A breakdown of how AI turned solo operators into one-person companies, and the exact team of tools they run instead of employees.
Posted
4 weeks ago
Duration
Format
Essay
hype
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228K
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57 · 43
Big Idea
The argument in one line.
AI replaced headcount as the source of business advantage, so one person can now orchestrate a team of AI workers to do what used to require an entire staff.
Who This Is For
Read if. Skip if.
READ IF YOU ARE…
You want to build or run a service business with AI doing most of the production work instead of hiring staff.
You already freelance or consult and want a repeatable AI team to take on more clients without working more hours.
You're deciding whether to leave a job to run a solo AI-powered business and want to see what the actual stack looks like.
SKIP IF…
You're looking for passive income with zero client contact. Every example here still requires outreach and ongoing client management.
You want a step-by-step build tutorial for one specific tool. This video names tool categories, not a walkthrough.
TL;DR
The full version, fast.
AI has broken the old rule that more output required more employees. A single operator can now delegate work to AI models the way a manager delegates to a team: a strategist and researcher to shape the offer, a builder like Base44 or Claude Code to ship the product, a writer and designer to produce content, and automation tools like Zapier or Intercom to run operations and support. The video grounds this in two cases: a solo operator earning $12,000 a month servicing local restaurants, and a founder who sold his AI-built startup to Wix for $80 million six months after launch. The real bottleneck isn't the tools anymore. It's whether you send the first message and own the result.
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Cold open claims solo operators with no employees are already outearning companies that have them, running businesses with a laptop and AI.
00:35 – 01:28
02 · History Of Work
For most of business history, labor was the limiting factor, so companies built layers of specialists and managers purely to coordinate more people.
01:28 – 02:14
03 · AI Broke The Traditional Way
Capacity, not creativity, was the historical advantage (Walmart's 2 million employees generate about $340,000 in revenue each), until AI made output cheap without adding headcount.
02:14 – 02:22
04 · Why Is This Shift Happening?
States the thesis directly: the unit of business scale has moved from employees to AI agents.
02:22 – 02:52
05 · AI Models Can Do REAL Work
Current frontier models handle real multi-step work, and a founder who built his interface almost entirely with Claude later sold the company for $80 million.
02:52 – 03:20
06 · AI Moved From Chat to Action
Agentic AI now operates a computer on its own; a cited benchmark shows real task completion jumping from about 15 percent in 2024 to about 80 percent today.
03:20 – 04:03
07 · The Cost Curve Collapsed
The price of a given level of AI intelligence dropped roughly 280-fold in two years, making it cheap enough to run several AI workers in parallel.
04:03 – 04:32
08 · How Does The One-Person Company Work
Reframes the one-person company: not one person doing every job, but one operator directing a team of AI workers.
04:32 – 06:45
09 · Meet Emma
Case study of a former hotel front-desk worker who now runs AI-powered marketing for eight restaurants at $1,500 each per month, about $12,000 a month total.
06:45 – 08:20
10 · How Far Can It Go?
Case study of Base44 founder Mayor Shlomo, who used Claude to write 90 percent of his product and sold the company to Wix for $80 million six months after launch.
08:20 – 08:37
11 · TAAFT
A plug for the host's own directory of 50,000+ AI tools, There's An AI For That.
08:37 – 11:04
12 · Let's Build Our AI Team!
Walks through nine AI-team roles and the specific tools for each: strategist, researcher, builder, writer, designer, video editor, operations, support, and analytics.
11:04 – 11:56
13 · The Dangerous Misunderstanding
Warns that cheap AI output makes production worthless on its own; the real advantage shifts to direction, distribution, trust, positioning, and taste.
11:56 – 14:46
14 · The One Skill You Need
Argues orchestration, breaking a goal into steps, assigning them to AI, and reviewing the result, is the one skill that separates people who get paid from people who don't.
14:46 – 15:30
15 · Which Person Are You?
