startup

also referred to as: startups

21 statements across 20 episodes · 3 bullish · 5 bearish · 20 people on the record · first statement Dec 5, 2013 by Mike Dauber · across every show →

Everything said about startup, oldest first

Dec 5, 2013
Insight
Completing the last mile of product execution kills many enterprise startups
“Creating feature functionality that goes across the board that works the enterprise scale, it actually proves to be pretty hard to do, and what happens, what ends up happening to a lot of startups is that, that last mile, if you will, proves to be the killer, …”
Mike Dauber Dec 5, 2013 ▶ 19:08 Mike Dauber, Battery Ventures // Data Driven NYC 19 // October 2013 (interviewed by Matt Turck)
Dec 5, 2013
Insight
Startups without traction need a core market insight to raise venture capital
“A venture firm early on, if there's no data points, we have to have something that we can hold onto and say, Yeah, these guys haven't done this before, but, right, they have some core insight or some knowledge of the market where they've spent more time on thi…”
Mike Dauber Dec 5, 2013 ▶ 11:41 Mike Dauber, Battery Ventures // Data Driven NYC 19 // October 2013 (interviewed by Matt Turck)
Dec 19, 2013
Insight
Wilson: Startups should build platform services on data rather than sell raw data
“I don't think selling the data is the right thing to do. I think the right thing to do is to build services on your platform that take advantage of the data that let the people who might buy the data from you instead come and build businesses And transact on y…”
Fred Wilson Dec 19, 2013 ▶ 13:11 Fred Wilson, USV // Data Driven NYC #18 // Sep 2013 (interviewed by Matt Turck)
Oct 16, 2014 neutral
Prediction Not checkable as stated
Big tech companies, not startups, will drive machine learning innovations
“I think we're gonna probably be seeing innovations from those types of companies, ah, before startups.”
Mike Abbott Oct 16, 2014 ▶ 18:53 Mike Abbott, KPCB // Data Driven #30 // Oct 2014 (Hosted by FirstMark Capital)
Feb 18, 2015 negative
Prediction Not checkable as stated
Doctors will not change workflows within a startup's timeframe
“Doctors are not going to change. And at least not in any sort of timeframe that matters for a startup. Maybe, maybe 1015 years.”
Zach Weinberg Feb 18, 2015 ▶ 10:58 Zach Weinberg, Flatiron Health // Using Data to Cure Cancer // Data Driven NYC (FirstMark Capital)
Sep 14, 2015 negative
Insight
Unfunded corporate partnerships with startups are always a waste of time
“Oh god, yeah so big companies will come to you. If you're a startup here, they'll come to you and say, hey, we don't have any money, but we want to do a partnership, and like, they'll use terms like joint value creation. Like, you should just run fast from the…”
Anand Sanwal Sep 14, 2015 ▶ 15:00 Anand Sanwal, CB Insights // What's Next? (Hosted by FirstMark Capital)
Sep 14, 2015 positive
Assertion Not checkable as stated
Deighton: Vast majority of new startup data lives in cloud
“If you look at any new company today, and I bet any startup in this room, most, if, you know, if not a hundred percent, certainly the vast majority of the data that you're working with is sourced, begins, and lives in the cloud.”
Anthony Deighton Sep 14, 2015 ▶ 1:50 Anthony Deighton, Qlik: Top 10 Requirements For Visual Analytics (Hosted by FirstMark Capital)
Dec 17, 2015 negative
Insight
Srivas: Startups should avoid emulating Google or Facebook engineering infrastructure
“Technology wise, they are more advanced, but there's only one Google and one Facebook, right, and everybody else is not like that, so don't try to do that. I mean, as a startup, that's very extreme.”
M.C. Srivas Dec 17, 2015 ▶ 31:46 A Fireside Chat with MapR CTO M.C. Srivas (Data Driven NYC / FirstMark)
Jan 25, 2016
Insight
Orad: Startups in competitive markets must be fundamentally different, not just better
“Don't be better than someone. Be totally different. It's the only way to stand out and provide value.”
Amir Orad Jan 25, 2016 ▶ 16:52 The Benefits of Fast Business Intelligence // Amir Orad, Sisense (Hosted by FirstMark Capital)
Sep 30, 2016 negative
Insight
Startups should not hire data scientists before reaching an MVP
“Basically my advice is not to start a startup with a data scientist. You know, focus on getting to MVP, getting some traction, generating some real data, make good decisions early on, and then hire data scientists as you scale.”
Jeremy Stanley Sep 30, 2016 ▶ 22:26 Making On-Demand Delivery Profitable // Jeremy Stanley, Instacart (Data Driven NYC / FirstMark)
Dec 8, 2016
Insight
Mason: Machine learning startups struggle with innovation due to lack of data
