Latest / AI Fire Daily / #686 Neil: Claude Code Agents Let 7 Advisors Debate Your Ideas

Transcript

#686 Neil: Claude Code Agents Let 7 Advisors Debate Your Ideas · AI Fire Daily

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Imagine sitting at a massive mahogany conference
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table. Jeff Bezos is staring you down. Oh, man,
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and Warren Buffett is just, you know, tapping
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his pen. Right. And they are aggressively tearing
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apart your latest small business idea. It sounds
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like an absolute billionaire fever dream. It
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really does. But today, well, it's actually something
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you can build right on your laptop. Welcome to
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the deep dive. We're looking at a profound shift
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in how we use artificial intelligence. Yeah,
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we are moving away from the standard polite chat
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box. Today's mission is about transforming AI
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into a dynamic, arguing board of directors. Exactly.
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We'll be breaking down a free tool called Roastroom,
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which completely redefines how we extract strategic
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advice from these models. It really is a massive
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upgrade for anyone making high -stakes decisions.
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So we've got a clear narrative roadmap for you
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today. First, we'll cover how to install this
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virtual boardroom without needing a computer
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science degree. Thankfully. Then we'll feed it
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a real -world financial dilemma to see how it
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handles pressure. And finally, we'll look at
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how you can clone the minds of your favorite
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experts to join your personal council. Which
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is just wild to think about. But to get this
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kind of elite advice, you first have to construct
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the room itself. Right, which brings us to understanding
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what Roastroom actually is under the hood. It's
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an open -source project. Meaning the underlying
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code is free software that anyone can legally
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use, inspect, or modify? Exactly. 12 words or
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less. You aren't locked into some rigid corporate
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software that you just can't customize. I love
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that because it means developers are constantly
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tweaking it. And by default, Roastroom leverages
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a tool called Claude Code to build this AI board
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out of the box. Yeah, it preloads seven incredibly
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famous business minds. And they aren't just generic
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smart people either. Right, that you bring a
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heavily guarded, highly specific worldview to
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your problems. Like, you've got Jeff Bezos locked
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in on long -term business strategy. And customer
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obsession, yeah. Plus, Paul Graham is there scrutinizing
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your product development like a startup founder.
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And Alex Hormozi is relentlessly focused on your
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sales leverage and pricing models. You balance
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that out with Gary Vaynerchuk pushing hard on
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the brand and marketing side. Dan Martel is analyzing
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your hiring practices. And Gina Wickman is quietly
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looking at your operational systems, plus...
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Warren Buffett is sitting in the corner constantly
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evaluating downside risk. It is an incredibly
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intimidating room to walk into. If you put all
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those guys in a physical room, they would argue
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endlessly about what your actual priorities should
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be. But that friction is the entire point, right?
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Standard AI just tries to please you and summarize
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things neatly. Yeah, these advisors actively
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challenge each other's assumptions. You get to
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watch their arguments unfold in real time. They
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debate aggressively before handing you any final
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recommendation. But to see that debate, you have
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to get the software running. Historically, deploying
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a multi -agent AI environment locally required
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serious technical chops. Oh, completely. Usually,
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you have to open a scary terminal window. You're
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typing in complex developer commands like git
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clone and just hoping you don't break your computer's
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registry. Command line anxiety scares most people
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off immediately. But Rostrum bypasses all of
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that. You just use the Cloud Code Desktop application.
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which is built with a simple graphical interface
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for regular users. You literally just open the
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app, navigate to the code tab, and paste in one
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single sentence. Yeah. You just tell it clone
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github .com slash nateherkai slash roast -room
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and start the room for me. That is the entire
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setup process. Cloud Code acts like your personal
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IT assistant. It reaches out, downloads the project,
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and runs all those messy installation commands
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quietly in the background. It even verifies that
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the skill is installed correctly without bothering
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you with weird temporary folder issues. And when
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it finishes, it just pops open a virtual meeting
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right in your browser. Right on your own machine
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at the address localhost 4730, which is crucial
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because it means your sensitive business data
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isn't being beamed out to a public server somewhere.
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Exactly. It functions as a totally private boardroom.
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And the architecture making this happen is fascinating.