Frames the real barrier as courage, not access to AI: sending the first message, charging money, and owning a decision with no one else to blame.
15:30 – 16:01
16 · Outro
Closes with two futures, doing nothing versus starting today, and a subscribe ask.
Atomic Insights
Lines worth screenshotting.
AI didn't just make work faster, it broke the link between headcount and output that businesses had depended on for a century.
In 2019, fewer than one in four startups had a single founder. Today it's more than one in three.
Americans filed a record 5.6 million new business applications last year, the highest number ever recorded.
AI task-completion on real computer work went from about 15 percent in 2024 to about 80 percent today, per METR's benchmark.
The cost of a given level of AI intelligence dropped roughly 280-fold between November 2022 and October 2024.
A solo operator can charge local restaurants $1,500 a month for AI-run marketing and still spend only about two hours a week per client.
Base44 hit $1 million in yearly revenue three weeks after launch and sold to Wix for $80 million six months later, built mostly by one founder and Claude.
When anyone can generate content for free, production stops being the advantage. Direction, distribution, trust, and taste become the advantage instead.
The gap between a generic AI prompt and a detailed, specific one is the same gap between a business that gets zero clients and one that gets paid.
Orchestration, not technical skill, is the single skill the new economy rewards: breaking a goal into steps, assigning them to AI, and reviewing the output.
Walmart employs over 2 million people and generates about $340,000 in revenue per employee per year, the old formula AI just broke.
The hard problems AI hasn't solved are the human ones: sending a message to a stranger who might ignore you, and charging money with your name attached to it.
Takeaway
Orchestration, Not Headcount, Is Now The Advantage
THE ORCHESTRATION SKILL
AI collapsed the cost of production, so the advantage shifted from headcount to orchestration: the ability to direct AI workers toward a result someone will pay for.
02History Of Work
For most of business history, output scaled only with headcount, so companies built management layers purely to coordinate more people doing the work.
Capacity, not creativity, was historically the advantage: Walmart runs over 2 million employees and generates about $340,000 in revenue per employee per year.
03AI Broke The Traditional Way
AI breaks the formula of more people equals more output by making output cheap to produce without adding a single employee.
In 2019 less than one in four new startups had a single founder; today it's more than one in three, and business applications hit a record 5.6 million last year.
04Why Is This Shift Happening?
The unit of business scale has shifted from employees to AI agents, which is the actual foundation of the one-person company.
Three forces stack together to make this possible: capable models, AI that can take action, and a collapsing cost of intelligence.
05AI Models Can Do REAL Work
Current models from OpenAI, Anthropic, and Google can now handle multi-step work with real context and structure, not just toy prompts.
A founder built his product's interface almost entirely with Claude and later sold the company for $80 million, evidence that AI output now clears a professional bar.
06AI Moved From Chat to Action
Agentic AI now operates a computer on its own, running code, testing it, and fixing its own mistakes instead of just answering chat prompts.
Real-world task completion by AI agents went from about 15 percent in 2024 to about 80 percent today, by METR's own benchmark.
07The Cost Curve Collapsed
The price of a given level of AI intelligence dropped roughly 280-fold between November 2022 and October 2024, making it cheap enough to run several AI workers at once.
Hiring an AI worker is now close to instant and inexpensive enough to run ten in parallel, which is what makes solo delegation viable.
08How Does The One-Person Company Work
A one-person company isn't one person doing every job alone, it's one operator directing a team of AI workers while staying the decision-maker at the center.
09Meet Emma
A solo operator can charge local businesses roughly $1,500 a month for AI-produced marketing (photos, social posts, review replies, booking reminders) and spend about two hours a week per client.
Eight clients at $1,500 a month is $12,000 a month run from an apartment, built on cold outreach, a free pilot, and then a recurring fee once the client sees it working.
The addressable market for this kind of offer is large on its own: over 1 million US restaurants, more than 100,000 gyms, and about 60,000 car washes and detailing shops.
