シャドーイング練習: The Only SaaS Moats Left in 2026 - 動画で英語スピーキングを学ぶ

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How the f* do you survive, if you're a SaaS company, how do you survive in this age of AI?

AI is more of a problem probably for every SaaS founder in this room than you think.

You don't, I could start one today and probably have pretty close feature parity in a few months.

They don't need your 50 features, they only need the three that they use.

If you don't agentify your software, build some type of agent on top of it, I think you're going to zero in the next couple years.

Because someone's going to come along and they're going to, QuickBooks is terrible software, I hate using it.

but I don't care because my accountant uses it and he likes it.

You're probably lucky.

You're probably doing pretty well if you have one or two of these.

I am going to try to scare you a little bit with this talk.

This is the, I think I have 91 slides, 92 slides.

It is by far the densest talk I've ever given.

This one has a lot of gravity to it.

You'll notice it's also the, I think the only talk I've ever written, co-written with someone.

So it says by Rob Walling and Anner Volset,

because Anner Volset spent about a month wrestling with 89 different papers written by think tanks,

private equity groups, Gartner, mashing them with Claude, Chachypt, going back and forth, trying to figure out how the f* do you survive,

if you're a SaaS company, how do you survive in this age of AI?

Because what SaaSpocalypse tells us, tells us on social media, is all SaaS is going to zero.

So we can say, well, that's not true.

It's just not true.

It's objectively not true.

But is it going to go back to normal?

Are we okay?

Should we ignore it?

That's not true either.

So there's something in the middle, and that's what we're trying to find with this.

So where we're going today, normally I have three acts, but today I have four.

I want to try to get you a little scared.

AI is more of a problem probably for every SaaS founder in this room than you think.

I don't want to scare you too much, but just enough to pay attention.

I'm going to talk about classic SaaS motes, what I mentioned in SaaS playbook, if you've read that.

I have a few motes, and how some of those are dying or have died.

then talk about what we think are the modes that still work

and then I have like three or four slides

that is really could be a whole four-hour workshop on how

do you evaluate your SaaS company what questions do you ask I tack it on at the end

because it's important but can't possibly cover that in a 45-minute talk

so this is a sentiment that we're hearing on the internet microconf tiny I'm a founder, SaaS founder.

AI is amazing.

I'm shipping so much faster.

And obviously, my customers are hairstylists or lawn care specialists.

They're never going to vibe code my product.

Okay?

So that is an attack.

That's one attack that AI can make against you.

Your customer specifically vibe codes your product.

So I'm going to now show you 10 attacks, 9 additional ones, several of which you probably haven't thought of.

They're grouped into two buckets, the supply side and the demand side.

Okay, so basic economics, if we have a widget and suddenly the supply of widgets goes way up, the price of widgets go down,

commodity, they get commoditized, you lose as a company, you lose as a founder, right?

Well, SaaS can be the same thing.

Imagine you have a single SaaS application that does scheduling links, and suddenly there are 99 others.

There's a huge supply.

It becomes very messy.

So when the supply gets shocked, that's a problem.

On the other side, demand is, well, these are my customers, right?

People buying.

Well, what if I have a million potential customers in the U.S and their businesses, and let's say 90% of them go out of business tomorrow.

Suddenly, my demand plummets.

This is bad.

Both of these are bad.

So, I'm going to cover 10 across supply and demand.

I'm going to break them into those buckets.

The supply shock has six different vectors that AI can come after you with.

The thing to remember is everyone gets AI, not just you and not just your customers.

Everyone gets AI.

So, the first attack is the one we all think about.

Your customer builds it, right?

Some people say, my app's pretty complicated.

It has 50 different features.

You're going to get the slides at the end, by the way.

50 different features, they're never going to vibe code it.

One thing to think about is they don't need your 50 features.

They only need the three that they use.

All right.

Second attack is competitors reaching parity very quickly.

This slide shows eight of the 46 different AI note takers that I could find on the internet.

and it's, what is it, Otter, Fireflies, Crisp, Fathom, TLDV, Read AI, Circleback, Granola, and I wanted to show them in this order because,

you know, you think about your Otter in 2016, and you're like, oh, I got this all to myself.

This is amazing.

And now we have Granola, and everyone in between who almost, they almost all have feature parity.

They're kind of the same product, and I know that would piss off the founders if they were here,

but you don't, I could start one today and probably have pretty close feature parity in a few months.

That's great for an upstart and it's really bad for your supply.

It's a supply shock that everyone can get to feature parity with most apps these days.

It buys you, features used to buy you a lot of time, they buy you a lot less time.

So attack number one was customers, attack number two, competitors.

Attack number three is open source.

I have already seen this.

There are more open source projects, there are more open source projects working, moving faster than they used to because, if I'm coding, everybody gets AI.

They're moving faster and non-technical buyers who used to stay away from open source,

they can deploy it because they talk to cloud or cloud code and they can run open source.

None of these causes saspocalypse.

Ten of them together makes a difference.

My estimate, and this is just me doing this for 20 years and taking a guess, said this multiple times.