“There are challenges for startups, because you don't have data.”
Hilary Mason Dec 8, 2016 ▶ 3:47 A Process for Discovery // Hilary Mason, Fast Forward Labs [FirstMark's Data Driven]
Oct 26, 2017 positive
Insight
Weak supervision is the sweet spot for early-stage AI startups
“The sweet spot these days is what we call weak supervision or semi supervision for startup.”
Jerome Pesenti Oct 26, 2017 ▶ 8:34 Using AI to Accelerate Drug Discovery // Jerome Pesenti, BenevolentAI (FirstMark's Data Driven)
May 18, 2018
Assertion Not checkable as stated
Piantino: Startups building deep learning products struggle with infrastructure
“If you have startups in your portfolio, I know we have at least one VC in the audience, so and they're trying to do something in deep learning. They're trying to build a new product with some of this technology. I think you'll find that they do struggle with i…”
Serkan Piantino May 18, 2018 ▶ 10:36 Make AI Less Mysterious // Serkan Piantino, Spell (FirstMark's Data Driven)
Jun 8, 2018
Insight
Chris Dixon: Startups facing bundlers need order-of-magnitude better technology
“The key is to, you just, you need, you just really need, like, an order of magnitude, kind of better technology and product, like, it just really raises the bar, right, because it's essentially an old problem in startups, which is you're competing against bund…”
Chris Dixon Jun 8, 2018 ▶ 55:08 Fireside Chat: Chris Dixon, General Partner at Andreessen Horowitz (FirstMark's Data Driven)
Apr 3, 2023 bullish
Insight
Catanzaro: AI startups must reimagine workflows rather than iterate existing tools
“And I think that that is the promise of LLMs and startups. It's not to build better versions of things that exist today, but rather to kind of reimagine some of the tools and systems that we use in an LLM centric way.”
Sarah Catanzaro Apr 3, 2023 ▶ 13:23 A Conversation with Sarah Catanzaro, Amplify Partners
Sep 6, 2023 neutral
Insight
AI startups prioritize rapid shipping over accuracy and factfulness
“If you care so much around about the factfulness of your applications, you're probably not a startup, right? Startups, you know, you want to ship fast. You do whatever works best. You assemble something, it's shipped.”
Milos Rusic Sep 6, 2023 ▶ 29:17 From NLP Start-Up to Generative-AI Platform: Milos Rusic (deepset) Unpacks Product-Market Fit
Feb 8, 2024
Insight
Alex Rinke: Do not scale GTM or raise big money before achieving PMF
“I would not recommend you thinking about partnerships, or scaling go to market, or hiring salespeople, or even raising a lot of money, to be honest, before you feel really confident that you have a product that solves a problem, that you can scale, that you ca…”
Alex Rinke Feb 8, 2024 ▶ 13:28 Bootstrapping a Decacorn on $15k with Celonis CEO Alex Rinke
May 16, 2024 bearish
Assertion Not checkable as stated
$1B to $10B foundation model training costs price out startups
“As the cost to train all these large language models becomes bigger and bigger, Amazon's talking about a billion dollars for a single run or ten billion dollars for a single run. It's beyond the realm of startups to really spend any time there.”
Tomasz Tunguz May 16, 2024 ▶ 20:18 AI, Data and Blockchain: a VC perspective | Tomasz Tunguz, Founder of Theory Ventures
May 31, 2024
Insight
Dines: Operational sales rigor does not matter for early-stage startups
“Initially, for a startup, I think it's operationally doesn't matter, in my opinion. All it matters, it's built an extreme customer-centric culture.”
Daniel Dines May 31, 2024 ▶ 1:04:34 From Tiny Romanian Startup to Global AI Automation Leader | Daniel Dines, CEO of UIPath
Jan 23, 2025
Insight
Rogojan: Early startups should hire fractional data engineers and full-time analysts
“I do think like if you're early starting out, There's no problem in probably bringing on some sort of consultant to do maybe more of the data engine work and then bring on a full-time maybe analyst to kind of work on top of that is what I'd imagine would be go…”
Ben Rogojan Jan 23, 2025 ▶ 46:35 Understanding Data Engineering in 2025 | Ben Rogojan, Seattle Data Guy
May 28, 2026 neutral
Insight
Levie: Savvy startups can exploit temporary VC subsidies for AI compute
“Cause like, if you were really savvy, there's probably some parts of the market where you keep like, oh, I could somehow use this LP capital to do work for me as my startup. And there's like a window where you can find those exploits.”
Aaron Levie May 28, 2026 ▶ 22:13 State of Enterprise AI 2026: Aaron Levie on Tokenmaxxing, Rise of Headless, and AI-Proofing Your Job
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