10How Far Can It Go?
A solo founder who launched Base44 in February 2025, with Claude writing 90 percent of the interface, hit $1 million in yearly revenue within three weeks.
Six months after launch, Wix bought Base44 for $80 million in cash; the founder's job was reviewing AI output and making decisions, not writing code.
12Let's Build Our AI Team!
An AI team for a solo operator breaks into named roles: strategist (Claude, ChatGPT, Gemini) for positioning, researcher (Perplexity, deep research modes) for competitive and customer insight, and builder (Base44, Claude Code) for the actual product.
Content roles split further: a writer (Claude, ChatGPT) for drafts, a designer (Midjourney, Higgsfield) for visuals, and a video editor (Descript, Opus Clip, Runway, Veo) for short-form content.
Operations run on Zapier, Make, or n8n for onboarding and follow-ups, Intercom's Fin or a trained chatbot for support, and ChatGPT or Claude for reading messy numbers and flagging what to fix.
13The Dangerous Misunderstanding
AI lowers the cost of production, but it doesn't remove the need for value, so when anyone can produce output easily, that output stops being worth anything on its own.
The real advantage shifts to direction, distribution, trust, positioning, and taste, which is understanding what to sell, to whom, and turning AI output into something people actually want.
14The One Skill You Need
Orchestration is the one skill the new economy rewards: breaking a messy goal into steps, assigning those steps to different AIs, and reviewing output until it matches reality.
A generic prompt like 'write me a landing page' gets a generic result and no clients; a specific prompt naming the audience, the promise, the tone, and the objection gets a draft worth refining and shipping.
The new economy doesn't reward being technical, it rewards being able to steer generation toward something people will actually buy.
15Which Person Are You?
The easy problem (building the site, writing the content, running the system) is already solved by AI for a few dollars; the hard problem is everything AI can't touch.
The hard problems are entirely human: sending a message to a stranger who will probably ignore you, charging money for something with your name on it, and owning a decision with no one else to blame.
Millions of people now hold the same tools that built an $80 million exit; almost none of them will send the first message, which makes courage, not access to AI, the real filter.
Glossary
Terms worth knowing.
One-person company
A business run by a single human operator who delegates production work to a team of AI tools instead of hiring employees.
Orchestration
The skill of breaking a goal into steps, assigning each step to the right AI tool, and reviewing the output until it matches what's needed.
Vibe coding
Building software by describing what you want in plain English and letting an AI model write the actual code, with no manual programming required.
Base44
A no-code AI platform, launched by a solo founder in February 2025, that builds a full app (database, login, design) from a plain-English description.
Agentic AI
AI systems that take action on a computer on their own, such as running code, testing it, and fixing mistakes, rather than just responding to chat prompts.
“By the end of this video, you'll know exactly how they are doing it.”
classic promise-hook, sets a clear payoff→ TikTok hook↗ Tweet quote
08:09
“One man, six months, eighty million dollars.”
tight punchline that compresses the whole case study→ IG reel cold open↗ Tweet quote
11:30
“Output equals easy equals worthless.”
contrarian one-liner that reframes the whole AI-abundance narrative→ newsletter pull-quote↗ Tweet quote
14:44
“AI is no longer a limit, but you are.”
closing thesis stated as a single quotable line→ TikTok hook↗ Tweet quote
The Script
Word for word.
Read-along
Don't just watch it. Burn it in.
See every word as it's spoken — crank it to 2× and still catch all of it. The same dual-channel trick behind Amazon's Kindle + Audible.
17px
metaphoranalogystory
In 2026, starting a profitable company no longer requires a team or money. It requires you, a laptop, and AI. And this already works.
Right now, people with no employees are running businesses that used to need entire teams. Some of them are making more money than the companies they left behind. And you don't need anything special to be a part of it.
