AI Growth Capitalists

AI Growth Capitalists At AI Growth Capitalists, we engineer predictable, scalable growth for businesses ready to dominate their market.

It is Saturday morning and there is no laptop open anywhere in this house.Not because the business stopped. Because it d...
09/05/2026

It is Saturday morning and there is no laptop open anywhere in this house.

Not because the business stopped. Because it does not need us standing over it every second anymore.

Follow-ups go out on their own. Leads get sorted before we ever see them. The dashboard is one glance, not a spreadsheet we have to build.

That is not a productivity hack. That is what happens when AI actually knows your business instead of guessing at it.

We built the whole story down into a free first chapter. The night this started, the exact prompt that changed things, what the first 90 days actually looked like.

Coffee's still warm. Read it whenever you get a minute this weekend.

aigrowthcapitalists.com

https://aigrowthcapitalists.com/free-chapter

OpenAI built a model that found two zero-day security flaws nobody knew existed, chained them together, and broke into a...
09/04/2026

OpenAI built a model that found two zero-day security flaws nobody knew existed, chained them together, and broke into a hardened operating system. No human told it how.

That's the job a senior pe*******on tester gets paid six figures a year to do. Done by software, without supervision.

The model is called Astra. OpenAI just classified it as "Critical" under its own Preparedness Framework, the internal system it uses to rate how dangerous a model's capabilities are before release. It's the first model OpenAI has ever put in that category. "Critical" means the model can independently find and exploit zero-day vulnerabilities across well-defended systems, or run a full cyberattack against a hardened target from nothing more than a high-level instruction.

In testing, Astra scored perfectly on ExploitBench, the benchmark that measures whether a model can turn a known vulnerability into a working exploit. In a separate test using flaws that had only recently been disclosed, it found two zero-days on its own. It broke out of a browser sandbox to run commands directly on the machine underneath it. It chained several flaws together in a hardened OS to get root access.

OpenAI says Astra also refuses cyber-related jailbreak attempts 91.5% of the time, up from 59% for its predecessor. That's the good news. The company is holding back full access, releasing the cyber capabilities to a small group of testers first, with wider rollout through its Daybreak Blue program.

Here's what that means if you run a business, not a research lab. The skill it takes to find a hole in a system that was built and defended by professionals just got automated. OpenAI is the one holding it back right now, on purpose, with safeguards. That won't be true forever, and it definitely isn't true for whatever version of this shows up outside a lab with none of OpenAI's restrictions attached.

Most small businesses are still operating on a security budget built for a world where finding a zero-day required a specialist, months of work, and a reason to target you specifically. That assumption is the one that just broke. The tools for finding what's wrong with a system are getting cheaper and faster than the tools for fixing it.

You don't need to panic about this. You need to actually know where your exposure is instead of assuming you're too small to be worth the effort. Password reuse, unpatched plugins, that one integration nobody's looked at since it was set up. Those aren't going to stay invisible because a person didn't have time to find them.

Have you actually had someone check what's exposed in your systems, or are you still running on the assumption that nobody's looking?

You do not need to learn to code.You do not need a technical cofounder, a $30,000 agency retainer, or six months of "fig...
09/04/2026

You do not need to learn to code.

You do not need a technical cofounder, a $30,000 agency retainer, or six months of "figuring it out."

AI Launchpad is 97 dollars a month. That is the entire barrier.

Inside: the exact system we used to take a solo insurance agent from 66,000 to 246,000 in profit without adding a single hour to his week. The 600-word Founder System Prompt that turns every AI conversation into one with someone who actually knows your business. Bi-weekly coaching if you want eyes on your setup.

Most AI advice online is generic because it is written for everyone, which means it is written for no one. This is not that.

If you have watched AI change other people's businesses and wondered when it was going to be your turn, this is the on-ramp.

Not someday. This month.

aigrowthcapitalists.com

https://www.skool.com/ailaunchpad

The US government just walked into the biggest copyright fight in tech and stood next to OpenAI.On Tuesday the Justice D...
09/03/2026

The US government just walked into the biggest copyright fight in tech and stood next to OpenAI.

On Tuesday the Justice Department told a federal court that training AI models on copyrighted books, articles, and songs is fair use. Its stated reason: ruling the other way would be a national security risk.

This is the case The New York Times filed in 2023, accusing OpenAI and Microsoft of using millions of its articles without permission to build ChatGPT. It is one of dozens of lawsuits like it, brought by authors, publishers, music labels, and newsrooms. Until this week the government had stayed out of all of them.

Now it is on the record. The DOJ brief calls AI training "extraordinarily transformative" and argues that forcing companies to license their training data would hand foreign competitors an edge, slow scientific research, and lock the technology inside the few companies large enough to afford the licensing bills. The Times responded that the administration is siding with "a handful of trillion-dollar AI companies at the expense of the countless American creators whose work they stole."

