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Julia Schottenstein (dbt Labs)13 July 2023

M&A, competition, pricing, and investing

8Frameworks
15Insights

Frameworks in this episode

Insights & moments

The myth-busts, hot takes, explainers, and tools worth keeping.

Hot Take· 4

Hot Take14:00

M&A Is About Creating Plan Bs — Inflict Pain, But Stay Friendly

Julia's core M&A advice: for any company there are only two or three buyers who find you strategic. Find the area where you have a competitive advantage and inflict pain on that potential buyer so they can't ignore you — but keep the relationship friendly and open, because founders who take too competitive a stance prematurely shut the door on optionality.

  • The best M&A strategy is a strong offense — the ability to stay independent gives you leverage in every conversation
  • For any one company there are only two to three genuinely strategic buyers
  • Inflict pain on a potential buyer in your area of advantage so they notice you
  • Do it while staying friendly and open; don't shut the door prematurely

I would figure out the area that you bring a competitive advantage and I would inflict pain on that potential buyer make it impossible for…

Julia Schottenstein · 15:00

the really important piece here is you want to do that in a way that's still friendly and open I see a lot of Founders…

Julia Schottenstein · 15:30
#m&a#strategy#fundraising#optionality
Hot Take33:00

'We're Happy to Lose to Ourselves': Value Creation Over Value Capture

One of dbt's core values is being more concerned with value creation than value capture. Customers say dbt is worth 20–35% of what they spend on their cloud data warehouse, yet dbt charges only a small fraction of that by design. Most deals the paid team loses are lost to dbt open source — and they like it that way.

  • A core value: more concerned with value creation than value capture
  • Customers value dbt at 20–35% of their cloud data warehouse spend
  • dbt deliberately charges only a small fraction of that value
  • When the paid team loses a deal, it most often loses to dbt open source — by design

when we lose a deal we most often lose it to DBT open source and we like it that way we're we're happy to lose…

Julia Schottenstein · 34:00
#pricing#values#open-source#dbt
Hot Take41:00

Sometimes You Should Quit — Your Investors Aren't Getting Their Money Back

Julia offers a candid, possibly unpopular take: investors already understand they won't get their money back, and 50% of early-stage portfolios return nothing. What they actually want is for founders to land somewhere great, not to grind out a mediocre outcome. Against the grit-and-never-quit mantra, sometimes quitting is the right, acceptable call.

  • Investors understand they may not make their money back — half of portfolios return nothing
  • They'd rather you end up at a great company than force a small outcome
  • Don't stay stuck at a company you hate just to return some money
  • Against grit-and-never-quit advice, sometimes you should quit

to get stuck at a company they hate and just so that they could return some money or have some kind of outcome like I'd…

Lenny · 42:00

a lot of times for Founders that are told like it's all about grit and not giving up and don't quit sometimes sometimes you should…

Julia Schottenstein · 42:30
#founders#investing#exit#mental-health
Hot Take52:00

Worse Is Better, and Tech Debt Is a Champagne Problem

Not a framework person, Julia leans on two sayings to fight perfectionism: 'worse is better' and 'tech debt is a champagne problem.' Shipping good-enough is when you actually learn from users. She points to dbt's first scheduler — an embarrassingly naive for-loop over a jobs table — that got the job done and only needed rebuilding once real scale (8,000 companies, 10M runs/month) arrived.

  • Two sayings fight perfectionism: 'worse is better' and 'tech debt is a champagne problem'
  • You can't anticipate real usage until you ship
  • dbt's first scheduler was a naive for-loop over a jobs table — and it worked
  • Tech debt means people are using the product; they didn't need a distributed scheduler with no users

and it's uh um worse is better and Tech debt is a champagne problem

Julia Schottenstein · 52:00

and I try to remind the engineers like we would be so lucky to have tech tech debt because that means people are using the…

Julia Schottenstein · 53:30
#shipping#tech-debt#product#engineering

Explainer· 4

Explainer11:00

The Clearest Product-Market-Fit Signal: Users Who Can't Stop Talking About It

Asked what specifically signals a company is special, Julia points beyond the emotional 'I want this now' reaction to a stronger tell: users who can't stop talking about the product and want to share it with teammates and people at other companies. That organic chatter does a lot of the go-to-market work because evangelists come from your user base.