Ordinary people with ordinary jobs are using the same AI to replace their salary. Most people have no idea this shift is happening. The ones who do are already one step ahead of everybody else.
By the end of this video, you'll know exactly how they are doing it.
For most of modern history, the limiting factor of a business was labor. If you wanted to do more, you needed more people. More work meant more time, coordination, hiring, meetings, payroll, management.
You couldn't scale output without scaling the headcount. That is why companies evolved into layers. You had specialists, departments, managers, operations, basically systems that were built purely to coordinate humans.
The real work was not only doing the work itself, it was also getting people aligned enough to do the work together. And because labor was so expensive, the most powerful companies were the ones who could afford the biggest teams. advantage wasn't creativity.
It was capacity. Whoever had the most people could produce the most output. Walmart is the perfect example.
Over 2 million employees and each one of them generates around $340 ,000 in revenue per year. That was the only formula for a century. More hands, more output, more money.
But then AI came and broke this. Because AI doesn't just make people faster. It also changes the economics output.
And when output becomes cheap, the business model built on headcount collapses. In all In the old world, hiring was how you increased capacity.
In the new world, the same person increases capacity just by adding AI workers. And this is no longer a theory. In 2019, less than one in four startups was founded by a single person.
Today, it's more than one in three. Last year, Americans filed a record 5 .6 million new business applications, the highest number ever recorded in history. Most of them will never hire a single employee.
the unit of scale has changed from employees to agents. And that is the foundation of the one -person company era.
The reason this happened isn't one single breakthrough. It's the stacking of three big forces that together will create our new reality. First of all, models became capable enough to handle real work.
And I'm not talking about toy prompts and writing emails, but actual tasks that involve context, structure, and multi -step reasoning. OpenAI's GPT -5, Entropiq's Claude, and Google's Gemini, all of these are models that now write, plan, analyze code and design at a level that passes professional review. One founder built his entire product with Claude, the AI wrote 90 % of the interface, and the product sold for $80 million.
I'm gonna tell you which company it is in a minute. Second, AI moved from chat into action. This was the big prediction two years ago, and it came true.
OpenAI shipped agents that operate a computer on their own. Anthropic built an AI that writes code, runs it, tests it, and fixes its own mistakes. In 2024, the best AI could complete around 15 % of a real computer's tasks.
Today, it completes around 80%. The moment AI could take action on its own, it stopped being software that you use and became software that works. Third, the cost curve collapsed.
The price of intelligence keeps dropping. What used to cost a dollar two years ago now costs pennies. In the old world, hiring a smart person was expensive and slow.
In the new world, hiring an AI worker is basically instant and cheap enough that you can run 10 of them at once. If you put all of these three pieces of the puzzle together, you get a new capability. A single human can delegate tasks to AI workers the same way a CEO delegates tasks to a team.
Most people miss what actually changed. AI doesn't just make you faster. It actually turns you into the manager of an entire workforce.
So what does this actually look like? I'm not talking about big startups in Silicon Valley. I'm talking about your normal everyday life.
When people hear the term one -person company, they usually imagine someone doing everything alone. That sounds stressful. And in the old world, it was.
If you try to run a business all by yourself, you become the bottleneck for everything. But that is not what's happening with AI. The one -person company is not one person doing all of the jobs.
It's one person orchestrating a team of AI workers. One single operator sitting at the center of a system. while AI handles the heavy work around them.
Let me show you what this looks like in real life. Meet Emma. She's not a programmer.
She's not a marketer either. Two years ago, she was managing a small hotel's front desk. Today, Emma runs a one -person company that serves local restaurants.
Her offer is simple. She turns their boring online presence into a customer machine. New photos of every single dish generated and polished with AI.
Social media posts that are written and scheduled automatically. Google reviews answered within the hour by an AI. agent that's trained to sound exactly like the owner.
A booking reminder system that fills out empty tables on slow days. Each restaurant pays her $1 ,500 a month. This is conservative.