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It's like stacking Lego blocks of data. You snap
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the Jeff Bezos block onto the Warren Buffett
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block. Yeah, and suddenly their distinct knowledge
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bases are interacting within the same structure,
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but they aren't bleeding into one another and
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becoming a blurry mess. Right. That data isolation
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is the secret sauce. But here's where I want
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to push back a little on the mechanics. OK, go
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for it. I understand stacking the blocks conceptually,
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but how does a single underlying AI model actually
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adopt seven distinct, highly argumentative personalities
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without just getting completely confused? It
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does it through independent sub -agents. Think
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of them as walled gardens. Roastroom doesn't
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just ask one big AI to roleplay seven people
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simultaneously. Oh, so they're separate. Yeah,
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it spins up separate, isolated, clawed code instances.
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Each subagent only has access to its specific
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expert's worldview. I see. They process your
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problem completely alone first, form their own
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solid argument, and then they bring it to the
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group to fight it out. So they act as independent
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brains debating your specific prompt. Yes. They
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refuse to merge into a polite average opinion.
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They defend their specific territory. Knowing
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how to build the boardroom is one thing. But
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now that the agents are seated, we need to feed
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them a high -stakes decision. We have to stress
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-test the system with real money on the line.
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And the sources provide a fantastic real -world
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financial dilemma for this. Let's walk through
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the exact use case. We have a coaching business
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owner. They have 20 active loyal clients. And
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each of those clients is currently paying $2
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,500 a month. So we're looking at a very solid
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$50 ,000 in monthly recurring revenue. It's a
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great baseline. But the owner is getting squeezed.
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Operating costs are increasing rapidly, and the
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margins are shrinking. Right. They need to raise
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the monthly price to $3 ,500. Which is a massive,
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terrifying jump. You're asking people for an
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extra $1 ,000 a month. If you mess up the delivery,
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you could trigger a mass exodus and tank the
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business overnight. Exactly. So the owner brings
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this existential dread. to the Roast Room Council
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and the outline three potential paths forward.
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Option A is the aggressive route. Raise prices
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for all clients immediately. Rip the bandaid
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off. Right. Then option B is the staggered approach.
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Charge any brand new clients $3 ,500 immediately,
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but give existing clients a 60 day grace period.
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And option C is the fearful approach. Just eat
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the shrinking margins and keep the price at $2
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,500 for another six months, hoping things magically
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improve. The owner's main constraint is clear.
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They desperately need to increase revenue, but
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they are terrified of destroying those long -term,
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loyal relationships. Now, I've got to make a
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vulnerable admission here. I still wrestle with
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prompt drift myself. Oh, it happens constantly.
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You know, when you give a standard AI a long,
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complex scenario like this. You list the revenue,
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the options, the emotional fears of losing clients.
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And by paragraph 3, the AI just completely loses
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the thread. Yes. It forgets your original constraints
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and gives you generic advice. Single AI models
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have a really hard time holding multiple conflicting
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variables in their working memory. They just
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drift toward the most common internet consensus.
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Which is exactly why this multi -agent setup
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caught my eye. Roast Room doesn't just throw
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all seven default advisors at a nuanced math
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problem. No, it actively curates the room. Right.
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It acts like a smart chief of staff. Right. Before
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anyone speaks, Roastroom analyzes the prompt.
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It saw this was a complex pricing and relationship
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dilemma. So it benched a few people and selected
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an optimal five -person council specifically
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for this math. It brought in Alex Hermosy because
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he's the pricing and leverage guy. It grabbed
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Warren Buffett to calculate the raw financial
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risk. It added Paul Graham to evaluate what the
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customers actually need. Dan Martel was pulled
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in for the operational reality of the change.
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And of all, Ravikant was seated to assess the
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long -term enterprise value. It's a highly tailored
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brain trust. They've got the math guys balancing
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the relationship guys. So they sit in this digital
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room and start arguing. What was the actual verdict
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they handed down? The council ultimately chose
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option B, the staggered approach. They rated
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it an 8 out of 10 for effectiveness. And they
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assigned their own decision a confidence score
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of 7 out of 10. Yeah. A 7 out of 10 confidence
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score is actually pretty humble for an AI. It
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shows they recognize the inherent risk. Absolutely.
