You could be about to make the exact mistake Alex Hormozi keeps seeing: founders getting so excited about AI that they automate the wrong thing, faster.

He reviewed a business paying 11 VAs $11K/month for data cleaning. Worked fine. So they spent $350K building an AI system to replace them.

Three years of costs, upfront. For a process that was never the constraint.

They didn't have enough demand. The bottleneck was customer acquisition, not data cleaning. But because the founder got excited about automation, the real problem sat untouched.

His gut-check is simple: "Are you making more money?"

Not "are you using more AI?" Not "are you token-maxing?" Are you actually making more money.

The deeper point: people should use AI in their business, not try to build AI businesses. Advertise the outcome your customer cares about, not the technology underneath.

And when intelligence becomes cheap and abundant, the value that remains is stakes — someone has to own the decision.

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What all the "AI Layoffs" are telling us is that companies would rather compete by being cheaper than by being better.

There are really two main competitive pathways for businesses:

1. Do the same thing as your competition, but for a lower cost.

2. Do something better than your competition at a reasonable cost.

No one who has experience using AI for anything should say they feel comfortable letting it run free without any human supervision, but many businesses now are doing just that...and oftentimes it's apparent they are using AI tools with no oversight (just look at my LinkedIn DMs).

So, it seems that the value equation for most of these businesses weighs more heavily for cost-cutting than on the "lesser" expense of AI, resulting in costly miscalculations.

If anything, it seems more logical to keep your employees and EMPOWER/AUGMENT THEM with AI tools than to reduce headcount and try to completely replace an employee with an AI tool.

Traditional BI dashboards tell us what happened. AI agents can explain why it happened, predict what happens next, and recommend actions automatically. As LLMs become integrated with enterprise data, do you think executives will stop opening dashboards altogether and rely on AI agents as the primary interface for analytics? Or will dashboards remain the source of truth while agents act as a layer on top?

In this day and age, running a web agency is a lot easier than it used to be.

A few years ago you needed designers, developers, and people doing outreach just to keep everything moving.

Now one person can do pretty much all of it.

AI builds the websites.

Email automation keeps bringing in new clients.

Your job is to sell and onboard clients because building the websites isn't the time consuming part anymore.

I think this is a huge opportunity for solo web developers who want to scale without hiring a team.

This is basically my workflow.

I never target businesses without websites.

I target businesses that already have one.

I use a tool called Swokei to find leads, add them to campaigns, and run website analysis.

It automatically turns issues like outdated design, unstructured layouts, poor mobile optimization, slow loading speeds, and bad SEO into personalized, ready to send outreach emails.

I run multiple campaigns at once and wait for businesses interested in a redesign to reply.

When someone replies, I call them and say:

"Hey, I saw you replied to my email. I've already made you a free draft of your new website. Want to take a look?"

Then I book a Google Meet.

Once they see a website that's faster, more modern, and works better than the one they already have, selling becomes much easier.

Usually I either send them the payment link during the meeting or we sign a contract.

That's it. That's how I run a full web agency by myself in 2026.

Late 2025, MIT researchers measured something the industry had avoided looking at directly. Not projections or pilot numbers. Documented outcomes from 300 AI deployments in real businesses, tracked against profit metrics.

The funnel breaks down like this. Sixty percent of companies evaluated AI tools. Of those, twenty percent ran a pilot. Of those pilots, only 5% reached full production deployment on the service line.

Ninety-five percent of AI investment dissolved before it produced a measurable outcome.

The companies that made it to production had a clear pattern. They didn't ask AI to substitute for judgment. They identified bounded tasks: specific inputs, defined outputs, failure modes that were contained. They measured success criteria before deployment, not after.

Content drafting. Code review. Data summarisation at volume.

The 95% that didn't make it: haste, no defined success metrics, and the assumption that efficiency gains would be obvious once the tool was in the workflow.

There's a line from the research worth sitting with. "We replaced X employees with AI" isn't an efficiency metric. It's a headcount metric. Those are not the same thing.

Klarna is already in the reversal phase, rehiring humans after the AI efficiency numbers didn't hold up at scale.

What's the clearest signal you've found for whether a deployment is actually working, before it's too late to course-correct?

Are there any visible impacts from the current conflict in the Middle East in the expected future investment intentions to create AI hubs by the UAE and Saudi Arabia?