In reality, you can make much more than that for such a service. She has eight clients. That is $12 ,000 per month from her apartment.
And here's what Emma's work week actually looks like. The AI produces everything. Emma just spends her time reviewing the output, adjusting the tone, and talking to her clients.
She spends around two hours per restaurant per week. Now, replace Emma's name with yours.
Because you could definitely do this. Pick any local business that's too busy to handle their own marketing. Restaurants, gyms, dental clinics, car washes, Then send them a simple message or email.
Tell them how you noticed that they barely show up online and that you can fix that. Offer to build their entire system for free. And once everything is in place and they see it working, you will manage it for a monthly fee.
Hard to say no to that. And listen, don't get discouraged if they don't reply. Most of them won't.
That's normal. Send tens of messages every single day and expect a handful of answers. That handful is all you need.
Because here's the thing, you will never run out of doors to knock on. In the United States alone, there are more than a million restaurants, more than 100 ,000 gyms and fitness clubs, around 60 ,000 car washes and detailing shops. That's more than 1 million businesses from three niches alone.
And these are not even the biggest niches out there. You don't need a funding for this. You don't need a degree.
You don't even need to quit your job to start this. You only need one single client paying you $1 ,000 a month, then a second one, then a third one. And by client five, you're already matching an average salary.
By client 10, you've This is not a fantasy. This is the exact business model that thousands of solo operators are running in 2026.
Now, if Emma could build something like this from her apartment, how far can one person actually go? This founder from Tel Aviv actually found out.
Meet Mayor Shlomo. In February 2025, he launched Base44, a platform where anyone can describe an app in plain English and the AI builds it. The database, the login system, the design, everything.
No coding required at all. He launched it alone. No team, no office, no funding, no none of that.
Here's how his company actually ran. Claude wrote 90 % of the product's interface and half of his backend. While he slept, AI agents read through user feedback and sorted it by priority.
Other agents ran quality tests on his code and flagged problems before users even saw them. And another one turned his product updates into marketing content automatically. His job was not building, it was deciding.
He reviewed what the AI produced overnight, corrected the decision according to his taste, and shipped it. Three weeks after launch, Base44 hit $1 million in yearly revenue.
In May, he posted the numbers publicly. $189 ,000 in profit in a single month. And six months after launch, Weeks knocked at the door and bought his company for $80 million in cash.
One man, six months, $80 million. The human stays in the loop. But in our case, the human becomes the director, not a laborer.
This is the core shift. Emma runs it at $12 ,000 a month. Mayor ran it to $80 million.
Same level Same skills, but different scale. So the obvious next question is, what team of AIs do they actually run?
Let's build it, piece by piece.
Now, before me telling you about the AI tools that you can use for building a business, make sure to check out There's an AI for That, which is the biggest website for AI tools in the world. We currently have more than 53 ,000 listed AI tools. You can filter them by the task you want to do, and the value that you can get is absolutely insane.
Now, in order to make this real, let's build an AI team that our one -person team can actually operate with. So, first of all, we need a strategist. Claude, Chad GPT, Gemini.
These are the AIs that help you clarify the business model, the offer, the market, and the positioning. They basically force you to pick a niche, define a promise, and sharpen your message.
Then you need to do a bit of research. For that, you can use Perplexity or the deep research modes inside ChatGPT and Cloud. These AIs will scan your competitors, summarize customer pain, extract insights from reviews, and build a map of what people already pay for.
What used to take a consultant two weeks and thousands of dollars now takes 20 minutes and it's for free. Then you need a builder. This one didn't even exist two years ago.
We could use Use Base44, the software that I talked about earlier, and Claude Code. You describe the product in English, and an AI writes the actual software.
This is the exact category that Mayor Shlomo built. Then you need a writer. Claude for long form, ChatGPT for hooks and sales copy.
