WEBVTT
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Hey Rob.
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It's good to see you, man.
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You are you're you're back from not just vacation.
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You flew out to work with uh uh one of the early startups uh that you helped get past a million now they're they're growing past that.
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Um it's it's good to see it to be back in the saddle.
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Yeah, well, one thing I was thinking about, which is like, you know, I have an 18-month-old daughter now, and one of the things that I have become quite aware of is like as being a dad, one of the one of the kind of like rites of passage is uh now when I travel for this trip, I arrived at the airport an average of four hours before my flight.
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Just you know, sitting, feeling good.
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I like I also have this kind of like a desire to start learning more about the World War II battles, uh, certain World War II battles.
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And so it's like, I don't know, there's there's just something about being a dad that that forces you down this path.
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I have been hoping it was a generational thing, but uh it's it's probably like an individual evolution thing.
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No, I'll just start tucking in polos into my jeans.
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Like that's that's where we're going.
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Uh well, hey Rob, we've got uh a really you know, you know, you gave us you gave us a gift and you're taking the gift away from us.
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Uh this week's post is called No More Pull Hypotheses.
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We're gonna we're gonna talk about what was happening, what you were observing with pull hypotheses, uh how founder like the limitation basically that it that was causing founders to or the problem that they were stumbling over.
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Uh and then we're gonna get into uh the pull anecdote.
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Real fast before we jump into that, uh, we're gonna publish this one, I think, September 5th.
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We've got a PMF camp that's coming up.
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It starts September 14th.
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Um, just a few quick sentences like that.
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The goal of this um uh is to get you know, startups that are a good fit are looking to get Rob's direct engagement on their pool, on their go-to-market, on their outbound, um, and to see an you know another group of startup founders like develop their intuition by watching Rob uh and and the whole group really interact around how other founders are approaching outbound, how they're how they're thinking about the case study factory, um, doing teardowns of live calls.
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It's gonna be uh it's a two-week, uh, two-week PMF camp, starts on a Monday, ends on a Friday, includes uh four working sessions, a couple AMAs with Rob, and uh two teardowns of full sales calls from other founders in the community.
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Rob, um, anything that you would add on on that before we jump in?
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Uh I I just I just say like the the thing that has been consistent.
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We've now done, I have no idea how many times we've done this now.
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We've probably done it like 10 times.
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And so it always kind of evolves each each time.
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Um this time the flavor we're doing is just like way, way, way more feedback per startup.
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So basically, all of the sessions, say for say for one are like, you're gonna bring something and get it roasted or torn down or or uh you'll get helpful feedback on it.
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And then one of the things that so everyone everyone who comes into it is like, yeah, I want feedback on my thing.
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And so that's that's awesome.
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Whether it's your outbound message, whether it's your um you know sales deck, whether it's you know, whatever, whatever that thing is.
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Um one of the things people do not expect to get a ton of value out of, but do find they get a ton of value out of, is like watching other founders' sales calls and watching me tear down other founders' sales calls because it's actually often um you you'll have a lot more epiphanies when you see somebody else.
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And like you see something really clearly on somebody else's call or in somebody else's thing, and then you're like, wait a second, I need to apply that to myself.
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So um that that's been that's just been a fun, fun thing.
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Yeah, I I totally agree with that.
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Um the the the public teardowns that you do and uh are some of my favorite things, the most impactful things that have led to changes in my business.
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Um you mentioned this there's a lot of one-on-one or like a lot of direct feedback.
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We're capping the uh PMF camp at 15 startups.
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Um and so if you're interested, reach out, ASAP, um, and we'll just go from there.
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Well, Rob, if there's if there's no uh oh, we'll put the I'll put the link in the in the show notes for anybody that's interested.
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It's just like a short application.
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Um nothing else.
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If there's nothing else on that, why don't we jump into no more poll hypotheses?
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Um all right, Rob.
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You've we got everybody running on poll hypotheses, and now you're saying like, all right, total like orthogonal.
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We're going in the other direction on this one.
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Um why is this one on your mind?
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Uh, maybe like who's it, who's it for?
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Let's just start there.
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Yeah, so this is this is um especially relevant if you're going zero to one.
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And and you could be going zero to one on a new product, you could be going zero to one on uh like your second product on your first starter.
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Like it could it could be kind of anybody who is trying to go zero to one on anything or in the kind of like zero to one stage.
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Um uh this is gonna be relevant for you.
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And it's going to be relevant specifically because I'm taking a concept away.
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And I'm taking a concept away that sounds right, but there's a one word that seems to cause us to occasionally, not always, but steer straight into the iceberg.
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And that word is hypothesis.
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Now, like zooming out if you're new here, uh, the pull hypothesis was a is was a thing that is it's basically just a statement of I believe this person has pull or this kind of person has pull.
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Um, and pull, if you're also new here, the pull framework is a way to state uh somebody who's weird not to buy your product, who would be weird not to buy your product, where they're trying to do something, but they can't do that thing.
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They need to do that thing right now, can't do that thing.
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They're grinding against their existing tools, methods, and options, and you show up and unblock them.
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So they have like a blocked product on their to-do list, you unblock them.
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That is what the pull framework is.
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A pull hypothesis is a um, I believe this specific person has pull, and it's um, and what we're killing today is the word hypothesis.
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Yeah, and here's what you write uh about that.
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Um hypothesis comes with baggage.
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It feels like the kind of thing that originates in your brain, which leads a lot of founders to sit around and guess as a way to create their pool hypothesis, this despite the real person rule in my book, which states that a pool hypothesis must be based on a real person with pool.
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So, Rob, what were you?
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And and honestly, I'm pretty sure I was guilty to a certain extent of of uh abusing the word hypothesis or uh in the pool hypothesis here over uh on a couple occasions.
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But Rob, why don't you give some color?
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Like, what did it look like?
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Um, you know, for a founder that's using a pool hypothesis, yeah, um, just so that they can self-reflect on it, uh, what is what is going wrong?
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What does it look like when it's being used wrong?
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So the word hypothesis just makes you think of uh I need to think um first.
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Like I need I need to come up with a hypothesis.
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And so the method that most people do, and and this is I think due to the word hypothesis, is you'll open a dock or you'll go walk to a whiteboard and you'll just start brainstorming plausible hypotheses.
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And these plausible hypotheses, like you know, I I was doing a workshop uh this week with a with a another company, and and they basically showed up to the workshop with a huge dock of possible poll hypotheses.
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And that's that's the normal thing.
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It's like, okay, cool, who do we think might have pull?
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Um but which which like this totally sounds like a reasonable thing to do, but the challenge is that something that originates from your brain, it's usually based on like some abstract market logic or something of like, well, agents are taking over the world, so therefore, or this startup just took off, so therefore, right, like it's it's kind of abstract, and you take that and you turn it into a belief about a specific person or like a hypothesis about a specific person, that hypothesis is basically guaranteed to be wrong.
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Which again, like okay, cool, it's it's okay if it's guaranteed to be wrong, but the problem is the the the word hypothesis, so it that causes you to do this brainstorming exercise and come up with something that is basically guaranteed to be wrong.
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And then the word hypothesis, for some reason, it makes us cling to it's my hypothesis, yeah, which blinds us to what poll actually is.
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It prevents us in a lot of different cases, not all the time, but but often enough, it like having that hypothesis is the thing we go out looking to validate the hypothesis.
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Um and and so I've seen startups do tens, hundreds of sales calls, like making minimal tweaks to their hypothesis that they have no reason to believe other than the fact that it came from a whiteboard and it has the word hypothesis and it sounds like science, right?
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And so, um, and so that's the like problem with the the word hypothesis is it causes us to go to the whiteboard, create something that is wrong by default, and we can explain explain why, and then cling to that.
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Yeah.
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That there's a a couple parts of that.
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You know, I've I ran with a poll hypothesis for longer than I should have.