I think somewhere, SaaSpocalypse says everything is going to zero and everyone is plateauing.

That's not happening.

That's not true.

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I think somewhere between 10

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and 20% of all SaaS companies in the world are either going to decline or go to zero.

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That's a lot.

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It's a lot and it's not.

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Does that include little indie hacker projects?

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Probably.

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That's still a lot, right?

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10%, 20%.

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That gives you an idea.

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Fact number four is a platform, like a system of record that you're tied into,

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ships your feature for free because they can build it in a week, a month.

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They can build it a lot faster.

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They already have the customers.

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You've basically given them a spec through your UI.

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They could feasibly, if you're an add-on to something, they could go out.

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I'm imagining if you're, well, anything that ties into a CRM isn't Salesforce and HubSpot

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and Close and any other CRM is just going to start building all the ancillary things

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because they're just easier to build now.

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So your platform.

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This is like an integration partner that's going to come for you, I think.

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Track number five, we're seeing this.

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Custom software at SaaS prices, approximately.

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If you're an agency, you used to charge 30 grand, 50 grand for a build because it took three months.

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Now you can vibe code it.

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You can code it with AI assistance in a third, fourth, fifth of the time.

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And you always want it.

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Agencies want recurring revenue, so if I'm charging $99 a month for mine, my one size fits all,

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agency charges, whether it's $299, $499, $999, whatever it is, completely custom, made for you, supported for you.

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This model is becoming a thing.

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In fact, if I were in my early 20s, I would think about something like this.

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This is a really interesting business model.

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It's still an attack on SaaS.

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And the sixth supply side is if the model absorbs your product.

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This may or may not happen,

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but you remember when we used to pay apps to generate like ad copy and headlines and images and all that stuff?

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Those apps went away, and there's a bunch of examples of others that have as well.

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All right, so that's the supply.

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Demand shock, there are four of these.

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this demand shock I find and

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when Anders started bringing these to me I was like oh I hadn't thought of that

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and most SaaS founders

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that I've talked to as I've been writing this talk are like f* I didn't even think about that

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what if your customers just go out of business 50%,

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90% whatever the number is huge swaths that AI wipes them out so imagine that your SaaS serves translation agencies

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or transcription agencies that used to have a human sitting there listening to something.

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The number of words translated and transcribed since AI have gone through the roof, right?

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There's a lot more volume of this happening.

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The revenue of these agencies is effectively going to zero because we are basically using AI.

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Now, one can argue there's going to stay some boutique agencies if you're doing medical transcription, I'm sure if you're, or translation,

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you know, there's certain areas where this is critical.

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But this ecosystem is going to take a big hit.

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I mean, I say 10 to 20% of SaaS is going to experience a problem.

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80%, 90% of these agencies are going to zero.

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There's big disruptions in copywriting as well.

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There's a lot of things.

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So while the activity grows, your customers' ability to pay you plummets.

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If your customers start going out of business, there's no recovery from that, right?

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In terms of that's just involuntary churn.

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Act number eight, are your seats going away?

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This one we've heard, remember when Saspocalypse came up and they're like, seats are going away because agents are gonna do everything.

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Yes and no. In some businesses,

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seats are gonna have a problem because if you are Zendesk and you are customer service or customer support software,

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I think when Derek and I left

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Drip, we had six or eight customer support and we had six customer success.

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Now, so that was about 12 people.

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Customer success these days still can't, is not agentic yet.

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Customer support is 80, 90% automated in a lot of things.

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So suddenly you have go from eight agents to maybe one or two that is supervising a bunch of,

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yes, eight human agents down to one or two AI agents, and they're just supervising them, right?

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So you have massive contraction of seats.

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And you'll see, you see Zendesk and Help Scout and these folks moving towards outcome-based.

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There's a bunch of things they're doing with pricing to try to get around this, it's still a big shock.

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Attack number nine of ten, does the thing you manage still matter?

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Are people using it at all?

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Or does it just go away because of AI?

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Whether it's agents?

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Imagine that you were software to manage take-home coding tests.

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We don't do those anymore, right?

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The whole category of software, managing take-home code, because if you give someone a take-home coding test, what do they do?

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Well, they're going to use AI for it, but you want to use AI,

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but how much did they do versus how much did the AI do?

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So Derek and I were just talking, you mentioned like six times in my talk, I guess.

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You and I were just talking on the podcast a couple weeks ago, talking about hiring, and it's like, well, we do pair programming now.

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That's what I would do, right?

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You're not gonna, I'm not gonna do a take-home coding test.

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So some people in this room impacted by it, others not, it's still an attack.

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The tenth and final one is, it's related to seats, but it's different.

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Imagine if you were software for receptionists, okay, or like, almost like call centers,

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where they are going to be replaced by AI agents.

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So you have a bunch of seats, there's a bunch of humans, and now if you, and you have software you're selling for $50 a month.

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If you don't agentify your software, build some type of agent on top of it,

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I think you're going to zero in the next couple of years.