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But they didn't just rubber stamp option B, did
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they? Not at all. They actively tore it apart
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and modified the timeline. They agreed with charging
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new clients the higher rate immediately. But
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for the legacy clients, they suggested sending
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a notice within seven days and then enacting
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the new price in exactly 30 days. They cut the
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owner's proposed 60 -day grace period in half.
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They realized 60 days was just leaving too much
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money on the table while operational costs were
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rising. It makes me wonder about the actual mechanism
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here. Does the AI just act as a rigid calculator
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in these scenarios? What do you mean? Like is
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it only looking at the spreadsheets to maximize
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short -term cash or does it... actually weigh
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the emotional risk of alienating those loyal
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long -term clients? Oh, it definitely factors
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in the relationship risks. The sub -agents representing
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customer value successfully pushed back against
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Option A's immediate price hike. Ah, I see. They
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argued that the lifetime value of those 20 loyal
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clients was too high to risk angering them with
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zero notice. They forced the math -focused agents
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to compromise on the 30 -day window. They don't
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just vote. They actively rewrite your plan for
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safety. They act like true fiduciaries. trying
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to protect your entire business, balancing the
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math with the human element. We are going to
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take a brief pause here for our sponsors. We
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will be right back with more on Roast Room. And
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we are back. Getting a great boardroom decision
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on a Tuesday doesn't really matter if you can't
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remember why you made that decision six months
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from now. So true. And it only works if you have
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the exact right experts in the room. Let's look
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at keeping score and expanding the team. This
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is where Roastroom transitions from being a neat
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party trick into a serious long -term strategic
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tool. It automatically generates documentation
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for every debate. You can just click to download
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a PDF report of the entire session. Yeah, it
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gives you the final verdict, the confidence scores,
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and a detailed breakdown of the key risks they
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identified during the argument, plus the immediate
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next steps you need to take. And it saves all
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this data locally on your own machine. It creates
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a simple markdown file named verdict .md right
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in your project folder. So you always have the
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receipts. You can easily retrieve it later using
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Cloud Code Desktop. The sources highlight a feature
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called replay that I found absolutely fascinating
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for long term accountability. It's incredible
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for improving your own judgment. Let's say you
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implement that 30 day price hike based on their
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advice. A few quarters pass. Right. You can go
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back into the app, find the past sessions tab
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and literally hit replay. You watch the original
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debate unfold again. Which lets you check their
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theoretical warnings against your actual real
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-world results. Did Warren Buffett warn you about
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a specific churn rate that ended up happening?
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Exactly. You can pinpoint exactly where the AI
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was prescient and where it was totally blind.
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It helps you calibrate how much you trust them
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the next time you face a similar problem. Having
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the default seven advisors is great, but every
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business has highly specific bottlenecks. And
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this is where the system gets wild. You can actually
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build custom Frank advisors. You are not limited
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to the preloaded personalities. You can clone
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the mind of almost any expert who has a significant
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amount of public data available online. The sources
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use Seth Godin as the prime example. Let's say
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your coaching business is struggling with positioning
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and you need elite marketing advice. You don't
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have to settle for the default room. You go into
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the interface and type a very simple command,
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slash new roaster Seth Godin. It asks you a couple
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of quick set of questions. You define his core
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expertise as positioning and marketing. You assign
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him a seat on your default board and you set
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the research depth to standard. And then you
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just step back and watch the subagents go to
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work. This research phase is honestly the most
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impressive part of the underlying technology.
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Claude Code deploys multiple separate agents
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to scour the internet. They relentlessly hunt
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down his specific worldview. They collect his
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public articles. They read years of his blog
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posts. They transcribe his podcast interviews
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and public talks. They are essentially building
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a custom, highly concentrated neural net of Seth
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Godin's brain. But they aren't just blindly scraping
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text. Right. They run it through an intense verification
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process. Which is necessary because we all know
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AI loves to hallucinate fake quotes that sound
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smart. Rostrum actively fights that tendency.
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Every single piece of scraped data goes through
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a rigorous quote check against the original source.
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The sources document a specific test run of this.