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Um, and they don't, it's kind of like they feel totally believable.
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It's like you're in this like kind of mind warp thing.
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And as a result of it feeling like something that you think exists, like even objectively, um, with without having validated it, like I built too many slides, like I redid our website, like you know, there's there's like a lot of this investment that happens, which is an indication of I'm holding way too strongly onto something that a uh, you know, your real person rule, a real human being has not said to me in a meeting is something that they're trying to accomplish and are willing to pay for.
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Uh, but uh Rob, are there you know, what was maybe we hit real quick the intent.
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Like the intent of the poll hypothesis was not originally to, you know, go down a theoretical rabbit hole.
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Like there was there was a purpose of uh related more closely to learning or learning through error, or you know, what what is the thing that we want to not lose from the pull hypothesis that that that was the reason you came up with it?
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Yeah, so it's so basically we're just killing the word hypothesis.
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The concept is going to stay the same, but something about the word steers us into the abyss.
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So we're still going to have a pull framework, but the difference is that we're not going to call it a hypothesis, and we're still we still have the real person rule, and we're and we're turning it from we're just turning that when when we come up with the when we use the word hypothesis, we create this kind of plausible reality in our head.
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And we have to get rid of that plausible reality that doesn't reflect actual reality.
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And so all everything else is the same here.
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It's it's but we're just gonna call, we're gonna use different words because words have like really, really important implications of uh they they they create behaviors uh uh for us.
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And so we're just moving from pull hypothesis, which causes us to create this plausible world often, to pull anecdote, um, which is just a way to combine pull hypothesis and real person rule into one thing, one much simpler thing, uh which I like.
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We'll come back to that.
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Um uh which is to say, okay, cool.
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I don't even we can't have nice things.
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I can't use the word hypothesis.
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I have to find an actual anecdote of a person with pull.
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It could be me, or it could like, you know, or it could be somebody else, whatever, but it has to be an anecdote.
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I don't get to go to the whiteboard or to a doc and and kind of like write out a bunch of a list of hypotheses.
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Yeah.
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Okay, let's let's hit a couple things on this.
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Uh, you write about how using an anecdote clarified um like the workshop that you ran this week.
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You you know, they they they came in with a document, a bunch of plausible pull hypotheses, probably struggling to to choose like where do I where do I focus, where do I go with this.
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You move to an anecdote, it made it, you write that it made it way more clear.
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What actually happened?
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Like um uh and and then let's I I want to start with like how did it feel like what was the result?
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And then let's get into what is an anecdote actually look like.
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Yeah, so um, yes, and and this is like, okay, so if you if you look at a list of hypotheses, you can uh what happens is you can create a ton of hypotheses, all of which sound like they should work.
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They all sound like they make a bunch of sense.
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You can kind of map out where they could lead as a business.
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You can you can do all of this work on them.
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And then what you're doing um is you have a bunch of hypotheses in a doc or on a whiteboard, and you then have to like figure out how to prioritize across these different hypotheses and which one's most attractive, which one's most plausible.
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You have to do all of this work, and you're doing it in like 40 different dimensions um because you're like looking into the future, you're like doing all this different stuff.
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Do we know like and well, what you know, but what about Claude Code?
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What about the you know next model release?
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And you're doing all of this kind of insane work in your head.
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And so what happens is you come up with a doc, you spend hours just like hitting your head against the wall, trying to come up with some, and then you come to some conclusion at the end of that that's like, cool, we're gonna prioritize this one or these seven uh different directions.
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Um again, all of which are unlikely to have any grounding in the real world, to have even a single person with real pull, but you can't see that because they're all on equal footing in a dock.
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They all seem, they all have words, they all they all seem coherent.
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And so what happens is you just say, okay, cool, we we're not allowed to do that.
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We can't do that.
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What evidence do we have of actual pull from a real person?
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And when you do that, almost everything in that doc gets cleared out, and you say, Oh, interesting.
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Yeah, so uh helping kind of I've done this on two sides.
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Uh the one is for a zero-to-one company, one is for a kind of like later stage company looking to launch new products.
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Um later stage company looking to launch new products is like, what have we seen in our existing sales funnel?
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What have we seen from customers?
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Are they asking, are they trying to buy additional stuff from us?
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Have we had conversations where people have tried to buy stuff from us that we didn't have?
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Right.
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And it's like, it's that's where the anecdote comes from.
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And that's where that's and so what we're looking for are anecdotes of real people who have had some form of pull or like seem to have had some form of pull, but we didn't double-click into it and we can go back and figure that out.
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And that's what we're looking for in those occasions.
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And what that does is that takes that the the entire, basically the infinite possibilities and constrains it just to like what what is real based on what have we seen to be real?
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You know, it's it's funny.
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It's like how I feel like I spent 15 years being like, oh, that's just an anecdote, and like discounting it to zero, and then kind of like doing the opposite, which was like going to I don't know, what does data say, etc.?
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And increasingly with your approach, it's like the anecdote is the thing that really matters.
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But uh let how let's before we go to the zero to one, let's say, um, let's say that maybe maybe they're not, you know, uh uh Series B, Series C, like maybe they're not huge, but it's a startup that has some customers.
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What should they be looking for in an uh in a customer anecdote to develop their kind of pull anecdote here?
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Yeah, so I'm saying, like, if you if you what often happens when you have existing customers and it's it still feels like you're kind of pushing, is that um you will not focus on the anecdotes of your existing customers or the people who have been in your sales process or the people who have churned out or whatever, right?
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And instead you go to the whiteboard to theorize, to create a hypothesis.
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And so so if I were gonna keep the word hypothesis, I would say the hypothesis has to be generated from an anecdote of a real person.
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And so that's that's always, but but the word hypothesis prevents uh that from happening.
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So that's why we're getting rid of it.
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But what they have to do is they have to look into the anecdotes of sales conversations they've had or whatever, or whatever.
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Um, and if you're PLG, it's helping a company that's PLG right now, it's like, um, well, we need to go and talk to the people who have either signed up and used it and churned or or what.
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Like we just but we need to get to the anecdote of real people who have chosen us or not chosen us for some reason and try to try to figure it out from those anecdotes.
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And then you come up with like a okay, you come up with a pull anecdote, which is here's a real person who had this on their to-do list.
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They could, for this reason, they tried this other option, didn't work for this reason, therefore they chose us and they bought it relatively quickly.
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It's like, okay, cool.
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I have an anecdote that is a real thing.
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I need to see if that repeats and if that's the right shape that repeats.
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And so then you can either go and look at your other existing customers and see with that with if that repeats with them, or you go out and use that to run a sales sprint, right?
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And say, okay, cool.
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There, I'm just gonna see if this anecdote repeats rather than this hypothesis that I just crafted in my mind.
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Yeah.
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It feels like um the pull hypothesis previous version was closer to like, I'm a um, you know, go-to-market director that's trying to implement and, you know, there, or I'm a go-to market director in a SaaS company that's trying to implement XYZ or that's running into, you know, these limitations.
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Is this one like should people be using like the name of a human being?
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Should it be written in the past tense?
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Like, how should how should they think about crafting this um in a way that's effective?
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Yeah, I think I think it's I think like that's not super I I would make it like the exact person.
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Uh I'd make it the exact person, I would not abstract it very much at all.
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And I would try to just make it as close to the actual anecdote as humanly possible.
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And let's say that a founder has a couple anecdotes that they're they're choosing between.
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What what makes a more compelling anecdote to go with?
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Yeah, so um uh what you want to do is you uh the useful thing about the poll framework is you will like actually write out what poll is there, and you can look and you can compare different anecdotes with each other.
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And you might actually say, Oh, wait, these are actually the same anecdote written just three different ways.
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That's often what happens.
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And it's like, oh, here's the repeatable anecdote, or here's the repeatable case study, essentially.