  • Beyond an emotional reaction, the real signal is users can't stop talking about the product
  • Chatter and wanting to share it with teammates and other companies is a great sign
  • Top-of-mind love means your users become your evangelists and drive distribution

yeah it's can they not stop talking about it and that's this like the chatter about a product they want to share it with like…

Julia Schottenstein · 11:30
#product-market-fit#distribution#early-stage
Explainer18:00

dbt's Competition Philosophy: Hold the Vision, Grow the Pie, Lean Into Strengths

Julia shares the three pillars dbt codified for handling competition. Hold true to your vision and treat competitor shade as noise; adopt a grow-the-pie mindset that partners with the ecosystem to expand the total opportunity; and lean into your strengths while leaving space for partners, defending only the transformation and semantic standards.

  • Hold true to your vision — most competitor noise is a distraction; run your own race
  • Grow the pie — work with ecosystem partners to expand the opportunity rather than slice it thin
  • Lean into your strengths but leave room for the ecosystem to serve users
  • dbt only holds its ground on the transformation and semantic standards

if you have a lot of conviction that you're going in the right Journey you want to just keep your eyes straight ahead and run…

Julia Schottenstein · 18:30
#competition#strategy#dbt#ecosystem
Explainer29:30

dbt's Open-Core Line: Open Source the Guts, Charge for State and Collaboration

Julia explains how dbt decides what stays open source versus proprietary. The open-source core is the guts of data transformation — where you describe your business logic — because keeping the standard open matters to the ecosystem. What dbt reserves for its paid Cloud offering is anything stateful and any cross-team or structural collaboration that supercharges the development lifecycle.

  • The open-source core is the guts of transformation — where you write business logic
  • Keeping the standard open is important for the ecosystem
  • Stateful interactions are reserved for the proprietary Cloud offering
  • Cross-team and structural collaboration are also part of the paid product

what we think about as leaving for our Cloud offering is we deal with state so stateful interactions and also any kind of cross team…

Julia Schottenstein · 30:00
#open-source#open-core#pricing#dbt
Explainer45:00

The M&A Code Words: If You Have Time, Don't Say M&A at All

Julia advises against being too clever with M&A phrasing — everyone knows 'evaluating strategic alternatives' means you're for sale. If you have runway, don't talk about M&A at all; talk about collaboration, partnerships, and knowledge sharing. If you're out of time, you're out of time and should be transparent.

  • Everyone understands 'evaluating strategic alternatives' means you're selling
  • If you have time, don't raise M&A; frame it as collaboration or partnership
  • M&A is a dirty word when you still have runway to pursue independence
  • If you're out of time, just be transparent

if you have time then don't talk about m&a at all like that's the last thing that you want to speak about instead you're talking…

Julia Schottenstein · 45:30
#m&a#negotiation#strategy#exit

Story· 3

Story06:30

The VC Who Bet 20% of Her Net Worth on DBT — Then Joined It

Julia describes her unusual path from professional early-stage investor at NEA into product management at dbt Labs. She was so convinced dbt was special that she asked to put ~20% of her liquid net worth into the round, lost the deal to Sequoia, and later called the CEO to ask if she could join the company instead.

  • Investors interested in product and vice versa is more common than people assume
  • She discovered dbt in 2019 as an open-source data transformation framework and was struck that users treated it as an identity, not just a tool
  • She asked to invest ~20% of her liquid net worth and lost the deal to Sequoia
  • The board vetoed her personal investment, so she joined dbt Labs to build the product instead

I asked to put like a very irresponsible IR rational amount um nearly like 20% of my liquid net worth into DBT because I was…

Julia Schottenstein · 07:00
#career#investing#dbt#product
Story16:00

How dbt Acquired Transform: A Friendly Rival With Product but No Distribution

Julia tells the story of dbt acquiring Transform, a pure-play semantic-layer company built by ex-Airbnb engineers. Transform had strong technical product and was vocal about solving hard problems but lacked distribution, while dbt had distribution but was behind on product. Because Transform positioned itself as a friendly partner and had already built dbt integration, the acquisition and post-deal integration went smoothly.