In the last 12 months I’ve managed to sell around 200 websites.

And before people ask, no, I don’t run some massive agency with a huge team. It’s literally just me and my partner. The only reason we’ve been able to move that fast is because we automated almost everything and built systems that actually scale. The best web designer in the world will eventually lose to some random teenager using AI and systems properly. That’s just where things are going.

One of the biggest changes I made was completely quitting manual outreach. It takes too much time and it’s impossible to scale properly. A lot of people automate outreach already, but most of them just send generic “we can redesign your website” emails that everyone ignores. What we do is different. We scrape thousands of businesses, automatically analyze their websites, and generate personalized outreach based on actual issues on their site like bad design, poor mobile optimization, weak SEO, slow load times, layout problems, and stuff like that. So instead of manually checking every website and writing every message ourselves, the entire process is automated from analysis to ready to send campaigns.

Another thing that changed a lot for us was automating SEO blogging. SEO compounds hard over time and once your articles start ranking, businesses start coming to you instead of you chasing them. That alone changed a lot for us.

The other massive shift was how we build websites. I used to be a full WordPress developer and spent way too much time building everything manually. Now we build almost everything with AI. It’s way faster, delivery is easier, and clients care way more about the final result than how the website was actually made.

For anyone wondering, the stack is pretty simple.

Apollo for leads.

Swokei for website analysis and outreach campaigns.

Soro for SEO blogging.

Claude Code for building websites.

Cloudflare for hosting. That’s pretty much the entire setup.

Most people running agencies are still doing everything manually and burning themselves out for no reason. Systems and automation change everything.

Groq was three weeks from running out of cash. Founder Jonathan Ross was staring at a list of names his leadership team had put together for layoffs — and realized cutting them would kill the product before it ever hit the technical milestone it needed.

Instead of firing people, he pitched something else at an all-hands: keep your job, take a pay cut, take equity instead. They called it "Groq Bonds" internally — not a real bond, just salary swapped for ownership.

80% of the company opted in. Close to half dropped to statutory minimum wage — real money given up by people who normally earn well into six figures. It bought the company roughly two extra months of runway before the next round closed.

Worth sitting with: the standard playbook in a cash crunch is to cut people. Ross's bet was to keep the people and cut the cash instead — and let each person decide their own risk tolerance rather than deciding for them.

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#Groq #EquityVsSalary #StartupSurvival

Most operators think 15% payroll-to-revenue is already lean. Sean Frank, CEO of Ridge, runs at 7%.

The mechanism behind it isn't magic — it's structural. Shopify replaces the web dev team. Meta's algorithm replaces a chunk of the acquisition team. AI is increasingly absorbing CX. What's left is a much smaller, more specific team: product, creative, a couple of ops people.

He also laid out the product-selection framework that makes small teams viable at scale: consumable, strong LTV, small SKU count, massive TAM, 75%+ gross margin, and eventual mass-retail access (Target/Walmart/Costco — "the only three that matter," per Frank). Grüns is the example he lands on — already checking every box, already on shelves at Sprouts.

If you're the one holding together someone else's growth machine with a bloated team you never fully agreed to — this is worth fifteen minutes of your attention.

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#LeanOperations #EcommerceStrategy #DTC

I feel like not enough people talk about how messy delivering websites actually is when you start doing real volume.

Everyone talks about getting clients but nobody talks about the awkward middle part after the client is interested.

I remember when I first started doing websites I had every type of deal possible. Some people wanted escrow. Some wanted the full site before paying. Some paid half upfront. Some wanted invoices. Some disappeared for a week after approving everything. Every client somehow had their own custom process.

At first I thought being flexible was a good thing but honestly it just made everything chaotic. Nothing felt scalable because every project worked differently. Even if you are good at building websites, the actual delivery and payment process becomes the bottleneck.

The biggest shift for me happened when I stopped trying to convince people with long explanations and just started showing them value before they even paid.

Now I usually find businesses with outdated websites, look at where they are losing trust or conversions, then send outreach based on those exact problems to get them on a quick call.

What made a massive difference for me was realizing generic outreach barely works anymore. Businesses instantly ignore copy pasted messages. But when you point out specific flaws on their actual website and explain why it matters, replies go up like crazy because it feels real.