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During the research phase for a custom advisor,
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Claude code systematically checked exactly 1
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,141 quotes. Well, imagine scaling to a billion
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queries. Right. The speed and scale are just
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staggering. It verified every single one of those
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quotes against the original source material.
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And if a quote was slightly misremembered or
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hallucinated by the scraping agent, the verification
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agent actively fixed it before allowing it into
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the Custom Advisor's memory bank. It completely
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changes the reliability of the advice. You aren't
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guessing if this is actually what Seth Godin
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would say. No. You have mathematical confidence
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that his digital clone is pulling from his verified
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philosophies. Once that research compiles, Seth
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Godin just pulls up a chair at your virtual table.
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You can start bouncing positioning ideas off
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him immediately. But deploying all these highly
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complex researching sub -agents isn't free behind
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the scenes. It definitely consumes your API credits.
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Every time these agents think and argue, you
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pay a fraction of a cent to the underlying AI
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provider. That can add up if you're running a
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massive debate for every minor email you write.
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Which is why Rostam includes specific management
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commands to control your costs. It gives you
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a lot of flexibility. If you are facing a massive
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bet the company pivot, you use the full counsel
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command. That brings every single advisor you've
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built to the table for an exhaustive deep dive
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review. And it costs a bit more in API usage,
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but the thoroughness is worth it. But for smaller,
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everyday ideas, you use quick mode. You just
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type dash dash quick. It streamlines the debate
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process. The agents don't argue quite as long,
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which saves you API credits and gives you faster
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answers. And if you want to be really surgical,
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you use the selected advisors command. You type
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dash dash seats, followed by the specific names
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you want. So dash dash seats, Hormozi, comma,
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Buffett. That isolates the room. You only pay
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for the exact brains you need for that specific
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problem. It's incredibly efficient. It is. But
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let me challenge the ultimate utility of all
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this. Isn't it profoundly dangerous to blindly
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execute a major business pivot just because a
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digital Seth Godin and a simulated Warren Buffett
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told you to? Oh, it's incredibly dangerous. You
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can never abdicate your responsibility as the
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decision maker. The AI is brilliant, but it lacks
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physical context. It doesn't know the exact emotional
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temperament of your specific client base. It
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doesn't know the subtle nuances of your local
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market conditions either. It's working off probabilities,
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not certainties. So treat their advice as a baseline,
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not a Bible. Precisely. You must always filter
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their recommendations through your own localized
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real -world data. It's a tool for stress testing
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your ideas, not a substitute for your own judgment.
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So what does this all mean for us? If we pull
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back and synthesize everything we've covered
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today, the shift here is profound. It completely
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changes our fundamental relationship with artificial
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intelligence. For years, we've treated AI like
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a single omniscient oracle. We walk up to the
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glowing box, we type in a question, and we expect
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one perfectly unified average answer. But that
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isn't how resilient decisions are made in the
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real world. Good decisions require friction.
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They require deeply smart people looking at the
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same data and vehemently disagreeing with each
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other on what it means. By leveraging a tool
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like Roastroom, we're moving away from the Oracle
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model. We're embracing a dynamic, argumentative
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team. We're actively building a system designed
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to poke holes in our logic and expose our strategic
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blind spots before they cost us actual capital.
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It is literally like having a billion dollar
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advisory board sitting right on your laptop,
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ready to pressure test your wildest ideas at
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three in the morning. We highly encourage you
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to go try this. Install Roast Room on your machine.
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Take the single biggest bottleneck currently
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suffocating your career or your business. Feed
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it to the council. Step back and just watch them
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argue about your future. You will be amazed at
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the angles and risks you completely missed. It's
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a phenomenal exercise in strategic thinking.
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But as we wrap up this deep dive, we want to
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leave you with a lingering thought. A little
16:49
something to chew on as you start building your
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own custom council of experts. Because the customization
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feature is incredibly powerful, but it comes
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with a hidden strategic trap. If you curate your
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AI board exclusively with experts who already
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share your exact same worldview and business
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philosophies, are you actually buying good critical
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advice? Or are you just using cutting -edge technology
17:12
to build the ultimate impenetrable echo chamber.