  • Transform was a pure-play semantic/metric layer company with strong technical product
  • They came from Airbnb, famous for its Minerva semantic layer
  • dbt had distribution and ecosystem but was behind on bringing the product to market
  • Transform applied pressure while positioning as a partner, which made the acquisition and integration easier

we felt that pressure from transform because they were doing such a great job at being vocal and loud about how their semantic layer solves…

Julia Schottenstein · 17:00
#m&a#dbt#semantic-layer#acquisition
Story26:30

Tying Up Engineers With Rope to Teach a New Algorithm

Inspired by an ant-farm scene in Gödel, Escher, Bach, Julia ran a team offsite where she used a spool of rope and sticky notes to physically build a graph — each engineer a node, the rope the edges — and walked the team slowly through a new data-transformation algorithm. The point was ownership: no one could leave without fully understanding it, so the whole team internalized every edge case rather than a few people running ahead.

  • The exercise was inspired by an ant-farm scene in Gödel, Escher, Bach
  • Engineers became nodes and rope became edges of the transformation graph
  • The goal was shared ownership so the team could anticipate all edge cases
  • The underlying change flipped dags from an imperative to a declarative model

so I showed up to a team offsite with uh spool of rope and uh sticky notes and I think my team looked at me…

Julia Schottenstein · 27:30

and it was a way that you couldn't leave that exercise without knowing exactly what was going on because everyone had a role to play

Julia Schottenstein · 28:00
#team#leadership#engineering#dbt

Q&A· 1

Q&A36:30

Should You Be Public That You're Selling? In a Hail Mary, Yes

Responding to Hunter Walk's argument that founders should be public about selling, Julia agrees it's good advice in a Hail Mary situation. Trying to be cute or evasive to drum up fake competitive interest doesn't work in today's climate where too many companies are visibly in that spot. There's no shame in a plain note saying you're looking for an exit.

  • Being transparent and casting a wide net is right when you need an exit
  • Founders used to be evasive to fake competitive interest; that no longer works
  • There's no shame in a simple note saying you're running a process
  • In team-acquisition scenarios, a clean data room of team members matters most

there's absolutely no shame in sending a note that says something like hey we're looking for an exit for our company X Y and Z…

Julia Schottenstein · 38:00
#m&a#selling#fundraising#exit

Tool· 1

Tool57:00

Julia's Book and Product Picks: Range, Quiet, Snowball, and Beli

In the lightning round Julia recommends two books that helped her understand herself — Range (about generalists) and Quiet (about introverts) — plus biographies she loves: Snowball, Made in America (about Sam Walton), and Leonardo da Vinci. Her recent favorite product is Beli, a consumer social app for finding and rating restaurants with friends.

  • Range — a book about generalists
  • Quiet — a book about introverts
  • Biography picks: Snowball (Buffett), Made in America (Sam Walton), Leonardo da Vinci
  • Beli — a consumer social app for discovering and rating restaurants with friends

so two books that helped me learn a lot about myself range it's a book about generalist and also quiet it's a book about introverts

Julia Schottenstein · 57:00
#books#recommendations#products#lightning-round

Takeaway· 2

Takeaway25:00

dbt Spent Two Years as a Consulting Firm Feeling the Pain Firsthand

A big part of dbt's story is that dbt Labs started as Fishtown Analytics, a consulting firm, for nearly two years. Working hands-on with clients' day-to-day data problems let the founders feel real pain firsthand and build fixes directly into dbt whenever they hit friction — maturing the product in a way that's hard to replicate.

  • dbt Labs began as Fishtown Analytics, a consulting firm, for almost two years
  • Working hands-on with clients surfaced real, firsthand pain points
  • Friction and paper cuts encountered in client work were built directly into dbt
  • Right-place-right-time (the cloud data warehouse boom) plus close customer work created the product

whenever they encountered paper cuts or friction or the workflow was taking longer than they expected they would build that into DBT and that really…

Julia Schottenstein · 26:00
#founding-story#dbt#product-development#consulting
Takeaway31:30

You Don't Decide If You'll Have a Pricing Conversation — Only When

Citing Madhavan Ramanujam's book on pricing, Julia argues that pricing and willingness-to-pay conversations are inevitable — you only get to choose their timing. It's far better to have them before you build than to discover, at sales time, that people aren't willing to pay for what you shipped. Many startups delay this, a side effect of the zero-interest-rate era of funding stars and usage over revenue.

  • You don't get to decide whether to have a willingness-to-pay conversation, only when
  • Have it before building rather than when sales is already trying to sell
  • Delaying pricing was a side effect of zero-interest-rate funding of usage over revenue

you don't get to decide if you're going to have a pricing or willingness to pay a conversation you only get to decide when

Julia Schottenstein · 32:30
#pricing#willingness-to-pay#startups