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Um but what will often happen is you'll write out three anecdotes, and two of them you'll be like, huh, those people could have bought something else, and they just bought us because blank, right?
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Like they actually didn't have pull, which explains why the sales cycle was kind of slow, which explains why blah, blah, blah, blah, blah, blah, blah.
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Um, and so pull flame gives you a way to assess, is it real pull?
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Do I actually believe that this anecdote repeats?
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Is this good enough?
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Yeah.
00:20:38.319 --> 00:20:48.880
Well, um, and then is is there anything else that changes that like I know it's just the word, uh, it's really like a reinforcement of the real human, uh, real human rule.
00:20:49.119 --> 00:20:59.119
Um, is there is there anything else that changes in the way that you use the anecdote versus uh the way that previously folks were using hypothesis?
00:21:00.640 --> 00:21:10.799
No, I just I think uh what I hope an anecdote does, and what I have experienced, the idea of that anecdote does, is it doesn't give you a thing to call your own.
00:21:10.960 --> 00:21:15.839
Um and so you're gonna care less about the anecdote being true.
00:21:16.000 --> 00:21:17.680
Or or like about the anecdote.
00:21:18.079 --> 00:21:20.559
Because it's not, it's not your it's somebody else's anecdote.
00:21:20.640 --> 00:21:22.000
It's not your hypothesis.
00:21:22.160 --> 00:21:26.480
Somebody else's anecdote, your job is literally just to go and see if that repeats.
00:21:26.559 --> 00:21:28.160
And if it doesn't, cool, okay.
00:21:28.640 --> 00:21:29.759
Down to figure out something else.
00:21:30.079 --> 00:21:30.799
Let's talk about that.
00:21:30.880 --> 00:21:43.599
Um, and so it's you know, we've we've talked about the Hail Mary question, or um, you know, but I think what you're basically you're saying here is like there's a point in a sales conversation where it's like not working or that they are not pulling.
00:21:43.680 --> 00:21:53.599
It becomes obvious if you were, if you were, if you took your mind out of your body and observed the call that was happening and you were like, okay, they are obviously not pulling here.
00:21:53.759 --> 00:21:59.759
Um that's the moment where it's like, I either am tied to this hypothesis or I'm not tied.
00:22:00.319 --> 00:22:00.720
To it.
00:22:00.880 --> 00:22:01.839
What should they do?
00:22:02.160 --> 00:22:06.319
Okay, let's say that the anecdot, you know, using an anecdote makes that easier to stomach.
00:22:06.480 --> 00:22:16.079
How should they be extracting themselves from a situation where it's like, okay, had an had an anecdote, had a hypothesis, and it was uh it has been, it is not playing out.
00:22:16.160 --> 00:22:21.359
Like, what should their response in that case be that the hypothesis was preventing?
00:22:21.599 --> 00:22:21.759
Yeah.
00:22:21.920 --> 00:22:32.000
So this is this is also the nice thing about it, because when you have something called a hypothesis, your intuition is going to be to go back to a hypothesis and like work on the hypothesis.
00:22:33.279 --> 00:22:35.680
There's no such thing as a hypothesis anymore.
00:22:35.839 --> 00:22:41.440
You have to go find an anecdote, which which just pushes you to, you can ask the Hail Merit question.
00:22:41.599 --> 00:22:43.039
Is there anything you'd pay me?
00:22:43.359 --> 00:22:47.599
You'd pay someone, you is there anything you came to this conference to look for that you haven't been able to find?
00:22:47.759 --> 00:22:47.920
Right.
00:22:48.000 --> 00:22:49.839
Is it like those kinds of things?
00:22:50.000 --> 00:23:10.240
Um, and and so it's um uh yeah, it like removes that step of going back to the whiteboard every time and like working, doing another version of the hypothesis, doing another version of this awful exercise where you kind of like stare into the infinite of this.
00:23:10.400 --> 00:23:12.400
And instead, it's just okay, cool.
00:23:12.559 --> 00:23:19.039
Like I think this actually changes a this I we already had the simplest way to go zero to one.
00:23:19.119 --> 00:23:25.119
Um, and it's just been made even simpler, which is um you don't even craft a hypothesis in this.
00:23:25.359 --> 00:23:45.680
You can have a search area or something, you can have a person you're looking for, or or something like you have something, but your job is not to have a hypothesis, it's to go find an anecdote of somebody who wants to pay to solve something, to get something off their plate, to that who's trying to do something blah, and will pay for it.
00:23:45.920 --> 00:23:48.640
And you don't like that's the job.
00:23:48.720 --> 00:23:52.079
There is no no other there's no other activity.
00:23:53.119 --> 00:23:55.119
And and what one, I love that.
00:23:55.200 --> 00:23:58.000
I I just think it's I think it's way more liberating.
00:23:58.079 --> 00:24:02.000
Um and it removes that temptation to to tweak.
00:24:02.079 --> 00:24:07.039
It's like, oh, okay, well, maybe maybe I got this part like framed a little bit wrong.
00:24:07.200 --> 00:24:12.319
Um, and it's it's increasingly like my belief is tell me I'm wrong here, Rob.
00:24:12.400 --> 00:24:33.519
It's like if you find pull, like the it should be strong enough to overcome those like kind of small things, but if you until you are willing to just like you know, control a delete basically what a hypothesis is and replace it with an anecdote, you're gonna tweak things that maybe maybe it's around the corner here when really it's it's likely not there.
00:24:33.759 --> 00:24:34.960
Yeah, yep, 100%.
00:24:35.279 --> 00:24:54.000
Yeah, they're like oh well, we could probably like if you go back to um like the founding of Microsoft, the if you if you look at the history of Microsoft, um they saw in it in Popular Electronics magazine that there was a personal computer.
00:24:54.559 --> 00:24:58.559
Um the Altair, like it was and it was like this cool, cool thing.
00:24:58.640 --> 00:24:59.920
It was brand new.
00:25:00.079 --> 00:25:01.039
And what did they do?
00:25:01.279 --> 00:25:06.720
They have a they have a hypothesis and go and like run some experiments and do some research.
00:25:06.880 --> 00:25:16.960
Or no, they called the person, they called the company out in Albuquerque and said, Hey, would you pay us to do XYZ for you?
00:25:17.200 --> 00:25:24.880
And he said, the, the, the, uh, I forget what his name was, but he answered and said, uh, yeah, I've gotten seven calls like this.
00:25:25.039 --> 00:25:28.480
If you come and show me that it works, yes, I'm gonna pay you to do that.
00:25:28.720 --> 00:25:30.480
And that's when they started writing code.
00:25:30.559 --> 00:25:37.680
That's when the but if he had said, no, I wouldn't pay for languages, but I'd pay for this other thing, they probably would have done that other thing, right?
00:25:37.839 --> 00:25:59.839
And so, um, and so the kind of if you look into like the history of entrepreneurship and read these stories, it's not like the the concept of this hypothesis, I think, comes from our desire to like scientize a thing where scientific language doesn't seem to help.
00:26:00.400 --> 00:26:02.559
Yeah, I I really I like that example.
00:26:02.720 --> 00:26:05.680
Let's hit a couple things uh before we wrap on this one.
00:26:05.839 --> 00:26:11.359
One uh that I'm I'm 98% sure if we don't talk about this, somebody is gonna leave it in the comments.
00:26:11.519 --> 00:26:14.240
Um, one is does this apply to consumer?
00:26:14.400 --> 00:26:15.359
You mentioned PLG.
00:26:15.519 --> 00:26:16.640
Does this apply to deep tech?
00:26:16.799 --> 00:26:25.759
Like how does it um does it abstract across all different are there limitations um that you know we should be thinking about with an anecdote?
00:26:26.400 --> 00:26:27.359
Uh no.
00:26:28.559 --> 00:26:32.960
Um uh so there goes the excuse of uh special snowflake.
00:26:33.039 --> 00:26:34.880
Let's talk about zero to one.