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Because someone's going to come along and they're going to say, yeah, you want that software plus like a fully autonomous,

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let's say 90% accurate agent for $300, $500 a month when you're paying $50 a month, but you can let the receptionist go,

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or the call center people, they're going to pay the $300 to $500 or whatever that is.

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So is the human even using your software anymore?

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Related to seats, but it's different.

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So that's the part that gets you scared, to make you think, you know, I need to pay attention.

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Because even if your business is doing okay today, and you're bootstrapping, and you just want to run it forever,

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some of this stuff's coming for you now, and some of it's coming for us over the next few years.

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All right, so we're going to talk about some, I'm going to zip through this part.

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This is like classic moats that I've thought about, that we've talked about in SaaS traditionally, why customers used to stick around.

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I came up with nine reasons.

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I saw this slide this morning, and I realized, yeah, there's probably eight, but whatever.

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It doesn't really matter.

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So, it used to be, I have unique features, they're not going to leave because they need these features.

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I have a real strong brand they're going to stick with me for or continue to buy for me for.

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I have these owned traffic channels, I have SEO that I've been doing for years, clever code, complex algorithms, five years of honing,

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refining, working around buggy APIs, whatever else.

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The team is familiar with my UX, they don't want to retrain people, so they're not going to switch.

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I have 30 integrations, man, those are complex to build, aren't they?

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High switching costs, it's hard to get my data out,

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I can't really export and then configuring in the new workflow thing on the other place is a pain in the butt.

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If multiple people are in my app coordinating, similar to retraining, it's like everyone has to move at once and we cut over on this day.

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And then I'm a system of record where all this data comes in and it's complicated to move, right?

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reasons I came up with, there are probably more.

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And we're just going to check a few of these off, shall we?

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So what does AI do?

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AI makes building features, doesn't bring it to zero.

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I don't want to act through this talk like suddenly I can build a year's worth of software in a week.

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That's not true.

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But it dramatically reduces the moat or the barrier to just rolling out new features that competitors have.

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Feature parity, I think products are going to all kind of converge because whoever's really good at product and UX,

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people are just gonna wind up copying them with AI.

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Own traffic channels.

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This one I'm 50-50 on.

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Yeah, if you have really good SEO, it's fine.

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Is AI making marketing and just like it's making kind of starting to trivialize code, is it starting to make marketing really muddy?

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It is.

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Clever code.

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I think we can just admit that someone can probably, now that AI is solving 100 math proofs.

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Anyone hear about this?

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There's like 100 math proofs that haven't been solved ever in human history, and they're saying inside it was Anthropic or Gemini or somebody.

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They just solved 100 of them.

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And Anar and I were talking, and I was like, well, glad I'm not getting my PhD in math.

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It's like, what do you do anymore, right?

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AI's doing it.

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UX familiarity, yes, if it's still humans.

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If things go agentic, your UX doesn't matter at all.

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Integrations, isn't the API really just the spec to hand to my bot now to f*ing code the thing.

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No, I'm getting depressed.

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All right, and high switching costs used to be a thing.

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They still are a little bit, but man, have you seen someone point an AI at an app and say,

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pull out all my data even when there's no export?

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Yeah, it really can and does happen.

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So of these nine, I think three are still, like system of record is a real thing.

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You're going to see it in this list here.

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Coordination between people is a thing and a brand plus some stuff is a thing.

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So we have these three, I'm gonna add five more and we're gonna dig into those now.

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This is the meaty, meaty part of the talk.

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So for each of these, hey, real quick, if you're getting value out of this talk, you should subscribe to the MicroConf YouTube channel.

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We're posting all the talks from MicroConf Europe.

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So even if you couldn't make it to Iceland, you can still get a lot of the learnings from the event.

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We also have a back catalog of some amazing talks from our previous events.

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All right, let's dive back in.

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I'm gonna talk about them.

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I'm going to say what the mode is.

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I'm going to give at least two examples for each one.

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And that's probably the important part of the talk.

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I tried to give a big name example we all know.

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And tried to do a smaller, like, microconf tiny seed company.

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Just because I don't want to just give, hey, you should be Slack, Facebook and Google.

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Like, this is not helpful, right?

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So I tried to do a big one, a small one.

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And then there's a question at the end to help you almost evaluate your own product in the context of this.

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Something I didn't say at the beginning is that the M&A market, one of the reasons Aynar,

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so Aynar came at this problem from private equity and the M&A market.

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Because a big part of what makes the whole SaaS ecosystem work and so valuable is that private equity,

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which does 70% of the acquisitions of our types of SaaS companies, they have been paying incredible multiples for the past six,

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eight years, maybe a little longer.

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and they follow public markets.

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So as HubSpot or Atlassian move, so does private equity and these multiples change.

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Even if you never plan to sell, this ecosystem works because a lot of money has been flowing into it.

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If you don't have any of these moats, what A&R has been seeing at Discretion Capital, right?

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He runs a sell-side M&A advisory for two to $20 million SaaS companies.

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What they've seen is that private equity and strategic buyers as well are really scared,

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not about the present, but they don't know if you're going to be around in a year, three, five years.

