous Agents and Human Workplace Displacement | 4 | 6 | 3 | 3 | The conversation shifts to broader macro questions regarding agent autonomy horizons and workplace displacement. Alex rejects corporate PR lines about AI merely assisting staff, predicting significant job replacement as digital employees expand their capabilities. | |
| Operational Margins, Reusable IP, and Final Reflections | 5 | 6 | 2 | 5 | Jesse and Alex debate output-based pricing risks, scope creep, and how reusable agent IP can protect margins. Andrew wraps up the episode by attempting to extract firm revenue numbers, which the founders playfully dodge. |
Statements from this episode (22)
Hazarkhani: Engineering drives most Tenex revenue, but AI transformation grows fastest
“So most of the revenue comes from engineering, but our fastest growing part of the business is AI transformation.”
Lieberman: Engineers are seeing greater AI leverage than any other knowledge workers
“And one of the things I've realized working around engineers now is engineers are living in the future. Like they are seeing the greatest leverage of AI relative to all areas of knowledge work.”
Lieberman uses 12-month engineering contracts as Trojan horse for AI consulting
“How do we use that to sign 12 month contracts that is highly retentive, highly recurring, and we use that as the Trojan horse to do transformation work after having that line of business.”
Hazarkhani: Software engineering demand is infinite and increases as price drops
“One of the core beliefs is that the demand for software engineering is infinite. It's completely, as price will go down, the demand will increase”
Lieberman: Service businesses will shift away from hourly billing starting in engineering
“We don't charge hourly. Like, we have a fundamental belief that service businesses are going to move away from hourly work, and we think it's starting with engineering.”
Lieberman says Tenex's top output-based engineer will make $1M next year
“Our clients pay us based on output, and our engineers are paid on output as well. And the reason that is so valuable is we can hire truly the best engineers I've ever worked with, because just as an example, like our best engineer will make a million bucks in …”
Hazarkhani says manual typing in an IDE is an outdated practice
“No one on our team actually types letters into an IDE. If I walk through a WeWork and I see someone typing letters in an IDE, they're working in like, 1990, right?”
Hazarkhani: AI engineers must act as architects delegating to agents
“An AI engineer needs to think like an architect. They have to think as if they're delegating all of their work to other engineers, and when they're delegating their work, how do they do that, right? And not only are they delegating their work to engineers, the…”
Hazarkhani: Voice AI is overblown and impractical in offices
“Frankly, I think that the voice thing's overblown. I think that when you work in an office, it's like unrealistic to talk out loud. I think that the voice thing is like useful if you're an executive driving your Tesla to and from work and you want to speak to …”
Lieberman: Modern AI dev shops use intelligence arbitrage, not labor arbitrage
“It's basically if traditional dev orgs or dev shops are labor arbitrage, we're intelligence arbitraging.”
Pujji: Red Ventures Doubled Bankrate's EBITDA in Nine Months
“When Red Ventures bought Bankrate, it was a publicly traded company, they paid 1.3 billion dollars for it. They paid 10 times EBITDA roughly, according to their math. Rick knew, he had done the math, he had seen all the levers, he knew that within a year of cl…”
Lieberman: Half of Tenex Clients Come Through Free AI Diagnostics
“Half of our clients have come through these free AI diagnostics we do. And so we run these diagnostics. They take two weeks. Most of it's been automated. The only thing that's not automated is basically three hours of stakeholder interviews, but half of those …”
Hazarkhani: Tenex acquires all customer business through LinkedIn, not X
“All of our businesses come through LinkedIn, not Twitter.”
Pujji: AI Model Updates Will Force Clients to Repeatedly Rehire Transformation Agencies
“Because every time AI changes, some new model's gonna launch, and then the same people who you did work for a year ago are gonna like, ah, shit, we need to do more work here, right?”
Lieberman: EOS implementers charge up to $15,000 a day for off-sites
“A lot of people hire actual implementers who either run your off-sites, help you with EOS implementation, and they charge a shit ton of money. Like, you know, it could be like 15,000 dollars a day for being at your off-site or with implementation.”
Hazarkhani says frontier developers consider Cursor outdated compared to CLI tools
“Our engineers would call you a boomer for using cursor. Like, that is like, so yesterday. And so the tools that are, like, the big ones right now are Codex CLI and Claude Code CLI.”
Hazarkhani: Failing to leverage near-free AI agents is a skill issue
“To that I say, basically, if you have a free or near free junior employee and you can't, and you have unlimited versions of this, you could spin up infinite numbers of these near free junior employees. If you can't find a way to generate leverage from that, th…”
Hazarkhani: Autonomous 24-hour digital employees will arrive before 2027
“Yeah, I would be more bullish than that person. I would say that it's actually much sooner.”
Lieberman asserts corporate claims that AI will not eliminate jobs are false
“Well, I mean, my, one thing I would say just specifically to the truism you just said, is I really just think it is, like, Bullshit. And like, basically every executive is like on one hand being like, how can I use AI in my company? On the other hand is saying…”
Hazarkhani: Tenex tracks daily margin per employee via output-based pay
“We have the margin down to the day, like we know our margin per employee because we're, we generate, we charge on output and we pay on output and everyone's aligned.”
Pujji: Output-based pricing requires narrow focus to protect margins
“When you think about costing based on outputs, what you're going to find pretty soon is you're going to want to narrow the things you start to focus on, like your example of the SDR thing, because then, you know, you can keep delivering it.”