You can use Claude if you want drafts for landing pages, email sequences, and content. Not final versions, but high -quality starting points that you can direct. As for your designer...
mid journey for concepts, Higgs field for layouts. And this way you can get product shots, ad creatives, brand ideas, all of them in seconds instead of days. Then you need a video editor.
You can use Descript for editing, Opus Clip for short form clips, Runway or Google's VO for footage that never existed. And this way you're getting a one person marketing department. For your operations layer, you can use Zapier, Make, N8n.
All of these can run AI agents inside of your workflows. They can also do onboarding emails, CRM updates, follow -ups, invoices, everything.
They are triggered automatically and they make all of those things while you sleep. This is what Emma's review answering agent runs on. For your customer support, you can use something like Intercom's Fin or any custom chatbot that's trained on your business.
It handles the common questions and escalates only what needs a human. For analytics, you can use something simple such as ChatGPT or Cloud. It basically reads your messy numbers and tells you what to fix and what to double down on.
Now, here's the point. None of these AI tools are perfect, but they don't even need to be. They only need to remove around 80 % of your work, which they do, so your human attention goes to the 20 % that actually matters.
Decisions, relationships, creative direction, and accountability. That's the one -person company stack. And it costs less per month than you would pay a single day of one employee's salary.
There's a dangerous misunderstanding going around right now. People think that the one -person company era actually means that anyone could get rich instantly with AI. That's not how it works.
AI lowers the cost of production, but it doesn't remove the need for value. If output becomes easy, then it also becomes worthless. That's the paradox.
When anyone can produce, production stops being the advantage. So, in this case, what becomes the advantage? Direction, distribution, trust, positioning.
And last but not least, taste. Also, understanding real customer pain. Knowing what to sell and to whom.
Being able to turn AI output into a product that people actually want. The winners won't be the ones who generate the most. They'll be the ones who choose the right problem, package the solution accordingly, and deliver outcomes consistently.
If I had to reduce the one -person company era to one single skill, it would be this. Orchestration. Orchestration means you can take a messy goal and turn it into a system that produces results.
It means that you can do three things consistently. Break a goal into steps, assign those steps to different AIs, and review the output until it matches your reality. This is what most people miss.
They think the new economy rewards you being technical. It doesn't. It rewards the person that's able to steer.
When everyone can generate, which is the case right now, the people who win are the people who can steer that generation towards something that people actually buy. They know what good looks like, they can judge quality, and they can make decisions. Let me show you what's the difference in practice.
Person A opens chat GPT and types, write me a landing page for my marketing agency. He gets a generic result, posts it, nothing happens, and he gives up. Person B breaks it down.
Write a landing page for restaurant owners in mid -sized cities who are losing customers to competitors with better online presence. The promise is 10 new bookings in your first month or you don't pay. Direct tone, no fluff.
Address their fear of wasting money on marketing that doesn't work. He gets a strong draft. He refines it 20 times.
He ships it. Then he lands a client. Person A used AI.
Person B orchestrated AI. That is the difference between people that are making $12 ,000 per month like emma and the millions of people whose ai business never gets a single customer and that's how one single person can now run an entire business that used to require 10 people they're not doing the work with their hands they're steering the system with their judgment Most people watching this video will do nothing with it.
Not because the opportunity is not real because you've seen the receipts. Not because they're not smart enough because they don't even need to be. They'll do nothing because AI already solved the easiest problem and left the hard one untouched.
The easy problem was execution. Building the website, writing the content, running the system. That is handled now.
An AI army does that for a few dollars. The hard problem is everything an AI cannot touch. Sending a message to a stranger knowing they will probably ignore you.
Charging money for something with your name on it. Sitting alone with a decision, no boss to approve it, and no team to share the blame with. In the old world, you could always point somewhere else when things got wrong.
The market, the manager, the economy. In the one -person company, there's nowhere to point. Every win is yours, and so is every loss.
