Hey friends 👋

You know the pattern: founder builds the product, polishes the product, adds “one more” feature, then waits for the market to notice.

Step one: build it. Step two: question mark. Step three: profit.

For episode 100, we continue the Startup Pseudoscience Series with the myth of “if you build it, they will come.” We steelman the best version first, because product quality does matter. Slack, Dropbox, Notion, Figma... the product-led legends are tempting for a reason.

Then we get into the part founders love to skip: survivorship bias, referral mechanics, switching costs, timing, trust, and the narrow conditions that make product-led growth work. A great product is not a distribution strategy. It only helps if customers can find it, understand it, trust it, and care enough to change.

From Amazon reviews and Best Buy’s showroom problem to Slack’s pivot out of a game studio, we break down why “build first, sell later” usually hides a stack of untested assumptions.

Plus, frivolous thoughts get unusually sincere: 100 episodes as an R&D lab for Traction Lab’s thinking, Cameron’s fifth marathon, and the weird endurance sport of showing up every week.

As always, thanks for listening.

—Cameron and JDM

Timestamps

00:00 - Introduction

02:15 - If you build it, they will come

05:30 - Survivorship bias and product-led myths

12:45 - Referral mechanics and Amazon reviews

25:00 - Product, distribution, and founder psychology

40:00 - Frivolous Thoughts

Hey friends 🤘

You know the pattern: founders hear encouraging words, dodge the uncomfortable price conversation, and call it traction because everyone is smiling.

Cute. Also dangerous.

For episode 99, we put Office Hours on the podcast feed and took four founder questions that all circle the same problem: founders trying to avoid the signal that matters. Will customers pay more? Will free pilots convert? Should contractor software start narrow? Can two engineers enter healthcare without a regulatory sherpa?

We get into price increases, the danger of unpaid pilots, why “everyone does things differently” is usually a reason to narrow instead of broaden, and why HIPAA probably should not be the first scary thing you fight at idea stage.

Plus, frivolous thoughts include Blues Traveler harmonica heroics, aging Cards Against Humanity references, and the unsettling moment your family reveals exactly how dark they think your sense of humor is.

As always, thanks for listening.

—Cameron and JDM

Timestamps

00:00 - Introduction

02:15 - Low T and episode 99

05:30 - Raising prices without panicking

12:45 - Free pilots that never convert

25:00 - Narrowing contractors and healthcare fear

40:00 - Frivolous Thoughts

Hey friends 👋

You know the pattern: founder builds the thing, founder lists the features, founder waits for customers to notice how obviously great it is. Very compelling!

But only for the founder.

This week, Cameron and JDM continue the Startup Pseudoscience Series with one of the sneakiest myths in startup land: people buy products. We steelman the case first, because products are tangible. Features are visible. Specs feel objective. Money does, in fact, get exchanged for the thing.

Except the thing is not the point.

Customers are buying a problem solved, an outcome reached, and a future state they can actually imagine. A drill bit is not about a drill bit. It is not even about the hole. It is about getting art on the wall without creating a new problem in the process.

From Command strips to Juicero to Instagram filters, we dig into why feature-first messaging falls flat, why “better, faster, cheaper” usually is not enough, and how switching costs protect the status quo.

Then we get practical: jobs to be done, customer discovery, needs/wants/fears, and experience maps as a way back from product obsession to actual customer problems.

Plus, in frivolous thoughts: Line of Duty, fancy Japanese whiskey glasses, spherical ice, shaken espresso, and the deeply relatable pain of paying for two Prime accounts because switching costs are real.

As always, thanks for listening.

—Cameron and JDM

Timestamps

00:00 Introduction

02:15 Steelmanning the product myth

05:30 People buy problems solved

12:45 Features, outcomes, and jobs to be done

25:00 Customer discovery and experience maps

40:00 Frivolous Thoughts

Hey friends 👋

You know the pattern: founder has an idea, founder needs a product, product needs money, so the next three months disappear into pitch deck purgatory.

Very official. Very polished.

Still just unfundable assumptions with pretty slides.

This week, Cameron and JDM continue the Startup Pseudoscience Series with one of the more seductive founder myths: you need to raise money to get started. We steelman the case first, because capital does buy talent, speed, infrastructure, and credibility. And it is genuinely necessary—sometimes.

But “sometimes capital is useful” is not the same as “fundraising is step one.”