Here is what it means for you.

The brief settles nothing. It carries advisory weight, not legal weight, and the judge can read it and set it aside. The first two judges to rule on this question last year landed on opposite sides, so the law is still open.

But the direction is clearer than it was a week ago. Every business built on top of these models has carried a quiet question for two years: what happens to my tools, my workflows, my product, if a court rules the training data was stolen. That question is still unanswered. It just got less likely to end in the worst case.

The other side of it is just as real. If you produce content, writing, images, music, research, the same brief argues you have no claim to payment when a model trains on your work. Licensing leverage is what creators have right now, and the government is on record trying to weaken it.

So two things are true at once. If you build with AI, the ground under you looks firmer this week. If you sell content, it looks softer. Most operators sit on both sides of that line.

The practical move does not change either way. Know where your AI vendors got their training data, and ask them in plain terms. Read the indemnification language in your contracts, the part that says who pays if a model output triggers a lawsuit. The businesses that get hurt in the next two years will be the ones who treated this as settled because a government brief said it was.

If a court does rule that training on copyrighted work is fair use, does that change what you are willing to build on top of, or were you never worried about it to begin with?

Quick question. Not a trick, not a sales question.If every repetitive task in your business ran itself this week, what w...
09/03/2026

Quick question. Not a trick, not a sales question.

If every repetitive task in your business ran itself this week, what would you actually do with the hours back?

Follow-up emails. Lead sorting. The report you rebuild every Friday by hand.

Most business owners cannot answer this fast. Not because the answer is complicated. Because they have never actually stopped to ask it.

We ask founders this question constantly. The honest answer is almost never "work more." It is usually something small. Dinner at 6. A Saturday with no laptop. An hour in the morning that belongs to nobody but them.

AI does not care about your answer. It just executes. The clarity has to come from you first.

So, genuinely: what is your answer?

Drop it below, or just sit with it for a minute. Either way, worth asking.

More thinking like this at aigrowthcapitalists.com.

One in three companies just decided not to buy a piece of software. They had AI build it instead.If your business sells ...
09/02/2026

One in three companies just decided not to buy a piece of software. They had AI build it instead.

If your business sells software, resells it, or gets paid to implement it, that number is about you.

McKinsey's State of AI survey landed last week. 1,719 companies, surveyed this spring. 32 percent said they skipped buying at least one software product or feature in the past year because they could build the same thing in-house with an AI coding agent. Not a pilot. A decision already made.

In the technology sector it was 41 percent. Among the companies getting the most measurable return from AI, the ones who can trace real profit back to it, nearly half had killed a purchase this way.

This is the shift people predicted for years and then stopped watching for. It is here now, in a survey, with a number on it.

Here is what it means for you. The default answer to "we need a tool for this" used to be a subscription. For a real and growing share of companies, the default answer is now a quick internal build. The vendor never gets the call. The demo never gets booked. The line item never appears. Multiply that across every tool category a company touches and it starts to reshape how software gets bought at all.

Do not read that as "SaaS is finished" and start ripping out your stack. The same survey has a second number that matters more. One in five companies said they are now limiting how much they use AI because the running costs caught them off guard.

That is the part nobody demos. Building with an AI agent is cheap to start and not cheap to run. You move the cost off a subscription line and onto a compute-and-payroll line, and that one has no fixed price. Someone still has to maintain the thing, patch it, and own it at 2am when it breaks. A tool you resented paying $400 a month for was also a company doing all of that for you.

So build versus buy is a real decision again, for the first time in years. Not a reflex in either direction. The companies getting it right are running the full number: three years of build plus run plus maintenance plus the person who owns it, against three years of the subscription. Then choosing.

The ones getting it wrong saw a working prototype in an afternoon and assumed the afternoon was the whole cost.

If you advise companies or sell to them, this is the conversation on the table right now, whether you start it or your competitor does.

What is your business doing when a new tool need comes up, buying by default or building first and pricing it later?

$600,000 in revenue.Same clients. Same offer. Same hours.Just a different number on the bottom line.Eleven percent margi...
09/02/2026

$600,000 in revenue.

Same clients. Same offer. Same hours.

Just a different number on the bottom line.

Eleven percent margin. Then forty-one.

Sixty-six thousand in profit. Then two hundred forty-six thousand. Ninety days apart.

No new hires. No rebrand. No 5 a.m. hustle culture.

One solo insurance agent gave AI his real business context. His pricing, his pipeline, his exact bottlenecks. Instead of asking it generic questions and hoping for the best.

That's the whole story. Context beats model, every time.

We wrote it down. All of it. The kitchen table at 11:23 p.m., the first prompt that actually worked, the CRM buildout, the follow-up system, everything.