00:26:35.279 --> 00:26:37.920
Um uh what if you're pre-anecdote?
00:26:38.000 --> 00:26:42.880
Like what should the founder that is like just getting started, or what do they do with this?
00:26:43.519 --> 00:26:57.599
Yeah, it's it's like pick some sort of a search area, which like we could call a hypothesis, but it's not a hypothesis of like you want X, it's just a hypothesis of like, here's who I want to talk to, here's who I want to serve, we'll see.
00:26:57.759 --> 00:27:14.000
Um, and then you basically go and find an anecdote, which is to say you go in person with them, you go talk to them, you get them as something, and try to figure out is there anything you would pay to get off your plate right now?
00:27:14.559 --> 00:27:19.359
And you don't come with a I believe you want to pay for X right now.
00:27:19.519 --> 00:27:23.279
You just you come hypothesis free, looking for an anecdote.
00:27:23.359 --> 00:27:24.880
Is there anything you're trying to buy that you haven't found?
00:27:24.960 --> 00:27:26.240
Is there anything you're trying to switch out?
00:27:26.319 --> 00:27:26.720
Is there anything?
00:27:27.920 --> 00:27:34.559
And then you can kind of pull up, fill out the pull framework from there and decide is that something we actually want to tackle.
00:27:34.720 --> 00:27:38.559
But your job is it's this should be super liberating.
00:27:38.720 --> 00:27:43.839
You don't have to sit around and come up with a ton of ideas and kind of predict the entire future.
00:27:44.000 --> 00:27:49.440
You just have to go find an anecdote and then see if it repeats, see if you want to serve it, da da da.
00:27:50.079 --> 00:27:53.200
But but the job is just find one anecdote.
00:27:53.279 --> 00:27:59.839
And if you're not doing the things that would enable you to find an anecdote, then it would be weird if you found both.
00:28:00.480 --> 00:28:01.119
Yeah.
00:28:02.000 --> 00:28:30.640
So it feels like I knowing our audience, which has a lot of computer engineers, a lot of folks that are focused on coding and developing AI applications, it's if you're in that zero spot, it's you know, choosing who is the customer that you want to serve, uh, doing whatever it takes using that hierarchy of interestingness, which we talked about, I don't know, two weeks ago or something like that, to try to get those conversations and uh coming in literally with the objective of trying to generate the anecdote.
00:28:30.799 --> 00:28:34.960
And uh there's probably like you know, some specifics you mentioned, the Hail Mary question.
00:28:35.119 --> 00:28:37.200
Um, you know, what what would you pay me to do?
00:28:37.279 --> 00:28:45.039
Are the frame of the conversation is still the same, but it instead of coming in saying, I believe like I want to see if you have pull for X.
00:28:45.519 --> 00:28:50.400
It's I just want to see if you have what if you have pull for anything and what if so what?
00:28:50.720 --> 00:28:51.359
Yeah.
00:28:51.599 --> 00:28:52.240
Yeah.
00:28:52.480 --> 00:28:53.599
Um awesome.
00:28:53.680 --> 00:28:58.079
Uh Rob, anything else that we wanna we wanna hit here before we wrap up today?
00:28:58.400 --> 00:28:58.960
Yeah.
00:28:59.279 --> 00:28:59.440
No.
00:28:59.839 --> 00:29:00.480
Okay, cool.
00:29:00.640 --> 00:29:04.880
Well, uh like we mentioned at the start, the PMF camp coming up September 14th.
00:29:04.960 --> 00:29:11.359
We'll we'll leave the uh my contact information and the link and uh for information in the show notes.
00:29:11.440 --> 00:29:13.279
Um and hope to see some of y'all there.
00:29:13.359 --> 00:29:14.720
Otherwise, Rob, we'll catch you in a week.
00:00:00.080 --> 00:00:00.719
Hey Rob.
00:00:01.120 --> 00:00:02.479
It's good to see you, man.
00:00:03.759 --> 00:00:06.959
You are you're you're back from not just vacation.
00:00:07.120 --> 00:00:14.960
You flew out to work with uh uh one of the early startups uh that you helped get past a million now they're they're growing past that.
00:00:15.199 --> 00:00:18.079
Um it's it's good to see it to be back in the saddle.
00:00:18.320 --> 00:00:38.320
Yeah, well, one thing I was thinking about, which is like, you know, I have an 18-month-old daughter now, and one of the things that I have become quite aware of is like as being a dad, one of the one of the kind of like rites of passage is uh now when I travel for this trip, I arrived at the airport an average of four hours before my flight.
00:00:39.759 --> 00:00:42.719
Just you know, sitting, feeling good.
00:00:42.880 --> 00:00:51.439
I like I also have this kind of like a desire to start learning more about the World War II battles, uh, certain World War II battles.
00:00:51.520 --> 00:00:59.039
And so it's like, I don't know, there's there's just something about being a dad that that forces you down this path.
00:00:59.439 --> 00:01:05.280
I have been hoping it was a generational thing, but uh it's it's probably like an individual evolution thing.
00:01:05.599 --> 00:01:08.719
No, I'll just start tucking in polos into my jeans.
00:01:08.879 --> 00:01:10.879
Like that's that's where we're going.
00:01:12.719 --> 00:01:20.640
Uh well, hey Rob, we've got uh a really you know, you know, you gave us you gave us a gift and you're taking the gift away from us.
00:01:20.799 --> 00:01:24.719
Uh this week's post is called No More Pull Hypotheses.
00:01:24.879 --> 00:01:36.159
We're gonna we're gonna talk about what was happening, what you were observing with pull hypotheses, uh how founder like the limitation basically that it that was causing founders to or the problem that they were stumbling over.
00:01:36.239 --> 00:01:38.879
Uh and then we're gonna get into uh the pull anecdote.
00:01:39.120 --> 00:01:44.799
Real fast before we jump into that, uh, we're gonna publish this one, I think, September 5th.
00:01:44.959 --> 00:01:47.040
We've got a PMF camp that's coming up.
00:01:47.120 --> 00:01:48.799
It starts September 14th.
00:01:48.959 --> 00:01:51.120
Um, just a few quick sentences like that.
00:01:51.200 --> 00:02:19.680
The goal of this um uh is to get you know, startups that are a good fit are looking to get Rob's direct engagement on their pool, on their go-to-market, on their outbound, um, and to see an you know another group of startup founders like develop their intuition by watching Rob uh and and the whole group really interact around how other founders are approaching outbound, how they're how they're thinking about the case study factory, um, doing teardowns of live calls.
00:02:19.759 --> 00:02:33.759
It's gonna be uh it's a two-week, uh, two-week PMF camp, starts on a Monday, ends on a Friday, includes uh four working sessions, a couple AMAs with Rob, and uh two teardowns of full sales calls from other founders in the community.
00:02:33.919 --> 00:02:37.919
Rob, um, anything that you would add on on that before we jump in?
00:02:38.879 --> 00:02:41.759
Uh I I just I just say like the the thing that has been consistent.
00:02:41.919 --> 00:02:43.840
We've now done, I have no idea how many times we've done this now.
00:02:43.919 --> 00:02:45.360
We've probably done it like 10 times.
00:02:45.520 --> 00:02:48.400
And so it always kind of evolves each each time.
00:02:48.639 --> 00:02:55.360
Um this time the flavor we're doing is just like way, way, way more feedback per startup.
00:02:55.439 --> 00:03:04.800
So basically, all of the sessions, say for say for one are like, you're gonna bring something and get it roasted or torn down or or uh you'll get helpful feedback on it.
00:03:04.960 --> 00:03:10.400
And then one of the things that so everyone everyone who comes into it is like, yeah, I want feedback on my thing.
00:03:10.560 --> 00:03:11.840
And so that's that's awesome.
