AI Consultant | AI Integration & Agentic Automation Engineer. Software, Apple Apps, AI search visibility & content systems. [email protected]

earth
Joined June 2017
I think the moat now is distribution. AI is making software faster and cheaper to build. More products are competing for the same customer. Railway caught my attention because its guides, deployment templates, and agent tools give people useful paths into the product. That takes time to build: an audience that trusts you, content that solves problems, and a place inside the tools customers already use. The product still has to deliver. But getting discovered, trusted, and chosen is becoming the advantage that compounds. How much effort are you putting into distribution compared with product development?
Moats! Does anyone have one anymore? Yes. Yes, they do. But only a small subset of what people call moats create real long-term value and defensibility. Not actually a moat: 1. Distribution: This does matter more than ever. Building products has gotten easier, but getting them to customers has not. Distribution, however, does not create durable defensibility. It helps create the raw ingredients for one, but it is not itself a moat. 2. Execution: Yes, speed is critical for startups. But a company that has to sprint forever is not a good business. Ultimately, it will misstep, slow down, and competition will catch up. Speed gives a company more shots on goal as it tries to build a great product and a great business, but it must eventually find something more durable. 3. Brand: The idea is that when everyone is building the same thing, the most resonant brand will win. But for startups, brand works more like customer acquisition spend: Put money in, get growth out. It’s not something that will effectively keep others from competing long-term. Brand can become a true moat over time (as with Coke or Nike or Apple), but it just takes too long to really matter for most startups. What you're looking for is compounding advantages: a self-reinforcing flywheel that gets stronger and stronger over time, ultimately making a company very hard to compete with long-term. There are only four compounding advantages that really matter. Every major tech company has at least one: 1. Switching costs: The more deeply embedded a product is in the way a customer works, the harder it is for that customer to switch. This increases retention and revenue per customer, which can be reinvested into the product. 2. Network effects: The more users a product has, the better it gets for everyone. This increases engagement and attracts more users. 3. Scale economies: The more volume a company has, the larger and more efficient its operations can be. This lowers unit costs, funding lower prices or a better product at the same price, further driving up volume. 4. Data effects: The more usage a product has, the more data it generates. This data can be used to improve the product and increase usage. If you can’t see the potential for any in the startup you’re considering joining, that’s a red flag. In today’s incredible post, @danhockenmaier shares a simple framework you can run in about an hour after getting an offer: 1. Identify a startup’s compounding advantage 2. Gauge how strong it could get 3. Measure whether it’s working Inside: dozens of real company examples, the specific metrics to track, and benchmarks for what good and great look like. Read it here: lennysnewsletter.com/p/how-t…
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Young men, avoid low-budget Nigerian women. If you don't have S.OT, discipline yourself instead.
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The difference in the quality of conversations between Nigeria and other countries. The Giveaway Economy.
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I handed a live Google Ads account to an AI agent. Here's what it found in a year of data. Google was counting every page view as a sale, so it spent the budget buying page views. Two of the three ads were still selling a discount that had expired. The account was paying for searches the business can't serve. And auto-apply was quietly changing the account, with nobody checking. The agent was Claude Code, powered by Opus 5.5. It read about 8,000 rows and showed me evidence for every problem. Then it fixed them through the Google Ads API. Google checked every change first, and nothing went live until I said yes. Before, the average click cost $1.51. In the first full week, it cost ninety-eight cents. So the account got 30% more clicks a day and still spent less. Claude Code with Opus 5.5 is the best setup I've found for running Google Ads. I wrote down the whole method. Comment ADs, and I'll send it.
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My boy while trying to help me do some work, a feature idea came to mind for our iOS app and I added it immediately.
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A page of MacBooks and Mac Studios, don't forget that. An ordinary X hustler is talking to me. Focus on selling your cheap courses bro, it takes more than that to build an Empire. We don't share all we do online as we ain't seeking online validation like you.
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Before you take your Google Ads Campaigns Live, the first thing you must do is visit your Auto-apply settings, uncheck every auto-apply setting, and you will save a lot of money when your Ads go live.
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When running Google Ads, avoid chasing Google's Optimization Score and Recommendations. If you do, you'll spend more than your budget with little to show for it.
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Would you spend the redesign budget on the wrong page?
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Replying to @SamuelOmogor
Here is the opening, all he needed to do was put on sit belt, force his way through that opening, that's how it works. Survival skills should be taught to people, everything must not be done by the book, or else you die before your time.
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When you can't even get a passport in 5 months, how can you then see what I'm seeing?
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Keep building, never sleep nor slumber.
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