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So he came at it as what can you have in your business

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that gives them confidence that you're going to be around in three to five years such

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that they will pay our old multiples that we've talked about all this time.

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I come at it from more of the founder side.

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He comes at it from kind of the finance, private equity side.

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And that's why these modes are important.

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Even if you never plan to sell, even if you're bootstrapped, these are defenses against AI.

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And the other interesting thing, I had a couple slides I pulled out,

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and it's about Atlassian and HubSpot within a day of each other in August, it's about five weeks ago, they reported their earnings.

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And HubSpot beat earnings, beat almost every expectation, did a billion dollar stock buyback, and their stock dropped 21%.

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and Atlassian had similar results but their MCP server had like doubled in use, it had a bunch of like AI was making it better,

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they went up 35%.

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It was a huge swing, like imagine you know tens of billions of dollars moving around

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and when we look at it it's like well Atlassian

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and Jira specifically has several of these moats and HubSpot's inbound marketing engine is probably going to, I wouldn't say wiped out,

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is massively negatively impacted by AI.

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So we're already seeing it in public markets, we're seeing it in private equity and acquisition markets,

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and obviously we are seeing or going to see it in the bootstrapper markets as well.

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Let's dive into the moats.

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The first one is that buyers know and trust you.

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I've tried to summarize each of these with this phrasing, but then there's bullets.

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It's like, well, what does that mean, right?

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It's a strong brand.

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And also, you know your buyers and you know how they buy.

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You have partners, potentially, that have built their businesses around recommending you.

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And you have a champion inside a company that will fight for you.

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So the true strongest form of this moat is when a competitor who came in with better software, who can vibe code it,

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still has to build all of this.

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All right?

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A lot of these moats, actually all of them, they're not on or off, it's not a bit.

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Maybe it's a zero to 10, right?

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A zero to 100.

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And you could say, well, Salesforce or Shopify are at 90 out of this, you know?

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And you can say, well, maybe I'm at 10 now.

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How do I get to 20 or 30?

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Examples of this.

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Strong brand, you know the buyers, partners recommend you.

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QuickBooks is a perfect example of this huge ecosystem.

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We could replicate QuickBooks tomorrow and we would be fighting against the accountants.

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Like every accountant, QuickBooks is terrible software.

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I hate using it, but I don't care because my accountant uses it

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and he likes it and a better product doesn't get you in this conversation.

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I mean, zero is doing okay, but what is zero?

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10, 12 years into this?

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Shopify is another example.

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Their partner network is extensive.

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There's a bajillion agencies, I think literally thousands of agencies that implement Shopify stores.

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So yeah, hey, there it is on the slide.

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It must be true.

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So when a merchant, if you go to a merchant goes to hire an agency and says, what cart should I use?

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Well, they're like, well, obviously we're going to do Shopify, right?

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The platform's already decided.

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The moat, two questions, I'm sorry, the moat, two examples, and now we have the question,

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which is who's built their business or their career around recommending or defending you.

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That's one way to evaluate this.

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Vote number two.

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You are a system of record.

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What does that mean?

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It's a source of truth within a business for data.

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This is where daily operations are built around you.

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It means people are logging in every day to do stuff.

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You might be the operating system of that business.

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That if you go down, the business is like, shit, out of luck.

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They can barely do stuff.

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There are systems of record that aren't just the operating system.

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If they have a source of data that can't be easily exported and that everyone's working in all the time.

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But I think the biggest mode here is daily operations are built around you.

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You have balances, you have approvals, you have statuses, you have all types of stuff, workflows, living.

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Roles and rules are configured

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and a lot of other systems are wired in either reading from it to act or pumping data in to you,

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and that data doesn't come out.

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JIRA is a good example of this, right?

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We think of it as just an issue tracker, but there is so much.

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I mean, devs and managers and product people, you have multiple teams in JIRA, and you could export your tickets in an afternoon,

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but migrating all the history, the audit trail, the integrations, and getting all those teams to move to a different system would be very, very painful.

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So there is, the fact that it is a system of record just has gravity, it has weight, and it pulls, keeps you there.

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Gymdesk is a tiny seed company.

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He had an amazing, amazing life-changing exit.

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And it's basically, imagine your gym, martial arts dojo, yoga studio, your entire business runs on him.

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And it started as, I don't even remember, it was like a part of the gym.

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And then suddenly he's like integrating with hardware so people can use like a fob to get in the door, and every aspect of the gym,

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it just, boop, boop, boop, invoicing and billing and just kept spreading.

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And so now if you're a gym, you get gym desk, done.

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No one, very few are going to switch off this for any type of AI.

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So the question is, if your customer wants to leave, what can't they export?

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What breaks downstream and what would they have to rebuild?

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Moat number three, this is where it starts to get esoteric,

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where Anar showed me these and I was like, what do these mean? and I had to spend hours like thinking through.

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You're allowed to act.

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What does that mean?

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So if you're a tool that recommends that a clerk makes a payment,

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you're one type of tool versus a tool that can make the payment, that can actually move money.