00:03:12.000 --> 00:03:19.520
Whether it's your outbound message, whether it's your um you know sales deck, whether it's you know, whatever, whatever that thing is.
00:03:19.759 --> 00:03:37.360
Um one of the things people do not expect to get a ton of value out of, but do find they get a ton of value out of, is like watching other founders' sales calls and watching me tear down other founders' sales calls because it's actually often um you you'll have a lot more epiphanies when you see somebody else.
00:03:38.000 --> 00:03:45.520
And like you see something really clearly on somebody else's call or in somebody else's thing, and then you're like, wait a second, I need to apply that to myself.
00:03:45.599 --> 00:03:48.319
So um that that's been that's just been a fun, fun thing.
00:03:48.560 --> 00:03:50.719
Yeah, I I totally agree with that.
00:03:50.879 --> 00:03:58.240
Um the the the public teardowns that you do and uh are some of my favorite things, the most impactful things that have led to changes in my business.
00:03:58.400 --> 00:04:02.560
Um you mentioned this there's a lot of one-on-one or like a lot of direct feedback.
00:04:02.719 --> 00:04:06.080
We're capping the uh PMF camp at 15 startups.
00:04:06.159 --> 00:04:10.960
Um and so if you're interested, reach out, ASAP, um, and we'll just go from there.
00:04:11.120 --> 00:04:17.600
Well, Rob, if there's if there's no uh oh, we'll put the I'll put the link in the in the show notes for anybody that's interested.
00:04:17.920 --> 00:04:19.680
It's just like a short application.
00:04:19.920 --> 00:04:21.439
Um nothing else.
00:04:21.600 --> 00:04:25.920
If there's nothing else on that, why don't we jump into no more poll hypotheses?
00:04:26.079 --> 00:04:27.920
Um all right, Rob.
00:04:28.240 --> 00:04:34.240
You've we got everybody running on poll hypotheses, and now you're saying like, all right, total like orthogonal.
00:04:34.319 --> 00:04:36.000
We're going in the other direction on this one.
00:04:36.240 --> 00:04:38.720
Um why is this one on your mind?
00:04:38.800 --> 00:04:40.639
Uh, maybe like who's it, who's it for?
00:04:40.800 --> 00:04:41.519
Let's just start there.
00:04:41.759 --> 00:04:47.600
Yeah, so this is this is um especially relevant if you're going zero to one.
00:04:47.759 --> 00:04:56.079
And and you could be going zero to one on a new product, you could be going zero to one on uh like your second product on your first starter.
00:04:56.240 --> 00:05:02.480
Like it could it could be kind of anybody who is trying to go zero to one on anything or in the kind of like zero to one stage.
00:05:02.639 --> 00:05:06.160
Um uh this is gonna be relevant for you.
00:05:06.319 --> 00:05:10.240
And it's going to be relevant specifically because I'm taking a concept away.
00:05:10.480 --> 00:05:25.360
And I'm taking a concept away that sounds right, but there's a one word that seems to cause us to occasionally, not always, but steer straight into the iceberg.
00:05:25.439 --> 00:05:27.199
And that word is hypothesis.
00:05:27.360 --> 00:05:40.160
Now, like zooming out if you're new here, uh, the pull hypothesis was a is was a thing that is it's basically just a statement of I believe this person has pull or this kind of person has pull.
00:05:40.240 --> 00:05:54.079
Um, and pull, if you're also new here, the pull framework is a way to state uh somebody who's weird not to buy your product, who would be weird not to buy your product, where they're trying to do something, but they can't do that thing.
00:05:54.319 --> 00:05:56.800
They need to do that thing right now, can't do that thing.
00:05:56.879 --> 00:06:01.680
They're grinding against their existing tools, methods, and options, and you show up and unblock them.
00:06:01.839 --> 00:06:05.519
So they have like a blocked product on their to-do list, you unblock them.
00:06:05.680 --> 00:06:07.920
That is what the pull framework is.
00:06:08.079 --> 00:06:20.560
A pull hypothesis is a um, I believe this specific person has pull, and it's um, and what we're killing today is the word hypothesis.
00:06:20.959 --> 00:06:24.000
Yeah, and here's what you write uh about that.
00:06:24.160 --> 00:06:27.040
Um hypothesis comes with baggage.
00:06:27.199 --> 00:06:43.600
It feels like the kind of thing that originates in your brain, which leads a lot of founders to sit around and guess as a way to create their pool hypothesis, this despite the real person rule in my book, which states that a pool hypothesis must be based on a real person with pool.
00:06:43.759 --> 00:06:45.199
So, Rob, what were you?
00:06:45.439 --> 00:06:54.720
And and honestly, I'm pretty sure I was guilty to a certain extent of of uh abusing the word hypothesis or uh in the pool hypothesis here over uh on a couple occasions.
00:06:54.800 --> 00:06:56.240
But Rob, why don't you give some color?
00:06:56.319 --> 00:06:57.600
Like, what did it look like?
00:06:57.759 --> 00:07:05.759
Um, you know, for a founder that's using a pool hypothesis, yeah, um, just so that they can self-reflect on it, uh, what is what is going wrong?
00:07:05.839 --> 00:07:07.600
What does it look like when it's being used wrong?
00:07:07.839 --> 00:07:15.839
So the word hypothesis just makes you think of uh I need to think um first.
00:07:16.079 --> 00:07:19.519
Like I need I need to come up with a hypothesis.
00:07:19.920 --> 00:07:34.720
And so the method that most people do, and and this is I think due to the word hypothesis, is you'll open a dock or you'll go walk to a whiteboard and you'll just start brainstorming plausible hypotheses.
00:07:36.480 --> 00:07:50.079
And these plausible hypotheses, like you know, I I was doing a workshop uh this week with a with a another company, and and they basically showed up to the workshop with a huge dock of possible poll hypotheses.
00:07:51.600 --> 00:07:53.600
And that's that's the normal thing.
00:07:53.680 --> 00:07:56.240
It's like, okay, cool, who do we think might have pull?
00:07:56.959 --> 00:08:33.440
Um but which which like this totally sounds like a reasonable thing to do, but the challenge is that something that originates from your brain, it's usually based on like some abstract market logic or something of like, well, agents are taking over the world, so therefore, or this startup just took off, so therefore, right, like it's it's kind of abstract, and you take that and you turn it into a belief about a specific person or like a hypothesis about a specific person, that hypothesis is basically guaranteed to be wrong.
00:08:34.720 --> 00:08:49.440
Which again, like okay, cool, it's it's okay if it's guaranteed to be wrong, but the problem is the the the word hypothesis, so it that causes you to do this brainstorming exercise and come up with something that is basically guaranteed to be wrong.
00:08:50.720 --> 00:09:01.840
And then the word hypothesis, for some reason, it makes us cling to it's my hypothesis, yeah, which blinds us to what poll actually is.
00:09:02.000 --> 00:09:13.679
It prevents us in a lot of different cases, not all the time, but but often enough, it like having that hypothesis is the thing we go out looking to validate the hypothesis.
00:09:13.919 --> 00:09:29.039
Um and and so I've seen startups do tens, hundreds of sales calls, like making minimal tweaks to their hypothesis that they have no reason to believe other than the fact that it came from a whiteboard and it has the word hypothesis and it sounds like science, right?
00:09:29.200 --> 00:09:44.960
And so, um, and so that's the like problem with the the word hypothesis is it causes us to go to the whiteboard, create something that is wrong by default, and we can explain explain why, and then cling to that.
00:09:45.279 --> 00:09:45.919
Yeah.
00:09:46.159 --> 00:09:48.399
That there's a a couple parts of that.
00:09:48.480 --> 00:09:52.720
You know, I've I ran with a poll hypothesis for longer than I should have.
00:09:52.879 --> 00:09:57.440
Um, and they don't, it's kind of like they feel totally believable.
00:09:57.519 --> 00:10:00.720
It's like you're in this like kind of mind warp thing.