Here's what this means in practice. Millions of people around the world are now holding the exact tools Emma holds. The same tools that made Mayor Shlomo $80 million.
Almost none of them will send the first message. And that's how the tools stopped being the filter. Courage becomes a filter.
AI is no longer a limit, but you are.
So, let me paint you two pictures. In the first one, you wake up tomorrow and everything stays the same. You scroll past this video without subscribing, you go to work, and over the next few years, you watch it happen from the outside.
The solo operators, the tiny empires, the people who moved early. You tell yourself the timing wasn't right. Guess what?
The timing was right. It was right today. In the second picture, you wake up tomorrow and open a blank document.
You subscribe to our channel, you write down 10 local businesses, send 10 messages nothing happens you send 10 more the next day and somewhere in that boring unglamorous repetition your first client says yes your ai team goes to work and a year from now there's a company that exists only because you decided it should A company of one.
Two pictures, same tools, same world, same 24 hours in a day. The one -person era doesn't reward the biggest teams anymore. It doesn't even reward the best ideas.
It rewards the person who starts. And right now, while everyone is debating whether this is real, you are early. The question is, what are you going to do with that?
Make sure to like this video and subscribe to our channel if you want to see more videos like this one. Have an amazing day. Until next time.
The Hook
The bait, then the rug-pull.
The video opens with a claim that would have sounded like hype five years ago: a company with zero employees can now out-earn one with a full staff, as long as its founder knows how to run AI like a team.
Frameworks
Named ideas worth stealing.
01:10model
Capacity vs. Creativity
Creativity
Capacity
Advantage
A simple two-input model the video uses to argue that for most of business history, capacity (headcount) decided competitive advantage, not creativity.
Steal forframing why AI changes competitive advantage in a pitch or explainer
02:22list
The Three Forces Behind The Shift
Models became capable of real work
AI moved from chat into action
The cost of intelligence collapsed
The video's explanation for why solo AI-run companies are possible now and weren't two years ago.
Steal forany talk or post explaining why now is the moment for a solo AI business
08:37list
The One-Person Company AI Team
Strategist
Researcher
Builder
Writer
Designer
Video editor
Operations
Customer support
Analytics
Nine named roles and the specific tools recommended for each, covering the full loop from offer to delivery to support.
Steal forbuilding or auditing your own solo AI operating stack
11:56concept
Orchestration
Break a goal into steps
Assign steps to different AIs
Review the output until it matches reality
The three-part definition of the single skill the video argues matters most once everyone has access to the same AI tools.
Steal fortraining yourself or a team to direct AI work instead of doing it by hand
CTA Breakdown
How they asked for the click.
VERBAL ASK
15:55subscribe
“Make sure to like this video and subscribe to our channel if you want to see more videos like this one.”
Direct, low-friction ask placed right after the closing two-futures framing, with no product pitch attached.
Add Modern Creator as a preferred source and Google shows you more of our breakdowns in Search, Top Stories, and AI Overviews. It only changes what you see, and you can undo it in your Google settings anytime.
Add to Preferred SourcesOpens your Google source preferences with us pre-loaded. Tick the box and you're done.
A decision-only model built for picking, not writing, paired with Claude Code across nineteen real automations, from spreadsheet tagging to routing which Claude model handles a prompt.
A screen-share walkthrough of all 18 building blocks of OpenAI's Codex, from project folders to voice-controlled sub-agents, aimed squarely at people who don't write code.
A creator back from OpenAI Dev Day walks through every launch, from a unified Dots agent to a $500 ChatGPT plan, with early hands-on impressions of each.
Anthony Pompliano rebuilds his company's org chart as AI bots: a chief-of-staff bot on top, specialized bots underneath for recruiting, design, and more, all holding their own daily standup.
Seven free, mostly-unknown GitHub repos that plug TypeSafe's Jev decision model into Claude Code and Codex to make routine agent decisions dozens of times cheaper and faster.
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34:33
1:12:43
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