We dig into why the startup mythology machine keeps retelling the same fundraising story, how capital can become a license to delay customer learning, and why weak evidence makes your cost of capital painfully expensive.

From pitch decks built on vibes to founders trying to take a giant swing before they have earned the count, we break down why traction should pull capital forward instead of capital pretending traction exists.

Plus, in frivolous thoughts: Sacramento’s MLB expansion hopes, why the big swing metaphor actually works, and JDM’s endorsement of Hacks as light, sharp, excellent TV.

As always, thanks for listening.

—Cameron and JDM

Timestamps

00:00 Introduction

02:15 Steelmanning the fundraising myth

05:30 The startup mythology machine

12:45 Capital, milestones, and evidence

17:45 Small swings before big swings

22:00 Frivolous Thoughts

Hey friends 👋

You know the pattern: you launch a thing, people say they are interested, and when it is time to show up… no one does.

Cool, data, I guess?

This week, Cameron and JDM record from Science and Startups Live, which was supposed to be a small in-person podcast event and instead became a very public lesson in failure.

Fifteen registrations. One attendee. Several empty chairs with excellent listening posture.

So we threw out the planned topic and turned the Traction Lab lens on ourselves: what happened, what can we actually infer from the data, and how do you avoid blaming the customer when your offer doesn’t land?

We chat about inference to the best explanation, the difference between weak marketing and weak value props, and why a free RSVP is not intent. Then we connect it to the TEAM framework — time, effort, access, and money — as ways to close the say-do gap before you bet too much on polite interest.

Founder (and friend of the pod) Da’Shena Payne also joins the conversation with the best customer discovery gift possible: telling us the name “Science and Startups” sucks.

Painful. Useful. Exactly the point.

Plus, in frivolous thoughts: Kings draft optimism, a UC Davis summer camp, and the reminder that you can be direct, even shitty, and still be kind.

As always, thanks for listening.

—Cameron and JDM

Timestamps

00:00 Introduction

02:15 The live event that did not go as planned

05:30 Inference, hypotheses, and interpreting failure

12:45 The say/do gap and the TEAM framework

25:00 Naming, value proposition, and customer feedback

40:00 Frivolous Thoughts

Hey friends 👋

You know the pattern: founder has a big idea, founder protects the idea, founder keeps polishing the idea until it becomes too precious to test.

It feels productive. It also feels safe.

Which is exactly the problem.

This week, Cameron and JDM kick off the Startup Pseudoscience Series by taking aim at one of the most comforting founder myths: that the great idea is the hardest part. We steelman the claim first, then put it through the same evidence-based lens we use on startup pitches.

Ideas are starting points. Hypotheses. Directions to walk in a messy process where the destination probably does not exist yet.

From survivorship bias and founder mythology to the very real temptation to brainstorm forever with Claude instead of talking to customers, we dig into why founders overvalue the thing that cannot hurt them yet. The stronger idea is not the one you have thought about longest. It is the one with evidence behind it.

Plus: Mezcal Old Fashioneds, Michelin Guide pizza in Sacramento, and a homework assignment you will absolutely try to avoid.

As always, thanks for listening.

—Cameron and JDM

Timestamps

00:00 - Introduction

02:15 - Steelmanning the “great idea” myth

05:30 - Evidence, survivorship bias, and founder mythology

12:45 - Time to customer and the safety of ideation

17:45 - Falsification: turning bad ideas into good businesses

23:45 - Frivolous Thoughts

Hey friends 👋

“AI native” is everywhere right now—and almost nobody using the label actually qualifies. This week, Cameron and JDM dig into what it actually means to build with AI at the core of your startup (it’s not about your workflow tools), and why the founders most excited about shipping fast are making the same old mistake in a shiny new wrapper.

There’s a meaningful difference between AI compressing your build cycle and AI being the reason your company exists. Get that wrong, and you’re efficiently moving in the wrong direction—stacking assumptions on top of assumptions, measuring inputs instead of outcomes, and calling it traction.

Building got faster. Validation didn’t. Customers still decide on their own timeline, no matter how quickly you ship.

JDM also has some personal news this week—Emilia has arrived, and the Miller family is officially a party of four. Cameron’s growing his own crew too, but his is decidedly more… reptilian.

As always, thanks for listening.