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So do you give them a spreadsheet with a list of PayPal emails and dollars?

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Okay.

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So you're like a report, you're an analysis, you're reporting to, or do you actually move the money?

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If you can move the money, then you act.

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Examples of this, Stripe Connect.

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No one's switching off

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Stripe Connect, doesn't just recommend a payment, it actually moves money.

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Tiny C Company, Reambi, it reimburses, if I wanted to pull a job candidate in, fly them out, and they have expenses,

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meals, hotel, other stuff, I don't want to set them up as a vendor in my system,

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I want to pay them via Venmo, PayPal, Cash App.

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Reamby does the whole thing soup to nuts.

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The fact that Reamby can act means that it has a pretty nice moat here.

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You don't have to be Stripe to have the authority to pay.

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And I threw a third one in here, churn key, which is if you're a SaaS company you can put churn key in

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and they have offers when people go to churn

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and they they help they offer discounts

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and they offer all kinds of different variations to try to reduce your churn

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and there's a lot of tools that will tell you who's about to churn

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but churn key is literally allowed to get in the cancellation flow

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and make an offer they're allowed to act they're allowed to step in front of your customers

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and you don't you don't even check on them

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so question here is can you act can your your software actor can only advise.

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Are you a reporting tool or something that actually does something?

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Mode number four is that, this is another one, when he said it, I was like, what are you talking about?

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They don't check your work.

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The best example of this is Gusto.

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I've used Gusto for 10 years at least.

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No, no, since 2013 probably.

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13 years.

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And I've never once checked their work.

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I could go to jail for IRS something or other

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if Gusto decided to f* me because I have never once looked at anything but the W-2 they issued to me.

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You just don't.

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And we can say, well, it's complicated.

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Why don't I?

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Well, I don't know.

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I don't understand it.

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Great.

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So am I going to switch when someone AI vibe codes a Gusto competitor?

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I'm not because these guys got it dialed.

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Another example, this is Avalara, also a tax.

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This is sales tax, though.

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Once again, we don't check the number.

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This was when I had, I struggled to find like a small, like a tiny seed microconf example of this.

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So I have two big ones.

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And it's not just, hey, we're trustworthy.

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They've earned this permission, right?

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They've been right for years and years and years.

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So if you were to, like I said, Vibecode, Gusto or Avalara, switching is not likely.

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All right.

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We're in the home stretch here.

420

The fifth one, oh yeah, this is the one we added the other day because it had gotten lumped in.

421

Man, you do this long enough and they start lumping in.

422

At one point we had 10 and then realized, yeah, you can imagine this, how this goes trying to build something like this from nothing.

423

So this one is that someone official already said yes.

424

And what I mean by that is this is where there are regulations, licenses, accreditation, certifications, right?

425

Anything where there's a third party

426

board or body that is monitoring these things and that you as the vendor have to qualify,

427

get certified, etc. Just because your customers do it, yeah, yeah.

428

Serving regulated customers isn't the same as holding an approval yourself and because the competitor can clone your code, again, every one of these is like,

429

alright, if cloning the code, the code let's just assume it gets faster and faster easier

430

and easier and it goes to zero much like hard drive space did internet speeds bandwidth all

431

that right it just approached zero didn't get to zero

432

but it approached zero let's assume for the sake of argument

433

code approaches zero what else are these modes doing for us

434

and um this is where you have to get this is this can be the iso 27001

435

It can be, I want to say GDPR, that's not what I mean.

436

What is, SOC 2 is what I'm thinking of.

437

But it can all, and these are just little speed bumps in the road.

438

But it can also be things like, well, I'll get to it in a second, I guess.

439

HIPAA is another one.

440

So compliance is so brutal that Vant has literally a billion dollar company and they just spring up over the past.

441

I mean, they haven't been around for more than five or six years.

442

Because these things are tough, and they take a while, they're expensive.

443

An example of a tiny seed company that works with this, and if you were to try to vibe code this exact same thing,

444

it would be very hard.

445

Because no one in here knows what ABA is, except for the founder.

446

I forget what it is.

447

But it's like an element of psychology, and it's related to that.

448

But they have courses that count towards credentials.

449

And if you try to vibe code this, you have to get board approval.

450

And are any of us going to go through that?

451

No. So she has a moat around her business.

452

Another example of this is one that I just thought of in the last couple days.

453

Sending text in the U.S is shockingly difficult.

454

And the laws are way worse than email.

455

We thought we had it bad with Drip.

456

When I deal with the text, the SMS companies, in TinySeed, I'm like, good Lord.

457

I would never start a business in that.

458

Well, that's a moat right there, right?

459

So, you have to, there's carrier registration, there's consent laws, there's all types of ways.

460

It is very cumbersome.

461

The software for this is not that hard to code, but dealing with texting is not fun.

462

So, that is a bit, you know, is it 100% no one's ever going to do it?

463

No, but it is going to be a barrier.

464

So, the question here is what approval, complexity, what legal stuff do you know, have you navigated that a competitor would have to earn?

465

Number six is that everyone's already in the software.