00:10:01.200 --> 00:10:29.279
And as a result of it feeling like something that you think exists, like even objectively, um, with without having validated it, like I built too many slides, like I redid our website, like you know, there's there's like a lot of this investment that happens, which is an indication of I'm holding way too strongly onto something that a uh, you know, your real person rule, a real human being has not said to me in a meeting is something that they're trying to accomplish and are willing to pay for.
00:10:29.440 --> 00:10:36.000
Uh, but uh Rob, are there you know, what was maybe we hit real quick the intent.
00:10:36.240 --> 00:10:45.519
Like the intent of the poll hypothesis was not originally to, you know, go down a theoretical rabbit hole.
00:10:45.679 --> 00:10:58.879
Like there was there was a purpose of uh related more closely to learning or learning through error, or you know, what what is the thing that we want to not lose from the pull hypothesis that that that was the reason you came up with it?
00:10:59.120 --> 00:11:03.440
Yeah, so it's so basically we're just killing the word hypothesis.
00:11:03.600 --> 00:11:10.480
The concept is going to stay the same, but something about the word steers us into the abyss.
00:11:10.720 --> 00:11:28.399
So we're still going to have a pull framework, but the difference is that we're not going to call it a hypothesis, and we're still we still have the real person rule, and we're and we're turning it from we're just turning that when when we come up with the when we use the word hypothesis, we create this kind of plausible reality in our head.
00:11:28.960 --> 00:11:33.679
And we have to get rid of that plausible reality that doesn't reflect actual reality.
00:11:33.840 --> 00:11:36.480
And so all everything else is the same here.
00:11:36.639 --> 00:11:50.000
It's it's but we're just gonna call, we're gonna use different words because words have like really, really important implications of uh they they they create behaviors uh uh for us.
00:11:50.159 --> 00:12:05.759
And so we're just moving from pull hypothesis, which causes us to create this plausible world often, to pull anecdote, um, which is just a way to combine pull hypothesis and real person rule into one thing, one much simpler thing, uh which I like.
00:12:05.840 --> 00:12:06.639
We'll come back to that.
00:12:06.799 --> 00:12:09.360
Um uh which is to say, okay, cool.
00:12:09.440 --> 00:12:12.080
I don't even we can't have nice things.
00:12:12.159 --> 00:12:14.240
I can't use the word hypothesis.
00:12:15.600 --> 00:12:20.159
I have to find an actual anecdote of a person with pull.
00:12:20.240 --> 00:12:26.639
It could be me, or it could like, you know, or it could be somebody else, whatever, but it has to be an anecdote.
00:12:26.879 --> 00:12:33.200
I don't get to go to the whiteboard or to a doc and and kind of like write out a bunch of a list of hypotheses.
00:12:33.440 --> 00:12:33.919
Yeah.
00:12:34.159 --> 00:12:36.720
Okay, let's let's hit a couple things on this.
00:12:36.799 --> 00:12:43.919
Uh, you write about how using an anecdote clarified um like the workshop that you ran this week.
00:12:44.000 --> 00:12:53.919
You you know, they they they came in with a document, a bunch of plausible pull hypotheses, probably struggling to to choose like where do I where do I focus, where do I go with this.
00:12:54.080 --> 00:12:57.840
You move to an anecdote, it made it, you write that it made it way more clear.
00:12:58.080 --> 00:12:58.960
What actually happened?
00:12:59.120 --> 00:13:05.440
Like um uh and and then let's I I want to start with like how did it feel like what was the result?
00:13:05.519 --> 00:13:08.639
And then let's get into what is an anecdote actually look like.
00:13:09.039 --> 00:13:23.919
Yeah, so um, yes, and and this is like, okay, so if you if you look at a list of hypotheses, you can uh what happens is you can create a ton of hypotheses, all of which sound like they should work.
00:13:24.080 --> 00:13:26.080
They all sound like they make a bunch of sense.
00:13:26.320 --> 00:13:29.360
You can kind of map out where they could lead as a business.
00:13:29.440 --> 00:13:31.279
You can you can do all of this work on them.
00:13:31.440 --> 00:13:45.759
And then what you're doing um is you have a bunch of hypotheses in a doc or on a whiteboard, and you then have to like figure out how to prioritize across these different hypotheses and which one's most attractive, which one's most plausible.
00:13:45.840 --> 00:13:53.840
You have to do all of this work, and you're doing it in like 40 different dimensions um because you're like looking into the future, you're like doing all this different stuff.
00:13:53.919 --> 00:13:58.399
Do we know like and well, what you know, but what about Claude Code?
00:13:58.480 --> 00:14:00.559
What about the you know next model release?
00:14:00.639 --> 00:14:04.000
And you're doing all of this kind of insane work in your head.
00:14:04.240 --> 00:14:19.279
And so what happens is you come up with a doc, you spend hours just like hitting your head against the wall, trying to come up with some, and then you come to some conclusion at the end of that that's like, cool, we're gonna prioritize this one or these seven uh different directions.
00:14:19.519 --> 00:14:34.240
Um again, all of which are unlikely to have any grounding in the real world, to have even a single person with real pull, but you can't see that because they're all on equal footing in a dock.
00:14:35.120 --> 00:14:39.759
They all seem, they all have words, they all they all seem coherent.
00:14:40.559 --> 00:14:44.480
And so what happens is you just say, okay, cool, we we're not allowed to do that.
00:14:44.639 --> 00:14:45.759
We can't do that.
00:14:47.120 --> 00:14:54.080
What evidence do we have of actual pull from a real person?
00:14:54.639 --> 00:15:02.000
And when you do that, almost everything in that doc gets cleared out, and you say, Oh, interesting.
00:15:02.320 --> 00:15:06.080
Yeah, so uh helping kind of I've done this on two sides.
00:15:06.159 --> 00:15:11.440
Uh the one is for a zero-to-one company, one is for a kind of like later stage company looking to launch new products.
00:15:11.600 --> 00:15:19.600
Um later stage company looking to launch new products is like, what have we seen in our existing sales funnel?
00:15:19.759 --> 00:15:22.000
What have we seen from customers?
00:15:22.159 --> 00:15:24.960
Are they asking, are they trying to buy additional stuff from us?
00:15:25.120 --> 00:15:28.960
Have we had conversations where people have tried to buy stuff from us that we didn't have?
00:15:29.120 --> 00:15:29.360
Right.
00:15:29.440 --> 00:15:32.960
And it's like, it's that's where the anecdote comes from.
00:15:33.039 --> 00:15:44.000
And that's where that's and so what we're looking for are anecdotes of real people who have had some form of pull or like seem to have had some form of pull, but we didn't double-click into it and we can go back and figure that out.
00:15:44.159 --> 00:15:46.320
And that's what we're looking for in those occasions.
00:15:46.480 --> 00:16:01.200
And what that does is that takes that the the entire, basically the infinite possibilities and constrains it just to like what what is real based on what have we seen to be real?
00:16:01.919 --> 00:16:03.360
You know, it's it's funny.
00:16:03.600 --> 00:16:16.879
It's like how I feel like I spent 15 years being like, oh, that's just an anecdote, and like discounting it to zero, and then kind of like doing the opposite, which was like going to I don't know, what does data say, etc.?
00:16:17.279 --> 00:16:22.559
And increasingly with your approach, it's like the anecdote is the thing that really matters.
00:16:22.720 --> 00:16:37.200
But uh let how let's before we go to the zero to one, let's say, um, let's say that maybe maybe they're not, you know, uh uh Series B, Series C, like maybe they're not huge, but it's a startup that has some customers.
00:16:37.440 --> 00:16:43.840
What should they be looking for in an uh in a customer anecdote to develop their kind of pull anecdote here?
00:16:44.639 --> 00:17:06.319
Yeah, so I'm saying, like, if you if you what often happens when you have existing customers and it's it still feels like you're kind of pushing, is that um you will not focus on the anecdotes of your existing customers or the people who have been in your sales process or the people who have churned out or whatever, right?