—Cameron and JDM

Timestamps

00:00 Introduction

03:15 What “AI native” actually means

06:00 The build vs. validation gap

15:00 Efficiency vs. evidence: the core mistake

20:00 Sequencing violations

23:00 Frivolous Thoughts

Hey friends 👋

There’s a moment every founder hits — you’re maxed out, you hate doing the thing, so you hire someone to take it off your plate. VP of Sales. Head of Product. Done. Problem solved.

Except it’s not. Not even close.

This week, Cameron and JDM break down the Founder Arc — the path from founder-only to founder-led to founderless — and why jumping straight from one end to the other is how startups quietly come apart. The middle phase isn’t optional. It’s where the playbook gets written, the trust gets built, and the real handoff actually happens.

From a franchise SaaS founder planning to exit sales entirely before his first hire has closed a single deal, to a vet-clinic platform founder holding product hostage because “nobody understands our customers like I do” — we rate each move on our conviction scale. Two score crash-and-burn. One almost earns a pass.

The third scenario? A support function that navigated the arc cleanly — but Cameron and JDM are squinting hard at the unit economics.

Plus: Cameron is fresh off go-karting through the streets of Tokyo at night (no shells were thrown, unfortunately). And JDM is recording this episode on the edge of a very big life event — probably the last episode in the queue before baby #2 arrives. Wish him luck.

As always, thanks for listening.

—Cameron and JDM

Timestamps

00:00 Introduction

02:15 The Founder Arc: founder-only, founder-led, founderless

05:30 Scenario 1: The too-fast sales handoff

12:45 Scenario 2: The product bottleneck problem

25:00 Scenario 3: A support arc done right

40:00 Frivolous Thoughts

Hey friends 👋

Every founder wants the J-curve — up and to the right, forever. But that chart has a boring flat part at the beginning that most founders try to skip. That’s the part where you figure out what actually works, prove it can happen again, and then pour gas on it. Skip it and you’re not scaling a growth engine. You’re just spending money faster.

This week we dig into one of our core frameworks: predictable, repeatable, scalable. In that order. Always in that order. The key question: can you tell the difference between what worked and what just happened to work that one time? Because your entire engine rests on that answer.

Three founders are convinced they’re ready to scale. One’s averaging two new customers a month (a number that might be doing some heavy lifting to hide the real variance). One has a genuinely tight LinkedIn playbook — but now wants to hand it to an SDR and go explore a new segment. And one had three TikTok videos go viral and wants to triple the content team to make the magic happen again. We rate all three on our conviction scale, and nothing gets above a six.

Cameron recommends a detective show. JDM withdraws a previous recommendation entirely.

As always, thanks for listening.

—Cameron and JDM

Timestamps

00:00 Introduction

02:15 Predictable, Repeatable, Scalable

05:30 Scenario 1: SaaS returns processing platform

12:45 Scenario 2: Warehouse safety compliance

25:00 Scenario 3: Consumer fintech / TikTok

40:00 Frivolous Thoughts

Hey friends 👋

You know the pattern.

* January: idea.

* February: market research.

* March: wireframes, logo, landing page.

* April: four customer convos. Two said routing is a pain point.

Ouch — that’s just a museum of artifacts nobody bought a ticket to.

This week, we break down Time to Customer: the single most important velocity metric for early-stage founders, and the one most likely to make you squirm.

It’s a simple measurement — how long from “I have an idea” to “I tested it with a real customer”? Turns out, that gap is where most founders hide. Cameron and JDM dig into why we delay, what “progressivity” looks like in the wild, and what it actually means to have a bias toward getting in front of customers.

We run three scenarios through the TTC lens — from a dog grooming app that spent three months in pre-production before a single customer call, to a churn prediction startup that got a prospect to ask “what would it cost to get this every month?”, to a compliance platform that built an entire outbound playbook before sending their first cold email.

tbh… conviction scores were grim, but we left every founder with a clear path forward. We hope.

And in frivolous Thoughts:

* Cameron caught the Buffalo Traffic Jam live at a 200-person DC venue (Bands in Town is the app you didn’t know you needed), and

* JDM makes a strong case for Sofia Isella as the reigning queen of dark pop.

As always, thanks for listening.

—Cameron and JDM

Timestamps

00:00 Introduction

02:15 Time to Customer

05:30 Scenario 1: Mobile dog groomer routing app

12:45 Scenario 2: SaaS churn prediction platform

25:00 Scenario 3: Home healthcare compliance training

40:00 Frivolous Thoughts