466

This is the idea of network effect.

467

Who has to move if they leave your software?

468

Is it one person?

469

Well, they can switch in an afternoon, right?

470

You have a whole team?

471

All right, everyone agrees, we move next week.

472

It's a whole community or a whole company all at once.

473

It's painful.

474

So the more folks that are in there coordinating, the bigger the moat.

475

Obviously prototypical example of this is Slack.

476

Some of us love it, some of us hate it.

477

We all try to move off of it.

478

No one does.

479

There's competitors to Slack.

480

We can't name them because Slack is the king.

481

But you don't have to be Slack.

482

Commit Swimming is a tiny seed company and swim team management built for coaches.

483

What they do is, and a lot of the swim,

484

there's adult swim teams, but imagine there's a bunch of kids swim teams and they get all the parents in,

485

signed up for it and it's notifications, right?

486

Here's the meet, here's the location, we're all doing this pizza party, blah, blah, blah.

487

Every family's all signed up.

488

These are all non-technical folks generally.

489

So switching doesn't just mean to move the software.

490

It's like everybody has to move all at once and the whole league has to agree.

491

Like it's a pain in the ass, right?

492

So the question here, this is a pretty, This one's very interesting and obviously hard to achieve.

493

Would a competitor have to move everyone at once is the question.

494

Number seven of eight.

495

Every customer that you have makes your software smarter.

496

You're going to hear me talk and use the phrase learning loop.

497

Anar is going to be talking about learning loops in a couple hours.

498

Example of this is Stripe Radar, which identifies fraud.

499

and every merchant that

500

Stripe has sees fraud patterns and that feeds up into a Borg-like mind that protects all the other merchants.

501

So if you were to try to go start your own

502

Stripe Radar with just your data, it's worth way, way, way, way, way less than Stripe Radar and their system gets smarter.

503

No single merchant could ever build it, right?

504

And if you leave it, you lose it.

505

The diagram here is a situation comes up, human or software takes an action,

506

you see what the result is and then you correct and make it better.

507

If you have a lot of data, it doesn't matter.

508

You have to be able to use that data to predict across all your customers

509

because that then becomes the moat because switching means you lose it.

510

Another example of this is Ramp,

511

which is bookkeeping, and every correction that one of their customers makes to a Verizon line item,

512

oh, I'm going to do that as a cell phone, whatever.

513

Well, everybody else gets that too, right?

514

That's a trivial example, but you get the idea.

515

And then churn key again, every cancellation in theory should make their engine better.

516

I don't actually, I didn't have a chance to contact the churn key guys.

517

I don't know if they're actually doing that, if they're doing a feedback loop,

518

but you can bet that I'll be contacting them after this talk and say, build that in because you should have this mode.

519

So this one only counts if you have clear three gates.

520

Number one, every customer makes it better for every other just be siloed

521

that this customer makes it better for themselves because then they can go build it or a competitor can build it.

522

Number two, customers can take their data but not what you learn from it.

523

Yeah, they can export it but they don't know what you learn.

524

And the last one is you have to keep learning, right?

525

Because if it's stagnant and you don't get better over time, then it doesn't matter, they can just leave.

526

Another Another example I thought about this is MailChimp.

527

MailChimp is the only ESP that ever made freemium work

528

because the biggest thing in email is spam

529

and they built an engine called Omnivore that figured out how to detect spam at a level, at a machine learning level,

530

this was in 09, like way before any of this AI came out.

531

They're another good example.

532

So your question is, does what happens to one customer make your product smarter for the rest?

533

And the last one that I added just a couple days ago based on this

534

Peter Lovell's tweet, it's hard to keep running.

535

So Peter Lovell's tweets, I've tried for weeks now, he's Peter Lovell's indie hacker, half a million followers on Twitter, he's just vibe coding everything.

536

I mean even like 20, 30 dollar stuff he wants to like vibe code and host it himself because that's what Peter does.

537

So he's at the extreme end of that.

538

He's trying to vibe code everything.

539

So he tried to do Scrapingbee, which is a proxy service that helps you not get blocked as you try to scrape things, right?

540

Because everybody blocks your IPs.

541

Tried to code it, tried to code it, finally he's like, it, I'm just going to pay him 99 bucks a month.

542

So if you look at his list, he said, these are the only things I'm paying for now.

543

It's Cloudflare, like raw server, bare metal server boxes and VPS and blah, blah, blah, and Scrapingbee.

544

And it's like, what a trip, these massive companies are scraping people, why is that?

545

It's because web scraping isn't that hard to build

546

but to keep it working and not get blocked is a pain in the ass.

547

It's a bunch of DevOps, it's servers, it's cycling IPs, it's a huge headache to run, it's a burden.

548

Scraping big guys sold, they had a great exit, eight figure cash exit, they've been public about.

549

But they didn't want to run it anymore.

550

It was such a pain in the ass, but that was their moat.

551

Cloudflare, same exact thing, right?

552

Are you going to vibe code to Cloudflare?

553

If someone else vibe codes Cloudflare, am I going to switch?