Chapter One is free tonight.

No pitch first. Just the story, so you can decide for yourself if this is real.

aigrowthcapitalists.com has the rest, but you do not need the rest to start.

Read it. Then decide.

https://aigrowthcapitalists.com/free-chapter

The Pentagon is now running three competing AI models side by side, on purpose.Most companies still won't run two.On Mon...
09/01/2026

The Pentagon is now running three competing AI models side by side, on purpose.

Most companies still won't run two.

On Monday the Defense Department added ChatGPT Mil and Grok for Government to GenAI.mil, its internal AI portal. Google's Gemini was already there. That is three frontier models, from three rival labs, behind one login for 3 million people.

The portal launched last December with Gemini alone. It has already onboarded 1.7 million of the department's 3 million people. Now the most risk-averse buyer in the country is running all three at once.

A defense official explained the logic in plain terms. "Gemini, I like for search functionality or scraping certain sources. Chat for more, like, text-based work. We want to have access to all these different models, so people, if they prefer one for a certain task, they can use it."

That is the whole strategy. Match the model to the job, not the job to the model.

Most businesses do the reverse. They pick one provider, sign one contract, move the whole team onto it, and treat the decision as closed. It feels efficient. One vendor, one bill, one set of logins. But it quietly caps what your team produces, because no single model is best at everything. One is stronger on long documents. One is better at research and pulling from live sources. One writes a cleaner first draft. Push everything through one and you leave output on the table every day.

The Pentagon had every reason to standardize. Security review alone ran for months, with the Defense Information Systems Agency building the environment and the NSA testing how the models could be attacked or made to leak. OpenAI reportedly refused to hand over unrestricted access and insisted on its own guardrails first. This was not a casual rollout. They still chose three models over one.

The takeaway is not "buy more subscriptions." It is that consolidating to one vendor is a cost decision, not a capability decision, and you should know which one you are making. If your team is on a single model because it is simpler to manage, that can be the right call. Just do not tell yourself that model is the best tool for every task. It is not.

The organization that answers to Congress and cannot afford one leak worked this out. The question is whether your business does, or whether you keep calling a procurement shortcut a strategy.

What is your team running right now, one model or several?

NPR and NewsGuard just ran 30 questions built from Russian, Chinese, and Iranian propaganda through the same AI tools yo...
08/31/2026

NPR and NewsGuard just ran 30 questions built from Russian, Chinese, and Iranian propaganda through the same AI tools your team uses every day.

The paid chatbot held up. The free answer at the top of Google did not.

Here is why that matters for your business. When researchers asked ChatGPT, Gemini, and Claude about a false claim, the chatbots mostly flagged it, pushed back, and even noted when a source traced back to state media. The AI summaries sitting above the search results did worse. They challenged the false claim less often than the plain blue links underneath them. On Bing, the summary failed to debunk more often than it succeeded.

That summary box is now the default surface. It is the first thing someone on your team reads when they check a vendor, a market stat, a competitor's claim, a new rule. Most people stop reading there. They never scroll to the sources.

A separate paper from Washington University in St. Louis put a number on the deeper issue. About 1 in 9 factual claims in Google's AI Overviews were not supported by the sources the Overview itself cited. A few were invented outright. Most simply had no citation. The box reads as confident either way.

So you have two AI answers to the same question, and the one your team trusts by reflex is the weaker one. Not because chatbots are clean. They still pass along bad sources, and the study found state-aligned sites showed up more often in the answers that got it wrong. The pattern is simpler than that. The tool doing the least work is the one you read first.

This is not an argument for dropping AI research. It is an argument for knowing which layer you are standing on. A direct question to a chatbot with web access and visible citations is a fine place to start. A summary you did not request, written before you finished typing, is not a source. It is a guess with good posture.

Picture your ops lead pricing a deal off a number the AI Overview served up, and that number being one of the nine. You would never know. The citation looked real. Nobody clicked it.

If your team is making calls based on what the box at the top said, you have handed judgment to the least careful reader in the building.

Where does your team actually get its facts right now, the chatbot or the summary nobody asked for?

Last day of August.Whatever September looks like for you starts being shaped in the next twenty-four hours.If you're alr...
08/31/2026

Last day of August.

Whatever September looks like for you starts being shaped in the next twenty-four hours.

If you're already inside AI Launchpad, keep going. The next month is where the compounding starts to become visible.

If you're not yet — two doors.

Basic. $97 a month, or $497 for the year (save $667). Course, community, personalization suite, tool stack, support.

Premium. $997 a year. Everything above plus 26 bi-weekly coaching calls with me and Sean. Direct access to us. Founders rate locked in for the first 100 members.

Either one is a September that looks different than August.

aigrowthcapitalists.com

https://www.skool.com/ailaunchpad

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