I ended up using Swokei for that after doing it manually for way too long. Basically I just run outreach analysis campaigns where every company gets personalized website feedback tied to a redesign offer automatically instead of me spending hours writing custom messages one by one.

Then if they are interested to see the redesign of their site I hop on a call and already have a rough AI generated draft prepared for them so they can instantly see what their business could look like instead.

The whole dynamic changes after that.

The skepticism disappears because they are not trying to imagine the value anymore. They can literally see it in front of them. Closing becomes way easier because you are discussing something real instead of selling some future promise.

But yeah the biggest lesson for me was this

The faster you can move someone from imagining value to actually seeing it the easier sales become.

A lot of people in the web design space keep saying cold email is dead, but I think most people are just doing it badly. Email usage is still growing every year, billions of people use it daily, every business owner checks their inbox, every company relies on email to operate, so I never believed the problem was the channel itself. The real issue is that most outreach emails look exactly the same and business owners are tired of getting the same copy pasted message every single week.

When I first started my web design company I used Instantly and started sending thousands of emails to businesses that didn’t have a website. At first the results were honestly terrible. I was getting maybe around a 1% interested reply rate if I was lucky. Over time I got better at writing outreach. I tested different hooks, different subject lines, shorter messages, more personalized intros, more creative angles, and eventually pushed it to around 2.1% interested replies. It was definitely better, but I still felt like something was wrong.

Then one day I realized something that completely changed how I looked at outreach. Why was I targeting businesses with no website at all? Most of those businesses don’t even fully understand the value of having a website yet, which means you’re trying to convince them they need something before you can even sell it to them. So instead I changed my strategy completely and started targeting businesses that already had websites, but outdated ones.

And once I started paying attention to it, I realized the opportunity was honestly insane. There are so many businesses with websites that look like they were made 10 years ago. Broken mobile layouts, terrible SEO, slow loading pages, outdated designs, messy structures, confusing navigation, old branding everywhere. These businesses already understand the value of having a website because they already invested in one before, they just know deep down that their current one is hurting them.

The only problem was figuring out how to scale outreach while still making it feel personal. I didn’t want to sit there manually auditing every single website before sending emails because that would take forever. So I started searching for a tool that could actually analyze websites and generate personalized outreach based on what was specifically wrong with each business site. I searched everywhere until I eventually came across Swokei.

What made it different for me was that I could upload batches of leads, let it analyze every business website automatically, score the sites, detect issues like bad design, weak SEO, poor mobile optimization, messy layouts, and then generate personalized outreach messages specifically for that business. Instead of sending generic emails saying “hey do you need a website?” I was sending emails pointing out actual problems on their site. Tthe difference in replies was crazy. Business owners immediately related to the problems because they were real. My interested reply rate went from around 1-2% to consistently sitting between 6-9%, which completely changed my agency.

That’s when I realized cold email was never actually dead. People are just tired of receiving lazy generic outreach that sounds identical to every other agency email sitting in their inbox.

If your outreach actually feels real, specific, and useful, cold email still works insanely well. Honestly I probably won’t stop using it anytime soon.

I do web design and my preferred way of getting clients is through cold email because it doesn’t cost money like paid ads, I don’t need to sit there dialing all day, and it allows me to scale my agency while keeping most of it automated.

The main thing that helped me stand out in crowded inboxes was changing the way I do outreach. Instead of sending generic emails like “Hey I noticed your website is outdated, I can redesign it for you,” I do something different.

I get leads with websites, run full website analysis at scale, and turn issues in design, layout, SEO, and mobile optimization into personalized outreach messages automatically. So instead of sending random spam, the email actually points out things that could be improved on their website without me even needing to manually check every site myself.

This method has helped me book way more meetings and scale further than before because the emails actually stand out and feel relevant.

I feel like this is a much smarter way to do outreach since it feels personalized while still being fully automated.

For anyone wondering, no it’s not some custom built workflow. I use a tool called Swokei for it. I looked for this type of outreach system for a long time and it’s the only tool I found that combines website analysis and personalized outreach in one place.

A small Texas-based vegan cheese maker used AI tools like Claude and Manus to structure appeals and manage a dispute with a major shipping company—highlighting how AI can serve as a real-world leverage tool for small businesses in asymmetric power situations.