554

No. It's a crazy moat.

555

It's just hard to run.

556

Drip.

557

God rest our souls, Derek Reimer, that we survived this.

558

Drip was, anyone can send an email.

559

And this is why when I see people, I've seen someone like vibe code kind of an ESP, right?

560

And say, just plug in your Amazon SES and you can send your own email.

561

And yep, Benedict, you as well.

562

We just kind of chortle because it's like, no, no, no, you don't understand.

563

We had multiple full-time people.

564

All they did was try to fight spam.

565

You hook it into your SES account, like, it's a problem, right?

566

So, these are moats.

567

The question here is, is it hard to build or is it hard to keep running?

568

Because that thing that you hate and resent can actually be a moat.

569

These are the eight.

570

And now I'm going to wrap up with just a couple slides.

571

These are more of a thought experiment that we're, I mean, we're going to be fleshing this next part out into hours and hours of stuff.

572

So, it's going to be quick.

573

But I want to answer the question quickly like

574

which of these are possible for you

575

and there's eight questions each one corresponds to a moat

576

there's probably two three four questions we could ask for each of these right

577

so it's like who has built you've heard some of these who's built their career

578

or business around recommending

579

you do you hold the definitive view of the work right

580

are you a record of the work are you a system

581

of record are you just a view of it do you take action

582

or do you just recommend it do customers trust your output enough that they don't check you, what approval, this is the regulation one, right?

583

What approvals, regulations do you hold that a newcomer has to wait for?

584

Who has to agree to replace you?

585

Does one customer's experience make it better for everyone?

586

And what do you maintain that you resent maintaining?

587

That's my favorite.

588

And I think this is the last slide.

589

It is, these are just examples that I was like, for each of the moats,

590

how would I go from where I am today to try to have that moat?

591

So if I was, and these are in the same order as well.

592

So it's like, if I had a vertical tool, I wanna build an ecosystem,

593

I want the vendor, I wanna become the one that the industry recommends, right?

594

If I'm a point solution, can I become a system of record?

595

If I'm a reporting tool that gives reports, can I figure out how to act and actually move the money or actually put the churn thing,

596

not just recommend it.

597

If I have something that calculates something, how do I get to be the output that nobody double checks?

598

If I'm in a regulated industry, how do I become an approved or the approved provider?

599

We see, don't we see Anthropic

600

and all the AI providers trying to basically regulate their industry so that they pull the ladder up behind them?

601

If I'm a single seat tool, can I build that network effect such that everyone's coordinating?

602

If I collect data, can I build a learning loop?

603

And if I have infrastructure that I babysit and I despise and hate, will that be a burden that no one else will carry?

604

So in conclusion, try to figure out which ones are yours or which ones you can move into.

605

Maybe you have one of these today.

606

You're probably lucky, probably doing pretty well if you have one or two of these, I think.

607

So if you figure out which ones are yours or you move towards them, you're worth more.

608

Business is more defensible.

609

And as I said, this talk was about moats, about defense.

610

And we're going to hear from Anar in a couple hours about how to go on offense.

611

So that's it for me for today.

612

We have time for questions.

613

of the Q&A from after the talk.

614

We're not posting that one on YouTube, so this is the only place to get it.

615

And if you wanna be in the room next time in 2027, MicroConf is headed to Austin, Texas in April and Dubrovnik, Croatia in October.

616

Watching these talks on YouTube is great, but the real magic happens in person.

617

You're in a room with about 250 founders who get exactly what you're building.

618

And some of the best conversations happen in the hallway between the talks.

619

The last seven, maybe eight MicroConf's has sold out.

620

So grab your tickets now at microconf.com slash events if you wanna go.

621

These events will sell out and I hope to see you there.

622

And if you already have your ticket or you're just ready for another great talk, check out this one right here.

623

I'll see you over there.

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The ‘Old Rules’ of SaaS Still Win

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このレッスンの語彙とスピーキングのポイント

このスピーキングレッスンは、動画「The Only SaaS Moats Left in 2026」を教材にしています。この動画には、シャドーイング用の文が622文、単語が7311語あります。音声の長さは39:50です。話す速さは速く、1分あたり約184語です。音のつながりや弱く発音される音が多くなります。単語の84%は英語の頻出3,000語に含まれます。残りは練習の前に確認しておきましょう。全622文のうち94文が疑問文なので、疑問文のイントネーションや短い受け答えの練習に向いています。

この動画の重要語彙

動画に出てくる覚えておきたい単語15語を、発音と意味つきで紹介します。

単語	発音	意味
vibe 名詞	/vaɪb/	氛囲気
founder 名詞	/ˈfaʊ̯n.dəː/	創設者, 創立者
slide 名詞	/ˈslaɪ̯d/	滑り台
competitor 名詞	/kəmˈpɛt.ɪ.tɚ/	競争者
equity 名詞	/ˈɛk.wɪ.ti/	衡平法
shock 名詞	/ʃɔk/	衝撃, ショック
export 名詞	/ˈɛks.pɔɹt/	輸出品
buyer 名詞	/ˈbaɪ.əɹ/	買い手, 購買者
ecosystem 名詞	/ˈikoʊˌsɪstəm/	生態系
server 名詞	/ˈsɝvɚ/	サーバー
integration 名詞	/ˌɪn.tɪˈɡɹeɪ.ʃən/	統合, 融合
swim 動詞	/swɪm/	泳ぐ
merchant 名詞	/ˈmɝt͡ʃənt/	商人
complicated 形容詞	/ˈkɑm.plɪˌkeɪ.tɪd/	複雑な
exit 名詞	/ˈɛɡzət/	出口