00:17:06.400 --> 00:17:11.920
And instead you go to the whiteboard to theorize, to create a hypothesis.
00:17:12.160 --> 00:17:20.880
And so so if I were gonna keep the word hypothesis, I would say the hypothesis has to be generated from an anecdote of a real person.
00:17:21.920 --> 00:17:27.039
And so that's that's always, but but the word hypothesis prevents uh that from happening.
00:17:27.200 --> 00:17:28.559
So that's why we're getting rid of it.
00:17:28.720 --> 00:17:36.480
But what they have to do is they have to look into the anecdotes of sales conversations they've had or whatever, or whatever.
00:17:36.640 --> 00:17:46.240
Um, and if you're PLG, it's helping a company that's PLG right now, it's like, um, well, we need to go and talk to the people who have either signed up and used it and churned or or what.
00:17:46.319 --> 00:17:59.279
Like we just but we need to get to the anecdote of real people who have chosen us or not chosen us for some reason and try to try to figure it out from those anecdotes.
00:17:59.440 --> 00:18:06.880
And then you come up with like a okay, you come up with a pull anecdote, which is here's a real person who had this on their to-do list.
00:18:07.039 --> 00:18:15.359
They could, for this reason, they tried this other option, didn't work for this reason, therefore they chose us and they bought it relatively quickly.
00:18:15.680 --> 00:18:16.720
It's like, okay, cool.
00:18:16.799 --> 00:18:19.440
I have an anecdote that is a real thing.
00:18:20.240 --> 00:18:25.119
I need to see if that repeats and if that's the right shape that repeats.
00:18:25.279 --> 00:18:35.599
And so then you can either go and look at your other existing customers and see with that with if that repeats with them, or you go out and use that to run a sales sprint, right?
00:18:35.680 --> 00:18:37.039
And say, okay, cool.
00:18:37.200 --> 00:18:44.240
There, I'm just gonna see if this anecdote repeats rather than this hypothesis that I just crafted in my mind.
00:18:44.640 --> 00:18:45.200
Yeah.
00:18:45.519 --> 00:19:03.519
It feels like um the pull hypothesis previous version was closer to like, I'm a um, you know, go-to-market director that's trying to implement and, you know, there, or I'm a go-to market director in a SaaS company that's trying to implement XYZ or that's running into, you know, these limitations.
00:19:03.680 --> 00:19:07.839
Is this one like should people be using like the name of a human being?
00:19:08.160 --> 00:19:09.519
Should it be written in the past tense?
00:19:09.680 --> 00:19:13.759
Like, how should how should they think about crafting this um in a way that's effective?
00:19:14.079 --> 00:19:20.400
Yeah, I think I think it's I think like that's not super I I would make it like the exact person.
00:19:21.519 --> 00:19:26.160
Uh I'd make it the exact person, I would not abstract it very much at all.
00:19:26.319 --> 00:19:29.839
And I would try to just make it as close to the actual anecdote as humanly possible.
00:19:30.880 --> 00:19:36.319
And let's say that a founder has a couple anecdotes that they're they're choosing between.
00:19:36.640 --> 00:19:40.720
What what makes a more compelling anecdote to go with?
00:19:41.359 --> 00:19:56.640
Yeah, so um uh what you want to do is you uh the useful thing about the poll framework is you will like actually write out what poll is there, and you can look and you can compare different anecdotes with each other.
00:19:56.960 --> 00:20:01.759
And you might actually say, Oh, wait, these are actually the same anecdote written just three different ways.
00:20:02.079 --> 00:20:03.039
That's often what happens.
00:20:03.119 --> 00:20:07.839
And it's like, oh, here's the repeatable anecdote, or here's the repeatable case study, essentially.
00:20:08.000 --> 00:20:18.799
Um but what will often happen is you'll write out three anecdotes, and two of them you'll be like, huh, those people could have bought something else, and they just bought us because blank, right?
00:20:18.880 --> 00:20:25.920
Like they actually didn't have pull, which explains why the sales cycle was kind of slow, which explains why blah, blah, blah, blah, blah, blah, blah.
00:20:26.079 --> 00:20:29.839
Um, and so pull flame gives you a way to assess, is it real pull?
00:20:30.079 --> 00:20:34.480
Do I actually believe that this anecdote repeats?
00:20:34.720 --> 00:20:36.319
Is this good enough?
00:20:37.279 --> 00:20:37.920
Yeah.
00:20:38.319 --> 00:20:48.880
Well, um, and then is is there anything else that changes that like I know it's just the word, uh, it's really like a reinforcement of the real human, uh, real human rule.
00:20:49.119 --> 00:20:59.119
Um, is there is there anything else that changes in the way that you use the anecdote versus uh the way that previously folks were using hypothesis?
00:21:00.640 --> 00:21:10.799
No, I just I think uh what I hope an anecdote does, and what I have experienced, the idea of that anecdote does, is it doesn't give you a thing to call your own.
00:21:10.960 --> 00:21:15.839
Um and so you're gonna care less about the anecdote being true.
00:21:16.000 --> 00:21:17.680
Or or like about the anecdote.
00:21:18.079 --> 00:21:20.559
Because it's not, it's not your it's somebody else's anecdote.
00:21:20.640 --> 00:21:22.000
It's not your hypothesis.
00:21:22.160 --> 00:21:26.480
Somebody else's anecdote, your job is literally just to go and see if that repeats.
00:21:26.559 --> 00:21:28.160
And if it doesn't, cool, okay.
00:21:28.640 --> 00:21:29.759
Down to figure out something else.
00:21:30.079 --> 00:21:30.799
Let's talk about that.
00:21:30.880 --> 00:21:43.599
Um, and so it's you know, we've we've talked about the Hail Mary question, or um, you know, but I think what you're basically you're saying here is like there's a point in a sales conversation where it's like not working or that they are not pulling.
00:21:43.680 --> 00:21:53.599
It becomes obvious if you were, if you were, if you took your mind out of your body and observed the call that was happening and you were like, okay, they are obviously not pulling here.
00:21:53.759 --> 00:21:59.759
Um that's the moment where it's like, I either am tied to this hypothesis or I'm not tied.
00:22:00.319 --> 00:22:00.720
To it.
00:22:00.880 --> 00:22:01.839
What should they do?
00:22:02.160 --> 00:22:06.319
Okay, let's say that the anecdot, you know, using an anecdote makes that easier to stomach.
00:22:06.480 --> 00:22:16.079
How should they be extracting themselves from a situation where it's like, okay, had an had an anecdote, had a hypothesis, and it was uh it has been, it is not playing out.
00:22:16.160 --> 00:22:21.359
Like, what should their response in that case be that the hypothesis was preventing?
00:22:21.599 --> 00:22:21.759
Yeah.
00:22:21.920 --> 00:22:32.000
So this is this is also the nice thing about it, because when you have something called a hypothesis, your intuition is going to be to go back to a hypothesis and like work on the hypothesis.
00:22:33.279 --> 00:22:35.680
There's no such thing as a hypothesis anymore.
00:22:35.839 --> 00:22:41.440
You have to go find an anecdote, which which just pushes you to, you can ask the Hail Merit question.
00:22:41.599 --> 00:22:43.039
Is there anything you'd pay me?
00:22:43.359 --> 00:22:47.599
You'd pay someone, you is there anything you came to this conference to look for that you haven't been able to find?
00:22:47.759 --> 00:22:47.920
Right.
00:22:48.000 --> 00:22:49.839
Is it like those kinds of things?
00:22:50.000 --> 00:23:10.240
Um, and and so it's um uh yeah, it like removes that step of going back to the whiteboard every time and like working, doing another version of the hypothesis, doing another version of this awful exercise where you kind of like stare into the infinite of this.
00:23:10.400 --> 00:23:12.400
And instead, it's just okay, cool.
00:23:12.559 --> 00:23:19.039
Like I think this actually changes a this I we already had the simplest way to go zero to one.
00:23:19.119 --> 00:23:25.119
Um, and it's just been made even simpler, which is um you don't even craft a hypothesis in this.
00:23:25.359 --> 00:23:45.680
You can have a search area or something, you can have a person you're looking for, or or something like you have something, but your job is not to have a hypothesis, it's to go find an anecdote of somebody who wants to pay to solve something, to get something off their plate, to that who's trying to do something blah, and will pay for it.
00:23:45.920 --> 00:23:48.640
And you don't like that's the job.
00:23:48.720 --> 00:23:52.079
There is no no other there's no other activity.
00:23:53.119 --> 00:23:55.119
And and what one, I love that.
00:23:55.200 --> 00:23:58.000
I I just think it's I think it's way more liberating.
00:23:58.079 --> 00:24:02.000
Um and it removes that temptation to to tweak.
00:24:02.079 --> 00:24:07.039
It's like, oh, okay, well, maybe maybe I got this part like framed a little bit wrong.
00:24:07.200 --> 00:24:12.319
Um, and it's it's increasingly like my belief is tell me I'm wrong here, Rob.
00:24:12.400 --> 00:24:33.519
It's like if you find pull, like the it should be strong enough to overcome those like kind of small things, but if you until you are willing to just like you know, control a delete basically what a hypothesis is and replace it with an anecdote, you're gonna tweak things that maybe maybe it's around the corner here when really it's it's likely not there.
00:24:33.759 --> 00:24:34.960
Yeah, yep, 100%.
00:24:35.279 --> 00:24:54.000
Yeah, they're like oh well, we could probably like if you go back to um like the founding of Microsoft, the if you if you look at the history of Microsoft, um they saw in it in Popular Electronics magazine that there was a personal computer.
00:24:54.559 --> 00:24:58.559
Um the Altair, like it was and it was like this cool, cool thing.
00:24:58.640 --> 00:24:59.920
It was brand new.
00:25:00.079 --> 00:25:01.039
And what did they do?
00:25:01.279 --> 00:25:06.720
They have a they have a hypothesis and go and like run some experiments and do some research.
00:25:06.880 --> 00:25:16.960
Or no, they called the person, they called the company out in Albuquerque and said, Hey, would you pay us to do XYZ for you?
00:25:17.200 --> 00:25:24.880
And he said, the, the, the, uh, I forget what his name was, but he answered and said, uh, yeah, I've gotten seven calls like this.
00:25:25.039 --> 00:25:28.480
If you come and show me that it works, yes, I'm gonna pay you to do that.
00:25:28.720 --> 00:25:30.480
And that's when they started writing code.
00:25:30.559 --> 00:25:37.680
That's when the but if he had said, no, I wouldn't pay for languages, but I'd pay for this other thing, they probably would have done that other thing, right?
00:25:37.839 --> 00:25:59.839
And so, um, and so the kind of if you look into like the history of entrepreneurship and read these stories, it's not like the the concept of this hypothesis, I think, comes from our desire to like scientize a thing where scientific language doesn't seem to help.
00:26:00.400 --> 00:26:02.559
Yeah, I I really I like that example.
00:26:02.720 --> 00:26:05.680
Let's hit a couple things uh before we wrap on this one.
00:26:05.839 --> 00:26:11.359
One uh that I'm I'm 98% sure if we don't talk about this, somebody is gonna leave it in the comments.
00:26:11.519 --> 00:26:14.240
Um, one is does this apply to consumer?
00:26:14.400 --> 00:26:15.359
You mentioned PLG.
00:26:15.519 --> 00:26:16.640
Does this apply to deep tech?
00:26:16.799 --> 00:26:25.759
Like how does it um does it abstract across all different are there limitations um that you know we should be thinking about with an anecdote?
00:26:26.400 --> 00:26:27.359
Uh no.
00:26:28.559 --> 00:26:32.960
Um uh so there goes the excuse of uh special snowflake.
00:26:33.039 --> 00:26:34.880
Let's talk about zero to one.
00:26:35.279 --> 00:26:37.920
Um uh what if you're pre-anecdote?
00:26:38.000 --> 00:26:42.880
Like what should the founder that is like just getting started, or what do they do with this?
00:26:43.519 --> 00:26:57.599
Yeah, it's it's like pick some sort of a search area, which like we could call a hypothesis, but it's not a hypothesis of like you want X, it's just a hypothesis of like, here's who I want to talk to, here's who I want to serve, we'll see.
00:26:57.759 --> 00:27:14.000
Um, and then you basically go and find an anecdote, which is to say you go in person with them, you go talk to them, you get them as something, and try to figure out is there anything you would pay to get off your plate right now?
00:27:14.559 --> 00:27:19.359
And you don't come with a I believe you want to pay for X right now.
00:27:19.519 --> 00:27:23.279
You just you come hypothesis free, looking for an anecdote.
00:27:23.359 --> 00:27:24.880
Is there anything you're trying to buy that you haven't found?
00:27:24.960 --> 00:27:26.240
Is there anything you're trying to switch out?
00:27:26.319 --> 00:27:26.720
Is there anything?
00:27:27.920 --> 00:27:34.559
And then you can kind of pull up, fill out the pull framework from there and decide is that something we actually want to tackle.
00:27:34.720 --> 00:27:38.559
But your job is it's this should be super liberating.
00:27:38.720 --> 00:27:43.839
You don't have to sit around and come up with a ton of ideas and kind of predict the entire future.
00:27:44.000 --> 00:27:49.440
You just have to go find an anecdote and then see if it repeats, see if you want to serve it, da da da.
00:27:50.079 --> 00:27:53.200
But but the job is just find one anecdote.
00:27:53.279 --> 00:27:59.839
And if you're not doing the things that would enable you to find an anecdote, then it would be weird if you found both.
00:28:00.480 --> 00:28:01.119
Yeah.
00:28:02.000 --> 00:28:30.640
So it feels like I knowing our audience, which has a lot of computer engineers, a lot of folks that are focused on coding and developing AI applications, it's if you're in that zero spot, it's you know, choosing who is the customer that you want to serve, uh, doing whatever it takes using that hierarchy of interestingness, which we talked about, I don't know, two weeks ago or something like that, to try to get those conversations and uh coming in literally with the objective of trying to generate the anecdote.
00:28:30.799 --> 00:28:34.960
And uh there's probably like you know, some specifics you mentioned, the Hail Mary question.
00:28:35.119 --> 00:28:37.200
Um, you know, what what would you pay me to do?
00:28:37.279 --> 00:28:45.039
Are the frame of the conversation is still the same, but it instead of coming in saying, I believe like I want to see if you have pull for X.
00:28:45.519 --> 00:28:50.400
It's I just want to see if you have what if you have pull for anything and what if so what?
00:28:50.720 --> 00:28:51.359
Yeah.
00:28:51.599 --> 00:28:52.240
Yeah.
00:28:52.480 --> 00:28:53.599
Um awesome.
00:28:53.680 --> 00:28:58.079
Uh Rob, anything else that we wanna we wanna hit here before we wrap up today?
00:28:58.400 --> 00:28:58.960
Yeah.
00:28:59.279 --> 00:28:59.440
No.
00:28:59.839 --> 00:29:00.480
Okay, cool.
00:29:00.640 --> 00:29:04.880
Well, uh like we mentioned at the start, the PMF camp coming up September 14th.
00:29:04.960 --> 00:29:11.359
We'll we'll leave the uh my contact information and the link and uh for information in the show notes.
00:29:11.440 --> 00:29:13.279
Um and hope to see some of y'all there.
00:29:13.359 --> 00:29:14.720
Otherwise, Rob, we'll catch you in a week.