動画に出てくる句動詞

単語	発音	意味
go away 動詞		去る, 出る
come out 動詞	/ˌkʌm ˈaʊt/	出る
come up 動詞		上がる, 登る
go down 動詞		降りる, 降下する
switch off 動詞		消す, 切る
check out 動詞		試験する, 検査する
go back 動詞		戻る, 帰る
go out 動詞		出る

繰り返し練習したい文

動画に出てくる短く完結した文です。日常会話でそのまま使えます。

Act number eight, are your seats going away?
Who has to move if they leave your software?
You have a whole team?
Who has to agree to replace you?
If I'm a point solution, can I become a system of record?

この動画の文法

話し手がよく使っている文型を、動画の実際の表現とともに紹介します。

文型	動画での表現
「used to」 used to + 動詞 — 今はもう違う過去の習慣や状態	used to buy · used to because · used to stay
現在完了進行形 have/has been + -ing — 以前に始まり今も続いている動作	I've been writing · I've been doing · have been paying
現在完了形 have/has + 過去分詞 — 過去の出来事が今も関係している	I've ever given · I've ever written · you've read
受動態 be + 過去分詞 — 誰がするかより、何が起きるかに焦点を当てる	be replaced · been solved · are built

注意したい発音

話し手はyou're, don't, I'mなど、短縮形や弱形を217回使っています。聞こえたとおりの短い形で発音しましょう。

「th」の音: mathematics /mæθ(.ə)ˈmæt.ɪks/, sixth /sɪksθ/
「sh」と「zh」の音: shock /ʃɔk/, integration /ˌɪn.tɪˈɡɹeɪ.ʃən/, translation /tɹænzˈleɪʃən/, speculation /ˌspɛk.jəˈleɪ.ʃən/, cancellation /kænsəˈleɪʃən/
長い単語（アクセントの位置に注意）: competitor /kəmˈpɛt.ɪ.tɚ/, ecosystem /ˈikoʊˌsɪstəm/, integration /ˌɪn.tɪˈɡɹeɪ.ʃən/, complicated /ˈkɑm.plɪˌkeɪ.tɪd/, mathematics /mæθ(.ə)ˈmæt.ɪks/

日本語話者が苦手な音：

/r/ と /l/ の区別 — /l/ は舌先を歯茎につけ、/r/ はどこにもつけない: translation /tɹænzˈleɪʃən/, regulate /ˈɹɛɡ.jə.leɪt/, trail /tɹeɪl/, regulation /ˌɹɛɡjʊˈleɪʃən/, brutal /ˈbɹuːtəl/
/v/ — /b/ にならないように、上の歯を下唇に当てる: vibe /vaɪb/, server /ˈsɝvɚ/, evaluate /ɪˈvaljʊeɪt/, vendor /ˈvɛn.dɚ/, solve /sɒlv/
/f/ — 「フ」ではなく、上の歯と下唇で出す: founder /ˈfaʊ̯n.dəː/, fraud /ˈfɹɔːd/, painful /ˈpeɪn.fl̩/, defend /dɪˈfɪnd/, infrastructure /ˈɪnfɹəˌstɹʌkt͡ʃə/

この動画での練習方法

まず声を出さずに動画を最後まで聞き、知らない単語をメモします。
まず0.75倍速で一文ずつシャドーイングし、慣れてきたら通常の速度に戻します。
自分の声を録音して元の音声と比べます。vibe, founder, slideなどの単語に特に注意しましょう。

シャドーイングとは？英語上達に効果的な理由

シャドーイング（Shadowing）は、もともとプロの通訳者養成プログラムで開発された言語学習法で、多言語習得者として知られるDr. Alexander Arguelles によって広く普及されました。方法はシンプルですが非常に効果的：ネイティブスピーカーの英語を聞きながら、1〜2秒の遅延で声に出してすぐに繰り返す——まるで「影（shadow）」のように話者を追いかけます。文法ドリルや受動的なリスニングと異なり、シャドーイングは脳と口の筋肉が同時にリアルタイムで英語を処理・再現することを強制します。研究により、発音精度、抑揚、リズム、連音、リスニング力、そして会話の流暢さが大幅に向上することが確認されています。IELTSスピーキング対策や自然な英語コミュニケーションを目指す方に特におすすめです。

シャドーイングのやり方: ステップ別の完全ガイドを読む →

シャドーイング練習: The Only SaaS Moats Left in 2026 - 動画で英語スピーキングを学ぶ

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